# Appendix A

Ambient	PM2.5	Data	Analysis

2015 Plan for the 1997 PM2.5 Standard

SJVUAPCDSan Joaquin Valley Unified Air Polluti on Control District April 16, 2015

Appendix A: Ambient PM2.5 Data Analysis

2015 Plan for the 1997 PM2.5 Standard 

### This page intentionally blank.San Joaquin Valley Unified Air Polluti on Control District April 16, 2015

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

2015 Plan for the 1997 PM2.5 Standard 

## Appendix A: Ambient P M2.5 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 environ ment, atmospheric chemistry, an d emissions of directly

emitted PM2.5 and PM2. 5 precursors from r egulated and unregulat ed sources. The

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

Board (ARB), and other agencies 1 

### monitor PM2.5 concentrations throughout the

Valley, 2 

### using filter-based monitoring (s tarting in 1999) and real-time concentration

monitoring (starting in 2002). T he U.S. Environmental Protecti on Agency (EPA) serves

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



### The District uses the collected data to show air quality improv ement through the

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

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

As shown in this appendix, the desi gn value (DV) data show stea dy, long-term air

quality improvement th at will lead to the attainment of the 199 7 PM2.5 Standard.

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

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

District with critical informa tion about how to develop control measures and incentive

programs that provide the most i mpact to public health improvem ents, as guided by the

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

This appendix provides the techni cal details used to evaluate a nd analyze the District’s

PM2.5 concentration data as su mmarized 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, e xceptional events) and

the evidence for air quality improvement through District regul atory actions, including

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

Heaters).

A.1 PM2.5 CONCENTRATIONS—MEASUREMENT AND INFLUENCES

The District, ARB, and other agencie s manage an extensive air m onitoring network

throughout the Valley. The inform ation obtained fr om the PM2.5 monitors within this

network provide the District wit h necessary information for dem onstrating attainment of

the NAAQS and valuable informati on for protecting public health throughout the year.

The monitoring network captures the spatial, seasonal, daily, w eekly, and annual

variations in PM2.5 concentra tions throughout the Valley that r esult from changing

meteorology, the occurrence of e xceptional events (e.g. high wi nds and wildfires), and

PM2.5 emissions from regulat ed and unregulat ed sources.

1 Other agencies include the Chu kchansi and Tachi Yokut Tribe an d 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-Networ k-Plan.pdf

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

Application. (2010). Available at http://www.epa.gov/ttn/airs/airsaqs/aqsweb/San Joaquin Valley Unified Air Polluti on Control District April 16, 2015

A-2 Appendix A: Ambient PM2.5 Data Analysis

2015 Plan for the 1997 PM2.5 Standard 

### A.1.1 PM2.5 Mo nitor Types

The District and ARB use three ty pes of PM2.5 monitors in the V alley:

 Filter-based Federal Reference Me thod (FRM) monitors, defined a s the

standard for data collection;

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

equivalent method (FE M) monitors, and herea fter referred to as BAM/FEM

monitors;

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

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

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

NAAQS, and are therefore used fo r design value calculations. R eal-time monitors

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

produce daily air quality foreca sts, wood burning declarations, public health

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

The filter-based speciation moni tors operate similarly to the s tandard FRM monitors;

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

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

to the development of an effect ive attainment strategy.

A.1.2 Meteorological Influen ces on PM2.5 Concentrations

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

air mass. Wind flow (horizontal m ixing) and temperature instab ility (decreasing

temperature with height leading to vertical mixing) provides th e strongest mechanisms

for dispersing pollutants. Wi nd speed can greatly influence th e pollutant concentrations

by horizontally mixing and disper sing pollutants over a large a rea. Generally, the higher

the wind speed the lowe r the PM2.5 concent rations; however, in some cases, excessive

winds may cause elevated PM2.5 le vels as high winds entrain PM1 0 as well as PM2.5.

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

inversion, or increasing temper ature with increasing height, ca n inhibit the vertical

mixing of an air mass, and create a situati on in which pollutan ts remain trapped near the

surface. Prolonged periods of h igh pressure and stable conditi ons 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. PM 2.5 concentrations can

decrease or increase depending on the strength and characterist ics of the low pressure

system.San Joaquin Valley Unified Air Polluti on Control District April 16, 2015

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

2015 Plan for the 1997 PM2.5 Standard 

### Atmospheric weather patterns infl uence climate conditions, loca l meteorology, and

PM2.5 concentrations. The next se ction describes the air quali ty impacts from the

extreme drought.

A.1.2.1 Valley Drought

According to the United States G eologic Survey, California is e xperiencing its worst

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

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

years. On January 17, 2014, the Go vernor of California declare d a drought emergency

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

Center depicting the extent and severity of the drought affecti ng California as of

November 4, 2014.

Figure A-1 Drought Extent and Severity in California

A persistently strong high pressu re ridge over the eastern Paci fic Ocean and the

western United States effectivel y blocked weather disturbances from entering California.

The historic strength and longevit y of this high pressure resul ted in a lack of rainfall

throughout the Valley, and Californ ia as a whole (Table A-1).San Joaquin Valley Unified Air Polluti on Control District April 16, 2015

A-4 Appendix A: Ambient PM2.5 Data Analysis

2015 Plan for the 1997 PM2.5 Standard 

### Many cities in California, inc luding those in the Valley, had r ecord low rainfall totals

during 2013 calendar y ear, with some recor ds that have stood fo r over 100 years being

broken.

Table A-1 2013 Calendar Year Rai nfall 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 Influe nces on PM2.5 Concentrations

Valley PM2.5 concentrations are a lso affected by exceptional ev ents such as wildfires,

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

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

unlikely to recur at a particula r 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 wi ldfires.

Since exceptional events are not reasonably preventable or cont rollable, it is

inappropriate to use data influenc ed by these events. With pro per documentation and

EPA concurrence, data influenced b y exceptional events can be e xcluded from official

attainment demonstration design value calculations. Design val ues, which will be

discussed fully in Section A.2, r epresent 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 attain ment as part of its ongoing ai r quality analysis. These

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

concentrations and attainment progress. The District has exper ienced fireworks activity,

high wind events, and wildfire ev ents in the past that caused P M2.5 concentrations to

exceed the PM2.5 Standard. Two e xamples include a fireworks ev ent in July 2007 and

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

illustrated how fireworks and wildfi re events can also influenc e the design value

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

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

(2007, March 22). (to be codifi ed in 40 C.F.R. pts. 50 and 51), (40 CFR 50.14)San Joaquin Valley Unified Air Polluti on Control District April 16, 2015

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

2015 Plan for the 1997 PM2.5 Standard 

### A.2 ATTAINMENT DEMONST RATION—DESIGN VALUES

Design values represent the offici al metric for assessing air q uality improvements and

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

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

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

data validity. The results prov ide consistency and transparenc y to determine basinwide attainment for both com ponents of the 1997 PM2.5 Standard, including the 24-

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

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

higher than the respective standar d, then the entire air basin is designated

nonattainment.

Table A-2 provides the generaliz ed descriptions of how the 24-h our average and annual

average design values are calcula ted for PM2.5. EPA provides d etailed guidelines and

standards for the calculation 5 

### and data handling 6 

### methodologies.

Table A-2 General PM2.5 Desi gn 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 an d 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 98 th 

### -percentile averages (T able A-3) are used to generate the three

year average 24-hour des ign values (Table A- 4). Single-year av erage PM2.5

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

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

5 Interpretation of the National Ambient Air Quality Standards f or 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=t ext&node=40:2.0.1.1. 1.0.1.18.15&idno=40

6 Environmental Protect ion Agency [EPA]: Office of Air Quality P lanning 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.pdfSan Joaquin Valley Unified Air Polluti on Control District April 16, 2015

A-6 Appendix A: Ambient PM2.5 Data Analysis

2015 Plan for the 1997 PM2.5 Standard 

### 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 replace ment site of FresnoGarland was opened soon after. To form a continuous data recor d, these two sites

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

Average ambient PM2.5 concentrati ons vary by monitoring site wi thin the Valley. In

general, monitoring sites in the nor thern part of the Valley re cord the lowest ambient

PM2.5 concentrations. Currently m ore Valley air monitoring sit es meet the 1997 24-

hour average standard of 65 μg/m 3 

### than the annual average standard of 15.0 μg/m 3



### . For 2013, all District sites hav e met the 1997 24-hour PM2.5 St andard. For the annual

average PM2.5 Standard, most monito ring sites are showing a dow nward trend;

however, the concentrations rem ain above the annua l mean NAAQS.

.

This section intentionally blank.San Joaquin Valley Unified Air Pollution Control District April 16, 2015A-7Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardTable A-3 Single Year 24-hour Average PM2.5 98th Percentile Values (μg/m3)SJV Monitoring Site199920002001200220032004200520062007200820092010201120122013Stockton79.055.058.050.041.036.044.042.048.061.640.429.744.833.956.3Manteca38.930.940.2Modesto100.071.069.069.047.045.055.052.057.453.954.537.354.740.856.4Turlock53.143.5*57.445.455.4Merced-Coffee39.947.435.642.3Merced-M91.960.049.355.144.243.048.343.852.754.045.235.538.541.867.3Madera-City57.059.143.254.6Fresno-First120.090.075.075.056.052.071.051.067.057.455.848.869.5Fresno-Garland52.663.8Fresno-Winery64.861.571.949.749.471.255.057.444.548.237.067.551.371.6Clovis59.272.571.553.248.152.463.051.360.949.049.044.368.548.056.2Tranquility27.727.526.935.7Corcoran53.0*55.189.565.142.249.474.550.157.947.953.447.240.8*40.0*66.0Hanford64.648.367.6Visalia114.0103.096.070.047.054.065.050.059.762.153.936.350.753.862.5Bakersfield-Golden95.393.995.980.451.953.974.964.467.760.868.6Bakersfield-California97.492.794.973.048.361.563.260.573.064.566.753.365.556.471.8Bakersfield-Planz76.590.666.847.547.666.464.772.272.365.556.243.240.696.7Table A-4 24-hour Average PM2.5 Design Values (Three-Year Averages, μg/m3), end year listed (2011-2013, 2013)SJV Monitoring Site2001200220032004200520062007200820092010201120122013Stockton64545042404145515044383645Manteca38*37Modesto80706254495155545549494451Turlock6055*51*49*53Merced-Coffee43**4142Merced-M67555047454548505145 42 40 49Madera-City5352Fresno-First9580696160586358605458Fresno-Garland58***Fresno-Winery63666157575961525043 53 53 63San Joaquin Valley Unified Air Pollution Control District April 16, 2015A-8Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardSJV Monitoring Site2001200220032004200520062007200820092010201120122013Clovis68665851555658545347545458Tranquillity30**2730Corcoran66706652555861525349 47* 4349Hanford54*60Visalia104907157555658575951474756Bakersfield-Golden959076626064696466Bakersfield-California95877261586266666862625865Bakersfield-Planz84786854546068707065554760Table A-5 Single Year Annual Mean PM2.5 Concentrations (μg/m3)SJV Monitoring Site199920002001200220032004200520062007200820092010201120122013Stockton19.715.513.916.713.613.212.513.112.914.411.310.611.312.417.7Manteca10.78.111.6Modesto24.918.715.618.714.513.613.914.815.016.013.012.114.711.9 14.3Turlock16.112.5*17.114.815.0Merced-Coffee16.315.611.013.3Merced-M22.616.714.5*18.715.715.214.114.815.214.9*13.611.210.49.513.5Madera-City21.1*20.416.017.8Fresno-First27.624.519.821.517.816.316.716.818.817.415.113.015.5Fresno-Garland14.116.8Fresno-Winery18.418.621.317.817.016.917.616.816.514.613.415.412.7*15.9*Clovis19.816.318.016.218.5*16.416.316.416.416.218.314.717.915.415.9Tranquillity7.0*8.27.08.3Corcoran14.3*16.419.221.516.217.417.516.918.415.817.717.912.8*16.5*15.6Hanford18.014.818.2Visalia27.623.922.523.218.217.018.818.820.419.816.013.616.114.818.9Bakersfield-Golden26.222.621.824.119.618.219.118.619.917.920.0Bakersfield-California23.822.521.222.717.118.918.018.722.021.919.014.216.213.020.0Bakersfield-Planz20.320.823.517.817.419.819.321.823.522.517.614.514.722.8San Joaquin Valley Unified Air Pollution Control District April 16, 2015A-9Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardTable A-6 Annual PM2.5 Design Values (Three-Year Averages, μg/m3), end year listed (2011-2013, 2013)SJV Monitoring Site2001200220032004200520062007200820092010201120122013Stockton16.415.314.714.513.112.912.813.512.912.111.111.4 13.8Manteca12.1*10.2Modesto19.717.716.215.614.014.114.615.314.713.713.312.913.6Turlock15.3*14.9*15.7Merced-Coffee18.2**14.313.3Merced-M17.9*16.6*16.3*16.515.014.714.715.014.613.211.710.411.1Madera-City18.2**18.1Fresno-First24.021.919.718.616.916.617.417.717.115.214.5Fresno-Garland15.5***Fresno-Winery18.519.419.218.717.217.217.117.016.014.914.513.8*14.7*Clovis18.016.817.617.017.116.416.416.317.016.4 16.816.016.4Tranquillity7.6**7.47.8Corcoran19.019.018.417.017.217.617.017.317.116.2*15.8*15.0*Hanford15.8*17.0Visalia24.723.221.319.518.018.219.319.718.816.515.214.816.6Bakersfield-Golden23.622.821.820.619.018.619.218.819.3Bakersfield-California22.522.120.319.618.018.519.620.921.018.416.514.516.4Bakersfield-Planz21.520.719.618.418.920.321.522.621.218.215.617.3Notes 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 athttp://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, 2009had minimal sampling, Value based on 2-year average of 2011-2012,2010 had minimal samplingTriple asterisk (***): Value based on 2-year average of 2012-2013San Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-10Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-2.1 throughA-2.32 24-hour and Annual Design Value TrendsSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-11Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-12Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-13Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-14Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-15Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-16Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-17Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardSan Joaquin Valley Unified Air Pollution Control District April 16, 2015



### A-18 Appendix A: Ambient PM2.5 Data Analysis

2015 Plan for the 1997 PM2.5 Standard 

### A.3 AMBIENT PM2.5 CONCE NTRATION DATA TRENDS

Design values summarize data fr om a monitoring site with just t wo concentration values

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

hour peaks. These parameters are required for attainment demon strations, 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 improve ments within such

parameters. The District uses dat a from air monitoring sites t o analyze air quality trends

to provide a deeper understanding of changes in ambient PM2.5 c oncentrations 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 ov er the PM2.5 Standard is another indicator of air quality

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

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

above the 1997 standard at the M odesto, Fresno-First/Garland, a nd BakersfieldCalifornia monitoring sites. T hese counts have been estimated and normalized to

account for the varying sampli ng 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 98 th 

### -percentile concentration

value from each monitoring site (higher values in the 99 th 

### and 100 th 

### percentiles are not

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

limited number of days over the standard, but still be consider ed in attainment.San Joaquin Valley Unified Air Pollution Control District April 16, 2015



### A-19 Appendix A: Ambient PM2.5 Data Analysis

2015 Plan for the 1997 PM2.5 Standard 

### Figure A-3 Trend in Days over t he 1997 24-Hour PM2.5 Standard

Note: Years and sites with no dat a (colored bars) represent zer o exceedances.



### As shown in Figure A-3, the Vall ey has experienced a significan t drop in the number of

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

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

sites of Modesto, Fre sno-First/Garland, and Bakersfield-Califor nia. 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 reducti on strategy, the investment fro m the regulated industry

in control technology, and the publ ic’s willingness to make a c hange for cleaner air have

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

winter, with unfavorable stagnant m eteorology as experienced du ring the 2011–2012

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

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

expected PM2.5 concentrations and exceedances under identical r egulatory controls.

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

however, under those similar co nditions, the number of exceedan ces in 2011 and

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

strongly suggests a real reduction in emissions.San Joaquin Valley Unified Air Pollution Control District April 16, 2015



### A-20 Appendix A: Ambient PM2.5 Data Analysis

2015 Plan for the 1997 PM2.5 Standard 

### A.3.2 Seasonal Trends - 1 st 

### and 4 th 

### Quarter Averages

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

months, in the 1 st 

### and 4 th 

### 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 average s can shed light on how

the peak of the PM2.5 seas on is changing over time.

The data used in this analysis u tilizes PM2.5 filter values fro m 1999 through 2013

focusing on the 1 st 

### and 4 th 

### quarters at six sites in the District that tend to have the

highest concentrations; Clovis, F resno-First/Garland, Corcoran, Visalia, BakersfieldCalifornia, and Bakersfield-Pl anz. 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 h istorical filter data depicts a general trend of

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

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

Top 5 Average data demonstrates the epi sodic nature of PM2.5 pollution, the s everity of

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

The Quarter Average charts shown below (Figures A-4 .1 through A-4.12) indicate tha t

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 upwa rd trend. However,

this may be due to random varia tion of the data resulting in th e unusually high values in

the first quarter of 2012 and t he fourth quarter of 2011 and 20 13 that pulls both quarter

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

significantly increasing or dec reasing. Despite Clovis, the ov erall 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 severi ty of the PM2.5 episodic peaks over time.

The Quarter Average with the greatest rate of reduc tion in PM2.5 is almost unanimo usly

in the fourth quarter and less so in the first quarter. Conver sely, 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 Clo vis).

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

the Top 5 Averages are important indicators for at taining the District’s Health-R isk

Reduction Strategy and the annual average PM2.5 standard.San Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-21Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-4.1 through A-4.12 QuarterAverage TrendsSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-22Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-4.1 through A-4.12 QuarterAverage TrendsSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-23Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-4.1 through A-4.12 QuarterAverage TrendsSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-24Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-5.1 through A-5.12 Collection ofTop 5 AverageTrendsSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-25Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-5.1 through A-5.12 Collection ofTop 5 AverageTrendsSan Joaquin Valley Unified Air Pollution Control DistrictApril 16, 2015A-26Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-5.1 through A-5.12 Collection ofTop 5 AverageTrendsSan Joaquin Valley Unified Air Polluti on Control District April 16, 2015



### A-27 Appendix A: Ambient PM2.5 Data Analysis

2015 Plan for the 1997 PM2.5 Standard 

### A.3.3 Annual Trends

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

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

declarations, public health notif ications, and Real-time Air Ad visory Network (RAAN)

notifications.

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

evaluate how PM2.5 concentrati ons vary throughout the day at ea ch of the Valley

monitoring sites that measure PM 2.5. An analysis of hourly mea surements can show

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

Understanding such profiles hel ps in the development of control strategies and

programs that target activities during times of peak concentrat ions.

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

year. The District compares relat ive changes in hourly PM2.5 co ncentrations from year

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

PM2.5 control measures, especia lly Rule 4901 (Wood Burning Fire places and Wood

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

curtailments. Such curtailment s became mandator y beginning in the 2003–2004 winter

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

Prior to the 2008-2009 winter s eason, the Rule was amended to s pecify that woodburning curtailments would be de clared when a PM2.5 concentrati on of 30 μg/m 3 

### or

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

was lowered to 20 μg/m 3 

### or higher and contained a tier ed system which effectively

mitigates emissions from resident ial wood-burning by discouragi ng, limiting, or

prohibiting wood burning in fir eplaces and other non-EPA certif ied residential wood

burning devices during the winter months.

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

over time at select real-time m onitoring sites within the Distr ict’s monitoring network. As

indicated in profiles A-8.1 through A-8.4, Modesto, Fresno 7 

### , Visalia, and Bakersfield

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

PM2.5 concentrations were much higher prior to the strengthenin g 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 April 16, 2015A-28Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-6.1 through A-6.16PM2.5 Diurnal ProfilesSan Joaquin Valley Unified Air Pollution Control District April 16, 2015A-29Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-6.1 through A-6.16PM2.5 Diurnal ProfilesSan Joaquin Valley Unified Air Pollution Control District April 16, 2015A-30Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-6.1 through A-6.16PM2.5 Diurnal ProfilesSan Joaquin Valley Unified Air Pollution Control District April 16, 2015A-31Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-6.1 through A-6.16PM2.5 Diurnal Profiles*Charts represent complete yearsof data within the past five years..San Joaquin Valley Unified Air Polluti on 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 pro vide daily information

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

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

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

current 8 

### 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/m 3 , 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 i n the PM2.5 data from the sit es with at least two years

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

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

pollutants. By excluding the ot her 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 referen ce for interpreting Figures A-8 .1 through A-8.11. The

stacked bars represen t the number of days within each year that fell within each of the

AQI categories (totaling 365 days) . Because of regular mainten ance 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. Withi n each stacked bar, the categorie s are ordered as Good,

Moderate, etc. from the bottom up.

8 CFR Appendix G to Part 58, Uniform Air Quality Index (AQI) and Daily ReportingSan Joaquin Valley Unified Air Polluti on 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 ai r quality. This finding is sig nificant and needs to be

emphasized because this improvem ent is expressed despite the da ta being subject to

the lowered AQI break points, a s noted above in Table A-7. Ove r these five years, the

frequency of Good AQI days increas ed, coupled with a decrease i n the frequency of the

Moderate and Unhealthy-for-Sensit ive-Groups AQI days. For exam ple, at the FresnoFirst /Garland site, the number o f Good days increased from 189 in 2008, to 207 in

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

41 to 31, respectively.

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

AQI days increasing, and the fr equency of the Moderate and USG AQI days

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

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

and 48 to 27, respectively.

These improvements over the 2008–201 3 timeframe reflect the emi ssions reductions

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

period is the District’s Rule 49 01 (Wood Burning Fireplaces and Wood Burning

Heaters), which was strengt hened just befor e the 2008–2009 wint er season, lowering

the curtailment threshold from 65 μg/m 3 

### to 30 μg/m 3 

### . The observed improvement in

PM2.5 AQI values is partly at tributable to the amended wood-bur ning rule.San Joaquin Valley Unified Air Polluti on 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 so me years, as compared

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

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

year drought and contributed great ly to this PM2.5 deterioratio n.

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

ridge over the eastern Pacific Oc ean and the wester n United Sta tes effectively blocked

weather disturbances from enterin g California that would normal ly 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 stagnatio n conditions leading to a

subsequent increase in the sus pended particulate matter in the atmosphere. This

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

throughout the state of Californi a. Despite these current cond itions the general trend

has been for improving air quality.

In Figure A-8.12, the data for eac h site was averaged for all y ears. In the graph the

sites are arranged from north to south along the horizontal axi s 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 a pproximately 72%

Good AQI), and have about 25% mor e days in the Good AQI categor y than the Visalia

and Bakersfield sites whic h 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 tha t the percentage of Good AQI day s is increasing for the

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

throughout the District. More s pecifically (and in terms of da ys instead of percent) for

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

increased by 58 days since 2003, w hile the number of days in th e Moderate, USG, and

Unhealthy AQI categories decreas ed by 46 days, 11, and 1 day, r espectively. 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 follo wing figures, it is apparent that the dominant annual PM2.5

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

is presented to summarize this observation. The data was avera ged 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 elev en years, that 92% of all

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

down further shows that the Valle y has averaged, 55% Good AQI d ays (199 days), 37%

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

days).San Joaquin Valley Unified Air Pollution Control District April 16, 2015A-35Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-8.1 through A-8.4 Number of Days per AQI Category perYear: Stockton-Hazelton, Tracy,Modesto, and TurlockSan Joaquin Valley Unified Air Pollution Control District April 16, 2015A-36Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-8.5 through A-8.8 Number of Days per AQI Category perYear; Merced, Clovis, FresnoFirst/Garland, and HanfordSan Joaquin Valley Unified Air Pollution Control District April 16, 2015A-37Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-8.9 through A-8.11 Number of Days per AQI Category per Year: Corcoran, Visalia, and BakersfieldCaliforniaSan Joaquin Valley Unified Air Pollution Control District April 16, 2015A-38Appendix A: Ambient PM2.5 Data Analysis2015 Plan for the 1997 PM2.5 StandardFigures A-8.12 through A-8.14 PM2.5 AQI Site Average, PM2.5 AQIYear Average, and PM2.5 AQI Average forAll Sites and all Years Combined92% of alldays areGood toModerateAQISan Joaquin Valley Unified Air Polluti on 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 matte r is established on the basis of the amount of

particulate matter, by mass (wei ght) that a filter sampler is a ble to collect per cubic

meter of air. Most air monitori ng devices for particulate matt er report only the mass of

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

source the particulate matter ma y have come from, or provide di rect evidence to

determine whether the St ate Implementation Pl an (SIP) measures are having the

expected impact on part iculate emissions.

Additional monitoring is conducte d with special samplers that c ollect filters for additional

analysis of contributing material s (species). The samples coll ected by speciation

samplers are subjected to ext ensive physical and chemical labor atory analysis. The

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

(species) that contribute to par ticulate emissions and provide information to verify

source contributions. The spec iation data is also used to supp ort some types of

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

to particulate matter shown by s amples collected over several y ears can reveal long

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

compared to the expected changes p redicted from emissions reduc tions and modeling.

A.3.5.1 Valley Speciation Monitoring

There are four speciation monito rs collecting samples in the Va lley these are located in

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

expensive laboratory analysis of the collected speciation filte rs and compiles the

resulting data.

A.3.5.2 Data provided by Speciation Analysis

Analysis of the filter collected by a speciation sampler report s a variety of contributing

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

emissions. However, the contributi ng source of the material ma y not be clear because

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

mass categories are im portant for use as “t racers” or fingerpri nts to help identify the

relative contribution of sources.

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

materials (species) that are i dentified by lab oratory analysis of the speciation sampler

filters.San Joaquin Valley Unified Air Polluti on 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 M ass Contributions Repor ted in Speciation An alysis

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 combustionSan Joaquin Valley Unified Air Polluti on 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 L evel 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 Pr ovided by Speciation Data

Speciation samples collected from 2001 through 2013 have been e valuated to

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

filter analysis has been evaluat ed to detect trends in the repo rted species. There are

limiting factors that affec t the trend analysis including:

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

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

representative of the Valley but m ay not explain every variatio n in total particulate

observed at other monitoring locationsSan Joaquin Valley Unified Air Polluti on 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 wa s moved to a new, but nearby, location in

2012. Data appear to be consisten t for both locations; therefo re, the trend

evaluation is interpreted as a continuous period of sampling

 Organic carbon and elemental car bon test methodology has chang ed during the

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

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

The two methods do not provide c omparable data fo r 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 w hich is not ideal for

trend evaluation.

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

 Trends (multiyear trends in tota l particulate and major contri buting species,

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

interpretation)

 Drought impacts (soil as an indi cator for drought impact, obse rved trends,

implications for the SIP)

 SIP implications (District strategy effectiveness)

Trends (multiyear trends in total particu late and major contributing s pecies, responsive

species and times of year, nonr esponsive species and times of y ear, interpretation)

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

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

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

maximum PM2.5 speciation mass. E ach of the four sites shows ve ry similar

trends to the group analysis. Thi s suggests that all of the Va lley sites are

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

data for confirmation at sites o ther than the four speciation s ampler sites. The

average of values for the entire year shows improvement from 24 μg/m 3 

### of air to

16 μg/m 3 

### . Both the Average value and Maximum value analyses show

improvement from March to October that is approaching the 15 μg /m 3 

### annual

standard. However, while impro ving, the late fall and winter m onths from

November through February are pr oving 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 Polluti on 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 PM 2.5 Speciation Mass

Figure A-10 Maximum PM 2.5 Speciation Mass

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

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

analysis of the components inclu ded in particulate matter requi res examining the major

constituents (species) of particu late matter. Particulate matt er can be divided into

several major constituents: Nit rates, Sulfates, Organic Carbon, Elemental Carbon and

Geologic material. Nitrates and Su lfates are formed in the atm osphere from gases

(ammonia, NOx, SOx). Organic car bon is both directly emitted a nd formed in theSan Joaquin Valley Unified Air Polluti on 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 (f rom combustion) and geological m aterial (soil related

plus trace elements) are direc tly emitted and do not change onc e emitted.

 Nitrate: Ammonium nitrate is the larges t contributor to particulate mat ter on an

annual basis. Ammonium nitrate i s a material that forms in th e atmosphere from

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

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

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

ammonium nitrate forms in the at mosphere it does not remain as particulate

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

October the amount of ammonium nit rate collected on filter samp les is very low

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

February levels of ammonium nitra te are a substantial portion o f the total

particulate mass. Ammonium nitra te is calculated from the spec iation data by

adding the reported amount of nitra te to a calculated portion o f the ammonium

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

ammonium sulfate formation). Fi gure A-11 shown below illustrat es the sum of

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

Figure A-11 Sum of Ammonium (NH4 +) and Nitrate (NO3-) Speciati on MassSan Joaquin Valley Unified Air Polluti on 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 av erage values observed for amm onium nitrate data do

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

average value ammonium nitrate t rend. Both the March to Octobe r low values and the

November to February higher val ues show reduction when looking at the average

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

emissions are having an impact on the formation of ammonium nit rate.

Figure A-12 Average Value Ammonium Nitrate TrendSan Joaquin Valley Unified Air Polluti on 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 n itrate observed have not follow ed the trend

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

show an improving trend; howev er 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 i n Figure A-14 below.

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

Figure A-14 Maximum Monthly Per centage of PM2.5 Attributable t o Ammonium

NitrateSan Joaquin Valley Unified Air Polluti on 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 Janua ry, February and December have not shown a

proportional reduction to the av erage emissions reduction and r eduction of average

observed values, it is difficul t to determine how much addition al reductions will be

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

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

and a target for additional reducti ons to achieve that objectiv e is difficult to forecast.

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

dominant source of PM2.5, contri buting more than half of the pa rticulate observed

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

reduction of NOx emissi ons (see Chapter 2).

The reason that nitrate emission reductions have not achieved t he improvement

predicted by the model may be at tributable to a variety of fact ors. 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 factor s. The potential factors incl ude but may not be limited

to:

o Aqueous atmospheric reactions not currently available for incl usion in the

model – missing reactions may a ccount for under-prediction of

atmospheric formation of nitrates in winter

o Horizontal diffusion parameters appropriate for winter, with d iffusion more

limited than the current 4 kilome ter grid representation of mix ing used in

the model – requires field invest igation to provide parameters and model

code enhancement to improve the si mulation of observed horizont al

diffusion

o Vertical diffusion parameters fo r winter inversions – requires field

investigation to provide paramet ers and model code enhancement to

improve the simulation of obs erved vertical diffusion

o Adjustment of atmospheric chemis try for impacts of drought (lo wer

humidity results in h igher photochemistry activity which provid es radicals

that promote particulate formation)

 Sulfate: Ammonium sulfate is a small cont ributor to particulate matter o n an annual

basis. Ammonium sulfate is a mate rial that forms in the atmosp here from materials

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

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

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

is removed by deposition to vegetat ion 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 av erage values observed for amm onium sulfate data

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

every month and do not show resist ance to improvement in winter except in

December. The cause of resistanc e to improvement in December m ay be due to

reduced inversion hei ghts and severe episodes of air stagnation . Improvement

throughout the year indicates tha t the reduction measures to re duce sulfur oxide

(SOx) emissions are having an impact on the formation of ammoni um sulfate.San Joaquin Valley Unified Air Polluti on 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 addi ng the reported

amount of sulfate to a calculat ed portion of the ammonium (tota l reported ammonium

minus the portion of ammonium tha t is involved in ammonium nitr ate formation).

Figure A-15 shown below illustra tes the sum of sulfate and nitr ate in the speciation

mass.

Figure A-15 Sum of Sulfate ((SO 4 

### ) 2- 

### ) and Nitrate (NO 3 - 

### ) Speciation Mass

 Elemental Carbon (EC) a nd Organic Carbon (OC) : Elemental carbon from

combustion is a small contribut or to PM2.5. Organic carbon fro m incomplete

combustion, evaporation and biogeni c sources is a large contrib ution to observed

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

changes in industrial VOC emissi ons. Organic carbon reflects c hanges in

evaporative VOC emissions and inco mplete combustion processes s uch as

charbroiling and residential wood combustion. Changes in the a tmospheric

levels of EC and OC are therefor e important for evaluating the effectiveness of

measure in the SIP.

Laboratory filter sample speciati on evaluation methods are used to determine

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

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

the EC and OC attri butions requires discussion of both as a sin gle topic. The

laboratory methods for determini ng this apportionment have to u se oxygen to

break down compounds that conta in carbon. The use of oxygen ma kes it difficult

to determine an accurate measur ement 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 Polluti on 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 ca rbon and elemental carbon changed during the sampling

period. Older methodology was us ed 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 a nalysis for the entire

2001 through 2013 period. Newer methodology reports low concen trations with a

narrow range of variability whi ch is not ideal for trend evalua tion.

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

not consider reliable. EPA has r ecommended differencing method s for modeling and

air monitoring speciation analysis where all easily quantifiabl e components are

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

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

for the 15 μg/m 3 

### annual standard due to the need for precision. Additionally t his

approach is not ideal for the 24-h our PM2.5 standard in areas l ike the Valley where

windblown dust emissions have t he potential to produce substant ial levels of inert

material, identifiable only from calculations for tracer compou nds 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 geologi c material also

includes trace elements related to different sources such as fi reworks, engine

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

generally the third largest sour ce following nitrate and organi c carbon. SIP

measures to reduce geologic mat erial have been effective but ar e beginning to show

impact from the continuing drought.

Drought Impacts

Drought related impacts can be asse ssed by examining the specia tion data trends of

materials commonly found in so il. 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 tr end analysis because soil is

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

in decreasing order, silicon, a luminum, iron, magnesium, calciu m, sodium, and

potassium. The organic fraction o f soil also includes phosphor us and sulfur. Additional

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

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

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

illustrates the increase soil el ements that occur during a drou ght.San Joaquin Valley Unified Air Polluti on 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 El ements during a Drought

Evaluation of major and trace components of PM2.5 reported in t he 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 sili con and aluminum are components of soil, and not the

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

the two tracer compounds. The tracers conservatively show an u p to 1 μg/m 3 

### increase

in PM2.5 mass due to increased soil emissions due to the drough t.

A.3.5.4 SIP Implications (Dis trict 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 winte r months from

November through February. Dec ember and January show strong re sistance to

improvement of peak values.

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

improvement in the average of mont hly data but also shows resis tance to

improvement of peak values in wi nter months (December through F ebruary).

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

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

component for reduction efforts.

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

less improvement than expected. T his source category is diffic ult to assess due

to limitations of the s peciation analysis methods.San Joaquin Valley Unified Air Polluti on 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 la rgest contributor to winter PM2 .5 mass) and trace

compounds show improvement. How ever, geologic material is tren ding upward

due to drought.

 Sulfate (a minor contribut or) shows improvement.

 Elemental carbon (a minor contri butor) shows improvement. This source category is difficult to assess due to limitations of the speci ation analysis

methods.San Joaquin Valley Unified Air Polluti on 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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