Ozone NAAQS Benefits Analysis: California Crops 

Table of Contents 

loO INTRODUCTION o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o 1 

2o0 BACKGROUND: STUDIES OF OZONE IMPACTS ON CALIFORNIA 

AGRICULTURE .................................................... 3 

2.1 Introduction ..................................................... 3 

2.2 Howitt et al., 1984. . .............................................. 6 

2.3 Olszyk et al., 1988(a) .............................................. 8 

2.4 Olszyk, et al., 1988(b ). . .......................................... 11 

2.5 Howitt and Goodman, 1989 ....................................... 13 

2.6 Winer et al., 1990 ................................................ 14 

2. 7 Air Resources Board. 1992. . ...................................... 18 

3o0 YIELD CHANGE ESTIMATES ...................................... 21 

3.1 Introduction .................................................... 21 

3.2 Exposure-Response Functions ..................................... 21 

3.3 Calculation of Ozone Indices ...................................... 21 

3.4 Calculation ofPercent Change in Yield .............................. 27 

4o0 ECONOMIC MODELING o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o 30 

5.0 RESULTS .......................................................... 32 

REFERENCES ..................................................... -......... 35 

APPENDIX 1: BENEFITS ESTIMATES BY CROP . o. o. o o o. o o o o o o o o o o. o o ••• o o o A-1 

Abt Associates Inc. July 5, 1995 Page i · California Crops Benefits Methodology 
OZONE NAAQS BENEFIT ANALYSIS: CALIFORNIA CROPS 

1.0 INTRODUCTION 

To date, estimation of the agricultural benefits of ozone NAAQS has been limited to 

commodity crops, such as com, soybeans, wheat, and cotton. National agricultural sector models 

do not currently support the analysis ofthe impacts on changes in supply or cost ofnoncommodity 

crops, such as fruits or vegetables. These crops are economically important in two ways, however. 

On a national scale, the value of fruit and vegetable production was nearly $20.8 billion in 1990 (the 

base year for this ozone NAAQS benefit analysis) (USDA 1994), compared to $62.4 billion for 

commodity crops in that year (USDA 1994). Fruits and vegetables are also an important component 

of several regional economies. As an indication ofthe potential importance of fruits and vegetables 

to regional economies, California alone accounted for 52 percent of the value of U.S. vegetable crop 

production in 1990 (USDA 1995), as well as 46.4 percent of the 1990 value of citrus production and 

55.6 percent ofthe 1990 noncitrus value offruit production (USDA 1993). · 

Because of the significance of the fruit and vegetable sector of the agricultural market, and 

because of California's dominance of this sector, this analysis was conducted to estimate the 

potential changes in the California agricultural economy due to proposed Ozone NAAQS. The 

objective ofthis analysis is to evaluate changes in the production of fruit, vegetable, and commodity 

crops in California due to ozone NAAQS, and to estimate the economic value of these changes in 

production .. The results of this analysis will not provide a national estimate of the impacts of ozone 

NAAQS on the fruit and vegetable sector, but will provide an indication of the potential magnitude 

ofthese benefits. 

This analysis evaluates several different levels of standards: five primary standards as well as 

three secondary standards. The secondary standards used in this analysis are defined in terms of 

levels ofprotection of agricultural crops. The W126 index of ozone was selected by OAQPS as the 

best indicator of exposure for agricultural crops, primarily because it is cumulative and puts more 

emphasis on peaks, but does not completely ignore the effect of low levels of ozone. Using all 

NCLAN exposure~response functions for which adequate data are available, a composite W126 

exposure-response function can be defined. This function can be used to calculate the level of ozone 

associated with different levels of crop loss. The levels of maximum permissible crop loss selected 

to be the basis for secondary standards are 30 percent, 20 percent, and 10 percent loss of 50 percent 

or more of the crops included in the composite function. The specific standards evaluated are 

reported below: 

Primary Standards: 

• 0.12 ppm second highest daily mean (2hdm) 1-hr (current primary standard) 

• 0.10 ppm second highest daily mean (2hdm) 1-hr 

• 0.09 ppm 8-hr daily maximum average 

Aht Associates Inc. July 5, 1995 Page 1 California Crops Benefits Methodology 
• 0.08 ppm 8-hr daily maximum average 

• 0.07 ppm 8-hr daily maximum average 

Secondary Standards: 

• 47.9 ppm-hr W126 index (maximum of30 percent yi~ld loss) 

• 34.9 ppm-hr W126 index (maximum of20 percent yield loss) 

• 21.0 ppm-hr W126 index (maximum of 10 percent yield loss) 

The secondary standards were evaluated in relation to assuming compliance with a primary standard, 

resulting in five sets of secondary standard analyses (e.g., secondary standards compared to 

attainment of a 0.12 ppm 1-hr primary standard; secondary standards compared to attainment of a 

0.10 ppm 1-hr primary standard; and so on). 

One feature of this analysis that is important to note is that the form ofthe ozone index used 

is relatively new to benefits analysis. As a result, the indices evaluated in this study are not directly 

comparable to those evaluated in previous ozone benefits analyses, such as those described in 

Section 2, below. In addition, the selection of a W 126 standard determined how available exposureresponse studies could be used. These issues are discussed in more detail in Section 3, as part of the 

analysis required to estimate yield changes. 

Section 2 summarizes the results of studies on the impact of ozone on California agriculture 

that have been conducted to date. Sections 3 through 4 describe the steps involved in this analysis, 

and Section 5 reports its results. Exhibit 1 graphically presents the steps and requirements for this 

analysis, including the general areas of estimating ozone concentrations, predicting yield changes, 

and estimating economic impacts. 

2.0 BACKGROUND: STUDIES OF OZONE IMPACTS ON CALIFORNIA 

AGRICULTURE 

2.1 Introduction 

A number of studies have been conducted in California evaluating the impact of ozone on 

agricultural crops and on the agricultural economy. This review summarizes those studies, with 

particular emphasis on (1) the form of ozone standard(s) evaluated; (2) the sources and forms of 

exposure-response models used; (3) the yield change results obtained; and (4) the economic impact 

results obtained, if any. The studies are presented in chronological order. Two studies were not 

included in this review because they relied on regression analyses, rather than exposure-response 

analyses, and were limited in their geographic scope (Leung et al., 1982; Rowe and Chestnut, 

1985). 

Abt Associates Inc. July 5, 1995 Page2 California Crops Benefits Methodology 

u 

' 
One study (ARB, 1992) provides results for the same base year as current NAAQS 

agricultural benefit analyses, 1990. While most published analyses of the impacts of ozone on 

California agriculture report yield effects relative to a defined level of "clean air", this study 

evaluated the economic impact of various standards relative to an ambient baseline. The ARB 

report presents the results of an analysis using 1990 ozone data and a 1990 economic baseline to 

evaluate the impact of two ozone standards relative to the baseline. The analysis evaluated 

standards that are based on a different ozone index than is being used to define the secondary 

NAAQS under consideration by OAQPS, however, and so its results are not representative of the 

benefits that would be associated with potential secondary N AAQS. This analysis does provide 

a basis for comparing the magnitude of the results obtained for the ozone NAAQS evaluated in 

this study. 

The results of two additional studies (Howitt et al., 1984; Howitt and Goodman, 1989) are 

also potentially pertinent for evaluating the results of this analysis of primary and secondary ozone 

NAAQS. These studies also analyzed a variety of standards relative to an ambient baseline. In 

addition, the levels of standards evaluated are analogous to the primary and secondary NAAQS 

under consideration, because they reflect protection from 10 percent, 20 percent, and 30 percent 

yield loss for 50 percent of crops. Although the levels of protection are the same as those used 

to defme the secondary standards being evaluated in this study, the benefits associated with 7-hr 

seasonal mean standards will differ from those associated with W126 standards because the pattern 

of ozone concentrations, and associated plant responses, will differ. There are two additional 

limitations to the usefulness of these results for analysis of the benefits associated with primary 

or secondary NAAQS, however. The baselines used in these studies are 1978 (Howitt et al., 

1984) and 1984 (Howitt and Goodman, 1989), making direct comparison with other NAAQSrelated agricultural benefits analyses impossible. An additional limitation of the Howitt et al. 

(1984) analysis is that it is limited to NCLAN crops, and so does not incorporate exposureresponse functions available for a variety of important California crops. Finally, although it 

includes a large number of additional crops important to California, Howitt and Goodman's 1989 

analysis does not appear to use exposure-response functions most suitable for analysis of 1990 

conditions (see Winer et al., 1990, for comparison), and does not include a recently published 

exposure-response function representative of stone fruits, a large component of California fruit 

production (Retzlaff et al., 1992). In summary, the results of Howitt et al. (1984) are too dated 

and limited to be. of use in secondary NAAQS analysis. The results obtained by Howitt and 

Goodman ( 1989) could be used as an indication of the magnitude of impacts of potential ozone 

NAAQS in California, but would not be expected to provide the same estimate as an evaluation 

of the proposed NAAQS using the 1990 California Agricultural Resources Model (CARM), with 

all available exposure-response functions. 

Abt Associates Inc. July 5, /995 . Page 3 California Crops Benefits Methodology 
Exhibit 1: Steps in California Crops Ozone Benefits Analysis 

Specify Regulatory Options '· 

• Form of ozone index 

(12-h Wl26) 

• Levels of primary and 

secondary standards 

Identify Exposure-Response Functions 

• Wl26 NCLAN functions if available 

• Identify a priori minimwn and maximwn functions 

• Review alternative functions for crops with no Wl26 functions: 

all indices 

-~ 

~ 

J~· ill 

• Identity ex post minimum and maximwn functions I ~~~·=·~.,=~,~-~,~==~~-~·-~-~~-~·~-.~~··· ~~~_. ................... f:~ 

• Select those that give rational response (inverse 

relationship between ozone concentration and yield) 

I I 

• Calculate median duration if several experiments exist for one crop and index ~~ 

I 

Fonn Ozone Indices 

• Identify experimental duration for each function, if available 

• Identify indices needed for selected functions 

• Identify state or county-level growing season for each crop 

• Use hourly ozone concentrations under each regulatory scenario to calculate index for cropspecific duration and growing season (anchor duration period on harvest) 

Estimate Yield Changes 

• Use calculated ozone index for each scenario in appropriate exposure-response function to 

estimate percent relative yield loss (PRYL) for each crop in each scenario, relative to "clean air" 

• Calculate overall PRYL for each crop between scenario and associated baseline 

• Apply PRYL for each crop to estimate change in per-acre yields for each scenario 

Estimate Change in Economic Surplus 

• Enter new per-acre yields into CARM input table 

• Run baseline CARM 

• Run CARM for each scenario 

- CARM allocates acreage to each crop based on new yield expectations 

-- CARM calculates producer and consumer surplus based on new acreage allocations 

and crop production levels 

I 

w~, 

* 

~~ 

1: 

I 

m· I 

~?-'' 

I 

I 

# 

I 

~:! }: 

-... ~~====~===~==~:::::::=~====~~::::::::~::::::~::::::~~::::::::::~::::::::::~.::::::::=::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::=:::::::::::::::::::=::::::::::::::::::::::~::::::::::::=:::::::::::::::::·::::::::::::::~::::::::=: -

Abt Associates Inc. July 5, 1995 Page4 California Crops Benefits Methodology 
2.2 Howitt et al., 1984. Effects of alternative ozone concentrations and response data on 

economic assessments: the case of California crops. 

Base year: 

Comparison to: 

Exposure-response models used: 

Form of evaluative standard: 

Exposure-response model functional 

form: 

Levels of evaluative standards: 

Air quality data: 

1978; regional ozone concentration baseline 

reported. 

baseline from evaluative standards. 

NCLAN1

; Oshima et al. (1976) (alfalfa). Specific 

models not reported. 

7-hr seasonal mean (ppm), 0900 to 1600 hours. 

various: linear, quadratic, Weibull 

0.04 ppm (improved air quality) 

0.05 ppm (slight degradation of air quality) 

0.08 ppm (significant degradation of air quality) 

EPA Storage and Retrieval of Aerometric Data 

system, and California Air Resources Board data. 

NCLAN studies were used to identify exposure-response functions for crops included in the 

CARM model. NCLAN functions for field corn (Heck et al., 1982; Heck et al., 1983(a); Heck 

et al., 1984(b)), cotton (Heck et al., 1982; Heck et al., 1983(a); Heck et al., 1984(b)), grain 

sorghum (Heck et al., 1984(b)), irrigated wheat (Heck et al., 1982; Heck et al., 1983(a); Heck 

et al., 1984(b)), dry beans (Heck et al., 1.982; Heck et al., 1983(a); Heck et al., 1984(b)), lettuce 

(Heck et al., 1982), and processing tomatoes (Heck et al., 1984(b)) were used. A response 

function for alfalfa was adapted from Oshima et al. (1976). When there were multiple functions 

available for a given crop, individual functions were selected based on significance and goodness 

of fit. Specific functions used were not reported. Several crop response functions were used as 

surrogates for crops that had not been evaluated for ozone response: 

• Irrigated wheat: 

• Lettuce: 

• Proc. tomatoes: 

• Grain sorghum: 

• Hay alfalfa: 

Dryland wheat 

Barley 

Celery 

Onions 

Fresh tomatoes 

Potatoes 

Rice 

Seed alfalfa 

The CARM model includes 25 additional crops for which yield losses were not estimated, 

comprising eight annual crops and 17 perennial crops. 

1

Heck et al., 1982; Heck et al., 1983(a); Heck et al., 1983(b); Heck et al., 1984(b) 

Abt Associates Inc. July 5, 1995 Page5 California Crops Benefits Methodology 
Results 

Howitt et al. do not report the percentage change in yield of individual crops for any of the 

evaluative scenarios, but do report changes (from the 1978 baseline) in production and changes 

in acreage for the 0.04 and the 0.08 scenarios. Since change in production reflects the change 

in yields times the change in acreage, we derived the estimated change in yield for the 0.04 ppm 

scenario and for the 0.08 ppm scenario, presented in Exhibit 2. 

r········--.-... -... -.-......... -.-.-.-.-.-.-.. -.. -.-......................... ·.·····-··········-·····----.-.-......... -.-.-.-. ----·-···············································-······················· -.-.----·-····························--.-.-.-.-.-.-.-... -......... -.-... -... -......... -... -... -........................ -... -....... -.-... -.-..................... -.-.-................... ._.. .................................. . 

j Exhibit 2 I 

;·:·,'· Change in Crop Yields from 1978 Baseline to Two Alternative Concentrations ~~;::·:· (Percent) 

Crop Change to 0.04 ppm Change to 0.08 ppm ~~~ 

~:~~ :d,~d (Impro;~r•nt) (Signm~~ljfrndation) I 

Barley, irrigated 4.5 -13.25 II 

0.90 

Lettuce 5.88 -24.92 

Onions 5.37 -14.79 

Potatoes 2.02 -6.14 

Rice 0.1 -3.99 

Tomatoes, fresh 4. 75 -8.59 

Tomatoes, processing 1.91 -10.82 

Wheat, dry land 1.11 -9.29 

Wheat, irrigated 4.55 -13.3 

~ I 

tt! , Source: Derived from Howitt et al., 1984, Exhibit 4 ("Production" and "Acreage" ~~! 

j data) ~! 

l..&w.m::m:::~=~=~==~=~:::::~;:~:~:::::::::~:;:::::~:::':~:?=:?~:~:':~:=:~=~=~=~=~=~=~==:~:~:~:=:~,,:::~::::::::,~::::::::'{:~:::;:~::,::~::::::::':'=:::::,'::,::':':::::::;,',::::::::::':::::::::':::;:::;:w::::~:=:~=~=~=~=~~=~=~=~:mm:m::;~:~:r:;:i~~=mm~i 

Abt Associates Inc. July 5, 1995 Page6 California Crops Benefits Methodology 
Exhibit 3 P.~e$~nts the change~ in economi~ surpl~ses esti~at~d with the LARM model based 

on estunated y1e10 cnanges. These cnanges m surpmses renect not oruy cnanges m the 13 crops 

for which yield changes could be estimated, but changes in the acreage that are predicted to occur 

as high value crops are allocated more acreage if their yields decrease. 

Exhibit 3 

Changes in Economic Surplus Compared to 1978 Baseline Under Alternative 

California Ozone Concentrations($ Millions) 

Change in Change in Change in Total 

Scenario (Relative 

to 1978 Baseline) . ~o;1ri;r~r Su!!ltls r~i~l~er ~tlo~~1ls .. S (Mi~irplut/o 

0.04 ppm 

(Improvement) 

0.05 ppm (Slight 

Degradation) 

0.08 ppm (Significant 

Degradation) 

13.7 

0.8 

-53.3 

0.52 22.0 

0.03 -3.7 

-2.03 -104.0 

1.28 35.7 0.82 

-0.21 -2.9 -0.07 

-6.04 -157.3 -3.62 

2.3 Olszyk et al., 198S(a). Crop loss assessment for California: Modeling losses with 

different ozone standard scenarios. 

Base year: 

Comparison to: 

Exposure-response 

models used: 

Form of evaluative 

standard: 

Exposure-response 

model functional form: 

Levels of evaluative 

standards: 

Air quality data: 

Abt Associates Inc. July 5, 1995 

1984; baseline ozone concentrations not reported. 

0.025 "clean air" (for 12-hr exposure; 0.027 for 7-hr), from 

baseline and evaluative standards; 0.04 ppm was used as 

background for the > 0.10 ppm scenarios. 

NCLAN (Heck et al., 1984(a)), Heagle et al., (1979) (spinach), 

Thompson and Olszyk, (1986) (alfalfa, grapes, lemons, 

oranges, sweet corn, sugar beets, rice), and McCool et al., 

(1986) (onions, strawberries, fresh tomatoes). Specific models 

used not reported. 

7-hr and/or 12-hr (0800 to 2000 hours) seasonal mean (ppm), 

and maximum hourly concentration. 

not specified. 

12-hr stnd: 0.04 ppm 

0.045 ppm 

0.05 ppm 

0.06 ppm 

1hr stnd: > 0.10 ppm 

7-hr stnd: 0.044 ppm 

0.049 ppm 

0.054 ppm 

0.065 ppm 

California Air Resources Board, Aerometric Data Division. 

Page 7 California Crops Benefits Methodology 
NCLAN studies were used when possible. NCLAN research in California was used for 

barley, cotton, lettuce, and processing tomatoes; research conducted in other regions was used for 

dry beans, field com, sorghum, and wheat (Heck et al., 1984(a)); all these are 7-hr seasonal mean 

functions. A study using protocols similar to NCLAN was used for spinach (Heagle et al., 1979), 

for which a 12-hr seasonal mean function was derived. More limited ozone concentrations for 12-

hr exposures were used in ARB-sponsored research (filtered, half flltered, and ambient) on alfalfa, 

grapes, lemons, oranges, sweet com, and sugar beets (Thompson and Olszyk, 1986). In addition, 

ARB-sponsored research provided data to generate a 7 -hr equation for rice (Thompson and 

Olszyk, 1986). A 12-hr average exposure was used to generate an exposure-response function for 

green onions, which was used for all onions in this analysis (McCool et al., 1986). A cumulative 

function of hourly exposures over 0.10 ppm was used to generate exposure-response functions for 

strawberries and fresh market tomatoes (McCool et al., 1986). Thirty crops in the agricultural 

production database were assumed to have yield changes of zero because no exposure-response 

information was available. 

To model how meeting current standards would be achieved, three different approaches were 

used. All represented compliance with the 1984 California 1-hr oxidant standard of0.10 ppm. 

Specific scenarios were developed as follows: 

• >0.10 = 0.10: peak shaving all hours over 0.10; leaving all other hours unchanged. 

• Modified rollback: proportional rollback, reducing peak at the site to 0.10 ppm and with 

background of 0.04 ppm: 0.04+ {[(hourly value-0.04)*(0.10-0.04)]/(peak-0.04)}. No 

change in site data if no values exceeded 0.10 ppm. 

• Simple rollback: all hourly values reduced proportionately by the change from the 

statewide peak ozone to 0.10 ppm. No change in site data if no values exceeded 0.10 

ppm. 

Alternative 12-hr standards of 0.04, 0.045, 0.05, and 0.06 ppm were modeled for crops and 

counties with conditions exceeding these averages. (Corresponding 7-hr standards of 0.044, 

0.049, 0.054, and 0.065 ppm were also modeled.) 

Results 

Exhibit 4 presents the results of all the scenarios evaluated, in terms of percentage yield 

losses compared to 0. 025 ppm. 

Olszyk et al. (1988(a)) report that using a background level of 0.04 would reduce all losses 

for the simple rollback scenario to zero and would reduce the losses for the 0.045 and 0.05 

standards by approximately 50 percent. 

Abt Associates Inc. July 5, 1995 Page8 California Crops Benefits Methodology 
.• 

: ............................................................................................................................................................................................................................................... ~· 

Exhibit 4 

Crop Losses Associated with 1984 Ambient Ozone and Three Standard Scenarios 

Compared to "Clean" Air, 0.025 ppm (Percent) 

Crop 

! L e at ~ Losses Under Standard Scenarios(%) ·"'\~ : oss s :·····················:··················:;·················:······················:,············••·•oO"•··········::"······························---~···--····---················ ... 

! Ambient i ! -~ ~ ! Peak !Modified! Simple ~ 

:Ozone(%)! 0.04 i 0.045: 0.05 i 0.06 ! t~hOJO !Rollback! Rollback ''' 

··Aii~1i~.h~y··············!···········s·.·9··········I······s:·4······r·····6:·s·····'=······7:'8'····· ······s·:s······1··········s·:6 ......... l' ........ 6:·i·· ....... · ........ 2:·8 ........ .. 

Barley 0 ~ 0 0 0 0 I 0 0 0 

Beans, dry 

Com, field 

Com, silage 

Com, sweet 

Cotton 

Grapes, all 

Lemons 

Lettuce 

Onions, all 

Oranges 

Rice 

Sorghum, grain 

Spinach 

Strawberries 

Sugar beets 

Tomatoes, fresh 

23.5 

1.5 

2.9 

6.1 

18.8 

22.4 

20.4 

0 

24.4 

19.8 

2.2 

0.7 

3.5 

0 

0 

2.9 

11.3 

0.5 

0.6 

3.8 

7.3 

9.8 

12.2 

0 

14.3 

8.9 

1.3 

0.2 

3.5 

0 

0 

14.8 

0.8 

1.1 

4.8 

9.7 

12.9 

15.8 

0 

18.6 

11.8 

1.7 

0.3 

3.5 

0 

0 

2.9 

17.5 

1.1 

1.5 

5.4 

12.2 

15.9 

17.7 

0 

21.4 

14.8 

2.0 

0.4 

3.5 

0 

0 

2.9 

20.9 

1.4 

2.2 

6.1 

16.2 

20.8 

19.8 

0 

24.0 

18.7 

2.1 

0.5 

3.5 

0 

0 

22.7 

1.5 

2.6 

5.9 

18.3 

21.9 

19.1 

0 

23.4 

18.6 

2.2 

0.6 

3.5 

0 

0 

0 

17.2 

0.9 

1.5 

3.6 

12.8 

15.6 

14.0 

0 

15.6 

13.0 

1.9 

0.4 

2.9 

0 

0 

0 

11.7 

0.4 

0.6 

0.7 

8.4 

8.6 

5.2 

0 

5.6 

6.7 

1.6 

0.3 

0.8 

0 

0 

! 'Tomatoes, proc 

j Wheat, all 

4.2 

0.8 

2.9 

0.9 

0.7 

1.4 

0.8 

1.9 

0.8 

2.9 

2.8 

0.8 

3.9 

0.8 

1.8 

0.5 

0 

0.8 

0.1 "l 

I Source: Olszyk et al. 1988(a), Tables 1 and 2. ~i := .. ~.::~::::::::::::::::::~=~.::::~::::::~~==~~~:::::::::::::::~~==~:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::~:::::::::::::::::: 

Abt Associates inc. July 5, 1995 Page9 California Crops Benefits Methodology 
2.4 Olszyk et al., 1988(b). California statewide assessment of the effects of ozone on crop 

productivity. 

Base year: 

Comparison to: 

Exposure-response models used: 

Form of evaluative standard: 

Exposure-response model functional 

form: 

Levels of evaluative standards: 

Air quality data: 

1984; baseline ozone concentrations not reported. 

0.025 "clean air" (for 12-hr exposure; 0.027 for 7-

hr), from baseline. 

see Exhibit 4, above. Specific models used 

reported. 

7-hr and/or 12-hr (0800 to 2000 hours) seasonal 

mean (ppm), and maximum hourly concentration. 

various: linear, Weibull. 

None. 

California Air Resources Board, Aerometric Data 

Division. 

The same studies as used for the Olszyk et al., 1988(a) analysis were apparently used for this 

paper, but are described in more detail. Exhibit 5 provides the citations for the individual 

exposure response functions used. The text notes that equations based on California research were 

used wherever possible, but the specific location of the experiments that generated the equations 

that were used is not reported. In one case (wheat), the cited source is described as an Illinois 

experiment, but an available and similar California result was mentioned in the text, but was not 

used. 

The reported estimated crop losses, comparing ambient conditions with "clean" air (0. 025 

ppm), are the same as reported in Exhibit 4, above. 

The authors list 15 crops that they categorize as potentially at risk from ozone because more 

than 50 percent of the state tonnage was exposed to relatively high levels of ozone during their 

growing season (i.e., 12-hr averages at or over 0.05 ppm): alfalfa seed, asparagus, avocados, 

cantaloupe melons, figs, grapefruit, honeydew melons, lima beans, nectarines, olives, pistachios, 

plums, potatoes, walnuts, and watermelons. No exposure response functions were available toestimate the yield losses associated with these crops. An additional 15 crops were not exposed to 

ozone levels exceeding 0.05 ppm. Of these, three had growing season averages near 0.05 ppm, 

and so "should not be considered as totally without risk at this time": almonds, apricots, and 

peaches. If a year were to experience elevated ozone levels, any of the remaining 12 crops that 

were not generally exposed to high concentrations of ozone during their growing season would 

fall into the "potentially at risk" category as well. 

Abt Associates Inc. July 5, 1995 Page 10 California Crops Benefits Methodology 

·. 
Exhibit 5 

Sources for Exposure-Response Functions Used by Olszyk et al., 1988(b) 

Crop 

NCLAN Studies 

Alfalfa 

Barley 

Beans, dry 

Com, field 

Cotton 

Lettuce 

Sorghum, grain 

Tomatoes, proc. 

Citation Notes 

Temple et al., 1987 Normal irrigation, 1984 

Temple et al., 1985(a) 

Heck et al., 1984(b ); Kohut 

and Laurence, 1983 

Kress and Miller, 1985(b) Used = 11618.5 as mean of 10725 for cv 

"Pioneer 3780" and 12512 for cv "PAG 397" 

Temple et al., 1985(b) 

Temple et al., 1986 

Kress and Miller, 1985(a) 

Heck et al., 1984(b); 

Temple et. al., 1985( c) 

Irrigated cotton, 1981 

Wheat Kress et al., 1985 Illinois experiment. m 

NCLAN-Related Studies ~ 

·: 

Spinach 

Rice 

CARB Studies 

Grapes, all 

Oranges 

Sugar beets 

CDF A Studies 

Onions 

l Strawberries ! Tomatoes, fresh 

! Other Studies 

! Lemons 

j Com, sweet 

Heagle et al., 1979 

Kats et al., 1985(a) 

Brewer, 1983 

Kats et al., 1985(b) 

Brewer, 1978 

McCool et al., 1986 

McCool et al., 1986 

McCool et al., 1986 

Thompson and Taylor, 

1969 

Thompson et al., 1976 

t.~ w 

CARB study analyzed by NCLAN researchers. ~~ Ozone added in 5-hr Monday - Friday period; , .~ 

equation assumed 0.025 ppm ozone ppm for all ~l 

~"' other hours. M 

·~ 

Ozone concentrations calculated from Fresno 

County monitor sites, over 16 km from 

experimental plot; unpublished 1986 data. 

Thompson seedless used for all grapes. 

Unpublished 1986 data. 

Ozone concentrations calculated from Fresno 

County monitor sites, over 16 km from 

experimental plot. 

Recalculated by McCool on a 12-hr basis. 

Original results for green onions, used for all 

omons. 

Cumulative dose> 0.10 ppm. 

Cumulative dose > 0.10 ppm. 

Based on oxidant, not ozone, data from San 

Bernardino, CA. 

Based on 1974 oxidant data from Riverside, 

CA. 

it 

~~ §~ 

~ 

~ u 

~ ~~ 

w I 

.··~ 

~ .. ··;m~~-ru:;:l=~~~=m:~:;r::~:;:~l:;:~=~=~=~=~=~=~=~=~=~=~=~=~=~=~=;=~=~=~=~=~=~n:!:i:i:i:~:i:i:i:i:~:;:l:i:;:;:;:;:;:;:;:;:;:;:;:r;:;:;:;:;:;:;:;:!:;:;:i:i:ri:i:ir:;:rrrrr;:;:;:;:;:r;:;:;:!:;:;:;:i:i:i:i:i:i:i:i:i:i:i:i:i:i:i:i:i:fu:~l~:;~:;:~;:;:;:fu:;:~: ·WJ. mrsUJ.~~ 

Abt Associates Inc. July 5, 1995 Page 11 California Crops Benefits Methodology 
2.5 Howitt and Goodman, 1989. The economic assessment of California field crop losses 

due to air pollution. Report to the California Air Resources Board, Contract No. AS105-32. June. (See also Howitt and Goodman, 1988.) 

Base year: 

Comparison to: 

Exposure-response models used: 

Form of evaluative standard: 

Exposure-response model functional 

form: 

Levels of evaluative standards: 

Air quality data: 

1984; baseline ozone concentrations not reported. 

baseline from evaluative standards. 

Olszyk 1988(a). Specific models used not reported. 

12-hr seasonal mean (ppm). 

various (Olszyk et al., 1988(a)). 

0.025 0.045 0.06 

0.04 0.05 

California Air Resources Board, Aerometric Data 

Division. 

This analysis estimates economic impact of alternative ozone standards compared to the 1984 

baseline (ozone conditions and yield) using CARM model, based on yield response functions from 

Olszyk et al., 1988(a), with two variations: 

• A 0.025 ppm standard was evaluated. 

• A regional standard was evaluated: setting a 0.045 ppm standard for the San Joaquin 

Valley and a 0.05 ppm standard for the rest of the state. 

The 0.045 ppm 12 hr seasonal mean standard is equivalent to a 0.049 ppm 7 hr seasonal mean 

standard, the level at which Tingey et al. ( 1990) indicate a 1 0 percent yield loss for 50 percent of 

crops would be experienced. 

The yield estimates associated with the comparison between baseline and each regulatory 

option were not presented, and cannot be discerned from the results presented in Olszyk et al., 

1988(a). 

Results 

Exhibit 6 presents the statewide benefits associated with seven alternative standards scenarios. 

The authors conclude that because the regional standard (0.045 ppm in the San Joaquin Valley with 

0.05 ppm in the rest of the state) captures 81 percent of the benefits of the stricter standard (0.045 

ppm statewide), with the expectation of lower implementation costs, this approach may be more 

efficient and equitable than adopting the stricter standard on a statewide basis. 

Abt Associates Inc. July 5, 1995 Page 12 California Crops Benefits Methodology 

,, 
........................................................................................................................................................................................... ':-

Exhibit 6 

Economic Benefits Associated with Alternative Ozone Standards 

Compared to 1984 Baseline Conditions 

Alternative Standards 

(12-hr seasonal, statewide Consumer Producer 

unless noted) Surplus Surplus Total 

0.025 ppm 160.0 172.9 332.9 

0.04 ppm 98.1 107.4 205.5 

0.045 ppm 88.2 70.4 158.6 

0.05 ppm State/0.045 ppm SJV 84.0 67.1 151.1 

0.05 ppm 66.2 52.7 118.9 

~: 

:s!~ 

~~ 

., 

§ 

0.06 ppm 26.0 23.9 49.9 ·~ 

Hourly0.10ppm 53.2 48.2 101.3 .~~ 

~1 

Source: Howitt and Goodman, 1989, Tables 3 and 8. . · [!i ··s:::~:::::~:::::::::::::::::::::::::::::::::;:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::':::::::::::::::::::::::::::::::::::::::::::::::::::':::::::::::':::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 

2.6 Winer et al., 1990. Air Quality Impacts on California Agriculture, 1990-2010. 

Base year: 

Comparison to: 

Exposure-response models used: 

Form of evaluative standard: 

Exposure-response model functional 

form: 

Levels of evaluative standards: 

Air quality data: 

1986; forecasts to 1995 and 2010. Ozone 

concentrations not reported, but precursor emissions 

reported. 

0.025 "clean air" from actual and forecasted 

baselines, and from attainment of standard. 

not specified. 

maximum hourly average (ppm) 

not reported. 

0.09ppm. 

California Air Resources Board. 

Using forecasted emissions inventories, this study estimates the impact of ozone on crops in 

the Central Valley of California in the base year of 1986, and future years 1995 and 2010. Emissions 

of"reactive organic gases" (ROG) (similar in composition to VOCs) and NOx were predicted based 

on predicted growth in both mobile and stationary sources. Ozone concentrations are assumed to 

increase in direct proportion to increases in NOx emissions (virtually no change for 1995, and an 

increase of 18 percent for 20 I 0). This increase is applied only to those hours over an assumed 

background level of0.04 ppm. This "worst case" scenario is compared to a "best case" scenario of 

attainment of California's 0.09 ppm highest hourly average ozone standard. Ozone conditions under 

attainment were estimated by a proportional rollback of all hours over 0.04 ppm (assumed 

Abt Associates Inc. July 5, 1995 Page 13 California Crops Benefits Methodology 
background). Yield losses for both cases estimated by comparison against a "clean air" ozone 

concentration of0.025 ppm (12 hr seasonal average). 

The results reported below indicate that exposure-response functions for five crops were used 

that were not available for use by Olszyk et al., 1988(a) or 1988(b ): alfalfa seed, cantaloupe, 

honeydew melons, potatoes, and watermelons. Crop losses associated with these functions are 

relatively high, thus economic results would be expected to differ from Howitt and Goodman (1989) 

if this standard had been included in their analysis. (Howitt and Goodman, 1989, evaluated a 0.10 

ppm maximum hourly standard, as opposed to the current 0.09 ppm maximum hourly standard 

evaluated in this analysis). In addition, a comparison of the estimated crop losses associated with 

ambient 1984 and 1986 ozone conditions (relative to "clean air") indicate that it is likely that Winer 

et al. ( 1990) used different functions for several crops than those used by Olszyk et al. (1988(a), 

1988(b )) and by Howitt and Goodman (1989). These crops are: lemons, dehydrated onions, oranges, 

spinach, and processing tomatoes. 

Results 

Exhibit 7 presents the estimated crop losses (compared to "clean air") associated with the 1986 

baseline, the forecasted 2010 baseline, and attainment of a 1-hour maximum hourly average of 0.09 

ppm. 

The forecasted changes in ozone concentrations differ between long term average 

concentrations and peak concentrations, because the long-term averages include unchanged hourly 

values less than or equal to 0.04 ppm. The cumulative index of exposures exceeding 0.10 ppm is 

predicted to more than double for many counties. If a cumulative index were used to estimate yield 

losses, in general crop losses would be predicted to be much higher. Yield changes for one crop, 

fresh tomatoes, are predicted from an exposure-response function using a cumulative index, which 

shows more than twice the yield losses between the 1986 and 201 0 baselines. 

Abt Associates Inc. July 5, 1995 Page 14 California Crops Benefits Methodology 
............................................................................................................................................................................................................................................... : 

·= 

Exhibit 7 

Estimated Crop Losses Relative to "Clean Air" (0.025 ppm) for 

Three Ozone Condition Scenarios in California's Central Valley (Percent Loss) 

Attainment 2010 Forecast 

Crop Ambient, of0.09 ppm 

Ambient 

1986 (no additional standard controls) 

Alfalfa, hay 10.6 6.7 11.5 

Alfalfa, seed* 8.5 4.6 9.2 

Barley 0 0 0 

Beans, dry 20.9 13.4 22.9 

Broccoli 0 0 0 

Cantaloupe* 33.5 19.2 36.2 

Com, field 1.7 0.8 2.1 

Silage, com 2.1 0.9 2.5 

Com, sweet 2.0 1.7 2.1 

Cotton 15.7 8.6 17.5 

Grapes, raisin 26.5 15.6 28.7 

Grapes, table 25.3 15.9 27.6 

Grapes, wine 22.5 14.1 24.4 

Honeydew melon* 21.3 16.0 23.3 

Lemons** 9.4 7.4 10.4 

Lettuce 0 0 0 

Onions, dehydrated** 1.0 0.5 1.1 

Onions, fresh 0.9 0.5 1.0 

Oranges** 9.3 4.8 11.9 

Potatoes* 10.6 7.1 11.4 

Rice 2.5 1.9 2.8 

Sorghum, grain 1.0 0.5 1.3 

Spinach** 0.4 0 0.5 

Strawberries 0 0 0 

Sugar beets 0 0 0 

Tomatoes, processed 2.4 0 5.3 

Tomatoes, 1.6 0.7 2.0 

Watermelon* 35.6 22.1 37.6 

Wheat 0.7 0.4 0.8 

Wheat, dryland 0.3 0.2 0.4 

Wheat, irrigated 0.8 0.5 0.9 

* Exposure-response function not available from Exhibit 4. 

** Potentially different exposure-response function from that used in Olszyk 1988(a) 

or 1988(b). 

Source: Winer, Olszyk, and Howitt, 1990, Table 2. 

Abt Associates Inc. July 5, 1995 Page 15 California Crops Benefits Methodology 
Economic impacts of attainment of regulatory standards and of experiencing predicted ozone 

concentrations in 20 I 0 are reported only in terms of producer benefits. Consumer benefits were not 

calculated because the crop production changes were evaluated on a limited regional scope, while 

consumer impacts would need to reflect changes in the overall market. The economic model was 

calibrated to 1987, rather than the 1986 ozone baseline, but the authors note that emissions did not 

change significantly between 1986 and 1987.2 Exhibit 8 reports the changes in producer surplus 

(reported as "producers' return to land and management") associated with the difference in yields 

from each of the baseline ozone levels to the attainment ofthe 0.09 ppm standard. Changes in crop 

mix are predicted to occur regardless of changes in ozone levels due to (unspecified) predicted 

changes in population and income: this explains the increasing returns associated with the 0.09 ppm 

scenario, even though ozone and yields remain constant. 

2 Alone, unchanged emissions would not necessarily result in stable ozone conditions between 

two years. The authors do not address the variability in meteorologic conditions between 1986 

and 1987, or their potential impact on ambient ozone levels. 

Abt Associates Inc. July 5, 1995 Page 16 California Crops Benefits Methodology 
.. 

........................................................................................................ ~~~·~·~~~·~·············"'''''''''""' ............................................................................. _ 

Central Valley Producers' Surplus Comparison of Baseline Ozone, ~·1 

Forecasted Ozone, and Attainment of0.09 ppm Standard 

Scenario 1995 2010 

No Further Action on Ozone 

1987 

5,240.3 5,345.8 5,416.4 

Attain 0.09 ppm Standard 5,445.4 5,558.6 5,693.4 

Net Change 205.1 212.8 277.0 t.) 

i ~ : Source: Winer, Olszyk, and Howitt, 1990, Table 5. ~ 

L~·~::::::::::;:~~~==~~=~=:::::::::::::~=::::::::::::::::::::~:::::~:::::::~~==:::::::~:;::::::::::::~:::::::;:::;:;:::::::::::::~;:;:;:::::::::::;:;:;:;:;:;:;:;:;:;:::::::::::::::~:~::::::::::~~=~:?..J::.~:::t~~~=;::::::..~====-~-=.:::::~==~==:::.~::::~: 

Another interpretation of these results is that the returns to producers would be expected to 

increase 4.6 percent between 1987 and 2010 in the absence of any changes in yields due to ozone, 

based on changes in population and income alone. Due to the production impacts predicted to occur 

due to ozone, however, this rate of growth is predicted to decrease to 3.4 percent. 

2.7 Air Resources Board. 1992. The Atmospheric Acidity Protection Program: annual 

report to the Governor and the Legislature, 1991 and Effect of air pollution on crops in 

the San Joaquin Valley: special report. 

Base year: 

Comparison to: 

Exposure-response models used: 

Form of evaluative standard: 

Exposure-response model functional 

form: 

Levels of evaluative standards: 

Air quality data: 

1990. Ozone concentrations not reported. 

baseline from evaluative standards. 

not specified. 

12-hr seasonal mean (ppm). 

not reported. 

0.04 ppm, 0.025 ppm. 

California Air Resources Board. 

This report presents an analysis of the impacts of ozone on agricultural production in the San 

Joaquin Valley and statewide. It provides no details on the crops included, or on the method for 

yield change estimates. Economic impacts were estimated with the CARM for 1990. 

Results 

Exhibit 9 presents the percent yield increases relative to 1990 for both standards for each of 

nine regions in the state. Exhibit 1 0 presents estimated benefits to producers and consumers 

associated with both standards. 

Abt Associates Inc. July 5, 1995 Page 17 California Crops Benefits Methodology 
Crop 

Exh·i~i~··~·······································································································

Estimated Yield Changes from 1990 Baseline due to 0.04 and 0.025 ppm Standards 

(percent). 

Sac. l N. SJV C. SJV S. S.JV Imp. S. Coast N. Coast N

.04/.025 1 .041.025 .04/.025 .041.025 .04/.025 .04/.025 .04/.025 .04

Alfalf~,hay 

4.6/5.6 j 5/5.8. 5.1/10.7 5.1/14.8 4.1/4.1 4.1/5.5 1.9/1.9 4.7

Beans,dry 11.2!15.7jll.9!17.8 11.9133.3 11.9148.8 010 11.3139.1 010 0

Cantaloupe 0/0 I 14.6126.6 14.6147.6 14.6170 12.6112.6 14.5127.7 010 0

Citrus 8.618.6 ! 010 10.4118 10.4124.2 9.419.4 9.2113.4 010 0

Cotton 010 ! 6.7127.9 6.7138.1 6.7150 5.8120.1 5.8120.1 010 0

Grapes,dry 010 I 10119.9 10131.2 10143.6 010 010 010 0

Grapes,table 010 j10112.3 10131.8 10143.6 010 10/45.2 010 

Grapes,wine 10/31.2 ! 10116.1 10130.2 10/43.6 010 7.6110.3 313 9.9

Lettuce 010 l 010.3 011 011.1 010 010.2 010 

; 

Onions,dry 4.314.3 ! 3.713.7 8111.5 8124 5.315.3 5110.8 010 6.

Rice 2.6 I 3.1 l 2.6 I 4 2.618 2.6110 0 I 0 0 I 0 0 I 0 2.

Sugarbeets 1.2/3.9 ! l 1.818.1 1.8113.6 1.819.9 1.313.8 1.113.4 010 1.8

Tomato,proc. 318.7 ; 3.613.7 4.216.6 4.2110.1 2.712.7 2.212.2 010 

. Wheat 1.311.3 I 1.611.6 8.819.7 9.4115 4.914.9 6.116.3 o I o 7.

1 Source: ARB, 1992, Table 1 

L.~=~~~~~:~-,_t@Z:-

. ..-..:-~~-&:$.:r:~=~=~:w.~~~-=~~r:~*r:=~~=~~~:;:r:~~~~=~~=~=~~=~=::;:~===~~==~=~~~~~=~:;:::::r::::::~:~:;:i::::::~=======~====~=~*~~=r:r:~~:;:r:~~~=~===~=~==*~:~$j*f:~r:~:;§::*::::::=~=~=~~=~~=~"i====~~==

Abt Associates Inc. July 5, 1995 Page 18 California Crops Benefits Methodology 
················~~ ..................................................................................................................................................... ,~ 

Exhibit 10 

California Statewide Economic Impact of Alternative Ozone Standards 

Relative to 1990 Baseline ($millions) 

Standard Consumer Surplus 

0.04 275 

0.025 713 

Producer Surplus 

215 

779 

Total Surplus 

490 

1,492 

. Source: ARB, 1992, Table 3 & ...... ~;~~=~:fu=~~=~=~=~=~=~=~=~=~=~=~=~=~t~=~:j:;:~=~=~=~=~=~=~=~=~=l:;:;:;:;:;:;:j:j:~:;:j:;:;:;:~:;:;:;:~:~:;:;:~:;:~:;:;:;:;:j:~=~=~:;:~;:;:~:::~:::::::;:j:;:r::::;:;:~:;:;:tt;:;:~:;:~:;:r;:;:;:;:::;:;:;:;:;:;:;:;:~~~~=;:;:;:;:l:f;:~;=~=j~:;:;:;~==~~&®~~ 

3.0 YIELD CHANGE ESTIMATES 

3.1 Introduction 

There are several steps involved in generating yield change estimates. One step is that ozone 

exposure-response functions for each crop need to be identified. Another step is that ozone indices 

need to be calculated for both the baseline (ambient) ozone conditions, and for each regulatory 

option, to be used in the identified exposure-response functions. Finally, percent relative yield 

change between a regulatory option and its associated baseline needs to be calculated. Each of these 

steps is detailed below. 

3.2 Exposure-Response Functions 

To estimate yield impacts from ozone, exposure-response functions are required for each crop 

to be analyzed. EPA's NCLAN program concentrated primarily on commodity crops, but also 

included research on kidney beans, lettuce, potatoes, and tomatoes. Use of cumulative ozone indices 

such as W126 is a relatively recent development in the study of ozone impacts on crops, and few 

experiments have been designed or reported in terms of this index. Because the NCLAN program 

used a consistent protocol and developed a database of experimental conditions and results for all 

its studies, U.S. EPAIERL was able to use the original data from NCLAN studies to develop W126 

exposure-response functions for most NCLAN crops.3 (Adequate data do not exist to develop a 

Wl26 form of the tomato exposure-response function.) To the extent possible, exposure-response 

functions expressed in terms of a W126 ozone index were used for this analysis. NCLAN was not 

able to include a wide variety of fruits and vegetables, however; thus other sources of information 

on crop response to ozone exposure were also used in this analysis. The level of data required to 

estimate W126 functions is not generally available from non-NCLAN exposure-response studies, 

and as a result, derivation of W 126 exposure-response functions was not possible for a large number 

of crops grown in California. In order to provide an indication of the potential magnitude of benefits 

associated with ozone NAAQS, available exposure-response functions were used in their original 

form. For this analysis, the functions included 7-hour seasonal mean indices, 12-hour seasonal 

3

This analysis was conducted by U.S. EPA, Environmental Research Lab (ERL). Corvallis. 

Abt Associates Inc. July 5, 1995 Page 19 California Crops Benefits Methodology 
mean indices, and AOT10 indices, and reflect both linear and Weibull functional forms. The AOT10 

index was used in some experiments for several reasons: 0.10 ppmwas the 1-hour California standard 

at the time, and so made a reasonable threshold level; and use of a threshold eliminated equal 

mathematical weighting of dose from many low concentration exposures and a few high ones.4 The 

exposure-response functions used and their sources are reported in Exhibit 11. Crop-specific 

.discussions of the source, use, and limitations of the exposure-response functions follow a discussion 

of how we handled individual crops for which multiple exposure-response functions are available. 

Minimum/Maximum Exposure-Response Functions 

Seven crops included in this analysis have several experimentally-derived exposure-response 

functions available. Two different approaches were used for modeling the benefits associated with 

these crops. In both cases, the functions demonstrating minimum and maximum responses were 

selected and used to represent the entire crop to present a range of benefit estimates. In actuality, 

a number of different cultivars are planted by producers, and so ozone response will be a weighted 

average of the responsiveness of each cultivar to its ozone condition and its proportion of total 

acreage. It is important to note that these values do not necessarily bound the analysis, since the 

number of cultivars evaluated is small relative to the number grown for many crops. In both cases, 

minimum and maximum functions were identified prior to their use in the analysis, but on different 

bases. 

For NCLAN crops (field corn, cotton, potatoes, and wheat), U.S. EPAIERL conducted an 

analysis to identify the ozone concentration required to result in a 10 percent yield loss for each 

experimentally-derived exposure-response function. The function with the lowest concentration 

demonstrates the maximum response, and the function with the highest concentration at 1 0 percent 

yield loss demonstrates the minimum response. In Exhibit 11, only the functions identified by US 

EP AIERL as minimum and maximum are reported for these crops. 

This type of direct comparison of ozone concentrations associated with a given level of crop 

protection is only possible if all the equations available use the same index. For some of the 

remaining crops with multiple functions, several different indices were used to characterize the 

responSe to ozone. As a result, an alternative approach was used to select minimum and maximum 

functions for all non-NCLAN crops with multiple exposure-response functions. Using 1990 baseline 

ozone data, each function was analyzed over a range of ozone values, the relative yield losses were 

arrayed from minimum to maximum, and the minimum and maximum functions were identified. 

There was no case where functions "crossed over", i.e., where under different ozone conditions, 

different functions resulted in minimum or maximum estimates. The identified functions were then 

used to estimate economic impacts. All the functions available for these crops are listed in Exhibit 

11, with the maximum and minimum functions identified. 

4

McCool et al., (1986) note that use of this index eliminates low ozone concentrations, and so 

assumes that they are not important to plant growth and yields in California, but that this 

assumption requires further investigation. 

Abt Associates Inc. July 5, 1995 Page 20 California Crops Benefits Methodology 
Alfalfa Hay 

Alfalfa hay is harvested several times in the season. Exposure-response studies generally 

measure the total yield in the season over several cuttings, compared to a seasonal ozone index. 

NCLAN experiments were conducted on alfalfa, but a W126 function for this crop was not included 

in the national exposure-response analysis due to a number of questions about how to calculate the 

correct cumulative ozone exposure statistic that reflects the number of days of exposure between 

harvests, and at what point in the regrowth cycle ozone has an effect. Alfalfa was included in the 

California analysis, however, because the issues associated with exposure duration do not affect 

seasonal mean indices in the same way as they do cumulative indices. Since the experiments used 

for the basis of the California analysis were conducted using seasonal mean indices over an entire 

cutting season, these functions should give a reasonable indication of the magnitude of yield changes 

associated with different ozone levels. Because of the uncertainty associated with the exposureeffect dynamic for alfalfa, however, the benefits estimated for alfalfa should not be considered 

accurate estimates. Rather, the value of benefits associated with alfalfa should be considered as 

indicators of the potential magnitude of the effect of ozone reduction on alfalfa, with a higher (but 

unquantifiable) level of uncertainty than for most other crops. 

The functions used for alfalfa come from a number of studies conducted in California. 

NCLAN studies (Temple et al., 1988) were conducted over two years, and so two functions are 

reported in Exhibit 11. One study (McCool et al., 1986) used the AOT1 0 ozone index but did not 

report the duration of the experiment. In estimating crop losses, we used a default duration of MaySeptember for alfalfa. 5 Yield losses for alfalfa seed were not estimated because the exposureresponse functions only evaluated the yield of cut alfalfa. 

Dry Beans 

The W126 function from NCLAN studies, derived by U.S. EPAIERL, was used. 

Cantaloupe 

Thompson et al. ( 1991) report a dose-response function derived from data presented in Snyder 

et al. (1988) for muskmelon in Indiana. The SAPRC has recommended its use for all melons in 

California5

, but because rimskmelon and cantaloupe are not the same species, the benefits estimated 

for cantaloupe should llOt be considered accurate estimates. Rather, the value of benefits associated 

with cantaloupe should be considered as indicators of the potential magnitude of the effect of ozone 

reduction, with a higher (but unquantifiable) level of uncertainty than for most other crops. 

Field Corn 

The W126 functions from NCLAN studies, derived by U.S. EPAIERL, were used. U.S. 

EP AIERL identified both a minimum and a maximum exposure-response function. 

5

Personal communication, Randall Mutters, California Statewide Air Pollution Research 

Center. 

Abt Associates Inc. July 5, 1995 Page 21 California Crops Benefits Methodology 
Sweet Corn 

Although experimental data exist for sweet corn's response to ozone (Thompson et al., 1976), 

this crop is not modeled in the economic model of California agriculture. This is a specialty crop 

with very small acreage. 

Cotton 

The W126 functions from NCLAN studies, derived by U.S. EPAIERL, were used. U.S. 

EP AIERL identified a minimum and a maximum exposure-response function. ERL excluded two 

NCLAN studies because the experimental duration was very short compared to other NCLAN 

studies for cotton, and the exposure duration was also shorter than the growth period reported in the 

experiments. 

Grain Sorghum 

The W126 function from NCLAN studies, derived by U.S. EPA!ERL, was used. 

Grapes 

Two studies on grapes found yield responses to ozone for different varieties: Brewer (1983) 

studied Thompson seedless (used for both table grapes and wine), and Thompson and Kats (1970) 

studied Zinfandel (used for wine). (Musselman et al., 1985 studied concord grapes and found no 

effect of ozone on yields). Data from both studies were used to derive the exposure-response 

functions reported in Thompson et al., 1991, with an exposure duration of 138 days for 1969 data 

from Thompson and Kats (1970) and 152 days for April-August exposure for data reported in 

Brewer (1983). 

Lemons 

Thompson et al. ( 1991) report an exposure-response function based on data in Thompson and 

Taylor, 1969. The experiment was a multi-year experiment with exposure occurring 365 days per 

year. Citrus yield impacts, however, appear to be the result of exposure during the one or two years 

prior to harvest. Olszyk et al. (1990) hypothesize that oranges respond to ozone concentrations two 

years prior to harvest, due to the ability of trees to support fruit set, as affected by ozone's impact 

on starch reserves in the previous year. Citrus flower buds usually form from about April to 

October; fruit is harvested in the following year. The SAPRC indicates that flower bud formation 

may be the most affected by ozone, in the year prior to harvest.6 As a result, the ozone data that 

should be used to estimate yield responses in one year should be from either one or two years prior. 

In this analysis, it was not possible to create a 1988 or 1989 ozone data set to be used in conjunction 

with 1990 cropping data, and the literature is not clear on which would be most appropriate for 

6

Personal communication, Randall Mutters, California Statewide Air Pollution Research 

Center. 

Abt Associates Inc. July 5, 1995 Page 22 California Crops Benefits Methodology 
analysis. As a result, the yield change and benefit estimates from this study are based on using 1990 

ozone data as a proxy for prior years' exposure data. 

The function used in this analysis is a modification of the exposure-response function presented 

in Thompson _et al., 1991 for lemons. Thompson et al. (1991) adjusted the lemon yield results to 

better estimate changes in overall production due to ozone: lemons and oranges tend to bear every 

other year, so the percent relative yield loss was reduced by an arbitrary 50 percent to reflect the fact 

that some orchards in a region will be "on" in a given year, while others will be "off'. The CARM 

model, however, uses per acre yields to estimate the resources that will be allocated to the 

production of a given crop: the "on/off' adjustment for the nwnber of acres bearing fruit is not 

appropriate for estimating the yield changes that an individual producer would expect to see due to 

ozone impacts. Therefore, we modified Thompson et al. 's (1990) function to remove the 50 percent 

adjustment factor. 

In the CARM, all citrus (lemons, oranges, and grapefruit) constitute one crop. Therefore, to 

estimate the yield changes for "citrus" as an input to the CARM, we weighted the county PRYL 

estimates for lemons and oranges, and a zero effect for grapefruit, by the proportion of each to total 

citrus production, to derive a single yield change estimate. To the extent that ozone affects 

grapefruit in a manner similar to the effects on lemons and oranges, the citrus estimate will 

underestimate benefits. 

Because of the uncertainty associated with the mechanism of ozone effect on citrus fruit 

formation, the use of proxy ozone concentration data, and the uncertain effect of ozone on grapefruit, 

the benefits estimated for changes in the yields of lemons and oranges should not be considered 

accurate estimates. Rather, the value of benefits associated with citrus crops should be considered 

indicators of the potential magnitude of the effect of ozone reduction on lemons and oranges, with 

a higher (but unquantifiable) level of uncertainty than for most other crops. 

Lettuce 

The W126 function from NCLAN studies, derived by U.S. EPAIERL, was used. 

Onions 

Onions are a very early crop, planted in January in California, when ozone concentrations are 

not expected to be high. Temple et al. (1990) studied four cultivars of onions (all bulb crops, as 

opposed to green onions). Only one variety showed significant yield losses at ambient ozone levels: 

Rio Bravo. This analysis uses the yield estimates for Rio Bravo to represent potential yield changes 

for all types of onions, thus possibly overestimating the benefits associated with ozone 

improvements for this crop. 

Abt Associates Inc. July 5, 1995 Page 23 California Crops Benefits Methodology 
Oranges 

Olszyk et al. (1990) studied continuous exposure of Valencia oranges over a four-year period, 

with exposure from April to October used to estimate yield impacts. Like lemons, orange yields are 

affected by ozone exposure one to two years prior to harvest, but in this analysis, 1990 ozone data 

are used as a proxy for data from prior years. An orange function developed by Thompson et al., 

(1990) to reflect a 50 percent reduction (see the discussion under Lemons, above) was·not used for 

this analysis. 

In the CARM, all citrus (lemons, oranges, and grapefruit) constitute one crop. Therefore, to 

estimate the yield changes for "citrus" as an input to the CARM, we weighted the county PRYL 

estimates for lemons and oranges, and a zero effect for grapefruit, by the proportion of each to total 

citrus production to derive a single yield change estimate. To the extent that ozone affects grapefruit 

in a manner similar to the effects on lemons and oranges, the citrus estimate will underestimate 

benefits. 

Because of the uncertainty associated with the mechanism of ozone effect on citrus fruit 

formation, or the use of proxy ozone concentration data, and the uncertain affect of ozone on 

grapefruit, the benefits estimated for changes in the yields of lemons and oranges should not be 

considered accurate estimates. Rather, the value of benefits associated with citrus crops should be 

considered indicators of the potential magnitude of the effect of ozone reduction on lemons and 

oranges, with a higher (but unquantifiable) level of uncertainty than for most other crops. 

Plums 

Only one study has examined the effect of ozone on the yield of stone fruits such as plums, 

peaches, nectarines, and apricots. Retzlaff et al. (1992) studied 1-year old plum trees for two years. 

Based on these data, Randall Mutters of the SAPRC provided two exposure-response functions, one 

for 1989, and one for 1990. 7 The 1990 function was used in this analysis to be consistent with the 

1990 CARM baseline. These results may not fully represent the effect of ozone on the yields of 

established orchards. 

Potatoes 

The W126 functions from NCLAN studies, derived by U.S. EPAIERL, were used. U.S. 

EP AIERL identified a tolerant and a sensitive exposure-response function. 

Rice 

Thompson et al. (1991) report three different functional forms based on data reported in Kats 

et al. (1985(a)). We used the Weibull function for this analysis~ The Kats et al. (1985(a)) 

experiment exposed the crop to ozone for 5 days a week for a total of 346 hours (we estimated an 

'Personal communication, Randall Mutters, California Statewide Air Pollution Research 

Center. 

Abt Associates Inc. July 5, /995 Page 24 California Crops Benefits Methodology 
exposure duration of 69 days from these data). The SAPRC used a linear extrapolation on the 

original Kats et al. (1985(a)) data to obtain estimates of yield impacts based on 7-hour seasonal mean 

ozone indices (Thompson et al., 1986). The experimental design for Kats et al., 1985(a) included 

both charcoal filtered treatments and ozone addition treatments. Therefore, it is not possible to say 

if the effect of no treatment two days a week would tend to bias the overall yield results up or down. 

Rice does not appear to be .very sensitive to ozone; the effect of uncertainties in yield change 

estimates is not likely to have a significant effect on overall benefit estimates. Nonetheless, the 

benefits estimated for changes in the yields of rice should not be considered accurate estimates. 

Rather, the value of benefits associated with rice should be considered indicators of the potential 

magnitude of the effect of ozone reduction on rice, with a higher (but unquantifiable) level of 

uncertainty than for most other crops. 

Soybeans 

Soybeans are not modeled in the CARM because California does not produce a sufficient level 

of the crop to affect the agricultural economy of the state. 

Tomatoes (Processing) 

The CARM does not model fresh tomatoes, due to their specialty crop nature, and so the 

tomato analysis is restricted to processing tomatoes. Processing tomato data are available from 

NCLAN, but adequate data were not available to derive a W126 function. Therefore, this analysis 

is based on three types of ozone indices: 7-hour seasonal mean data, 12-hour seasonal mean data, 

and AOT10 data. Heck et al. (1984) report two exposure-response functions, but only one was used 

in this analysis based on the recommendation of the SAPRC (Thompson et al., 1986). The excluded 

function predicted very large yield reductions under California ambient conditions, and did not 

appear reasonable. 

3.3 Calculation of Ozone Indices 

The pattern of ozone concentrations associated with achieving standards set according to 

different ozone indices will vary, even ifthe target level of protection achieved is the same. For 

example, the pattern of hourly ozone concentrations associated with meeting a 7-hr seasonal mean 

standard that achieves 1 0 percent maximum crop loss will not necessarily provide the same level of 

protection in terms of a W126 index. This analysis required that either exposure-response functions 

be converted to W126 terms to analyze the impact of the secondary standards, or that the hourly 

ozone concentrations associated with meeting these standards be used to calculate the index used in 

the response study. Most of the experimental data on crop response to ozone has followed a protocol 

similar to that used in the NCLAN analyses, and ozone exposure has been designed to reflect various 

levels of 7-hour or 12-hour seasonal mean concentrations. As long as hourly concentration data 

associated with the experiment are available, other indices can be calculated and used to characterize 

crop response; this was done for NCLAN crops other than tomatoes. In those cases where 

experimental data do not permit conversion of the exposure-response function to W126 terms, the 

hourly ozone concentrations predicted to be associated with each standard were used to calculate the 

index needed for use in available exposure-response functions. 

Abt Associates Inc. July 5, 1995 Page 25 California Crops Benefits Methodology 
r····················-·············--············································-··················· ················E~~-i~~~--~-~ ~-- -E~~~-~~-r~~~~~~~~~··;·~~-~~~~~--······················· ······························

: Crop ! Cultivar ! Ozone !Equation! Yield Function (PRYL, ppm) l Duration l 

1 Index i Type 1 

, l · [hom 

Alfalfa Hay 1 NK 512 12 hr 1 Max p2.67-(139.02*12hr))/(32.67-(139.02*bascl2))(2-yr study) 1 114/40 al. (

.............................................. ..... Mao ... ii.69 ...... ................. : .................. ·r······ .................................................................................. ··· · ................................. : ............................. r......

AlfalfaHay . . W~512 12hr j . fll8.96-(408.8*12hr))/(118.96-(408.8*basel2)) ... ·. . 210 ['"o

~A;::~~~:~:-~H~::·:::.·:·.·::::·:·:::·.:::~·:::r:·:·:·ww:·::·:Lf.~s~:l(4~::·:·::.:r::·:l(2f.:h~~:::·:r:.·::·:::· .. :.:::.:.:li~~-~~~!f.~~::!.[ii1J)~\~~12~~Nf2:~~~1tl~~ff.~:~t/~~e·l·~~i~-~-.:.: ... ·:::·:::·:.· .... ·:::·:r·::::·:.:·::2~-o~l:::·::·:::::·::r~~

,a ,a ay r i {612S•base 12)) (Irrigated) : 1' em

Grain Sorghum DeKalb A28+ Wl26 ( . ~-exp(-(WI26/205.3) 1 ... . . .. ..... ·.· ............ ····· f' ........

g~;t.~;.::·::·::::·:::·:·:·:·:·::·:·::::::·:::·:·:·:·:·:r·:·J~~;.t.~k:.:J·:·:·:·Jr~F-:J:·:·:·:·:·:·:~~-:·:·:·:·:·Jr~Mi:r&

::~~-a~ft?Xrw;~~~~:~t~~-;;~:~;)~lrv~~~~~;-;lt~~ :·:·:·:·:·:···: .. :···:·:·:·:·:·:···:·:·:·:·:·:·J 

Lemons . ! NA ! 12 hr j l0.5004-(12hr•62.24))/(0.5004-(ba~el2•62.24)) i : ,, : : use 

~---------J- Plum Casselman '12 hr ) [377.9-(1373.1•12hr))/(377.9-(1373.1*basel2))(2-year study) 191/214 -~

J'ers

··miw.mm:~~H%t~M=~=~=mm.w.n~w~=~.,,& ... &,.-::,{m~=~~~W:w.:~mn:%~mt:i~=~=:t:=:::m:~:':;=:tr::::m:m~-w:==rwn:;1:1:1:mmmwm·:mm~tf'::::::=:::::=w=;~mmffif:fmmr:1:mf:=ft:=:;:~=;nw.m;~r:

Abt Associates Inc. July 5, 1995, Page 26 California Crops Benefits Methodology 
Ozone data were provided by U.S. EPAIERL (Corvallis). The regulatory options analyzed 

consist of five alternative primary standards, and three levels of stringency for secondary standards 

associated with each of the primary standards. All secondary standards are defined in terms of a 

W126 ozone index, and reflect levels of crop protection to be attained: no more than 10 percent yield 

loss, 20 percent, and 30 percent, in order of decreasing stringency. Yield loss for the purposes of 

establishing secondary standards is derived from a composite exposure- response function that 

reflects most of the NCLAN ozone exposure-response experiments on commodity crops. 

Each ozone exposure-response experiment exposed the crop being studied over a season. The 

actual duration of each experiment varied, but to enable comparison of results, the median duration 

was used for crops with multiple experiments.8 U.S. EP A/ERL provided all data on a monthly basis. 

For Wl26 functions, the duration ofNCLAN experiments was provided by ERL, and we rounded 

to the nearest month. Based on planting and harvesting data developed by USDA (USDA, 1984) 

and emergence periods used in agricultural pesticide fate and transport models (U.S. EPA 1993), we 

developed state-specific growing seasons for all field crops. The standard growing season for other 

crops in California was obtained from the California Statewide Air Pollution Research Center 

(Randall Mutters, personal communication). Since the W126 and AOTIO indices are cumulative, 

monthly data for these indices from ERL were summed for the experimental duration, with the 

exposure period anchored on the harvesting date. For seasonal mean indices, the monthly data for 

the same period were averaged to obtain the statistic used in estimating yield losses. 

3.4 Calculation of Percent Change in Yield 

To develop estimated changes in per-acre yields as input to the CARM, several steps were 

required. First, the exposure-response functions were used to calculate yield losses relative to the 

"clean air" treatment in exposure experiments, then the change in yield was estimated between each 

scenario and its relevant baseline. Finally, this change was applied to the per-acre yields for the 

relevant baseline. 

Ozone exposure-response functions are expressed as a percent relative yield loss (PRYL) 

function, where the ozone level being analyzed is implicitly being compared to the level of ozone 

associated with the charcoal filtered air treatment, which represents "clean air". For cumulative 

ozone indices, this level is essentially zero ozone, while for 7-hr seasonal mean indices this level is 

0.027 ppm and for the 12-hr seasonal mean it is 0.025 ppm (Olszyk et al, 1988(a)). To calculate a 

percent yield change to apply to a nonzero baseline, we calculated a PRYL using the baseline ozone 

le'vel, and a PR YL using the regulatory ozone level. The change in yield, measured as a percent of 

the hypothetical zero-ozone crop production, is then: 

(PR YL(base )-PR YL(rollback)) 

To obtain the change in terms of our (non-zero) baseline yield, we divide by that yield, and get: 

8

This approach is predicated on the assumption that the duration of an experiment does not 

affect the coefficient for yield in any way other than through the value of the ozone concentration 

variable. 

Abt Associates Inc. July 5, 1995 Page 27 California Crops Benefits Methodology 
(PRYL(base)-PRYL(rollback))/(1-PRYL(base)). 

These percent yield losses were then used to modify input data on regional yield per acre in 

the economic model used to estimate benefits from ozone regulation (see below). The per-acre 

yields under 1990 baseline conditions were the basis for estimating yields for each primary 

standard. The estimated per-acre yields for each primary standard then became the basis for 

estimating yields for its associated secondary standards. To modify the yield per acre input files 

to reflect changes in yield due to ozone, it was necessary to construct weighted average percent 

yield change estimates for each region from county-level yield change estimates. We used a 

county's proportion of total regional production to weight that county's predicted percent yield 

change. Some counties are included in two CARM regions, so it was also necessary to specify 

the proportion of the production in these counties that is allocated to each region. 

4.0 ECONOMIC MODELING 

The California Agricultural Resources Model (CARM), developed by Dr. Richard Howitt at 

the University of California, Davis (Howitt, 1995), was used to estimate the economic benefits 

associated with ozone NAAQS. The CARM is a nonlinear optimization (mathematical 

programming) model of California agriculture. It assumes that producers maximize farm profit 

subject to land, water, and other agronomic constraints, and the model maximizes total economic 

surplus in its objective function. The CARM predicts producers' shifts in acreage planted to 

different crops due to changing market conditions or resource constraints. 

The CARM uses constant elasticity of substitution (CES) production functions, which permits 

the substitution of variable inputs in response to a change in conditions, such as due to changes in 

yields associated with ozone exposure. To reach its optimum solution, the CARM uses a three stage 

approach to calculate equilibrium production function coefficients for variable inputs. In the first 

stage, a constrained profit maximization linear progrc:un is specified. In the second stage, regional 

production and cost parameters that calibrate the nonlinear CES model to the base year data are 

derived from the results of the linear program. The third stage model is then specified with a 

nonlinear objective function that incorporates the nonlinear CES production functions and land costs. 

Calibrated Production Equilibrium (CPE) models such as the CARM have a number of 

advantages from the perspective of microeconomic theory. Linear programming models often result 

in a step-wise response to policy changes, where the range between steps may be larger than the level 

of policy change, making the models inflexible over some range of data. CPE models are 

characterized by nonlinear and continuous functions, allowing for analysis of small policy changes, 

such as the small changes in yields that may be associated with incremental regulation of ozone. 

Because the profit function is nonlinear, the slopes of supply and demand functions derived from 

CPE models are respectively positive and negative, as required for microeconomic analysis. 

The CARM is disaggregated into nine production regions, and it includes 38 different cropping 

activities. The CARM does not have a livestock sector, although the demand function for some 

Abt Associates Inc. July 5, 1995 Page 28 California Crops Benefits Methodology 
crops reflects livestock feed demand over time. The version of the CARM used in this analysis was 

calibrated to 1990 production and price data. The CARM regions and their associated counties are 

reported in Exhibit 12, with the proportion of split counties' production allocated to a given region 

reported in parentheses. 

CARM Region 

Sacramento 

Northern San 

Joaquin Valley 

Central San 

Joaquin Valley 

Southern San 

Joaquin Valley 

Imperial 

South Coast 

North Coast 

Northeast 

Southeast 

Exhibit 12 

CARM Regions and Associated Counties 

Counties (Proportion of Production,%) 

Sacramento, Tehama, Butte, Glenn, Colusa, Yolo, Sutter, Solano 

(1 00), Placer (50), Yuba 

Merced, Stanislaus, San Joaquin, Alameda (25), Contra Costs (25) 

Madera, Fresno, Tulare, Kings 

Kern (100) 

Imperial 

Contra Costa (75), Alameda (75), San Francisco, San Mateo, 

Santa Clara, San Benito, Santa Cruz, Monterey, San Luis Obispo, 

Santa Barbara, Ventura, Los Angeles (75), Orange, Riverside (33), 

San Diego 

Del Norte, Humboldt, Mendocino, Lake, Sonoma, Napa, Solano 

(0) 

Siskiyou, Trinity, Shasta, Modoc, Lassen, Plumas, Sierra, Nevada, 

Placer (50), Amador, ElDorado, Alpine, Calaveras, Tuolumne, 

Mono, Mariposa 

lnyo, San Bernardino, Kern (0), Los Angeles (25), Riverside (67) 

Abt Associates Inc. July 5, 1995 Page 29 California Crops Benefits Methodology 
5.0 RESULTS 

Because many crops have multiple exposure-response functions available, two different 

levels of response were evaluated for each standard to reflect the minimum response and the 

maximum response. This approach treats all production of a given crop as being typified by a 

single cultivar, which is not an accurate portrayal of crop production. It does, however, provide 

an indication ofthe range of benefits that can be estimated based on the available data. Exhibit 

13 presents the total surplus associated with each standard evaluated. 

Estimated benefits associated with primary standards, including both minimum and 

maximum estimates, range from $82.4 million to $484.3 million. The largest benefits are 

associated with the 0.07 ppm 8-hour primary standard, followed by the 0.08 ppm 8-hour standard 

and the 0.10 ppm 1-hour standard. Under the 0.07 ppm 8-hour standard, grapes (taken together) 

account for $162.4 million (minimum) to $212.6 million (maximum) of the estimated benefits. 

Raisins account for between $70 million and $91.5 million in estimated benefits, followed by 

table grapes ($56.8 million to $74.3 million), and wine grapes ($35.4 million to 46.6 million). 

Citrus is responsible for approximately $97.9 million in benefits (both minimum and maximum). 

(Under the minimum and maximum scenarios, there are differences in the benefits estimates for 

crops with only a single exposure response function, due to changes in the yield per acre for 

other crops.) As discussed in Section 3 .2, this may be an underestimate if grapefruit have a 

response similar to that of oranges and lemons. 

Depending on whether the response of the predominant alfalfa cultivars grown in 

California is similar to the maximum or the minimum response functions, the benefits associated 

with alfalfa for the 0.07 ppm 8-hour standard could be as high as $88.4 million or as low as 

$11.9 million. Benefits associated with cantaloupe are approximately $38 million, dry beans $15 

million, and plums $14 million. Processing tomato benefits could be as high as $28.3 million, 

based on the maximum exposure-response function available for this crop; the minimum 

estimate, however is only $2.4 million. Several crops actually show negative benefits under the 

0.07 ppm 8-hour standard (as well as under other standards). It is still profitable to grow these 

crops under the new standard, but their overall benefits have declined relative to those associated 

with higher ozone levels due to shifts to other crops. Appendix .1 contains crop-by-crop results 

for each scenario. 

In most cases, secondary standards do not add significant incremental benefits. Benefits 

associated with a secondary standard exceed those of the primary standard in only one case: the 

most stringent secondary standard (associated with a maximum of 10 percent yield loss) for the 

0.12 ppm 1-hour standard. For both the 0.12 and the 0.10 ppm 1-hour standards however, 

benefits associated with one or more secondary standard are relatively large. In these cases, the 

benefits of secondary standards are primarily associated with citrus, grapes, cantaloupe, dry 

beans, and alfalfa hay. 

Abt Associates Inc. July 5, 1995 Page 30 California Crops Benefits Methodology 
Standard 

Primary: 

0.12 ppm 1-hr 

Secondary: 

10 percent 

20percent 

30 percent 

Primary: 

0.10 ppm 1-hr 

Secondary: 

10 percent 

20 percent 

30 percent 

Primary: 

0.07 ppm 8-hr 

Secondary: 

10 percent 

20 percent 

30 percent 

Primary: 

0.08 ppm 8-hr 

Secondary: 

10 percent 

20 percent 

30 percent 

Primary: 

0.09 ppm 8-hr 

Secondary: 

10 percent 

20 percent 

30 percent 

Exhibit 13: Changes in Economic Surpluses for 

Alternative Primary and Secondary Standards ($1,000) 

Producer Surplus Consumer Surplus Total SurplUs 

Minimum 

69,554 

113,907 

42,460 

28,521 

159,891 

44,917 

-313 

1,086 

285,448 

7,064 

7,064 

7,064 

203,713 

19,031 

-9,057 

-9,057 

125,842 

57,749 

22,464 

12,6033 

Maximum 

87,236 

153,949 

63,236 

37,813 

213,455 

65,019 

19,353 

2,560 

387,076 

15,104 

15,104 

15,104 

276,692 

29,789 

252 

252 

171,590 

86,123 

29,577 

7,097' 

Minimum 

12,854 

25,291 

1,497 

6,545 

31,667 

14,167 

-7' 147 

3,386 

65,006 

-1,807 

-1,807 

-1,807 

41,478 

3,841 

-8,785 

-8,785 

15,143 

15,762 

16,1191 

16,311· 

Maximum 

25,530 

45,460 

3,951 

6,838 

54,433 

20,138 

6,139 

5,304 

97,255 

11,794 

11,794 

11,794 

75,795 

8,762 

293 

293 

43,962 

18,539 

11,429" 

3,9961 

Minimum 

82,408 

139,198 

43,957 

35,066 

191,558 

59,084 

-7,460 

4,472 

350,454 

5,257 

5,257 

5,257 

245,191 

22,872 

-17,842 

-17,842 

140,985 

73,511 

38,583 

28,9141 

Maximum 

112,766 

199,409 

67,187 

44,651 

267,888 

85,157 

25,492 

7,864 

484,331 

26,898 

26,898 

26,898 

352,487 

38,551 

545 

545 

215,552 

104,662 

41;006 

11,093" 

"Minimum estimates exceed maximum estimates because no change in the ozone index was estimated for the maximum 

function, but the index for the minimum function did vary between scenarios. 

I t: 

Ill 

~i 

: 

I 

M 

** 

~).l 

I 

I ti' 

~{ 

;:!::: 

I 

I 

~~]! 

I I 

I 

I 

~ I 

-CC!ll!l%_,___) 

Abt Associates Inc. July 5, 1995 Page 31 California Crops Benefits Methodology 
- I 

In some cases, not only do individual crops demonstrate negative benefits under more 

stringent ozone standards, but total benefits are estimated to be negative as well. There are nine 

cases when minimum estimated benefits are, in fact, negative relative to the relevant baseline. In 

these cases, the CARM model is shifting resources between crops (such as land and water) very 

slightly in response to minor increases in yields, resulting in changes in the slope of the supply 

curve. This type of a shift can result in not only a new price, but changed relationships between 

the price, the quantity produced, total revenue, and economic surpluses. In some cases, these 

changes result in decreases in consumer and producer surplus in response to increased yields. 

Finally, there are four cases where the minimum estimated benefits exceed the maximum 

estimated benefits. This anomalous result is a function ofthe estimated ozone concentrations for 

different indices in these scenarios. Specifically, the 12-hour seasonal mean indices, used for the 

maximum analyses, were not predicted by U.S. EPAIERL to change between these scenarios, but 

the AOTl 0 (minimum) indices did change. Therefore, yields were estimated to increase for the 

minimum analysis but not for the maximum analysis, resulting in higher benefits for the former. 

Abt Associates Inc. July 5, /995 Page 32 California Crops Benefits Methodology 
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Abt Associates Inc. July 5, 1995 Page 36 California Crops Benefits Methodology 
APPENDIX 1 

Benefits Estimates By Crop 
CROP P.12 ppm 1hr 0.10 ppm 1hr 

Min Max Min Max 

ALFA-HAY 7,615 11,483 8,643 

ALFA-SEED -654 70 -2 

ALMONDS -403 -71 26 

APPLE+PEAR -31 -10 -8 

APRICOTS -25 -4 -7 

ASPARAGUS -9 -8 -8 

AVOCADOS 0 2 -8 

BARLEY -199 -23 -50 

BEANS-DRY 3,378 3,414 7,631 

BROC+CAULI -95 -31 -60 

CANTALOUPE 7,709 7,739 16,311 

CARROTS -19 -19 -26 

CELERY -4 -6 -4 

CITRUS 16,790 16,861 39,055 

CORN 52 5 2 

COTTON 246 -59 -112 

GRAINHAY -35 9 5 

GRAINSORGH -28 -17 -4 

GRAPE-DRY 12,236 18,939 35,309 

GRAPE-TABL 9,789 13,285 25,140 

GRAPE-WINE 4,740 6,702 15,493 

LETTUCE -132 -32 -66 

ONIONS-DRY 676 767 1,585 

PASTURE 3,772 -326 637 

PEACH+NECT -162 3 -42 

PLUMS 1,948 2,195 6,215 

POTATOES 342 806 664 

PRUNES -24 -6 -2 

RICE 580 657 717 

SAFFLOWER 182 181 160 

SILAGE 169 -51 -34 

SUGARBEETS -84 -32 20 

TOMATO-PRO 1,364 4,734 2,992 ~ALNUTS -175 -24 -8 ~EAT 235 13 -53 

XFIELDCROP 175 183 28 

XFRUITVEG -298 -96 -179 

XTREENUTS -68 3 -67 

Total PI'Qducer 69,554 87,236 159,891 

Surplus 

FRUIT AND VEGETABLE CROPS: 

PRODUCER SURPLUS BY CROP 

($1,000) 

PRIMARY STANDARDS RELATIVE TO BASELINE 

0.07 ppm 8hr 0.08 ppm 8hr 

Min Max Min 

27,201 6,240 49,198 8,213 

-40 -640 -656 -648 

-399 

-··-

-182 ·-------=464 - -348 

-29 -15 -32 -17 

-21 -6 -25 -14 

-

-8 4 -10 -6 

-1 -13 1 -3 

-133 44 -276 -124 

7,643 10,991 10,979 9,487 

28 8 -42 -39 

16,332 29,647 29,640 20,734 

-16 -16 -20 -15 

-3 -3 -4 -3 

38,927 72,720 72,713 51,117 

52 48 56 63 

-56 -185 -1,456 -387 

-29 -28 -44 -5 

-14 -9 -28 6 

46,173 66,948 87,272 45,452 

32,642 46,840 61,289 33,295 

20,473 31,154 40,937 20,859 

45 -112 -115 -38 

1,486 2,832 2,826 2,018 

2,571 2,407 -4,463 1,639 

-444 -444 -447 -430 

5,911 12,332 12,330 8,402 

1,708 936 2,761 755 

-23 -23 -24 -19 

736 1,460 1,418 741 

159 133 184 143 

314 144 -5 124 

-103 -102 -109 -34 

12,956 2,237 25,031 2,829 

-174 10 -175 -51 

-323 -332 -344 419 

373 326 -490 51 

-163 -------- -391 -320 -385 

-67 -67 -68 -67 

213,455 285,448 387,076 203,713 

0.09ppm 8hr 

Max Min 

32,702 8,762 

-68 -681 

-213 -380 

-13 -35 

-11 -25 

-7 -15 

3 -2 

-123 -278 

9,515 6,550 

-29 -87 

20,768 13,613 

-19 -24 

-2 -4 

51,314 32,986 

-9 55 

-102 -1,455 

2 -52 

-19 -44 

61,755 27,721 

43,781 21,267 

26,823 10,798 

-49 -135 

2,010 1,205 

-280 -345 

-29 -448 

8,773 5,168 

2,117 564 

-2 -24 

812 672 

176 184 

49 -190 

-38 -108 

16,665 1,945 

32 -175 

118 -369 

256 -344 

40 -361 

-6 -68 

276,692 125,842 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Producer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

PRODUCER SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELAnVE TO 0.10 1-HR PRIMARY STANDARD 

10% Loss 20°.4 Loss 30% Loss 

Min Max Min Max Min Max 

-2,198 6,108 -204 1,802 -450 

-96 90 -655 -608 32 

-210 300 -435 527 -20 

-11 20 -28 42 -6 

-1 14 -18 20 -13 

1 8 ·2 3 1 

-18 8 9 0 6 

-156 -22 -228 22 160 

992 979 -32 -40 27 

5 -59 53 -17 64 

3,790 3,765 1,352 1,338 193 

7 -2 5 1 11 

0 0 0 0 1 

13,115 13,436 3,862 3,997 572 

-20 -6 63 -3 45 

174 -154 -1,344 -124 40 

-51 26 -54 0 -39 

-2 17 -24 7 -37 

12,815 15,891 1,070 4,070 622 

9,132 12,115 2,323 3,700 360 

3,755 5,064 778 836 900 

-5 -112 -48 -153 -26 

400 476 -24 77 -55 

19 -1,301 -4,923 1,911 371 

41 344 -405 22 -401 

2,485 3,052 698 1,025 84 

116 434 3 78 6 

-18 17 -21 18 -1 

-35 13 -91 -26 -10 

-8 -40 26 13 -66 

350 172 48 76 219 

-53 63 -142 53 -35 

-59 3,565 -792 1,487 -757 

-140 161 -170 4 -26 

207 299 -295 54 40 

180 -193 -465 -908 -533 

314 394 -201 50 -191 

96 80 -1 1 1 

44,917 65,019 -313 19,353 1,086 

-920 

262 

239 

12 

13 

7 

5 

143 

6 

-60 

121 

-3 

2 

918 

-36 

-29 

-30 

-2 

1,283 

705 

591 

-58 

147 

-3,407 

436 

651 

-5 

21 

9 

53 

-472 

92 

1,177 

178 

372 

-247 

329 

57 

2,560 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Producer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

PRODUCER SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELATIVE TO 0.09 8-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

-462 9,832 -1,639 3,077 -2,200 

27 -395 576 334 881 

-24 -228 60 159 331 

3 5 11 21 30 

0 -17 21 15 17 

7 -4 7 21 -1 

3 -4 -4 9 -8 

78 385 324 189 67 

1,830 1,803 50 30 34 

100 -18 20 51 33 

3,965 3,917 1,343 1,333 37 

5 -2 5 8 -2 

0 0 0 2 1 

16,882 16,684 5,833 5,812 1,610 

-2 35 -4 2 -85 

-1 -809 1,080 642 1,345 

13 -1 -5 -17 0 

16 23 34 -26 19 

14,867 17,140 7,261 6,826 2,523 

11,617 15,138 4,015 5,196 992 

4,811 6,343 1,878 2,436 1,543 

3 -72 33 0 72 

463 358 137 147 128 

40 10,093 -876 370 934 

1 -92 393 214 604 

3,186 2,906 1,114 794 632 

67 290 2 0 -4 

0 -1 20 13 8 

6 -5 -34 -18 34 

-2 41 -35 60 -99 

221 1,582 202 244 43 

1 -84 56 -8 -40 

141 2,945 95 1,462 775 

0 -161 46 10 252 

21 -38 71 532 643 

-120 -1,008 294 -296 787 

-13 -393 64 -68 580 

0 -67 15 -2 85 

57,749 86,123 22,464 29,577 12,603 

1,176 

320 

-184 

25 

-5 

-5 

-18 

211 

22 

50 

13 

-3 

0 

1,233 

-33 

328 

-24 

-15 

959 

918 

1,263 

-18 

57 

-734 

258 

304 

-3 

14 

9 

30 

227 

-9 

895 

-22 

249 

-329 

-57 

-5 

7,097 
CROP [Q.12 ppm 1hr 0.10 ppm 1hr 

Min Max Min Max 

ALFA-HAY -1 10,358 558 

ALFA-SEED -6 1 0 

ALMONDS -518 -80 34 

APPLE+PEAR -15 -10 -11 

APRICOTS -2 0 -1 

ASPARAGUS -3 -1 -2 

AVOCADOS -34 -4 -24 

BARLEY -259 -477 -547 

BEANS-DRY 1,224 1,353 3,033 

BROC+CAULI -54 -18 -37 

CANTALOUPE 2,117 2,290 4,896 

CARROTS -7 -8 -11 

CELERY ~3 -5 -3 

CITRUS 5,574 5,759 13,618 

CORN -223 42 -42 

COTTON 951 -391 -701 

GRAINHAY -14 3 0 

GRAINSORGH -6 -18 -1 

GRAPE-DRY 398 945 1,771 

GRAPE-TABL 1,927 2,819 5,384 

GRAPE-WINE 355 976 2,258 

LETTUCE -83 -37 -92 

ONION8-DRY 49 94 210 

PASTURE 1,860 318 . 1,185 

PEACH+NECT -22 6 -30 

PLUMS 187 295 915 

POTATOES 49 170 137 

PRUNES -49 -18 -8 

RICE 138 130 268 

SAFFLOWER -531 -234 -227 

SILAGE 367 -618 -487 

SUGARBEETS -159 -32 38 

TOMATO-PRO -3 560 439 

!WALNUTS -210 -21 -17 

WHEAT 25 -421 -567 

XFIELDCROP 126 -98 -24 

XFRUITVEG -183 -105 -139 

XTREENUTS -109 6 -107 

Total Consumer 12,854 23,530 31,667 

Surplus - '--------- ·-- -----

FRUIT AND VEGETABLE CROPS: 

CONSUMER SURPLUS BY CROP 

($1,000) 

PRIMARY STANDARDS RELATIVE TO BASELINE 

0.07 ppm Shr 0.08 ppm Shr 

Min Max Min 

18,907 5,701 39,209 1,492 -

0 -6 -6 -6 

-513 -232 -522 -448 

-13 -5 -16 -11 - ·-

-2 -1 -2 -2 

-3 2 -3 -2 

-30 -9 -35 -17 

-326 666 -395 -510 

3,069 4,271 4,241 3,664 

21 12 -20 -21 

4,902 9,214 9,206 6,398 

-5 -5 -7 -5 

-3 -3 -3 -3 

13,293 25,181 25,172 17,560 

-221 -214 -231 -249 

-326 -870 -6,098 -1,718 

-13 -11 -18 -2 

-11 0 -6 14 

2,314 3,241 4,264 2,108 

6,856 9,937 13,033 7,096 

3,187 4,273 5,679 2,936 

12 -69 -82 -33 

159 339 338 263 

1,738 1,674 -127 1,247 

-154 -153 -156 -149 

781 1,741 1,740 1,155 

362 205 584 158 

-48 -45 -53 -41 

434 809 596 211 

-428 -98 -536 -259 

336 326 218 313 

-189 -186 -198 -62 

1,621 122 3,309 379 

-211 12 -215 -64 

----

-1,027 -1,043 -1,092 237 

259 325 -203 139 

-185 15 -197 -183 

-108 -108 -109 1-----·--·- -107 

54,433 65,006 97,255 41,478 

--L__ ---

0.09 ppm Shr 

Max Min 

28,271 280 

-1 -6 

13 -492 

-9 -22 

-1 -

-1 -

-3 -4

-768 -39

3,786 2,47

-19 -5

6,596 4,01

-10 -

-2 -

18,076 11,22

32 -23

-526 -6,11

2 -2

-15 -2

3,112 1,18

9,367 4,39

3,991 1,35

-51 -9

260 12

535 1

-3 -15

1,325 66

445 12

0 -5

515 24

-238 -53

-1,080 -48

-58 -19

2,297 7

31 -21

-125 -1,13

51 -40

-52 -23

54 -10

75,795 15,14
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Net Total Surplu1 

FRUIT AND VEGETABLE CROPS: 

TOTAL SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELATIVE TO 0.07 8-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

-397 494 -397 494 -397 

705 551 705 551 705 

137 14 137 14 137 

-1 42 -1 42 -1 

-2 4 -2 4 -2 

-24 3 -24 3 -24 

30 3 30 3 30 

-1,436 1,064 -1,436 1,064 -1,436 

156 242 156 242 156 

-57 37 -57 37 -57 

1,198 942 1,198 942 1,198 

1 5 1 5 1 

2 0 2 0 2 

580 11 580 11 580 

165 7 165 7 165 

242 6,899 242 6,899 242 

30 17 30 17 30 

-2 9 -2 9 -2 

2,967 2,419 2,967 2,419 2,967 

624 805 624 805 624 

2,182 1,122 2,182 1,122 2,182 

68 146 68 146 68 

158 9 158 9 158 

-3,603 8,282 -3,603 8,282 -3,603 

643 685 643 685 643 

523 38 523 38 523 

-25 4 -25 4 -25 

66 11 66 11 66 

-266 29 -266 29 -266 

-115 368 -115 368 -115 

-1,011 325 -1,011 325 -1,011 

205 10 205 10 205 

1,034 206 1,034 206 1,034 

-138 15 -138 15 -138 

1,091 1,222 1,091 1,222 1,091 

-528 905 -528 905 -528 

-202 -53 -202 -53 -202 

259 3 259 3 259 

5,257 26,898 5,257 26,898 5,257 

494 

551 

14 

42 

4 

3 

3 

1,064 

242 

37 

942 

5 

0 

11 

7 

6,899 

17 

9 

2,419 

805 

1,122 

146 

9 

8,282 

685 

38 

4 

11 

29 

368 

325 

10 

206 

15. 

1,222 

905 

-53 

3 

26,898 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTION 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETIUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

!WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Net Total Surplue 

FRUIT AND VEGETABLE CROPS: 

TOTAL SURPLUS BY CROP 

($1,000) 

~ECONDARY STANDARDS RELATIVE TO 0.08 8-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

1,916 5,290 -137 -626 -137 

62 63 -8 -589 -8 

661 -25 -129 -710 -129 

-4 2 -19 -22 -19 

11 15 -11 -13 -11 

6 6 -5 -2 -5 

-1 32 -14 -32 -14 

-41 803 17 1,183 17 

294 227 -30 83 -30 

-70 31 83 31 83 

2,689 2,472 108 -113 108 

-4 18 -7 7 -7 

0 5 0 -3 0 

8,420 8,440 739 38 739 

260 15 11 . -188 11 

-3,363 -607 -5,450 2,468 -5,450 

-58 -37 -58 -47 -58 

-75 17 -54 0 -54 

8,277 8,227 2 -2,388 2 

4,517 6,143 -259 -320 -259 

2,028 2,668 -345 -262 -345 

-51 5 -125 -83 -125 

262 207 -129 -112 -129 

-2,664 891 -7,190 2,629 -7,190 

380 -32 -25 -568 -25 

1,964 1,446 -13 -553 -13 

5 68 8 5 8 

80 -11 -16 -64 -16 

37 17 55 -28 55 

-153 23 -233 -280 -233 

-834 676 -127 1,576 -127 

129 -137 -210 -193 -210 

420 2,082 -910 -603 -910 

-125 -81 -280 -438 -280 

.-2,011 -229 -2,135 570 -2,135 

-697 -232 -922 250 -922 

547 31 -17 168 -17 

57 19 -3 -224 -3 

22,872 38,551 -17,842 545 -17,842 

-626 

-589 

-710 

-22 

-13 

-2 

-32 

1,183 

83 

31 

-113 

7 

-3 

38 

-188 

2,468 

-47 

0 

-2,388 

-320 

-262 

-83 

-112 

2,629 

-568 

-553 

5 

-64 

-28 

-280 

1,576 

-193 

-603 

-438 

570 

250 

168 

-224 

545 
APPENDIX 1 

Benefits Estimates By Crop 

• 

' 
CROP ~.12 ppm 1hr 0.10 ppm 1hr 

Min Max Min Max 

ALFA-HAY 7,615 11,483 8,643 

ALFA-SEED -654 70 -2 

ALMONDS -403 -71 26 

APPLE+PEAR -31 -10 -8 

APRICOTS -25 -4 -7 

ASPARAGUS -9 -8 -8 

AVOCADOS 0 2 -8 

BARLEY -199 -23 -50 

BEANS-DRY 3,378 3,414 7,631 

BROC+CAULI -95 -31 -60 

CANTALOUPE 7,709 7,739 16,311 

CARROTS -19 -19 -26 

CELERY -4 -6 -4 

CITRUS 16,790 16,861 39,055 

CORN 52 5 2 

COTION 246 -59 -112 

GRAINHAY -35 9 5 

GRAINSORGH -28 -17 -4 

GRAPE-DRY 12,236 18,939 35,309 

GRAPE-TABL 9,789 13,285 25,140 

GRAPE-WINE 4,740 6,702 15,493 

LETIUCE -132 -32 -66 

ONIONS-DRY 676 767 1,585 

PASTURE 3,772 -326 637 

PEACH+NECT .. -162 3 -42 

PLUMS 1,948 2,195 6,215 

P<»TATOES 342 806 664 

PRUNES -24 -6 -2 

RICE 580 657 717 

SAFFLOWER 182 181 160 

SILAGE 169 -51 -34 

SUGAR BEETS -84 -32 20 

TOMATO-PRO 1,364 4,734 2,992 

!WALNUTS -175 -24 -8 

[WHEAT 235 13 -53 

XFIELDCROP 175 183 28 

XFRUITVEG -298 -96 -179 

XTREENUTS -68 3 -67 

,, 

Total Producer 69,554 87,236 159,891 

Surplus 

-· 

-

FRUIT AND VEGETABLE CROPS: 

PRODUCER SURPLUS BY CROP 

($1,000) 

PRIMARY STANDARDS RELATIVE TO BASELINE 

0.07 ppm 8hr 0.08 ppm 8hr 

Min Max Min 

27,201 6,240 49,198 8,213 

-40 -640 -656 -648 

-399 

.. 

-182 --·-------=464 -348 

-29 -15 -32 -17 

-21 -6 -25 -14 

-

-8 4 -10 -6 

-1 -13 1 -3 

-133 44 -276 -124 

7,643 10,991 10,979 9,487 

28 8 -42 -39 

16,332 29,647 29,640 20,734 

-16 -16 -20 -15 

-3 -3 -4 -3 

38,927 72,720 72,713 51,117 

52 48 56 63 

-56 -185 -1,456 -387 

-29 -28 -44 -5 

-14 -9 -28 6 

46,173 66,948 87,272 45,452 

32,642 46,840 61,289 33,295 

20,473 31,154 40,937 20,859 

45 -112 -115 -38 

1,486 2,832 2,826 2,018 

2,571 2,407 -4,463 1,639 

-444 -444 -447 -430 

5,911 12,332 12,330 8,402 

1,708 936 2,761 755 

-23 -23 -24 -19 

736 1,460 1,418 741 

159 133 184 143 

314 144 -5 124 

-

-103 -102 -109 -34 

12,956 2,237 25,031 2,829 

-174 10 -175 -51 

-323 -332 -344 419 

373 326 -490 51 

-391 163 -320 -385 

-67 -67 -68 -67 

213,455 285,448 387,076 203,713 

0.09ppm8hr 

Max Min 

32,702 8,762 

-68 -681 

-213 -380 

-13 -35 

-11 -25 

-7 -15 

3 -2 

-123 -278 

9,515 6,550 

-29 -87 

20,768 13,613 

-19 -24 

-2 -4 

51,314 32,986 

-9 55 

-102 -1,455 

2 -52 

-19 -44 

61,755 27,721 

43,781 21,267 

26,823 10,798 

-49 -135 

2,010 1,205 

-280 ,345 

-29 -448 

8,773 5,168 

2,117 564 

-2 -24 

812 672 

176 184 

49 -190 

-38 -108 

16,665 1,945 

32 -175 

118 -369 

256 -344 

40 -361 

-6 -68 

276,692 125,842 
CROP 

ALFA·HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS .. 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

IPEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Producer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

PRODUCER SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELATIVE TO 0.10 1-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

-2,198 6,108 -204 1,802 -450 

-96 90 -655 -608 32 

-210 300 -435 527 -20 

-11 20 -28 42 -6 

-1 14 -18 20 -13 

1 8 -2 3 1 

-18 8 9 0 6 

-156 -22 -228 22 160 

992 979 -32 -40 27 

5 -59 53 -17 64 

3.790 3,765 1,352 1,338 193 

7 -2 5 1 11 

0 0 0 0 1 

13,115 13,436 3,862 3,997 572 

-20 -6 63 -3 45 

174 -154 -1,344 -124 40 

. -51 26 -54 0 -39 

-2 17 -24 7 -37 

12,815 15,891 1,070 4,070 622 

9,132 12,115 2,323 3,700 360 

3,755 5,064 778 836 900 

-5 -112 -48 -153 -26 

400 476 -24 77 -55 

19 -1,301 -4,923 1,911 371 

41 344 -405 22 -401 

2,485 3,052 698 1,025 84 

116 434 3 78 6 

-18 17 -21 18 -1 

-35 13 -91 -26 -10 

-8 -40 26 13 -66 

350 172 48 76 219 

-53 63 -142 53 -35 

-59 3,565 -792 1,487 -757 

-140 161 -170 4 -26 

207 299 -295 54 40 

180 -193 -465 -908 -533 

314 394 -201 50 -191 

96 80 -1 1 1 

44,917 65,019 -313 19,353 1,086 

-920 

262 

239 

12 

13 

7 

5 

143 

6 

-60 

121 

-3 

2 

918 

-36 

-29 

-30 

-2 

1,283 

705 

591 

-58 

147 

-3,407 

436 

651 

-5 

21 

9 

53 

-472 

92 

1,177 

178 

372 

-247 

329 

57 

2,560 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+ PEAR 

APRICOTS 

ASPARAGU'S 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTION 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETIUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Producer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

PRODUCER SURPLUS BY CROP 

($1,000) 

!SECONDARY STANDARDS RELATIVE TO 0.09 8-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

-462 9,832 -1,639 3,077 -2,200 

27 -395 576 334 881 

-24 -228 60 159 331 

3 5 11 21 30 

0 -17 21 15 17 

7 -4 7 21 -1 

3 -4 -4 9 -8 

78 385 324 189 67 

1,830 1,803 50 30 34 

100 -18 20 51 33 

3,965 3,917 1,343 1,333 37 

5 -2 5 8 -2 

0 0 0 2 1 

16,882 16,684 5,833 5,812 1,610 

-2 35 -4 2 -85 

-1 -809 1,080 642 1,345 

13 -1 -5 -17 0 

16 23 34 -26 19 

14,867 17,140 7,261 6,826 2,523 

11,617 15,138 4,015 5,196 992 

4,811 6,343 1,878 2,436 1,543 

3 -72 33 0 72 

463 358 137 147 128 

40 10,093 -876 370 934 

1 -92 393 214 604 

3,186 2,906 1,114 794 632 

67 290 2 0 -4 

0 -1 20 13 .8 

6 -5 -34 -18 34 

-2 41 -35 60 -99 

221 1,582 202 244 43 

1 -84 56 -8 -40 

141 2,945 95 1,462 775 

0 -161 46 10 252 

21 -38 71 532 643 

-120 -1,008 294 -296 787 

-13 -393 64 -68 580 

0 -67 15 -2 85 

57,749 86,123 22,464 29,577 12,603 

1,176 

320 

-184 

25 

-5 

-5 

-18 

211 

22 

50 

13 

-3 

0 

1,233 

-33 

328 

-24 

-15 

959 

918 

1,263 

-18 

57 

-734 

258 

304 

-3 

14 

9 

30 

227 

-9 

895 

-22 

249 

-329 

-57 

-5 

7,097 
CROP Q.12 ppm 1hr 0.10 ppm 1hr 

Min Max Min Max 

ALFA-HAY -1 10,358 558 

ALFA-SEED -6 1 0 

ALMONDS -518 -80 34 

APPLE+PEAR -15 -10 -11 

APRICOTS -2 0 -1 

ASPARAGUS -3 -1 -2 

AVOCADOS -34 -4 -24 

BARLEY -259 -477 -547 

BEANS-DRY 1,224 1,353 3,033 

BROC+CAULI -54 -18 -37 

CANTALOUPE 2,117 2,290 4,896 

CARROTS -7 -8 -11 

CELERY ~3 -5 -3 

CITRUS 5,574 5,759 13,618 

CORN -223 42 -42 

COTTON 951 -391 -701 

GRAINHAY -14 3 0 

GRAINSORGH -6 -18 -1 

GRAPE-DRY 398 945 1,771 

GRAPE-TABL 1,927 2,819 5,384 

GRAPE-WINE 355 976 2,258 

LETTUCE -83 -37 -92 

ONION$-DRY 49 94 210 

PASTURE 1,860 318 1,185 

PEACH+NECT .t" -22 6 -30 

PLUMS 187 295 915 

POTATOES 49 170 137 

PRUNES -49 -18 -8 

RICE 138 130 268 

SAFFLOWER -531 -234 -227 

SILAGE 367 -618 -487 

SUGARBEETS -159 -32 38 

TOMATO-PRO -3 560 439 

WALNUTS -210 -21 -17 

[WHEAT 25 -421 -567 

XFIELDCROP 126 -98 -24 

XFRUITVEG -183 -105 -139 

XTREENUTS -109 6 -107 

,.._ 

Total Consumer 12,854 23,530 31,667 

Surplus 

--

FRUIT AND VEGETABLE CROPS: 

CONSUMER SURPLUS BY t:ROP 

($1,000) 

PRIMARY STANDARDS RELATIVE TO BASELINE 

0.07 ppm 8hr 0.08ppm8hr 

Min Max Min 

18,907 5,701 39,209 1,492 

0 -6 -6 -6 

-513 -232 -522 -448 

-13 -5 -16 -11 

·-

-2 -1 -2 -2 

-3 2 -3 -2 

-30 -9 -35 -17 

-326 666 -395 -510 

3,069 4,271 4,241 3,664 

21 12 -20 -21 

4,902 9,214 9,206 6,398 

-5 -5 -7 -5 

-3 -3 -3 -3 

13,293 25,181 25,172 17,560 

-221 -214 -231 -249 

-326 -870 -6,098 -1,718 

-13 -11 -18 -2 

-11 0 -6 14 

2,314 3,241 4,264 2,108 

6,856 9,937 13,033 7,096 

3,187 4,273 5,679 2,936 

12 -69 -82 -33 

159 339 338 263 

1,738 1,674 -127 1,247 

-154 -153 -156 -149 

781 1,741 1,740 1,155 

362 205 584 158 

-48 -45 -53 -41 

434 809 596 211 

-428 -98 -536 -259 

336 326 218 313 

-189 -186 -198 -62 

1,621 122 3,309 379 

-211 12 -215 -64 

-· 

-1,027 -1,043 -1,092 237 

259 325 -203 139 

-185 15 -197 -183 

-108 -108 -109 -107 -r----··· 

54,433 65,006 97,255 41,478 

-

0.09 ppm 8

Max Min 

28,271 2

-1 

13 -4

-9 

-1 

-1 

-3 

-768 -

3,786 2,

-19 

6,596 4,

-10 

-2 

18,076 11,

32 -

-526 -6,

2 

-15 

3,112 1,

9,367 4,

3,991 1,

-51 

260 

535 

-3 -

1,325 

445 

0 

515 

-238 -

-1,080 -

-58 -

2,297 

31 -

-125 -1

51 

-52 

54 

75,795 15
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+ PEAR 

APRICOTS 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAIN HAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Net Total Surplus 

FRUIT AND VEGETABLE CROPS: 

TOTAL SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELAnVE TO 0.07 8-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

-397 494 -397 494 -397 

705 551 705 551 705 

137 14 137 14 137 

-1 42 -1 42 -1 

-2 4 -2 4 -2 

-24 3 -24 3 -24 

30 3 30 3 30 

-1,436 1,064 -1,436 1,064 -1,436 

156 242 156 242 156 

-57 37 -57 37 -57 

1,198 942 1,198 942 1,198 

1 5 1 5 1 

2 0 2 0 2 

580 11 580 11 580 

165 7 165 7 165 

242 6,899 242 6,899 242 

30 17 30 17 30 

-2 9 -2 9 -2 

2,967 2,419 2,967 2,419 2,967 

624 805 624 805 624 

2,182 1,122 2,182 1,122 2,182 

68 146 68 146 68 

158 9 158 9 158 

-3,603 8,282 -3,603 8,282 -3,603 

643 685 643 685 643 

523 38 ' 523 38 523 

-25 4 -25 4 -25 

66 11 66 11 66 

-266 29 -266 29 -266 

-115 368 -115 368 -115 

-1,011 325 -1,011 325 -1,011 

205 10 205 10 205 

1,034 206 1,034 206 1,034 

-138 15 -138 15 -138 

1,091 1,222 1,091 1,222 1,091 

-528 905 -528 905 -528 

-202 -53 -202 -53 -202 

259 3 259 3 259 

5,257 26,898 5,257 26,898 5,257 

494 

551 

14 

42 

4 

3 

3 

1,064 

242 

37 

942 

5 

0 

11 

7 

6,899 

17 

9 

2,419 

805 

1,122 

146 

9 

8,282 

£85 

38 

4 

11 

29 

368 

325 

10 

206 

15 

1,222 

905 

-53 

3 

26,898 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTs·· 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUilVEG 

XTREENUTS 

Net Total Surplus 

FRUIT AND VEGETABLE CROPS: 

TOTAL SURPLUS BY CROP 

($1,000) 

~ECONDARY STANDARDS RELATIVE TO 0.08 8-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

1,916 5,290 -137 -626 -1~7 

62 63 -8 -589 -8 

661 -25 -129 -710 -129 

-4 2 -19 -22 -19 

11 15 -11 -13 -11 

6 6 -5 -2 -5 

-1 32 -14 -32 -14 

-41 803 17 1,183 17 

294 227 -30 83 -30 

-70 31 83 31 83 

2,689 2,472 108 -113 108 

-4 18 -7 7 -7 

0 5 0 -3 0 

8,420 8,440 739 38 739 

260 15 11 -188 11 

-3,363 -607 -5,450 2,468 -5,450 

-58 -37 -58 -47 -58 

-75 17 -54 0 -54 

8,277 8,227 2 -2,388 2 

4,517 6,143 -259 -320 -259 

2,028 2,668 -345 -262 -345 

-51 5 -125 -83 -125 

262 207 -129 -112 -129 

-2,664 891 -7,190 2,629 -7,190 

380 -32 -25 -568 -25 

1,964 1,446 -13 -553 -13 

5 68 8 5 8 

80 -11 -16 -64 -16 

37 17 55 -28 55 

-153 23 -233 -280 -233 

-834 676 -127 1,576 -127 

129 -137 -210 -193 -210 

420 2,082 -910 -603 -910 

-125 -81 -280 -438 -280 

-2,011 -229 -2,135 570 -2,135 

-697 -232 -922 250 -922 

547 31 -17 168 -17 

57 19 -3 -224 -3 

22,872 38,551 -17,842 545 -17,842 

.. 

-626 

-589 

-710 

-22 

-13 

-2 

-32 

1,183 

83 

31 

-113 

7 

-3 

38 

-188 

2,468 

-47 

0 

-2,388 

-320 

-262 

-83 

-112 

2,629 

-568 

-553 

5 

-64 

-28 

-280 

1,576 

-193 

-603 

-438 

570 

250 

168 

-224 

545 

4 

' 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS .. 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Producer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

PRODUCER SURPLUS BY CROP 

($1,000) 

~ECONDARY STANDARDS RELATIVE TO 0.121-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min :Max 

538 15,425 745 7,017 -820 

6 -28 -1 .fJ77 750 

208 -2 -3 -~89 303 

16 1 -4 -24 17 

17 -2 0 -8 16 

10 4 -1 5 4 

1 -8 1 6 102 

205 45 -83 -165 176 

4,114 4,100 1,182 1,169 28 

56 6 15 .fJ 57 

8,967 8,964 4,124 4,097 2,496 

5 14 -1 -1 5 

0 3 0 3 2 

30,880 31,029 14,714 14,692 7,614 

19 13 7 18 -22 

-883 -273 -1,702 -1,145 -742 

-4 -36 -10 -47 22 

.fJ 24 0 -16 9 

30,698 37,935 12,720 16,388 9,352 

22,645 29,160 9,910 12,489 5,805 

9,760 11,926 3,637 4,546 2,940 

67 -31 -1 .fJ7 68 

917 945 357 323 251 

-2,131 59 -4,764 -479 -3,457 

-281 -36 -285 43 149 

6,106 5,991 3,099 2,864 1,970 

243 786 -9 115 -14 

2 .fJ 0 -5 40 

97 27 25 -10 81 

-92 -120 21 30 36 

367 178 -207 -17 -190 

-19 -2 -26 -17 77 

1,221 7,619 343 3,466 998 

8 13 0 -139 164 

139 38 -592 -308 -116 

103 95 .fJ83 -318 59 

-92 164 -83 -234 240 

1 -72 0 .fJ1 51 

113,907 153,949 42,460 63,236 28,521 

5,190 

-119 

.fJ1 

3 

-1 

1 

-2 

221 

14 

37 

2,468 

13 

6 

7,324 

45 

-19 

-40 

-10 

6,765 

7,021 

3,088 

-19 

50 

2,873 

-439 

1,744 

5 

8 

.fJ 

-3 

360 

-71 

2,499 

-148 

-352 

-271 

-293 

-71 

37,813 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS 

ASPARAGl.JS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Net Total Surplus 

FRUIT AND VEGETABLE CROPS: 

TOTAL SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELATIVE TO 0.09 I·HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

564 13,794 1,949 4,196 2,658 

27 -398 581 338 889 

-51 -515 141 370 756 

9 12 20 30 38 

0 -18 22 18 18 

7 -6 8 28 -1 

9 -29 11 38 16 

212 1,666 899 1,117 -10 

2,566 2,457 230 107 142 

165 -25 33 81 46 

5,348 5,109 1,843 1,777 228 

7 0 7 11 -5 

0 -1 0 4 1 

22,593 21,908 7,848 7,835 2,605 

3 -128 6 92 166 

14 -4,097 5,509 3,439 6,706 

17 -17 -7 -40 -8 

34 21 52 -51 26 

15,633 17,817 7,824 7,215 2,828 

14,123 18,333 4,939 6,401 1,331 

5,646 7,242 2,197 2,937 2,079 

21 -94 54 ·2 102 

532 378 165 181 184 

993 13,756 -178 500 1,283 

-6 -123 527 291 791 

3,662 3,259 1,304 843 812 

82 357 5 7 -15 

3 -24 67 13 58 

61 203 44 33 -128 

8 -65 95 124 265 

945 2,837 932 107 -358 

3 -241 161 27 -84 

163 3,246 114 1,716 1,081 

4 -392 112 -16 549 

50 -82 224 1,369 1,852 

41 -844 698 -83 1,069 

23 -457 108 -48 722 

0 -173 41 0 220 

73,510 104,662 38,583 41,007 28,914 

•• 

903 

323 

-415 

37 

-5 

-6 

-32 

1,183 

140 

79 

61 

-4 

-1 

1,347 

5 

1,686 

-47 

-43 

989 

1,171 

1,536 

-39 

77 

-85 

349 

343 

-1 

21 

337 

124 

-209 

-23 

1,148 

-96 

643 

-319 

-76 

-8 

11,092 

4 

' 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+ PEAR 

APRICOTS.-

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Producer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

PRODUCER SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELAnVE TO 0.07 8-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

880 163 880 163 880 

698 545 698 545 698 

61 5 61 5 61 

5 29 5 29 5 

-2 4 -2 4 -2 

-19 2 -19 2 -19 

16 -1 16 -1 16 

-157 383 -157 383 -157 

34 53 34 53 34 

-30 26 -30 26 -30 

715 678 715 678 715 

3 4 3 4 3 

1 0 1 0 1 

158 5 158 5 158 

-17 -5 -17 -5 -17 

39 1,348 39 1,348 39 

21 12 21 12 21 

3 15 3 15 3 

2,629 2,150 2,629 2,150 2,629 

391 552 391 552 391 

1,688 756 1,688 756 1,688 

64 90 64 90 64 

106 6 106 6 106 

-2,059 6,551 -2,059 6,551 -2,059 

487 498 487 498 487 

363 26 363 26 363 

-8 2 -8 2 -8 

24 2 24 2 24 

-26 61 -26 61 -26 

-51 -90 -51 -90 -51 

30 178 30 178 30 

77 4 77 4 77 

727 179 727 179 727 

-51 4 -51 4 -51 

416 420 416 420 416 

-155 515 -155 515. -155 

-99 -67 -99 -67 -99 

99 1 99 1 99 

7,064 15,104 7,064 15,104 7,064 

... 

163 

545 

5 

29 

4 

2 

-1 

383 

53 

26 

678 

4 

0 

5 

-5 

1,348 

12 

15 

2,150 

552 

756 

90 

6 

6,551 

498 

26 

2 

2 

61 

-90 

178 

4 

179 

4 

420 

515 

-67 

1 

15,104 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGAR BEETS 

TOMATO-PRO 

[YIIALNUTS 

rwtiEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Producer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

PRODUCER SURPLUS BY CROP 

($1,000) 

~ECONDARY STANDARDS RELATIVE TO 0.08 8·HR PRIMARY STANDARD 

10".b Loss 20% Loss 30% Loss 

Min Max Min Max Min ft'Aax 

-1,568 2,216 131 1,588 131 

62 62 -8 -583 -8 

287 114 -56 -186 -56 

3 1 -14 ·17 -14 

10 12 -10 -13 -10 

4 6 -3 0 -3 

-2 15 4 -3 4 

-249 60 -131 191 -131 

148 133 -9 17 -9 

-41 17 49 15 49 

2,008 1,985 88 59 88 

-2 13 -5 2 -5 

0 2 0 -1 0 

6,248 6,263 531 340 531 

9 38 -8 54 -8 

-654 -120 -1,070 468 -1,070 

-41 -25 -41 -33 -41 

-42 11 -34 -9 -34 

7,704 7,780 3 -2,092 3 

3,693 5,022 -137 -164 -137 

1,656 2,293 -139 -38 -139 

-31 -5 -77 -63 -77 

201 170 -86 -72 -86 

-1,914 945 -5,872 1,711 -5,872 

285 -18 -17 -418 -17 

1,638 1,283 -9 -380 -9 

-1 58 1 2 1 

26 -4 -5 -21 -5 

-23 10 -42 -68 -42 

65 -35 39 3 39 

-363 116 -71 126 -71 

44 -43 -74 -65 -74 

283 1,799 -641 -395 -641 

-5 -46 -125 -205 -125 

-761 -172 -780 273 -780 

-180 -188 -443 204 -443 

511 -2 5 86 5 

23 23 -1 -62 -1 

19,031 29,789 -9,057 252 -9,057 

... 

1,588 

-583 

-186 

-17 

-13 

0 

-3 

191 

17 

15 

59 

2 

-1 

340 

54 

468 

-33 

-9 

-2,092 

-164 

-38 

-63 

-72 

1,711 

-418 

-380 

2 

-21 

-68 

3 

126 

-65 

-395 

-205 

273 

204 

86 

-62 

252 

.J 

' 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS .. 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTION 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETIUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Consumer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

CONSUMER SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELATIVE TO 0.121-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

1,619 15,370 1,189 1,663 3,311 

0 0 0 -6 7 

269 -15 -7 -414 385 

10 -11 -5 -14 0 

1 -1 0 -2 1 

3 1 0 -2 3 

28 -9 -1 -38 138 

-188 669 -113 -455 -36 

1,703 1,666 467 345 104 

36 4 9 -36 32 

2,930 3,004 1,371 1,228 967 

2 5 .0 -6 0 

0 3 0 2 2 

10,566 10,897 5,077 5,004 3,179 

190 -88 -14 -295 230 

-2,389 1,297 -7,048 -4,822 -3,142 

-1 8 -5 -28 22 

-11 25 0 -1 -8 

1,720 1,913 682 682 729 

4,999 6,264 2,156 2,602 1,419 

1,937 2,083 647 526 829 

37 -22 -3 -79 24 

134 146 53 17 76 

-364 -334 -1,558 -93 -1,715 

-131 -19 -138 -148 18 

. 1,016 981 463 369 378 

74 147 23 15 16 

7 21 -7 -50 69 

180 78 -60 -121 51 

474 178 -38 -247 156 

-284 -217 -166 -378 -888 

-29 26 -41 -212 154 

356 1,191 45 405 367 

8 -8 -5 -166 177 

199 49 -1,133 -583 -513 

179 177 -318 -475 -151 

6 95 -24 -141 74 

2 -114 0 -99 82 

25,291 45,460 1,497 3,951 6,545 

-1,197 

-1 

-88 

6 

-1 

-1 

-28 

933 

63 

24 

754 

6 

5 

2,400 

-260 

-32 

-16 

12 

157 

1,387 

553 

3 

-23 

1,421 

-157 

278 

3 

24 

232 

-277 

1,063 

-156 

473 

-186 

-632 

287 

-79 

-114 

6,838 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTION 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETIUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGAR BEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Consumer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

CONSUMER SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELAnVE TO 0.10 1-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

4,043 7,916 462 1,869 1,000 

-1 1 -6 -6 0 

-272 383 -567 729 -22 

-1 1 -8 24 5 

0 1 -1 1 -1 

-1 3 •1 1 0 

-9 28 -12 1 -5 

-367 -155 144 218 843 

419 391 -148 -153 86 

1 -40 38 -7 39 

1,561 1,546 493 495 355 

3 -3 4 1 6 

0 0 0 0 0 

4,193 5,003 1,068 1,401 -77 

40 155 -209 5 -168 

858 -281 -5,399 -442 305 

-18 8 -22 1 -14 

-4 15 -5 4 -14 

698 825 -124 225 35 

1,993 2,733 377 1,037 131 

585 619 -143 -330 208 

4 -75 10 -79 30 

61 103 -40 12 -45 

-784 -1,175 -1,248 530 140 

31 119 -129 6 -123 

285 535 15 159 -58 

28 74 7 45 10 

-39 30 -54 39 4 

-93 -159 -352 1 210 

95 257 -317 -13 150 

559 -349 722 150 855 

-83 132 -259 86 -63 

-25 672 -333 252 -319 

-165 166 -206 10 -23 

331 807 -547 105 68 

13 -354 -279 -263 -131 

74 76 -77 24 -33 

153 129 -2 1 1 

14,167 20,138 -7,147 6,139 3,386 

... 

3,602 

4 

306 -' 

5 

1 

3 

29 

436 

-48 

-40 

222 

-4 

2 

831 

207 

-132 

-12 

6 

77 

284 

-180 

-41 

58 

-1,404 

153 

191 

-9 

38 

-254 

58 

-737 

168 

354 

264 

1,001 

-339 

73 

131 

5,304 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+ PEAR 

APRICOTS 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAIN HAY 

GRAINSORGH 

GRAPE~DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Consumer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

CONSUMER SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELATIVE TO 0.07 B·HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

-1,277 331 -1,277 331 -1,277 

6 5 6 5 6 

76 9 76 9 76 

-6 13 -6 13 -6 

0 0 0 0 0 

-5 0 -5 0 -5 

13 5 13 5 13 

-1,278 681 -1,278 681 -1,278 

122 189 122 189 122 

-27 12 -27 12 -27 

483 264 483 264 483 

-2 2 -2 2 -2 

1 0 1 0 1 

423 7 423 7 423 

181 13 181 13 181 

203 5,552 203 5,552 203 

9 5 9 5 9 

-5 -5 -5 -5 -5 

337 269 337 269 337 

233 253 233 253 233 

494 366 494 366 494 

4 56 4 56 4 

52 2 52 2 52 

-1,544 1,, 31 -1,544 1,731 -1,544 

156 187 156 187 156 

160 12 160 12 160 

-17 2 -17 2 -17 

41 9 41 9 41 

-240 -32 -240 -32 -240 

-64 458 -64 458 -64 

-1,042 147 -1,042 147 -1,042 

128 7 128 7 128 

306 28 306 28 306 

-87 10 -87 10 -87 

675 801 675 801 675 

-373 390 -373 390 -373 

-103 14 -103 14 -103 

160 2 160 2 160 

-1,807 11,794 -1,807 11;794 -1,807 

•• 

331 

5 

9 

13 

0 

0 

5 

681 

189 

12 

264 

2 

0 

7 

13 

5,552 

5 

-5 

269 

253 

366 

56 

2 

1,731 

187 

12 

2 

9 

-32 

458 

147 

7 

28 

10 

801 

390 

14 

2 

11,794 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Consumer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

CONSUMER SURPLUS BY CROP 

. ($1,000) 

!SECONDARY STANDARDS RELAnVE TO 0.08 8-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min ·Max 

3,484 3,074 -268 -2,214 -268 

1 1 0 -5 0 

374 -138 -73 -524 -73 

-7 1 -5 -5 -5 

1 2 0 0 0 

2 0 -1 -2 -1 

1 17 -19 -29 -19 

208 743 149 991 149 

146 94 -22 67 -22 

-29 13 34 16 34 

681 487 20 -173 20 

-1 6 -2 4 -2 

0 2 0 -1 0 

2,171 2,177 207 -302 207 

251 -23 19 -242 19 

-2,709 -487 -4,381 2,000 -4,381 

-17 -11 -17 -14 -17 

-33 6 -20 9 -20 

573 447 -1 -296 -1 

825 1,122 -122 -156 -122 

372 376 -207 -224 -207 

-19 10 -48 -20 -48 

61 38 -44 -40 -44 

-750 -54 -1,318 918 -1,3~8 

95 -15 -8 -151 -8 

326 163 -4 -174 -4 

6 10 7 3 7 

55 -7 -12 -43 -12 

60 7 97 39 97 

-219 59 -272 -283 -272 

-471 560 -56 1,450 -56 

85 -95 -136 -129 -136 

137 283 -269 -207 -269 

-120 -35 -155 -234 -155 

-1,250 -57 -1,355 297 -1,355 

-518 -44 -479 47 -479 

35 33 -22 82 -22 

34 -4 -2 -162 -2 

3,841 8,762 -8,785 293 -8,785 

•• 

-2,214 

-5 

-524 

-5 

0 

-2 

-29 

991 

67 

16 

-173 

4 

-1 

-302 

-242 

2,000 

-14 

9 

-296 

-156 

-224 

-20 

-40 

918 

-151 

-174 

3 

-43 

39 

-283 

1,450 

-129 

-207 

-234 

297 

47 

82 

. -162 

293 
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTS 

ASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTION 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETIUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT. 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Total Consumer 

Surplus 

FRUIT AND VEGETABLE CROPS: 

CONSUMER SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELATIVE TO 0.09 8-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

1,027 3,961 3,588 1 '119 4,857 

0 .... 5 3 8 

-28 -287 81 211 425 

6 7 8 10 8 

0 -1 1 3 1 

0 -2 1 7 0 

6 -25 15 29 24 

134 1,281 574 928 -77 

735 654 180 78 108 

65 -7 13 30 13 

1,383 1,191 500 444 191 

2 1 2 3 -3 

0 -1 0 2 1 

5,711 5,223 2,014 2,023 995 

5 -163 11 90 251 

15 -3,288 4,429 2,797 5,361 

4 -16 -2 -22 -7 

18 -2 18 -24 7 

765 677 563 389 305 

2,506 3,195 924 1,205 339 

836 899 318 501 535 

18 -22 21 -2 30 

69 20 28 34 56 

953 3,664 698 130 349 

-6 -32 134 77 187 

476 353 190 49 180 

16 67 2 7 -11 

3 -23 47 0 50 

55 208 78 51 -162 

10 -107 129 64 364 

724 1,255 730 -136 -401 

1 -157 105 35 -44 

22 301 19 254 306 

4 -231 66 -25 297 

29 -44 153 836 1,208 

161 164 405 213 282 

36 -65 45 20 142 

0 -106 26 1 135 

15,762 18,539 16,119 11,429 16,311 

... 

-274 

3 

-231 

11 

-1 

0 

-14 

972 

117 

30 

47 

-1 

0 

113 

38 

1,357 

-23 

-28 

31 

254 

273 

-21 

20 

649 

91 

39 

2 

7 

328 

94 

-435 

-14 

253 

-74 

394 

10 

-19 

.... 

3,996 
CROP ~.12 ppm 1hr 0.10 ppm 1hr ~in Max Min 

ALFA-HAY 7,614 21,842 9,201 

ALFA-SEED -660 71 -2 

ALMONDS -920 -151 60 

APPLE+PEAR -46 -19 -19 

APRICOTS -27 -4 -8 

ASPARAGUS -12 -10 -10 

AVOCADOS -34 -1 -32 

BARLEY -459 -500 -597 

BEANS-DRY 4,602 4,767 10,664 

BROC+CAUU -149 -49 -97 

CANTALOUPE 9,826 10,029 21,207 

CARROTS -26 -27 -37 

CELERY -7 -11 -7 

CITRUS 22,364 22,620 52,672 

-

CORN -171 47 -39 

COTTON 1,197 -451 -812 

GRAINHAY -50 12 5 

GRAINSORGH -34 -35 -6 

GRAPE-DRY 12,634 19,885 37,080 

GRAPE-TABL 11,716 16,104 30,524 

GRAPE-WINE 5,095 7,678 17,751 

LETTUCE -214 -69 -157 

ONIONS-DRY 725 861 1,794 

PASTURE 5,633 -8 1,821 

PEACH+NECT -185 9 -72 

PLUMS 2,135 2,490 7,130 

P<}TATOES 391 976 801 

PRUNES -73 -23 -10 

RICE 718 787 986 

SAFFLOWER -349 -53 -67 

SILAGE 536 -669 -522 

SUGARBEETS -243 -63 58 

TOMATO-PRO 1,361 5,294 3,431 

rwALNUTS -385 -45 -25 

~EAT 

259 -408 -620 

XFIELDCROP 301 85 4 

XFRUITVEG -481 -201 -319 

XTREENUTS -177 10 -174 

--

Net Total Surplus 82;4o7 110,766 191,558 

FRUIT AND VEGETABLE CROPS: 

TOTAL SURPLUS BY CROP 

($1,000) 

PRIMARY STANDARDS RELATIVE TO BASELINE 

0.07ppm8hr 0.08ppm 8hr 

Max Min Max Min 

46,107 11,941 88,407 9,706 

--- -40 1-· -645 -662 -654 

. 

-912 -414 -926 -796 

-

-43 -21 -48 -29 

-22 -7 -27 -16 

-10 5 -13 -8 

-31 -22 -35 -20 

-459 709 -671 -634 

.. 

10,712 15,262 15,220 13,151 

49 21 -62 -60 

21,233 38,861 38,846 27,132 

-21 -21 -27 -20 

-6 -7 -7 -6 

52,220 97,901 97,885 68,677 

-169 -166 -175 -186 

-382 -1,055 -7,554 -2,104 

-42 -39 -63 -6 

-25 -8 -34 19 

48,488 70,189 91,535 47,560 

39,498 56,776 74,321 40,392 

23,660 35,427 46,616 23,795 

57 -181 -197 -72 

1,644 3,171 3,164 2,281 

4,309 4,081 -4,590 2,885 

-599 -598 -604 -579 

6,692 14,073 14,070 9,557 

2,070 1,141 3,345 913 

-71 -68 -77 -60 

1,170 2,270 2,013 951 

--269 35 -353 -116 

650 470 213 437 

-292 -288 -307 -96 

14,577 2,359 28,340 3,207 

-385 22 -390 -115 

-1,350 -1,374 -1,436 656 

631 651 -692 190 

-· 

-575 178 -517 -568 

-175 -175 -177 -174 

267,888 350,454 484,331 245,192 

0.09ppm8hr 

Max Min 

60,973 9,04

-68 -68

-200 -87

-22 -5

-12 -2

-8 -1

0 -4

-892 -67

13,301 9,02

-48 -13

27,364 17,62

-29 -3

-4 

69,390 44,20

23 -17

-629 -7,56

4 -7

-33 -6

64,867 28,90

53,148 25,65

30,814 12,14

-101 -23

2,270 1,32

255 -32

-32 -59

10,098 5,83

2,562 68

-2 -7

1,328 91

-62 -35

-1,031 -67

-96 -30

18,962 2,01

63 -39

-8 -1,50

307 -74

-12 -59

48 -17

352,487 140,98
CROP 

ALFA-HAY 

ALFA-SEED 

ALMONDS 

APPLE+PEAR 

APRICOTSASPARAGUS 

AVOCADOS 

BARLEY 

BEANS-DRY 

BROC+CAULI 

CANTALOUPE 

CARROTS 

CELERY 

CITRUS 

CORN 

COTTON 

GRAINHAY 

GRAINSORGH 

GRAPE-DRY 

GRAPE-TABL 

GRAPE-WINE 

LETTUCE 

ONIONS-DRY 

PASTURE 

PEACH+NECT 

PLUMS 

POTATOES 

PRUNES 

RICE 

SAFFLOWER 

SILAGE 

SUGARBEETS 

TOMATO-PRO 

WALNUTS 

WHEAT 

XFIELDCROP 

XFRUITVEG 

XTREENUTS 

Net Total Surplus 

FRUIT AND VEGETABLE CROPS: 

TOTAL SURPLUS BY CROP 

($1,000) 

SECONDARY STANDARDS RELATIVE TO 0.121-HR PRIMARY STANDARD 

10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

2,157 30,795 1,934 8,680 2,491 

6 -28 -1 -683 757 

477 -17 -11 -704 688 

26 -10 -8 -37 17 

18 -3 0 -10 18 

13 6 -1 3 7 

29 -17 -1 -31 240 

17 713 -176 -620 140 

5,817 5,766 1,648 1.514 132 

92 10 24 -43 89 

11,896 11,968 5,495 5,325 3,463 

6 20 -2 -7 5 

1 6 0 5 5 

41,446 41,926 19,791 19,696 10,792 

208 -75 -7 -277 208 

-3,272 1,024 -8,750 -5,967 -3,884 

-4 -27 -15 -75 44 

-16 49 -1 -17 0 

32,419 39,848 13,402 17,070 10,082 

27,644 35,424 12,066 15,091 7,225 

11,697 14,009 4,284 5,072 3,769 

104 -53 -4 -146 92 

1,051 1,091 410 340 328 

-2,495 -275 -6,322 -572 -5,172 

-411 -55 -423 -105 166 

7,121 6,972 3,562 3,233 2,348 

316 933 14 130 2 

9 15 -7 -54 108 

277 105 -.35 -131 132 

382 57 -18 -217 192 

82 -39 -373 -396 -1,078 

-47 24 -67 -229 231 

1,577 8,810 388 3,871 1,365 

16 5 -5 -305 341 

338 87 -1,725 -891 -630 

283 272 -1,001 -793 -93 

-86 259 -107 -374 314 

3 -185 0 -160 133 

139,198 199,410 43,958 67,187 35,066 

.. 

3,993 

-120 

-149 

9 

-2 

-1 

-30 

1,154 

77 

61 

3,222 

19 

11 

9,723 

-214 

-51 

-56 

2 

6,922 

8,409 

3,641 

-16 

27 

4,294 

-595 

2,023 

8 

32 

225 

-280 

1,424 

-227 

2,972 

-334 

-985 

16 

-371 

-184 

44,652 
FRUIT AND VEGETABLE CROPS: 

TOTAL SURPLUS BY CROP 

($1,000) 

!SECONDARY STANDARDS RELAnVE TO 0.10 1-HR PRIMARY STANDARD 

CROP 10% Loss 20% Loss 30% Loss 

Min Max Min Max Min Max 

ALFA-HAY 1,845 14,024 258 3,671 551 

ALFA-SEED -97 90 -661 -614 32 

ALMONDS -481 683 -1,002 1,255 -42 

APPLE+PEAR -12 21 -36 66 -1 

APRICOTS.· -1 15 -19 21 -14 

ASPARAGUS 0 11 -3 4 0 

AVOCADOS -26 36 -3 1 2 

BARLEY -524 -178 -84 239 1,003 

BEANS-DRY 1,411 1,370 -180 -193 113 

BROC+CAULI 7 -99 92 -24 103 

CANTALOUPE 5,351 5,311 1,845 1,834 548 

CARROTS 10 -5 9 2 17 

CELERY 0 1 1 0 1 

CITRUS 17,308 18,439 4,929 5,398 495 

CORN 20 149 -146 2 -123 

COTTON 1,033 -435 -6,743 -566 345 

GRAINHAY -69 33 -76 0 -52 

GRAINSORGH -6 32 -29 12 -52 

GRAPE-DRY 13,513 16,71'5 946 4,295 656 

GRAPE-TABL 11,124 14,848 2,700 4,737 491 

GRAPE-WINE 4,340 5,682 635 506 1,107 

LETTUCE -1 -186 -38 -233 4 

ONIONS-DRY 461 579 -64 89 -100 

PASTURE -765 -2,476 -6,171 2,441 511 

PEACH+NECT 72 464 -534 27 -524 

PLUMS 2,770 3,586 713 1,183 26 

POTATOES 145 508 10 123 16 

PRUNES -57 46 -76 56 3 

RICE -128 -147 -442 -25 201 

SAFFLOWER 88 217 -291 1 84 

SILAGE 909 -176 770 226 1,073 

SUGARBEETS -136 195 -401 139 -98 

TOMATO-PRO -84 4,236 -1,125 1,739 -1,076 

WALNUTS -304 327 -375 15 -50 

WHEAT 538 1,106 -842 159 108 

XFIELDCROP 193 -547 -744 -1 '171 -664 

XFRUITVEG 388 470 -278 74 -224 

XTREENUTS 249 210 -2 2 2 

Net Total Surplus 59,084 85,157 -7,460 25,491 4,472 

.. 

2,682 

266 

545 

17 

14 

10 

34 

579 

-42 

-100 

343 

-7 

4 

1,749 

171 

-161 

-42 

5 

1,360 

.989 

411 

-98 

205 

-4,811 

590 

842 

-14 

60 

-245 

111 

-1,209 

260 

1,532 

442 

1,373 

-586 

402 

188 

7,865 

J 

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