# San Joaquin Valley

1

- Hour Ozone

Clean Data Determination

Appendices

February 8 , 2016

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### i

Table of Contents

Appendix A : San Joaquin Valley 1

- Hour Ozone Estimated Expected Number

of Exceedance Days and Missing Data Analysis

................................ ......................... A

- 1

Estimated Expected Number of Exceedance Days

................................ .................. A

- 1

Missing Data Analysis

................................ ................................ ............................... A

- 4

2013

- 2015 Preliminary Estimated Expected Number of Exceedance Days

............. A

- 8

Appendix B : Estimated Design Values and Expected Number of Exceedance

Days at Arvin

- Bear Mountain

................................ ................................ ....................... B

- 1

Introduction

................................ ................................ ................................ ............... B

- 1

Methods for Estimating Design Values

................................ ................................ ..... B

- 1

ARB Methods for Estimating Design Values

................................ ............................. B

- 5

San Joaquin Valley District Methods for Estimating Arvin

- Bear Mountain

Design Values

................................ ................................ ................................ ........ B

- 11

ARB Methods for Estimated Expected Number of Exceedance Days

.................... B

- 15

Data

................................ ................................ ................................ ........................ B

- 15

Methodology

................................ ................................ ................................ ........... B

- 15

Appendix C : Meteorology, Emissions, and Ozone Chemistry

in the San Joaquin Valley

................................ ................................ ............................ C

- 1

Meteorology in San Joaquin Valley

................................ ................................ .......... C

- 1

Emissions in the San Joaquin Valley

................................ ................................ ....... C

- 3

Ozone Chemistry in the San Joaquin Valley

................................ ............................ C

- 8

Conclusion

................................ ................................ ................................ ............... C

- 9

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### A

- 1 Appendix A

S an J oaquin V

alley 1

- Hour Ozone Estimated Expected Number of Exceedance

Days and Missing Data Analysis

Estimated Expected Number of Exceedance Days

According to the rules of 40 CFR § 50.9 and Appendix H, as well as Guideline for the
Interpretation of Ozone Air Quality Standards , January 1979, EPA

- 450/4

- 79

- 003, for the

2012

- 2014 three

- year period, no site in the San Joaquin Valley Air Basin (SJVAB)

violated the 1

- hour ozone standard. To violate the standard, the three

- year average estimated expected number of exceedance days (rounded to one decimal place) must

be gr eater than 1.0.

If all days are represented by a valid daily maximum hourly ozone measurement, the

average is simply the average of the number of days over the standard for each year in

the three

- year period. Since that is rarely the case, Appendix H inc ludes a formula that

adjusts the estimated expected number of days in each year for missing days.

Appendix H defines how one estimates the expected number of exceedances in each

year as: e = v + [(v/n) * (N

- n

- z)] (Appendix H F ormula 1)

where "e" is the estimated expected number of exceedances, "v" is the number of daily

one

- hour maxima above the level of the standard, "N" is the number of required
monitoring days in the year (for San Joaquin Valley, "N" is the number of days in the

year) , "n" is the number of days with valid daily one

- hour maxima, and "z" is the number
of days assumed to be less than the level of the standard. "e" is rounded to one decimal

place. The 1

- hour ozone standard is violated if the average estimated expected numb er

of exceedances over three consecutiv e years, rounded to one decimal
(i.e., the three

- year average "e"), is greater than 1.0.

Paragraph 5 of Section 3 of Appendix H states “A missing daily maximum ozone value

may be assumed to be less than the level of the standard if the valid daily maxima on

both the preceding day and the following day do not exceed 75 percent of the level of
the standard.” This means that a missing day can be “excused

- by

- rule ” when this

condition is met

.

The guidance, in the context of this single missing day rule, states “other data might

indicate whether or not the missing value would have been likely to exceed the standard
level.” The guidance cite s “solar radiation, temperature, or other pollutants” as possible

information to us e to dismiss the missing value. S uch an analysis to could also be used

to dismiss consecutive missing values.

In this evaluation, staff included only those days that are excused by rule (per
Paragraph 5 of Section 3 of Appendix H ) in Formula 1's "z" term and did not to include

any other missing days in that term. Doing this maximizes the missing day adjustment

### A

- 2

(i.e., the [(v/n * (N

- n

- z)] part of F ormula 1), which in turn gives us an upper bound on

"e".

Using this method, "e" and the three

- year average " e" for all sites in the San Joaquin

Valley during 2012

- 2014 are:

Table A 1

. Estimated Expected Number of Exceedances, 2012

- 2014

n z v A e Avg e

County Site 2012 2013 2014 2012 2013 2014 2012 2013 2014 2012 2013 2014 2012 2013 2014

Fresno Clovis

- N Villa

Avenue 357 343 331 2 4 9 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Fresno Fresno

Drummond Street 357 359 356 5 4 3 1 0 0 0.011 0 0 1.0 0.0 0.0 0.3

Fresno Fresno

- Garland 351 358 355 6 7 3 1 0 0 0.02 6 0 0 1.0 0.0 0.0 0.3

Fresno Fresno

- Sierra

Skypark #2 356 348 332 6 3 8 1 0 1 0.011 0 0.075 1.0 0.0 1.1 0.7

Fresno Parlier 352 344 347 5 4 5 1 0 0 0.02 6 0 0 1.0 0.0 0.0 0.3

Fresno Tranquility

- 32650

West Adams

Avenue 355 354 325 5 1 8 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Arvin

- Di Giorgio 366 362 362 0 3 2 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Bakersfield

- 5558

California Avenue 358 315 310 6 2 5 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Bakersfield

Municipal Airport 174 331 352 6 9 9 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Edison 360 362 307 2 3 4 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Maricopa

Stanislaus Street 293 340 354 3 1 4 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Oildale

- 3311

Manor Street 359 356 357 1 3 4 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Shafter

- Walker

Street 361 282 363 1 1 2 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kings Hanford

- S Irwin

Street 310 331 349 6 9 14 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Madera Madera

- 28261

Avenue 14 353 335 343 4 12 8 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Madera Madera

- Pump

Yard 350 331 340 2 14 12 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Merced Merced

- S Coffee

Avenue 354 344 355 1 3 6 0 0 0 0 0 0 0.0 0.0 0.0 0.0

San

Joaquin Stockton

Hazelton Street 359 330 360 3 2 5 0 0 0 0 0 0 0.0 0.0 0.0 0.0

San

Joaquin Tracy

- Airport 347 283 346 10 2 4 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Stanislaus Modesto

- 14th

Street 348 358 364 8 3 1 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Stanislaus Turlock

- S Minaret

Street 328 354 326 5 3 12 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Tulare Porterville

- 1839

Newcomb Street 350 341 346 3 5 6 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Tulare Sequoia and Kings

Canyon Natl Park 363 333 350 2 2 3 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Tulare Sequoia Natl

Park

- Lower

Kaweah 359 296 189 0 2 2 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Tulare Visalia

- N Church

Street 357 356 356 4 9 1 0 0 0 0 0 0 0.0 0.0 0.0 0.0

### A

- 3

The terms "n", "z", "v", and "e" are as described above. "A" is the missing day

adjustment, also described above. Finally, the "N" ter m of Formula 1 is 366, 365, and
365, for years 2012, 2013, and 2014, respectively.

The values shown under "n" are the number of days at each site and year that produced

a valid daily maximum hourly measurement. Note that at least 273 days with valid daily
maxima are required for 2012 to be considered complete (i.e., 75 percent of 366 days in
the year), whereas a minimum of 272 days wit h valid maxima are required for 2013 and
2014 (75 percent of 365 days in the year). All site/years e xcept for

Bakersfield

- Municipal Airport in 2012 are complete (there are no ozone data for this site
during the first and second quarters of 2012)

.

The values shown under "z" include only those d ays that can be excused by rule
(as described above).

The values shown under "v" a re simply a count of d ays at the site during the year that a

daily maximum hourly measurement was above the level of the standard

(i.e., 0.125 ppm or higher).

The values shown under "A" are the missing data adjustments, equal to (v/n) * (N

- n

- z).

The values shown under "e" are determined as defined in Formula 1, specifically the
number of measured exceedances of the standard (i.e., "v") plus the missing data

adjustment, with the sum rounded to the nearest single decimal place.

The values shown und er "Avg e" are the three

- year averages of each site's yearly "e"

values for 2012, 2013, and 2014, rounded to a single decimal place.

Table A 1 lists all sites that collected ozone da ta in San Joaquin Valley during

2012

- 2014 , except for Fresno

- First Street

. On Janua ry 1, 2012, Fresno

- First Street was replaced by Fresno

- Garland

. Fresno

- First Street ceased operation on

January 31, 2012. Since Fresno

- Garland took the place of Fresno

- First Street in the

area's required monitoring and First Street operated only during January in 2012 , we have chosen to disregard consideration of Fresno

- First Street in this evaluation.

Table A 1 shows that there were only 4 sites during 2012

- 2014 that experienced

exceedances: Fresno

- Sierra Skypark #2

, Fresno

- Garland

, Fresno

- Drummond Street

, and Parlier. Of those, only Fresno

- Sierra Skypark #2 experienced more than one day

over the standard during the three

- year period, with one measured exceedance in 2012

and another in 2014. That site's three

- year average "e" was 0.7, the highest estimated
expected exceedance days in the San Joaquin Valley during 2012

- 2014

.

### A

- 4

Missing Data Analysis

As mentioned above, one site/year in the San Joaquin Valley in 2012

- 2014 had

insufficient data to be considered complete. In 2012, the ozone da ta record for

Bakersfield

- Municipal Airport starts as of July 1. The site experienced no exceedances

during the time for which there are data for the site (the highest daily maximum hourly

ozone measurement recorded at the site during 2012

- 2014 was 0.120 ppm on July 10, 2012). The pertinent questions are whether an exceedance of the standard

may have occurred between January 1, 2012 and June 30, 2012.

There are three sites that surround Bakersfield

- Municipal Airport : Bakersfield

- 5558

California Avenue, Oildale

- 3311 Manor Street, and Edison (see Figure A 1, below)

. Of these, the first two are typically upwind of the Bakersfield

- Municipal Airport site and
the third is typically downwind. In the first half of 2012, the highest daily maximum

hourly ozone mea surements for these three surrounding sites were 0.101 ppm at
California Avenue, 0.099 ppm at Oildale, and 0.101 ppm at Edison, all occurring on

June 1, 2012.

Figure A 1

. Bakersfield

- Municipal Airport and Three Surrounding Sites

We performed an analysi s that compares the differences between daily maximum

1

- hour ozone measurements occurring on the same day from the three surrounding

sites and the Bakersfield

- Municipal Airport site. The intent of the analysis is to place an

upper bound on the possibility that Bakersfield

- Municipal Airport exceeded the standard

### A

- 5

during the first half of 2012. We first found a ll days during the first halves
(i.e., January 1 through June 30) of 2013 and 2014 when at least one of the sites

experienced a daily maximum hourly ozone measurement of at least 0.090 ppm. We

chose this cut point because 1) we wanted to make use of the relative behaviors of the
sites on high days, and 2) the difference between 0.090 and 0.125 ppm (0.035 ppm)

was greater than the differences our inspe ction of the data had led us to expect and that

would yield at least ten days on which to base our evaluation

.

There are 11 days during the first halves of 2013 and 2014 when these conditions were

met:

Table A2

. Daily Maximum 1

- hour Ozone Measurements, ppm

Date Edison Oildale

- 3311 Manor Street Bakersfield

- 5558 California Avenue Bakersfield

- Municipal Airport

5/4/2013 0.073 0.074 0.087 0.091

5/11/2013 0.072 0.074 0.087 0.092

6/6/2013 0.083 0.078 0.0859 0.092

6/7/2013 0.081 0.0899 0.0976 0.098

6/8/2013 0.093 0.0995 0.1076 0.109

5/2/2014 0.0936 0.0703 0.0749 0.079

5/15/2014 0.0973 0.0824 0.0924 0.093

6/5/2014 0.0901 0.0728 0.0782 0.079

6/8/2014 0.093 0.0843 0.0943 0.096

6/9/2014 0.1041 0.0814 0.0914 0.108

6/30/2014 0.1073 0.0799 0.0865 0.091



### We then found the difference between the sites on each of these days, with the

difference defined as the value for Bakersfield

- Municipal Airport minus the value for the

surrounding site:

Table A3

. Differences Between Listed Site's Daily Maximum

and that for Bakersfield

- Municipal Airport , ppm

Date Edison Oildale California

Avenue

5/4/2013 0.018 0.017 0.004

5/11/2013 0.020 0.018 0.005

6/6/2013 0.009 0.014 0.0061

6/7/2013 0.017 0.0081 0.0004

6/8/2013 0.016 0.0095 0.0014

5/2/2014

- 0.0146 0.0087 0.0041

5/15/2014

- 0.0043 0.0106 0.0006

6/5/2014

- 0.0111 0.0062 0.0008

6/8/2014 0.003 0.0117 0.0017

6/9/2014 0.0039 0.0266 0.0166

6/30/2014

- 0.0163 0.0111 0.0045

Maximum

Difference 0.020 0.0266 0.0166



### We then identified those days during the first half of 2012 (i.e., January 1 through

June 30, 2012) when at least one of the surrounding sites produced a daily maximum of

0.090 ppm or greater. This method is equivalent to considering each day in the first half

### A

- 6

of 2012, but we only explicitly consider those da ys above 0.090 ppm since it is

impossible for other days to exceed the standard.

Table A4

. Daily Maxima Above 0.090 ppm at Surrounding Sites

During the First Half of 2012 and

Estimates for Bakersfiled

- Municipal Airport Based on those Maxima , ppm

Date Max ima at

Edison Maxima at

Oildale Maxima at

California

Avenue Muni

Based on

Edison Muni

Based on

Oildale Muni

Based on

California Avenue Maximum

Estimate s

4/21/2012 0.090 0.082 0.089 0.110 0.1086 0.1056 0.110

4/22/2012 0.091 0.086 0.091 0.111 0.1126 0.1076 0.1126

5/31/2012 0.096 0.087 0.086 0.116 0.1136 0.1026 0.116

6/1/2012 0.101 0.099 0.101 0.121 0.1256 0.1176 0.1256

6/16/2012 0.091 0.094 0.100 0.111 0.1206 0.1166 0.1206



### Table A4 add s the maximum difference for each surrounding site to that site's

first

- half

- of

- 2012 daily maxima to estimate what the daily maxima at

Bakersfield

- Municipal Airport may have been. Table A4's Maximum Estimates column

suggests that there may have been one day in the first half of 2012

— June 1

— when

Bakersfield

- Municipal Air port could potentially have exceeded the standard.

Table A5 examines the impact of an exceedance during the first half of 2012 on the

three

- year average "e". Table A5 also projects how many exceedances during the first

half of 2012 would be required to 1 ) equal the highest three

- year average "e" for

2012

- 2014 on record (i.e., the three

- year averag e "e" of 0.7 from Fresno

- Sierra
Skypark #2) and 2) cause a violation of the standard.

Table A5

. Impacts of Possible Exceedances at Bakersfield

- Municipal Airport

During the First Half of 2012

on the Estimated Expected Number of Exceedances

n z v A e Avg e

Scenario Site 2012 2013 2014 2012 2013 2014 2012 2013 2014 2012 2013 2014 2012 2013 2014

As

reported Bakersfield

Municipal Airport 174 331 352 6 9 9 0 0 0 0 0 0 0.0 0.0 0.0 0.0

1 Exceed Bakersfield

Municipal Airport 356 331 352 6 9 9 1 0 0 0.0112 0 0 1.0 0.0 0.0 0.3

2 Exeeds Bakersfield

Municipal Airport 356 331 352 6 9 9 2 0 0 0.0225 0 0 2.0 0.0 0.0 0.7

3 Exceeds Bakersfield

Municipal Airport 356 331 352 6 9 9 3 0 0 0.0337 0 0 3.0 0.0 0.0 1.0

4 Exceeds Bakersfield

Municipal Airport 356 331 352 6 9 9 4 0 0 0.0449 0 0 4.0 0.0 0.0 1.3



### This analysis effectively assigns values to all days in the first half of 2012, so in the

scenarios postulating e xceedances, the only adjustment needed for missing values is

that for the data in the second half of 2012 (i.e., the data that are neither present nor
assigned a value). In other words, the number of complete days for 2012 becomes 356,

or 182 assigned days from the first half of 2012 and 174 measured days from the

second half of 2012.

### A

- 7

If we assume that June 1 did experience an exceedance, then "e" becomes 1.0 for 2012

and the three

- year average "e" becomes 0.3. This, of course, is not a violation and

does not displace the San Joaquin Valley maximum three

- year average "e" of 0.7 from

Fresno

- Sierra Skypark #2

.

Even though more exceedances at Bakersfield

- Municipal Airport are unlikely to have

occurred, Table A5 explores several potential scenarios as a bound ing exercise . It

shows that for Bakersfield

- Municipal Airport to equal the three

- year average "e" of 0.7

that occurred at Fresno

- Sierra Skypark #2 , it would have had to have experienced two
exceedance days in the first half of 2012. Table A4 shows that J une 16 was the next

highest estimated daily maximum at 0.1206 ppm. While we cannot dismiss with one hundred percent confidence that June 16 did not exceed the standard, assuming that

June 16 did exceed

, the three

- year average "e" at Bakersfield

- Municipal Airport would

still have met the standard with a value equivalent to that of Fresno

- Sierra Skypark #2

. No other days can reasonably be considered to have exceeded the standard. For the

site to have violated the standard, Table A5 shows that there would h ave had to have
been at least four exceedance days in the first half of 2012. It's extremely unlikely that

that occurred.

This evaluation assumes the worst case scenario, i.e., that the maximum difference
applies between the sites on all days. Given that , it is reasonable to conclude that

Bakersfield

- Municipal Airport may have exceeded the standard on only one day in the

first half of 2012. As a result, at worst, the three

- year average "e" for

Bakersfield

- Municipal Airport in 2012

- 2014 did not violate th e standard.

Therefore, this analysis demonstrates that Fresno

- Sierra Skypark #2 was the site with

the highest expected exceedances in 2012

- 2014 and that it did not violate the standard.
Our upper bound estimate of that site's three

- year average "e" is 0.7, which attains the
standard. Further, the missing data from Bakersfield

- Municipal Airport was unlikely to

have included enough daily 1

- hour maxima above the standard to supplant

Fresno

- Sierra Skypark #2 as the site with the highest three

- year average "e".

### A

- 8

2013

- 2015 Preliminary Estimated Expected Number of Exceedance Days

Table A6

, Estimated Expected Number of Exceedance Day s, 2013

- 2015

, calculates

preliminary three

- year average estimated expected number of exceedance days for all
sites in the San Joaquin Valley for the 2013 through 2015 period. It uses official data

for 2013 and 2014. The 2015 data are a mixture of official and preliminary data. The

extent of the official data record in 2015 varies from site

- to

- site.

Table A6

. Estimated Expected Number of Exceedance Day s, 2013

- 2015

n z v A e Avg e

County Site 2013 2014 2015 2013 2014 2015 2013 2014 2015 2013 2014 2015 2013 2014 2015

Fresno Clovis

- N Villa

Avenue 343 331 341 4 9 6 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Fresno Fresno

- Drummond

Street 359 356 340 4 3 11 0 0 1 0 0 0.041 0.0 0.0 1.0 0.3

Fresno Fresno

- Garland 358 355 356 7 3 5 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Fresno Fresno

- Sierra

Skypark #2 348 332 350 3 8 8 0 1 0 0 0.075 0 0.0 1.1 0.0 0.4

Fresno Parlier 344 347 343 4 5 9 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Fresno Tranquility

- 32650

West Adams Avenue 354 326 344 1 8 4 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Arvin

- Di Giorgio 362 362 351 3 2 5 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Bakersfield

- 5558

California Avenue 315 310 355 2 5 4 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Bakersfield

Municipal Airport 331 352 358 9 9 5 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Edison 362 307 334 3 4 3 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Maricopa

- Stanislaus

Street 340 354 354 1 4 4 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Oildale

- 3311 Manor

Street 356 357 340 3 4 6 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kern Shafter

- Walker

Street 282 363 359 1 2 4 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Kings Hanford

- S Irwin

Street 331 349 361 9 14 4 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Madera Madera

- 28261

Avenue 14 335 343 356 12 8 7 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Madera Madera

- Pump Yard 331 340 337 14 12 8 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Merced Merced

- S Coffee

Avenue 344 355 330 3 6 7 0 0 0 0 0 0 0.0 0.0 0.0 0.0

San

Joaquin Stockton

- Hazelton

Street 330 360 357 2 5 3 0 0 0 0 0 0 0.0 0.0 0.0 0.0

San

Joaquin Tracy

- Airport 283 346 354 2 4 5 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Stanislaus Modesto

- 14th

Street 358 364 358 3 1 1 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Stanislaus Turlock

- S Minaret

Street 354 326 347 3 12 8 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Tulare Porterville

- 1839

Newcomb Street 341 346 338 5 6 5 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Tulare Sequoia and Kings

Canyon Natl Park 333 350 349 2 3 3 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Tulare Sequoia Natl Park

Lower Kaweah 296 189 309 2 2 2 0 0 0 0 0 0 0.0 0.0 0.0 0.0

Tulare Visalia

- N Church

Street 356 356 352 9 1 2 0 0 0 0 0 0 0.0 0.0 0.0 0.0

### A

- 9

The terms used in Table A6 are those def ined in F ormula 1 of Appendix H : e = v + [(v/n) * (N

- n

- z)]

where:

"n" is the number of days with valid daily 1

- hour maxima,

"z" is the number of days assumed to be less than the level of the standard,

"v" is the number of daily 1

- hour maxima above the level of the standard,

"e" is the estimated expected number of exceedance s, rounded to one decimal

place, and

"N" is the number of req uired monitoring days in the year (for San Joaquin Valley,

"N" is the number of days in the year, always 365 in Table A6 ).

In addition, Table A6 lists:

"A" , which is the missing day adjustment (i.e., the [(v/n) * (N

- n

- z)] part of

formula 1), and

"Avg e" , which is the three

- year average of the yearly "e" values, rounded to one

decimal place.

At least 272 days with a valid daily one

- hour maximum are required for a year to be
considered complete. All site/years shown in Table A6 are complete, except fo r Sequoia National Park

- Lower Kaweah in 201 4

. In that year, the Sequoia National Park

Lower Kaweah site had no ozone data before April 24 and after October 31. It is

unlikely that any ozone exceedances occurred there during those missing parts of the

yea r.

The values shown under "z" in Table A6 include only those days that can be excused by
rule (see Paragraph 5 of Part 3 of Appendix H). No other missing days are included in

"z".

If we compare this Table A6 to the analogous Table A 1 shown in Part 1 of this Appendix
(which shows the 2012

- 2014 period), we see that the maximum three

- year average "e"

drops from 0.7 for the 2012

- 2014 period to 0.4 for the 2013

- 2015 period. The

three

- year average "e" values for Fresno

- Garland and for Parlier drop from 0.3 to 0.0

, and the three

- year average "e" value at Fresno

- Drummond Street remain s at 0.3 . The

three

- year average "e" for the 2012

- 2014 period's maximum site,

Fresno

- Sierra Skypark #2 , drops from 0.7 to 0.4.

Based on our assumptions about the last three months of 2015 and the use of

preliminary data, it appears that the three

- year average "e" for the 2013

- 2015 period will

improve over that for the 2012

- 2014 period.

### A

- 10 This page intentionally left blank

### B

- 1 Appendix B

Estimated Design Values and Expected Number of Exceedance Days

at Arvin

- Bear Mountain

Introduction

The Arvin

- Bear Mountain ozone monitoring station ceased operating in late 2010 at the
end of the ozone season. Because high ozone levels had often been measured at

Arvin

- Bear Mountain , several methods were developed to estimate daily maximum

1

- hour ozone values following the si te’s closure in 2010. From the estimated daily data,

design values and estimated expected number of exceedance days to support

attainment of the national 1

- hour ozone standard could then be estimated . The most
useful of these methods rely on linear relat ionships between daily ozone measurements

at Arvin

- Bear Mountain and at two nearby sites, Arvin

- Di Giorgio and Edison , with

Arvin

- Di Giorgio

- based estimates proving to be the most reliable

.

Methods for Estimating Design Values

The most compelling way to estimate Arvin

- Bear Mountain design values is to assume

that prior relationships between measured ozone data at Arvin

- Bear Mountain and at

other sites would continue as they once did. The site closest to the former

Arvin

- Bear Mo untain location is Arvin

- Di Giorgio (~ 2 miles) and the second closest is

Edison (~ 10 miles). Overall, the tendency is for ozone at all three locations to increase

and decrease together day

- to

- day and year

- to

- year. Design value estimation methods

rely o n this fact.

Design value estimation methods were prepared by staff of the California Air Resources

Board (ARB) and by the San Joaquin Valley Air Pollution Control District District ). The
primary methods developed by each group rely on “linear regression ” (a straight

- line
model fitted to a scatter plot) to relate daily ozone values at Arvin

- Bear Mountain to daily

ozone values at Arvin

- Di Giorgio or Edison . However, significant details of the various

methods differ, resulting in different estimated design values that are subject to different

levels of uncertainty.

Two statistical issues connected with methods used by ARB staff or District staff are presented here as a foundation for subsequent discussions.

Statistical Issue #1: The impact of variability on linear regression

 When two variables, X a predictor variable and Y a predicted
variable, are related by a straight regression line, the slope of the

line tends to decrease as variation that affects the “X” variable

increases.

Variability in environmental data usually affects both the X and Y coordinates on scatter

plots. If X and Y represent two ozone monitors, the data from both are typically affected

by similar causes of random variation. Figures B1a, B1b, and B1c below show how

### B

- 2

increasin g random variability affecting the “X” variable causes regression slopes to be

increasingly biased toward zero. The underlying linear relationship is exactly the same

in all three cases, but increasing random variabil ity (5 percent, 10 percent, and

15 per cent) was added to the X and Y data. The “true” slope (behind the scenes) is

one, but the slopes of the regression lines are 0.9682, 0.8695, and 0.7652. As noted in

the titles of the charts, average slopes for 190 simulated cases were < 0.97 for 5

percen t noise, < 0.88 for 10 percent noise, and < 0.78 for 15 percent noise.

This characteristic of linear regression is natural to the classic, “least squares”,

regression method of fitting a straight line to a scatter plot. If one application is subject

to s ubstantially less variation affecting the “X” variable compared to a second

application, the first application is likely to produce preferable, more accurate,

estimates.

Figure B1a

### B

- 3 Figure B1b

Figure B1c

### B

- 4 Statistical Issue #2: Conventional evaluation of the uncertainty of a

predicted value based on linear regression

 Many statistics textbooks provide the formula in the box below for use in
assessing the uncertainty of a predicted “y” value based on a straight

- line
model fitted to a scatter plot of (x,y) data pairs.

o is an individual predicted (unobserved) y coordinate

o S(y) is the standard error of an individual predicted y

coordinate, when the corresponding x coordinate is x*

o s (to the right of the “=”) is the standard deviation of all the

residuals in the sample of data used to fit the line;

calculated as follows, s having (n

– 2) degrees of freedom:

o x* is the x

- value used to calculate , the predicted value for

the unknown y coordinate, by using it in the equation for the

fitted straight line, y = mx* + b

o n is the number of (x,y) pairs in the sample used to fit the line

o is the mean of all the “x” coordinates in the sample

o The denominator of the fra ction inside the radical is the sum of

squared deviations of the x coordinates from their mean ( );

which means that the more spread out the x coordinates are in

the sample, the more reliable is the slope of the fitted line and

the more reliable is the predicted value

The above formula is a standard approach that takes into account (1) the uncertainty in

the distance of an unknown y value from the line, (2) the uncertainty in the mean of all

the y coordinates, which moves the entire line up or down, (3) the uncertainty in the

slope, and (4) the effect of the position of the x* value in relation to the center (mean) of

the “x” coordinates; the further x* is from the center of the “x” domain, the less reliable is

the predicted value. This method used to assess uncertainty in regression estimates as
carried out by the U.S. EPA and the San Joaquin Valley.

### B

- 5

A shortcoming of this standard approach is that the resulting straight line is optimized

for the specific sample and for the assumed underlying model . Uncertainty within the
optimized model commonly understates the uncertainty for the non

- optimal real

- world,
where biases such as those shown above (see Statistical Issue #1: The impact of

variability on linear regression) are involved.

In addition, confidence intervals that build on the formula must rely on an assumed
distribution, usually “t” or “z” (standard normal), for the residuals around the line. These

assumed distributions, though used conventionally, may not be appropriate.

A RB Methods for Estimating Design Values

ARB staff used well

- established methods to estimate the ranked values for daily

maximum 1

- hour ozone at Arvin

- Bear Mountain for years following the site ’ s closure at
the end of the 2010 ozone season. The following methods and applications are

addressed in this section :

1. Analysis using rank

- by

- rank regression instead of date

- by

- date regression

2. “Bootstrap” uncertainty assessment instead of conventional assessment

3. Estimated 2014 design value for Arvin

- Bear Mountain using Top95 rank

- by

- rank

at Arvin

- Di Giorgio in 2010

4. Estimated 2014 design value for Arvin

- Bear Mountain using Top95 rank

- by

- rank

at Edison in 2010

1. Analysis using rank

- by

- rank regression to estimate post

- 2010 design values at

Arvin

- Bear Mountain based on data from Arvin

- Bear Mountain and Arvin

- Di Giorgio

or Edison during years when the sites operated in parallel

In simplified terms, the federal 1

- hour ozone design value for a monitoring site is the

fourth

- ranked (fourth

- highest) daily maximum 1

- hour ozone value measured in a

three

- year period for which the data are 100 percent complete. Because design values

are calculated based on the ranked data for each monitoring site separately, the most
appropriate design value estimates for Arvin

- Bear Mountain are those based on

rank

- by

- rank comparisons to other sites rather than on date

- by

- date comparisons.

Rank

- by

- rank means that the first

- highs, second

- highs, etc., are paired when plotting

the data, though the values in a pair may have been mea sured on different dates.

Rank

- by

- rank comparisons of daily maximum 1

- hour ozone data from

Arvin

- Bear Mountain

, Arvin

- Di Giorgio , and Edison also tend to produce the most

accurate estimates for Arvin

- Bear Mountain design values, because they are subject t o less variation around the regression lines. Figures B2a and B2b illustrate this point.

Figure B2a shows the date

- by

- date relationship between 1

- hour daily max imum ozone

at Arvin

- Bear Mountain and Edison in 2006 (R 2 

### =0.857), leading to a 0.112 ppm predic ted design value for 2014 at Arvin

- Bear Mountain based on Edison ’s design value

of 0.108 ppm for 2014. Figure B2b shows the rank

- by

- rank relationship between 1

- hour

daily maximum ozone at Arvin

- Bear Mountain and Edison in 2006 (R 2 

### =0.985), which

### B

- 6

leads to a 2014 predicted design value of 0.114 ppm for Arvin

- Bear Mountain based on

Edison ’s 2014 DV of 0.108 ppm.

Figure B2a

Figure B2b

### B

- 7

2. “Bootstrap” uncertainty assessment applied to estimated design values based on

rank

- by

- rank regression

ARB staff used a n alternative approach to uncertainty assessment known as “bootstrap”

re

- sampling . This method is appropriate for regression estimates in the manner done

by ARB. Bootstrap uncertainty assessments will be used in this report along with the

“standard ” method discussed above.

Bootstrap methods rely on a simple essential assumption: “the sample looks like the

population from which it came”. Measured air quality data represent the actual air

quality imperfectly. Monitors represent air quality within a spatial scale, though actual

pollutant levels vary within that space. Furthermore, air quality today would have been

different if the relevant and variable emissions had been combined with the relevant and
variable meteorology in a different way. Such c onsiderations lead to an understanding

that the measured air quality data on a particular day at a monitoring site represent a
larger population of possibilities for that particular day. Similarly, the data measured

during a year represent a larger popula tion of possible datasets that could have been

measured during that year. The bootstrap assumption in this case is that the collection
of measured daily values has characteristics that make it look like the larger population

of possibilities from which th e measured data actually came.

It is not possible to go back in time to measure more values from a previous year. But,
we can go back and take new random samples (bootstrap samples) from our measured

data. Because the measured data look like the larger population, the bootstrap samples
are treated like additional measured samples from that previous year. For each

bootstrap sample, we can recalculate things like design values, exceedance days,

per

- capita exposure, etc. If we re

- sample and recalculate ma ny times, the distribution
of the resulting statistics (design values, etc.) can be used to assess uncertainty in our

original statistic that was based on the actual measured data.

The key to a good bootstrap analysis of uncertainty is an appropriate way of generating

bootstrap samples from the basic dataset of measured values.

3. Final estimated 2014 design value for Arvin

- Bear Mountain using rank

- by

- rank
regression of the Top95 daily maximum 1

- hour ozone for 2010 at

Arvin

- Bear Mountain (y

- axis) and Arvin

- Di Giorgio (x

- axis) with a bootstrap

assessment of uncertainty

ARB conducted rank

- by

- rank regression analysis of daily maximum 1

- hour ozone for

Arvin

- Bear Mountain vs Arvin

- Di Giorgio and Arvin

- Bear Mountain vs Edison . Although

design values are ba sed on the highest one to two percent of the data distribution, the

form of the federal standard is based on the expected number of exceedance days, for

which U.S. EPA staff needs estimated daily maxima far down into the distribution. ARB

chose to estimat e daily maximum 1

- hour ozone values when Arvin

- Di Giorgio data were

as low as 0.070 ppm in 2010. This led to rank

- by

- rank analysis of the highest 95 values

(Top95).

### B

- 8

Figure B3 shows the linear relationship between the Top95 daily maximum 1

- hour

ozone meas urements at Arvin

- Bear Mountain and at Arvin

- Di Giorgio during the 2010

ozone season plotted rank

- by

- rank (solid circles) . The figure also shows the Top95

daily maximum 1

- hour ozone plotted date

- by

- date (open circles). The Top95 values are

~ 0.070 ppm an d higher at Arvin

- Di Giorgio . Data for August 25, 2010

, are not plotted

because the monitor at Arvin

- Di Giorgio did not record hourly data for the high

- ozone portion of the day. When Arvin

- Di Giorgio is set to 0.109 ppm, the 2014 design value

for Arvin

- D i Giorgio , the estimated design value for Arvin

- Bear Mountain is 0.117 ppm. To assess the uncertainty of this estimated design value, ARB conducted an

appropriate bootstrap analysis.

Figure B 3

The bootstrap analysis used ten blocks of ten ranks each, covering the Top100 daily

maximum values, rank

- by

- rank , for Arvin

- Bear Mountain and Arvin

- Di Giorgio . Ten

random values were resampled from each of the ten blocks, and the lowest five values

were d ropped, with the remaining 95 values representing a resampled “Top95”. A

straight line was fit to the data and the equation was used to estimate the Top95 values

for Arvin

- Bear Mountain in 2012, 2013, and 2014 based on the Top95 measured values

at Arvin

- D i Giorgio for each of those years. The “root mean square error” (RMSE) was

also calculated, together with the 95 estimated values. This procedure was repeated

10

, 000 times.

### B

- 9

Based on the 10

, 000 bootstrapped samples, the uncertainty in the estimated 0.117 ppm design value for Arvin

- Bear Mountain in 2014 is calculated to be between 0.0021 ppm (2013 and 2014 data) and 0.0024 ppm (2012 data ). Table B1 shows relevant
uncertainty results from ARB’s boostrap analysis. A RB used the 0.0024 ppm value

when applyin g uncertainty.

Table B1

. Bootstrap Uncertainty (in ppm) for Arvin

- Bear Mountain ’s Estimated

2014 Design Value Based on Top95 Rank

- by

- Rank Regression

for Arvin

- Bear Mountain and Arvin

- Di Giorgio in 2010
(Relevant values are those in the row labeled “Total ”)

Year of daily estimates  2012 2013 2014

Uncertainty of line** 0.0011* 0.0008 0.0008

Unce rtainty around line*** 0.0013 0.0013 0.0013

Total 0.0024 0.0021 0.0021

* Each reported number is base d on 10,000 bootstrap samples.

** “Uncertainty of line” is e valuated at maximum (rank #1).

*** Uncertainty around line is the mean of RMSEs.



### 4. Evaluation of a 2014 estimated design value for Arvin

- Bear Mountain using

rank

- by

- rank regression of the Top95 daily maximum 1

- hour ozone in 2010 at

Arvin

- Bear Mountain (y

- axis) and Edison (x

- axis) with a bootstrap assessment of

uncertainty

A rank

- by

- rank regression analysis of the Top 95 daily maximum 1

- hour ozone values at

Arvin

- Bear Mountain and at Edison is illustrated in Figure B4 . The rank

- by

- rank

relationship is somewhat less consistent for Arvin

- Bear Mountain vs Edison (Figure B4
solid circles) than it is for Arvin

- Bear Mountain vs Arvin

- Di Giorgio (Figure B3 solid
circles). In addition, the date

- by

- date relationship for Arvin

- Bear Mountain and Edison is

much more variable around the line (Figure B4 open circles with R 2



### = 0.6926) compared

to the date

- by

- date relationship for Arvin

- Bear Mountain and Arvin

- Di Giorgio (Figure B3

open circles with R 2



### = 0.874). Based on the 2010 rank

- by

- rank relation ship between

Arvin

- Bear Mountain and Edison and on Edison ’s 0.108 ppm design value in 2014, the

estimated 2014 Arvin

- Bear Mountain design value is 0.110 ppm.

Table B2 provides bootstrap estimates of the uncertainties of estimated

Arvin

- Bear Mountain desig n values based on 10

, 000 bootstrap samples with

rank

- by

- rank regression analyses of the Top95 values at Arvin

- Bear Mountain and

Edison for 2010. As shown in Table B 2 , the uncertainty in the estimated 2014 design

values for Arvin

- Bear Mountain is calculate d to be between 0.0034 ppm (2013 data) and

0.0039 ppm (2012 data). A RB used the 0.0039 ppm value when applying uncertainty.

ARB staff recommends assessments of attainment at Arvin

- Bear Mountain after 2010

be based on the 2010 relationship between Arvin

- Bear Mountain and Arvin

- Di Giorgio

for these three reasons: (1) Arvin

- Di Giorgio is much nearer to Arvin

- Bear Mountain ; (2) uncertainties in estimated daily maximum 1

- hour ozone at Arvin

- Bear Mountain are significantly larger when based on Edison data in 2010, the most recent available year,

### B

- 10

and (3) the estimated Arvin

- Bear Mountain design value in 2014 based on Edison is

substantially lower (0.110 ppm) , and thus less conservative, compared to the estimated

Arvin

- Bear Mountain design value based on Arvin

- D i Giorgio (0.117 ppm).

Figure B 4

Table B 2

. Bootstrap Uncertainty (in ppm)

for Estimated 2014 Arvin

- Bear Mountain

Design Values Based on Top95 Rank

- by

- R ank Regression

for Arvin

- Bear Mountain and Edison in 2010
(Relevant values are those in the rows labeled “Total”)

Year of daily estimates  2012 2013 2014

Uncertainty of line** 0.0011* 0.0007 0.0009

Uncertainty around line*** 0.0028 0.0028 0.0028

Total 0.0039 0.0034 0.0037

* Each reported number is based on 10,000 bootstrap samples.

** “Uncertainty of line” is evaluated at maximum (rank #1).

*** Uncertainty around line is the mean of RMSEs.



### Analyses by the San Joaquin Valley District staff are considered below. Note that

results for each of the analyses performed by the two agencies al l projected

Arvin

- Bear Mountain design values meeting the standard.

### B

- 11

San Joaquin Valley District Methods for Estimating Arvin

- Bear Mountain Design

Values

As part of their justification for a Clean Data Determination (CDD)

, District staff
conducted an evaluation of ozone monitoring in the Arvin area (District report,

Attainment Determination Request for the Revoked 1

- H our Ozone Standard, beginning

on page 14).

The District staff’s primary analyses of the parallel monitoring data available for

Arvin

- Bear Mountain and Arvin

- Di Giorgio are shown in Figure 2 and Figure 3 of the

District’s report. For this work, the District staff used date

- by

- date linear regression to

relate daily maximum 1

- hour ozone at Arvin

- Bear Mountain (AB M) to corresponding

values at Arvin

- Di Giorgio (DIG) during the period when both monitors were operating.

The District reported estimated design values and their uncertainties.

In reviewing the District’s regression analyses, ARB staff considered the “le verage”

exerted by influential data points. Leverage is an important consideration in regression
analysis. A standard regression line must pass through the point, where the “x” value is

the mean of the “x” coordinates and the “y” value is the mean of the “y” coordinates.

This point acts as a “fulcrum”. Data points whose “x” coordinates are very low or very

high and are far away from the fulcrum have high leverage to influence the slope of the

line. Data points whose “x” coordinates are near the fulcrum have very little effect on

the slope of the line. For estimating the 2014 Arvin

- Bear Mountain design value, the

District relied on two alternative selections of the 2010 data. In each case, influential

data points exerted high leverage, causing one regr ession line to have a higher slope

than was warranted and the other to have a lower slope than was warranted.

Figure B5a shows the results of a date

- by

- date analysis by the D istrict staff, in which all

available data were used, including data from winter months. Several points with very

low values (shown in the box) exerted significant leverage to drag down the left side of

the line and tip up the right side. The tilted line leads to a predicted 2014 design value

of 0.119 ppm for Arvin

- Bear Mountain with standard error of 0.005 ppm; these values
were included in the district’s CDD request to the U.S. EPA.

ARB refined the analysis by removing the winter data altogether, including those with

high leverage . Because ozone is formed through the photchemical effects of sunlight,

winter data are virtually irrelevant when considering attainment of ozone air quality

standards. Federal rules recognize this point as they allow for the exclusion of winter

days when calculating the estimated expected number of excee dance days on which

attainment is based. Figure B5b shows results comparable to Figure B5a after the

winter data are removed. The slope of the line is no longer tilted upward by the high

leverage winter data, and the estimated 2014 design value for Arvin

- Bear Mountain is

0.117 ppm instead of 0.119 ppm. The standard error of this estimate was 0.004 ppm.

### B

- 12 Figure B 5 a

Figure B 5 b

### B

- 13

Figure B6a shows the results of another date

- by

- date analysis, in which the D istrict staff

selected dates on which the Arvin

- Bear Mountain data were 0.080 ppm or more. A

number of points that would have been at the low end of the Arvin

- Di Giorgio data, the
region of the triangle in Figure B6a , were omitted, together with their leverage. The

points above the triangle reta in and exert their leverage without compensating balance.
Accordingly, the left side of the line is dragged up, which tips down the right side of the

line. This tilted line leads to a predicted 2014 design value of 0.115 ppm for

Arvin

- Bear Mountain with a standard error of 0.005 ppm; these values were also
included in the district’s CDD request to the U.S. EPA.

ARB staff refined the analysis by applying the 0.080 ppm cutoff from Figure B7a to the

Arvin

- Di Giorgio data on the x

- axis instead of the Arvin

- Bear Mountain data on the

y

- axis

. Figure B6b is comparable to Figure B6a with the leverage issue removed,
though the range of the data on the X axis is also reduced. The analysis in Figure B6b

lea ds to a predicted 2014 design value of 0.116 ppm for Arvin

- Bear Mountain with a

standard error of 0.005 ppm.

Figure B 6 a

### B

- 14 Figure B 6 b

Table B3 provides a summary of the District estimates of 2014 Arvin

- Bear Mountain
design values based on the District’s report submitted to the U.S. EPA and to the ARB,

together with supporting spreadsheet analyses that the District staff shared with ARB.

Table B3

. Summary of District Estimates

of 2014 Arvin

- Bear Mountain Design Values

Agency Parallel Site Used Data Used Estimated

Value Uncertainty

San Joaquin Valley Arvin

- Di Giorgio All parallel

monitoring data

2009

- 2010 0.119 ppm 0.005 ppm

ARB refinement Arvin

- Di Giorgio 2010 parallel

data for

May

– October 0.117 ppm 0.004 ppm

San Joaquin Valley Arvin

- Di Giorgio 2010 parallel

data when ABM

>= 0.080 ppm 0.115 ppm 0.005 ppm

ARB refinement Arvin

- Di Giorgio 2010 parallel

data when DIG

>= 0.080 ppm 0.116 ppm 0.005 ppm

### B

- 15

ARB Methods for Estimated Expected Number of Exceedance D ays

The federal 1

- hour ozone standard has an “expected exceedance days” form, for which

a Clean Data Determination requires the estimated expected number of exceedance
days to be 1.0 or lower (when rounded to one decimal place). Because

Arvin

- Bear Mountain ceased operations after the 2010 ozone season, the estimated

expected number of exceedance days must be based on estimated daily maximum

1

- hour ozone values for Arvin

- Bear Mountain

.

The U.S. EPA has clearly stated that estimated daily maximum 1

- hour ozone values are
needed for “all potentially relevant days” at Arvin

- Bear Mountain in order to make a

post

- 2010 Clean Data Determination for the San Joaquin Valley. To this end, estimated

daily values down to approximately 0.070 ppm would provide sufficient confidence tha t

the estimated expected number of exceedance days per year (rounded to one decimal
place) would not exceed 1.0.

ARB prepared estimated daily maximum 1

- hour ozone values for Arvin

- Bear Mountain

down to 0.071 ppm and calculated the estimated expected number of exceedance days

for 2012

- 2014 and for 2013

- 2015 (based in part on preliminary data 2015) to be 0.3 per
year. These results support a Clean Data Determination for the San Joaquin Valley.

Data

For this work, daily maximum 1

- hour ozone data were taken from the “OzoneDailySite”

table in ARB’s ADAM 1 

### database, which draw s hourly ozone data from the AQS
database maintained by the U.S. EPA. Values were set to “missing” if the

“CompleteS tate ” flag was “Incomplete” (more than two missing hours from 9am to 4pm).

This specification is usually more rigorous than the “Complete N ational ” specification.

Methodology

A CDD for the San Joaquin Valley requires estimated daily maxima deep into the

annual distributions. ARB chose to estimate daily maximum 1

- hour ozone values when

Arvin

- Di Giorgio data were ~ 0.070 ppm. To estimate da ily maximum 1

- hour ozone

values deep into the annual distributions, a distribution

- to

- distribution , or rank

- by

- rank

, association is appropriate. These considerations led ARB to use the regression line

based on the Top95 values in 2010 for Arvin

- Bear Mount ain and Arvin

- Di Giorgio , to estimate daily values for 2012 through 2015. The highest 155 values at

Arvin

- Di Giorgio were determined for each year and these were used with the 2010

regression line to estimate the corresponding 155 highest values at

Arvin

- Bear Mountain

.

Figure B7 presents the linear relationship between daily maximum 1

- hour ozone at

Arvin

- Bear Mountain and Arvin

- Di Giorgio in 2010. The rank

- by

- rank equation,

1 Air quality data in ARB’s ADAM database rarely differ from those in U.S. EPA databases.

### B

- 16

ABM
= 1.0348(DIG) + 0.0044 (where "ABM" is Arvin

- Bear Mountain and "DIG" is

Arvin

- Di Giorgio) , was then used to estimate the daily maximum 1

- hour ozone values for

Arvin

- Bear Mountain in 2012

- 2015, which are shown in Table B 9 ( see page B

- 23 ).

Table B 9 shows the highest 155 values for each year to cover estimated daily maxima

at Arvin

- B ear Mountain as low as ~0.070 ppm.

Figure B7

. Relationship B etween D aily M aximum 1

- H our O zone

at Arvin

- Bear Mountain and Arvin

- Di Giorgio in 2010

The first four rows, ranks 1

- 4, of Table B 8 are shown below, with design values

highlighted in pink and exceedances highlighted in blue. The estimated design value for

Arvin

- Bear Mountain during 2012

- 2014 is 0.117 ppm. The uncertainty analysis
discussed earlier in this Appendix, found that the uncertainty (standard error) in the

estimated values at Arvin

- B ear Mountain based on measured data at Arvin

- Di Giorgio is

0.0021 to 0.0024 ppm. The first four rows of Table B8 also show the results for a n upper bound scenario in which 0.0024 ppm uncertainty is added to each of the rank

based estimated values. Based on the augmented values, the design value for 2014,

rounded to three decimal places, is 0.120 ppm. Whether based on the estimated or on

the augmented dat a for 2012

- 2014, the estimated 2014 design value for

Arvin

- Bear Mountain is well below the required 0.124 ppm.

Design values based on measured data from 2012 through 2015 for other sites
throughout the San Joaquin Valley can be found in Table B9.

### B

- 17 Partial Table B 8 ( see page s B

- 2 0 through B

- 2 4 for full table )

Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn. Upper bound scenario :
Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn.

(0.0024 ppm added uncertainty)

Rank in

Year 2012 2013 2014 (prelim)

2015 2012* 2013* 2014* (prelim)

2015*

1 exceed

0.1306 0.1172 0.1172 exceed

0.1336 exceed

0.1330 0.1196 0.1196 exceed

0.1360

2 0.1213 0.1141 0.1172 0.1161 0.1237 0.1165 0.1196 0.1185

3 0.1192 0.1110 0.1161 0.1146 0.1216 0.1134 0.1185 0.1170

4 2014 dv

0.1172 0.1110 0.1161 0.1133 2014 dv

0.1196 0.1134 0.1185 0.1157



### Federal regulations (40 CFR, Part 50, Appendix H and Guidance for the Interpretation
of Ozone Air Quality Standards

- 1979) establish the procedures for determining the

estimated expected number of exceedance days per year. Attainment requires the

average estimated expected number of exceedance days over three consecutive years

to be 1.0 or less. The procedures are n ormally applied to measured daily maximum

1

- hour ozone data. For Arvin

- Bear Mountain , ARB applied the procedures to the

estimated daily maximum 1

- hour ozone values for Arvin

- Bear Mountain in 2012

- 2014,
after rounding the values to three decimal places.

I n 2012

- 2014, data for Arvin

- Di Giorgio were more than 99 percent complete for each

year and for the respective ozone seasons, so the adjustment formula given in federal
regulations is appropriate (see Appendix A). When the formula below was applied to

the estimated Arvin

- Bear Mountain data in Table B8, the estimated expected

exceedance number of exceedance days was found to be 0.3 (see Table B4 below).
This result supports a CDD for the San Joaquin Valley.

e = v + [(v/n) * (N

- n

- z)]

In the equation, "n" represents the number of days with valid daily 1 hour maxima, "z"

represents the number of days assumed to be less than the level of the standard, "v"

represents the number of daily 1 hour maxima above the level of the standard, "e" is the

calculated n umber of exceedance days for each year, and “Avg e” is the estimated
expected number of exceedance days . The term, [(v/n) * (N

- n

- z)] is the missing day
adjustment (called “A” in Table B1), and "N" is the number of required monitoring days

in the year (for the San Joaquin Valley, "N" is the number of days in the year). In Table

B4, "Avg e", the estimated expected number of exceedance days , is the 3 year average
of the yearly "e" values after rounding to 1 decimal place.

Table B4 shows the basis for “e ” when using the estimated daily maxima for

Arvin

- Bear Mountain from 2012

- 2014

. The three

- year average, or estimated expected
number of exceedance days, is 0.3. Whenever a measured value was available at

### B

- 18

Arvin

- Di Giorgio , a calculated value was then avai lable for Arvin

- Bear Mountain . Only

nine missing values occurred at Arvin

- Di Giorgio , which resulted in nine missing

estimated values for Arvin

- Bear Mountain . For this exercise, taking the most
conservative approach, none of the missing Arvin

- Bear Mounta in values were assumed
to be below the standard, though five occurred in winter and two more occurred in May
or October, with low measured ozone on the surrounding days.

Table B 4

. Estimated Expected Number of Exceedance Days in 2012

- 2014

Table B5 s hows an upper bound scenario for the value of “e” in which 0.0024 ppm uncertainty is added to all of the estimated daily maxima for Arvin

- Bear Mountain from

2012

- 2014. The estimated expected number of exceedance days (Avg e) is 0.3 per

year, which is well within the maximum value of 1.0 that would sustain a CDD for the
San Joaquin Valley.

Table B 5

. Estimate of the Expected Number of Exceedance Days in 2012

- 2014
for an Upper Bound Scenario in W hich Uncertainty I s A dded to E ach V alue

Table B6 shows the b asis for “e” when using the estimated daily maxima for

Arvin

- Bear Mountain from 2013

- 2015. Whenever a measured value was available at

Arvin

- Di Giorgio , a calculated value was then available for Arvin

- Bear Mountain . In

2015, 16 missing values occurred at Arvin

- Di Giorgio , which resulted in 16 missing

estimated values for Arvin

- Bear Mountain . Again, the most conservative approach was
used, so none of the missing Arvin

- Bear Mountain values were assumed to be below

the standard, though nine occurred in Febru ary, April, or at the end of October. The

remaining seven values occurred at the end of May ( five days) and in the first half of

June ( two days), when all other values were 0.093 ppm, which is 75 percent of the

0.124 ppm level for the national 1

- hour ozon e standard.

Completeness by quarter in 2015 was 99 percent for the first quarter, 88 percent for the

second quarter, 100 percent for the third quarter, and 95 percent for the fourth quarter
(assuming that November and December will have complete sampling) . So, overall,

### B

- 19

2015 was 96 percent complete. The data from July 1 to October 27, 2015

, are preliminary values, which may change when official data become available.

The estimated expected number of exceedance days for 2013

- 2015 is 0.3, which is well
within the maximum value of 1.0 that would sustain a CDD for the San Joaquin Valley.

Table B 6

. Estimated Expected Number of Exceedance Days in 2013

- 2015

Table B7 shows a n upper bound scenario for “e” in which 0.0024 ppm uncertainty is

added to all of the estimated daily maxima for Arvin

- Bear Mountain from 2013

- 2015.

The estimated expected number of exceedance days was 0.3 per year, which again is
well within the maximum value of 1.0 that would sustain a CDD for the San Joaquin

Valley.

Table B 7

. Estimate of the Expected Number of Exceedance Days in 2013

- 2015

for an Upper Bound Scenario in Which Uncertainty I s A dded to E ach V alue

The estimated data shown in Table B8 indicate that Arvin Bear Mountain is not the site

with the highest ozone in the San Joaquin Valley in 2014. As Table B9 shows, two
monitors in the Fresno area (Clovis and Fresno

- Drummond) had design values of
0.118 ppm, greater than Arvin Bear Mountain’s estimated 0.117 ppm in 2014 (as shown

in Table B8), and another site (Fresno

- Ga rland) had the same value as Arvin Bear

Mountain. Additionally, as shown in Table A1 in Appendix A, one monitor in the Fresno
area (Fresno

- Sierra Skypark #2) had a higher three

- year average estimated expected
number of exceedance days (0.7), and three mon itors (Fresno

- Garland,

Fresno

- Drummond and Parlier) had the same three

- year average estimated expected
number of exceedance days (0.3) as Arvin Bear Mountain in 2014 (as shown in

Table B4).

### B

- 20

Table B 8

. Estimated Daily Maxiumum 1

- H our O zone V alues (ppm)

for 2012

- 2014 at Arvin

- Bear Mountain (ABM)

W here ABM = 1.0348(DIG) + 0.0044

Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn. Upper bound scenario : Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn.
(0.0024 ppm added uncertainty)

Rank in

Year 2012 2013 2014 (prelim)

2015 2012* 2013* 2014* (prelim)

2015*

1 exceed

0. 1306 0.1172 0.1172 exceed

0.1336 exceed

0.1330 0.1196 0.1196 exceed

0.1360

2 0.1213 0.1141 0.1172 0.1161 0.1237 0.1165 0.1196 0.1185

3 0.1192 0.1110 0.1161 0.1146 0.1216 0.1134 0.1185 0.1170

4 2014 dv

0.1172 0.1110 0.1161 0.1133 2014 dv

0.1196 0.1134 0.1185 0.1157

5 0.1172 0.1079 0.1130 0.1111 0.1196 0.1103 0.1154 0.1135

6 0.1151 0.1068 0.1099 0.1089 0.1175 0.1092 0.1123 0.1113

7 0.1141 0.1068 0.1079 0.1089 0.1165 0.1092 0.1103 0.1113

8 0.1120 0.1058 0.1068 0.1080 0.1144 0.1082 0.1092 0.1104

9 0.1120 0.1048 0.1068 0.1059 0.1144 0.1072 0.1092 0.1083

10 0.1099 0.1037 0.1048 0.1054 0.1123 0.1061 0.1072 0.1078

11 0.1099 0.1037 0.1037 0.1053 0.1123 0.1061 0.1061 0.1077

12 0.1089 0.1037 0.1037 0.1047 0.1113 0.1061 0.1061 0.1071

13 0.1089 0.1027 0.1027 0.1045 0.1113 0.1051 0.1051 0.1069

14 0.1079 0.1027 0.1027 0.1041 0.1103 0.1051 0.1051 0.1065

15 0.1079 0.1016 0.1027 0.1037 0.1103 0.1040 0.1051 0.1061

16 0.1079 0.1016 0.1016 0.1031 0.1103 0.1040 0.1040 0.1055

17 0.1068 0.1016 0.1016 0.1016 0.1092 0.1040 0.1040 0.1040

18 0.1068 0.1006 0.1016 0.1015 0.1092 0.1030 0.1040 0.1039

19 0.1068 0.1006 0.1016 0.1015 0.1092 0.1030 0.1040 0.1039

20 0.1068 0.1006 0.1016 0.1008 0.1092 0.1030 0.1040 0.1032

21 0.1068 0.1006 0.1006 0.1007 0.1092 0.1030 0.1030 0.1031

22 0.1058 0.1006 0.1006 0.1007 0.1082 0.1030 0.1030 0.1031

23 0.1058 0.1006 0.0996 0.0997 0.1082 0.1030 0.1020 0.1021

24 0.1058 0.0996 0.0996 0.0995 0.1082 0.1020 0.1020 0.1019

25 0.1048 0.0996 0.0996 0.0988 0.1072 0.1020 0.1020 0.1012

26 0.1048 0.0996 0.0985 0.0976 0.1072 0.1020 0.1009 0.1000

27 0.1037 0.0996 0.0975 0.0975 0.1061 0.1020 0.0999 0.0999

28 0.1037 0.0985 0.0975 0.0965 0.1061 0.1009 0.0999 0.0989

29 0.1037 0.0985 0.0975 0.0954 0.1061 0.1009 0.0999 0.0978

30 0.1037 0.0985 0.0975 0.0954 0.1061 0.1009 0.0999 0.0978

31 0.1027 0.0985 0.0975 0.0950 0.1051 0.1009 0.0999 0.0974

32 0.1016 0.0985 0.0965 0.0950 0.1040 0.1009 0.0989 0.0974

### B

- 21 Table B8 (cont.)

Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn. Upper bound scenario : Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn.
(0.0024 ppm added uncertainty)

Rank in

Year 2012 2013 2014 (prelim)

2015 2012* 2013* 2014* (prelim)

2015*

33 0.1016 0 .0975 0.0965 0.0944 0.1040 0.0999 0.0989 0.0968

34 0.1016 0.0975 0.0965 0.0934 0.1040 0.0999 0.0989 0.0958

35 0.1016 0.0965 0.0954 0.0933 0.1040 0.0989 0.0978 0.0957

36 0.1006 0.0965 0.0954 0.0932 0.1030 0.0989 0.0978 0.0956

37 0.1006 0.0954 0.0954 0.0928 0.1030 0.0978 0.0978 0.0952

38 0.0996 0.0954 0.0954 0.0923 0.1020 0.0978 0.0978 0.0947

39 0.0996 0.0954 0.0944 0.0923 0.1020 0.0978 0.0968 0.0947

40 0.0996 0.0954 0.0944 0.0923 0.1020 0.0978 0.0968 0.0947

41 0.0996 0.0944 0.0944 0.0919 0.1020 0.0968 0.0968 0.0943

42 0.0996 0.0934 0.0944 0.0905 0.1020 0.0958 0.0968 0.0929

43 0.0985 0.0934 0.0944 0.0903 0.1009 0.0958 0.0968 0.0927

44 0.0985 0.0934 0.0944 0.0901 0.1009 0.0958 0.0968 0.0925

45 0.0985 0.0934 0.0934 0.0901 0.1009 0.0958 0.0958 0.0925

46 0.0975 0.0934 0.0934 0.0900 0.0999 0.0958 0.0958 0.0924

47 0.0975 0.0923 0.0934 0.0892 0.0999 0.0947 0.0958 0.0916

48 0.0965 0.0923 0.0923 0.0892 0.0989 0.0947 0.0947 0.0916

49 0.0965 0.0923 0.0923 0.0887 0.0989 0.0947 0.0947 0.0911

50 0.0965 0.0923 0.0923 0.0883 0.0989 0.0947 0.0947 0.0907

51 0.0965 0.0923 0.0923 0.0883 0.0989 0.0947 0.0947 0.0907

52 0.0965 0.0913 0.0923 0.0882 0.0989 0.0937 0.0947 0.0906

53 0.0954 0.0913 0.0913 0.0882 0.0978 0.0937 0.0937 0.0906

54 0.0954 0.0913 0.0913 0.0879 0.0978 0.0937 0.0937 0.0903

55 0.0954 0.0913 0.0913 0.0878 0.0978 0.0937 0.0937 0.0902

56 0.0944 0.0903 0.0913 0.0867 0.0968 0.0927 0.0937 0.0891

57 0.0934 0.0903 0.0913 0.0864 0.0958 0.0927 0.0937 0.0888

58 0.0934 0.0903 0.0913 0.0863 0.0958 0.0927 0.0937 0.0887

59 0.0934 0.0903 0.0913 0.0861 0.0958 0.0927 0.0937 0.0885

60 0.0934 0.0903 0.0903 0.0858 0.0958 0.0927 0.0927 0.0882

61 0.0934 0.0892 0.0903 0.0858 0.0958 0.0916 0.0927 0.0882

62 0.0934 0.0892 0.0903 0.0856 0.0958 0.0916 0.0927 0.0880

63 0.0923 0.0892 0.0903 0.0856 0.0947 0.0916 0.0927 0.0880

64 0.0923 0.0892 0.0903 0.0851 0.0947 0.0916 0.0927 0.0875

65 0.0923 0.0892 0.0903 0.0846 0.0947 0.0916 0.0927 0.0870

66 0.0913 0.0892 0.0892 0.0843 0.0937 0.0916 0.0916 0.0867

67 0.0913 0.0882 0.0892 0.0843 0.0937 0.0906 0.0916 0.0867

68 0.0913 0.0882 0.0892 0.0842 0.0937 0.0906 0.0916 0.0866

### B

- 22 Table B8 (cont.)

Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn. Upper bound scenario : Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn.
(0.0024 ppm added uncertainty)

Rank in

Year 2012 2013 2014 (prelim)

2015 2012* 2013* 2014* (prelim)

2015*

69 0.0913 0 .0882 0.0892 0.0842 0.0937 0.0906 0.0916 0.0866

70 0.0903 0.0882 0.0892 0.0842 0.0927 0.0906 0.0916 0.0866

71 0.0903 0.0872 0.0892 0.0841 0.0927 0.0896 0.0916 0.0865

72 0.0903 0.0872 0.0892 0.0841 0.0927 0.0896 0.0916 0.0865

73 0.0903 0.0872 0.0882 0.0836 0.0927 0.0896 0.0906 0.0860

74 0.0903 0.0872 0.0882 0.0836 0.0927 0.0896 0.0906 0.0860

75 0.0903 0.0872 0.0882 0.0834 0.0927 0.0896 0.0906 0.0858

76 0.0892 0.0872 0.0872 0.0830 0.0916 0.0896 0.0896 0.0854

77 0.0892 0.0872 0.0872 0.0830 0.0916 0.0896 0.0896 0.0854

78 0.0892 0.0861 0.0872 0.0824 0.0916 0.0885 0.0896 0.0848

79 0.0892 0.0861 0.0872 0.0824 0.0916 0.0885 0.0896 0.0848

80 0.0892 0.0851 0.0872 0.0820 0.0916 0.0875 0.0896 0.0844

81 0.0892 0.0851 0.0872 0.0820 0.0916 0.0875 0.0896 0.0844

82 0.0882 0.0851 0.0861 0.0819 0.0906 0.0875 0.0885 0.0843

83 0.0882 0.0851 0.0861 0.0813 0.0906 0.0875 0.0885 0.0837

84 0.0882 0.0851 0.0861 0.0812 0.0906 0.0875 0.0885 0.0836

85 0.0882 0.0851 0.0861 0.0810 0.0906 0.0875 0.0885 0.0834

86 0.0882 0.0851 0.0861 0.0810 0.0906 0.0875 0.0885 0.0834

87 0.0882 0.0851 0.0861 0.0801 0.0906 0.0875 0.0885 0.0825

88 0.0872 0.0841 0.0861 0.0799 0.0896 0.0865 0.0885 0.0823

89 0.0872 0.0841 0.0861 0.0799 0.0896 0.0865 0.0885 0.0823

90 0.0872 0.0841 0.0851 0.0793 0.0896 0.0865 0.0875 0.0817

91 0.0872 0.0830 0.0851 0.0789 0.0896 0.0854 0.0875 0.0813

92 0.0861 0.0830 0.0851 0.0789 0.0885 0.0854 0.0875 0.0813

93 0.0861 0.0830 0.0841 0.0789 0.0885 0.0854 0.0865 0.0813

94 0.0861 0.0820 0.0841 0.0789 0.0885 0.0844 0.0865 0.0813

95 0.0861 0.0820 0.0841 0.0780 0.0885 0.0844 0.0865 0.0804

96 0.0861 0.0820 0.0841 0.0780 0.0885 0.0844 0.0865 0.0804

97 0.0851 0.0820 0.0841 0.0778 0.0875 0.0844 0.0865 0.0802

98 0.0851 0.0820 0.0841 0.0777 0.0875 0.0844 0.0865 0.0801

99 0.0851 0.0820 0.0841 0.0770 0.0875 0.0844 0.0865 0.0794

100 0.0851 0.0820 0.0841 0.0768 0.0875 0.0844 0.0865 0.0792

101 0.0841 0.0820 0.0841 0.0768 0.0865 0.0844 0.0865 0.0792

102 0.0841 0.0820 0.0841 0.0763 0.0865 0.0844 0.0865 0.0787

103 0.0841 0.0810 0.0830 0.0758 0.0865 0.0834 0.0854 0.0782

104 0.0841 0.0810 0.0830 0.0758 0.0865 0.0834 0.0854 0.0782

### B

- 23 Table B8 (cont.)

Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn. Upper bound scenario : Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn.
(0.0024 ppm added uncertainty)

Rank in

Year 2012 2013 2014 (prelim)

2015 2012* 2013* 2014* (prelim)

2015*

105 0.0841 0.0810 0.0830 0.0758 0.0865 0.0834 0.0854 0.0782

106 0.0830 0.0810 0.0830 0.0752 0.0854 0.0834 0.0854 0.0776

107 0.0820 0.0810 0.0830 0.0752 0.0844 0.0834 0.0854 0.0776

108 0.0820 0.0810 0.0830 0.0747 0.0844 0.0834 0.0854 0.0771

109 0.0820 0.0810 0.0830 0.0747 0.0844 0.0834 0.0854 0.0771

110 0.0810 0.0799 0.0820 0.0747 0.0834 0.0823 0.0844 0.0771

111 0.0810 0.0799 0.0820 0.0746 0.0834 0.0823 0.0844 0.0770

112 0.0810 0.0799 0.0820 0.0742 0.0834 0.0823 0.0844 0.0766

113 0.0810 0.0789 0.0820 0.0740 0.0834 0.0813 0.0844 0.0764

114 0.0799 0.0789 0.0820 0.0737 0.0823 0.0813 0.0844 0.0761

115 0.0799 0.0789 0.0820 0.0734 0.0823 0.0813 0.0844 0.0758

116 0.0799 0.0789 0.0820 0.0731 0.0823 0.0813 0.0844 0.0755

117 0.0799 0.0778 0.0810 0.0729 0.0823 0.0802 0.0834 0.0753

118 0.0799 0.0778 0.0810 0.0727 0.0823 0.0802 0.0834 0.0751

119 0.0799 0.0778 0.0810 0.0727 0.0823 0.0802 0.0834 0.0751

120 0.0799 0.0778 0.0810 0.0727 0.0823 0.0802 0.0834 0.0751

121 0.0799 0.0778 0.0810 0.0721 0.0823 0.0802 0.0834 0.0745

122 0.0799 0.0768 0.0810 0.0718 0.0823 0.0792 0.0834 0.0742

123 0.0789 0.0768 0.0810 0.0717 0.0813 0.0792 0.0834 0.0741

124 0.0789 0.0758 0.0810 0.0716 0.0813 0.0782 0.0834 0.0740

125 0.0789 0.0758 0.0799 0.0715 0.0813 0.0782 0.0823 0.0739

126 0.0789 0.0758 0.0799 0.0710 0.0813 0.0782 0.0823 0.0734

127 0.0789 0.0758 0.0799 0.0710 0.0813 0.0782 0.0823 0.0734

128 0.0778 0.0758 0.0789 0.0708 0.0802 0.0782 0.0813 0.0732

129 0.0778 0.0758 0.0789 0.0706 0.0802 0.0782 0.0813 0.0730

130 0.0778 0.0758 0.0789 0.0706 0.0802 0.0782 0.0813 0.0730

131 0.0778 0.0758 0.0789 0.0703 0.0802 0.0782 0.0813 0.0727

132 0.0768 0.0758 0.0789 0.0701 0.0792 0.0782 0.0813 0.0725

133 0.0768 0.0758 0.0789 0.0698 0.0792 0.0782 0.0813 0.0722

134 0.0768 0.0747 0.0789 0.0692 0.0792 0.0771 0.0813 0.0716

135 0.0768 0.0747 0.0789 0.0689 0.0792 0.0771 0.0813 0.0713

136 0.0758 0.0747 0.0789 0.0689 0.0782 0.0771 0.0813 0.0713

137 0.0758 0.0747 0.0789 0.0686 0.0782 0.0771 0.0813 0.0710

138 0.0758 0.0747 0.0778 0.0685 0.0782 0.0771 0.0802 0.0709

139 0.0758 0.0747 0.0778 0.0685 0.0782 0.0771 0.0802 0.0709

140 0.0758 0.0747 0.0778 0.0683 0.0782 0.0771 0.0802 0.0707

### B

- 24 Table B8 (cont.)

Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn. Upper bound scenario : Estimated Daily Max 1

- Hour

Ozone at Arvin

– Bear Mtn.
(0.0024 ppm added uncertainty)

Rank in

Year 2012 2013 2014 (prelim)

2015 2012* 2013* 2014* (prelim)

2015*

141 0.0747 0.0737 0.0778 0.0682 0.0771 0.0761 0.0802 0.0706

142 0.0747 0.0737 0.0778 0.0677 0.0771 0.0761 0.0802 0.0701

143 0.0747 0.0737 0.0778 0.0669 0.0771 0.0761 0.0802 0.0693

144 0.0747 0.0737 0.0768 0.0666 0.0771 0.0761 0.0792 0.0690

145 0.0747 0.0737 0.0768 0.0665 0.0771 0.0761 0.0792 0.0689

146 0.0747 0.0737 0.0768 0.0665 0.0771 0.0761 0.0792 0.0689

147 0.0747 0.0727 0.0758 0.0665 0.0771 0.0751 0.0782 0.0689

148 0.0737 0.0727 0.0758 0.0656 0.0761 0.0751 0.0782 0.0680

149 0.0737 0.0727 0.0758 0.0654 0.0761 0.0751 0.0782 0.0678

150 0.0737 0.0716 0.0758 0.0654 0.0761 0.0740 0.0782 0.0678

151 0.0727 0.0716 0.0758 0.0646 0.0751 0.0740 0.0782 0.0670

152 0.0727 0.0716 0.0758 0.0646 0.0751 0.0740 0.0782 0.0670

153 0.0727 0.0716 0.0758 0.0644 0.0751 0.0740 0.0782 0.0668

154 0.0716 0.0706 0.0758 0.0643 0.0740 0.0730 0.0782 0.0667

155 0.0716 0.0706 0.0758 0.0643 0.0740 0.0730 0.0782 0.0667

### B

- 25

Table B 9

. National 1

- H our Ozone Design Values (ppm) for 2012

- 2015*

at Sites in the San Joaquin Valley Air Basin

2012 2013 2014 2015 (preliminary)* Site

0.118 0.112 0.109 0.109 (S) Arvin

- Di Giorgio

0.104 0.101 0.101 0.099 (S) Bakersfield

- 5558 California

0.120 0.119 0.114 0.111 (S) Bakersfield

- Municipal Airport

0.118 0.113 0.108 0.107 (S) Edison

0.123 0.109 0.104 0.107 (S) Hanford

- S Irwin Street

0.102 0.102 0.090 0.09 0 (S) Maricopa

- Stanislaus Street

0.102 0.099 0.096 0.093 (S) Oildale

- 3311 Manor Street

0.104 0.104 0.099 0.100 (S) Porterville

- 1839 Newcomb St

0.102 0.097 0.098 0.098 (S) Shafter

- Walker Street

0.111 0.102 0.101 0.100 (S) Visalia

- N Church Street

0.130 0.123 0.118 0.116 (C) Clovis

- N Villa Avenue

0.124 0.118 0.117 0. 111 (C) Fresno

- 1st St/Fresno

- Garland

0.127 0.127 0.118 0.107 (C) Fresno

- Drummond Street

0.118 0.114 0.109 0.109 (C) Fresno

- Sierra Skypark #2

0.106 0.102 0.102 0.102 (C) Madera

- 28261 Avenue 14

0.097 0.096 0.100 0.100 (C) Madera

- Pump Yard

0.122 0.118 0.116 0.115 (C) Parlier

0.096 0.091 0.089 0.087 (C) Tranquility

- West Adams Ave

0.110 0.112 0.110 0.104 (E) Sequoia and Kings Canyon NP

0.098 0.101 0.101 0.101 (E) Sequoia NP

- Lower Kaweah

0.108 0.098 0.098 0.098 (N) Merced

- S Coffee Avenue

0.092 0.091 0.093 0.095 (N) Modesto

- 14th Street

0.092 0.086 0.087 0.089 (N) Stockton

- Hazelton Street

0.106 0.099 0.098 0.096 (N) Tracy

- Airport

0.112 0.111 0.106 0.102 (N) Turlock

- S Minaret Street

* D esign V alue s for 2012

- 2014 based on official data; 2015 D esign V alues based on a combination of

preliminary and official data.

** S an J oaquin V alley s ub r egions: S= Southern; C=Central; E=Elevated; N=Northern.

### B

- 26 This page intentionally left blank

### C

- 1 Appendix C
Meteorology, Emissions, and Ozone Chemistry in the San Joaquin Valley

Meteorology in S an J oaquin V alley

The San Joaquin Valley (Valley) is located in the Central Valley of California. The

Valley is in a semi

- arid climate with long, hot, and dry summers, and mild winters. The

Valley is also situated between three mountain ranges that meet in the south of the
Valley near Bakersfield. On the west side of the Valley is the Coast Range, on the east

side is the Sierra Nevada , and to the south are the Tehachapi Mountains . During the

summer season, a high pressure system builds up over the eastern Pacific Ocean and

a thermal low pressure system over the desert in the southwestern United States

produces hot, dry conditions that causes thermally driven wind flow patterns across the
Valley. Such meteorological conditions cause poor dispersion and stagnation which are
conducive to the formation of elevated ozone concentrations in the Valley.

Wind flow patterns play a significant role in the dispersion of air pollutants. Figure C 1
depicts the typical daytime and nighttime wind flow patterns dur ing the ozone season in
the Valley. The dominant wind flow pattern during the daytime in the Valley is from the
northwest to the southeast. Surface winds, known as the Delta Breeze, enter the Valley

from the northwest through the delta passes in the Coas t Range. The airflow generally
moves from Stockton to Bakersfield, carrying ozone and the precursor emissions that

contribute to ozone formation.

The effect of transport is seen in the accumulation of ozone in the central and southern

portions of the Val ley. Historically, the cities of Parlier (downwind of Fresno) and Clovis,

and the communities of Edison and Arvin (downwind of Bakersfield) have often

experienced the highest ozone levels in the Valley. High ozone levels also occur closer

to emission sou rces. In recent years, high ozone levels have also occurred in the cities

of Clovis and Fresno.

At night, the general northwest

- to

- southeast surface wind flow pattern continues along

the western parts of the Valley; however, some nighttime wind circulati on changes also

occur when:

1) The airflow is no longer able to exit the s outhern end of the Valley because it

encounters cooler drainage winds from the surrounding mountains.

2) A nocturnal jet stream approximately 1,000 feet above the surface flows at

speeds up to 33 miles per hour , transporting air into the s outhern portion of the
Valley (over the eastern parts of the Valley); however, the mountains surrounding

the s outhern end of the Valley cause the air to turn counterclockwise and flow

back toward the nort h along the surface e astern edge of the Valley. This flow,

referred to as the Fresno eddy, circulates the pollution plume back toward

Fresno, where it encounters more ozone precursors.

### C

- 2

3) Pollutants carried in the upslope mountain flow during the day via day time

heating are carried back downslope toward the Valley floor via drainage flows

cause d by nocturnal surface cooling.

Figure C 1. San Joaquin Valley W ind P attern s D uring the O zone S eason

Source: http://www.valleyair.org/Air_Quality_Plans/OzoneOneHourPlan2013/05AppendixAAmbientAnalysis.pdf

### C

- 3

Emissions in the S an J oaquin V alley

Anthropogenic emissions trends for NOx and ROG in the San Joaquin Valley are shown

in Figure C 2. Emissions are based on S tate Implementation Plan (SIP) planning

inventory version 1.03 with approved external emission adjustments and do not include
emissions from natural (biogenic) sources. Figure C 2 shows summer emissions of
anthropogenic NOx and ROG from 2000 to 2020 as a p ercent of emissions in 2000.

The figure shows that during 2000

- 2020 anthropogenic NOx is predicted to decrease by
66 percent and ROG by 40 percent.

Figure C 2

. NOx and ROG Emissions Trends for the Valley

The ROG/NOx ratio is an important consideration when planning emissions reduction
strategies. For higher ROG/NOx ratios, ROG emissions reductions will be less effective
in lowering ozone while NOx emissions reductions will be more effective. This is known

as a NOx

- limited regime. A ROG

- limited regim e occurs when the ROG/NOx ratios are
lower, indicating relatively higher NOx emissions. In this regime, ROG emissions
reductions will be more effective than NOx emissions in reducing ozone concentrations.
(In photochemical modeling the ratio of ROG/NOx i s different as it als o includes

biogenic, or natural , emission sources)

.

Figure C 3 shows ROG/NOx emissions ratios for the northern subregion of the Valley
(defined as Merced, Stanislaus, and San Joaquin Counties)

, the central subregion of
the Valley (defi ned as Madera, Fresno, and Kings Counties)

, the southern subregion of
the Valley (defined as Tulare County and the valley portion of Kern County) , and for the

entire Valley.

### C

- 4

Accordingly, the ROG/NOx ratio for anthropogenic emissions in 2020 is expected to be

almost 1.8 times the ratio that prevailed in 2000 in the Valley. The ratio of ambient
ROG to ambient NOx is likely to increase even more, as non

- anthropogenic ROG is the
majority of the total ROG inventory in the Valley for most of the ozone season, w hile

non

- anthropogenic NOx is a tiny fraction of the total NOx inventory. The trend towards
higher ROG/NOx ratios in the Valley indicates that the area will become more

NOx

- limited, thus NOx controls will become increasingly effective for lowering ozone

concentrations. Photochemical modeling in attainment plans includes substantial levels
of biogenic ROG in the San Joaquin Valley. Inclusion of biogenic ROG will further

incr ease ROG/NOx ratios , making NOx emission reductions more effective in lowering

ozone concentrations

.

Figure C 3

. Anthropogenic ROG/NOx E missions R atio Trends
in the Northern, Central, and Southern Subregions of the Valley,

and for the Entire Valley

Sum mer emissions trends (in tons/day) for anthropogenic NOx and ROG for the

n orthern, c entral and s outhern Valley subregions are shown in Figures C 4

- C 6. These
trends show similarities that reflect the Valley

- wide adoption of significant rules

regarding contr ol of NOx and ROG emissions. In the c entral and s outhern subregions
of the Valley, emissions inventories show greater overall reductions in NOx (51 percent

in the n orthern subregion , 53 percent in the c entral subregion , and 56 percent in the

s outhern subregion ) than ROG (32 percent in the n orthern subregion , 36 percent in the

c entral subregion , and 40 percent in the s outhern subregion ) from 2000 to 2014, with
the downward pattern continuing through 2020. In the year 2014, NOx emissions in the

n orthern and s outhern subregions of the Valley were 95 tons/day while in the c entral
subregion of the Valley they were 102 tons/day. Similarly, ROG emissions in the

### C

- 5

n orthern subregion (112 tons/day) and s outhern subregion were almost same
(113 tons/day), while in the c entral subregion they were 99 tons/day. Th e th ree

sub regions of the Valley have shown variation in NOx and ROG emissions that was due
to differences in emission source profiles. The implementation of State and District

emission reduction regulation s have benefitted the Valley’s emissions and air quality.

The ozone levels improved more in the southern subregion than in the central subregion

due to larger emission reductions in the southern subregion, as well as a larger
ROG/NOx ratio change , with th e southern sub region becoming and remaining more responsive to NOx reductions

. Therefore, we expect the highest ozone levels to occur

in the central subregion. Based on the current trends, we expect that ozone would

continue to decline and attainment of the 1

- hour ozone standard would be expected to

continue.

Figure C 4

. Anthropogenic NOx and ROG Emissions Trends

for the Northern Subregion of the Valley

### C

- 6 Figure C 5

. Anthropogenic NOx and ROG Emissions Trends

for the Central S ubregion of the Valley

Figure C 6

. Anthropogenic NOx and ROG Emissions Trends

for the Southern S ubregion of the Valley

### C

- 7

The county

- by

- county trends are shown in Figures C 7 and C 8. The trends have similar
shapes but differ in the magnitude of the emissions, with the highest NOx and ROG

emissions in Fresno and Kern C ounties, respectively. NOx emissions in Fresno and

Kern C ounties follow similar trends with an almost constant difference throughout the
period, while ROG emissions showed declining differences from 2000 to 2009 a nd a

near

- constant difference after that.

The preceding figures showing anthropogenic NOx and ROG emissions in the central
and southern subregions of the Valley in general show consistent emission trends.
Similarities stem from the fact that heavy

- duty t rucks and passenger vehicles, which are
among the top emission source categories in the Valley, are ubiquitous and uniformly

controlled. However, some differences exist in emission trends. These are largely due

to emissions contributions from a number of predominant stationary, areawide, and
other mobile emission source categories which vary in significance between regions.

Figure C 7

. Summer Anthropogenic NOx Emissions by County

### C

- 8 Figure C 8

. Summer Anthropogenic ROG Emissions by County

Ozone Chemistry in the S an J oaquin V alley

Because ozone formation is not a linear function of precursor emission concentrations,

reductions in precursor emissions can have mixed results. Both photochemical

modeling and observational approaches have been used to evaluate the sensitivity of

ozone to volatile organic compound reactivity (VOCR) and NOx. The results of a study
using observational data are relevant to the outlook for the San Joaquin Valley and are

described below.

Pusede and Cohen, 2012 2 

### have studied the effects of temperature, NOx, and VOC R on the frequency of high ozone days in the San Joaquin Valley. The study included

observed data from 1995

- 2010. Monitoring sites for which data were evaluated were

chosen based on location upwind, within , and downwind of three cities. The authors

classified the Valley into Northern, Central, and Southern regions. The assessment was
done to estimate the probability of exceeding the California 8

- hour average ozone
standard of 70.4 parts per billion (ppb)

, which is also relevant to the new federal ozone

standard set in 2015 . The manuscript described changes in the frequency of high

ozone days based on routine observed data as mentioned above to provide direct
insight into the probabilistic response of ozon e to emissions reductions.

2 S. E. Pusede and R. C. Cohen, On the observed response of ozone to NOx and VOC reactivity

reductions in San Joaquin Valley California 1995

– present, Atmos. Chem. Phys. , 12, 8323

- 8339, 2012.

### C

- 9

The authors inferred from the study results that chemical production and not
meteorology dominated the statistics of State standard ozone exceedances in the

Valley. Results also indicate that local ozone production plays a larg er role as the
number of exceedance days increased from upwind to downwind sites which

underscore the importance of controlling local sources of emissions in the Valley.

Over the study period, decreases in VOCR were shown to dramatically reduce the
frequency of exceedance days for the State 8

- hour ozone standard, particularly at
moderate temperatures (28

- 33 ° C). While the publication addressed ozone production

over a range of temperatures, the interactions of ozone precursors at higher

temperatures ( 34

- 45 ° C) is most significant with respect to highest ozone concentrations

and attainment of the federal 1

- hour ozone standard. At these higher temperatures,
ozone production in the Northern and Central regions of the Valley is currently NOx

sensitive. Sim ilarly, at higher temperatures the Southern region of the Valley became

NOx sensitive in the 2007

- 2010 timeframe. The study noted that with NOx reductions

projected to occur in the post

- 2010 timeframe on the basis of local, State and federal

rulemakings, the Valley was poised to experience improved ozone air quality. Indeed,

emission reductions have continued to accrue since 2010 and ozone levels have

responded as predicted in this study.

Pusede and Cohen also showed that the ozone chemistry in the Centr al region in

2007

- 2010 was nearer to peak ozone production than in the Southern region.

Therefore, while NOx emission reductions were expected to result in lower peak ozone
concentrations, progress in the Central region would be outpaced by progress in th e Southern region.

Conclusion

A mbient ozone concentrations in the Valley have declined significantly in last two

decades along with declines in the ozone precursor emissions , a conclusion that is
further corroborated by Pusede and Cohen, 2012 . The emissions trends strongly

suggest that the V alley is becoming increasingly NOx

- limited

, especially in the c entral

and s outhern subregions Valley. The implementation of State and District regulations

and effective plans have significantly decrease d ozone precursor emissions.
Reductions in NOx are the key factor in improved federal 1

- hour ozone levels in the

central and southern subregions of the Valley, which have transitioned to NOx

- limited
conditions on days when temperatures are highest. Continu ed emission reductions
programmed in SIPs and required by regulations or effected through other mechanisms

such as incentive programs, will continue to drive down peak ozone levels in the Valley.