### 6A

- 1

APPENDIX 6A : METHODS AND DATA USE D TO DEVELOP ESTIMAT ES OF

OZONE EFFECTS ON CRO P AND FOREST PRODUCT IVITY

Incorporating the impacts of different ambient ozone concentration levels into

FASOMGHG requires determining crop yield and forest productivity impacts associated with

changes in concentrations. Productivity impacts are required for each crop/region and forest

type/region combination included within the model. In this section, we describe our methods for

calculating relative yield losses (RYLs) an d relative yield gains (RYGs) of crops and tree species

under alternative ambient ozone concentration levels.

These data are essential for our market analysis because crop and forest yields play an

important role in determining the economic returns to agri cultural and forest production

activities. Thus, they affect landowner decisions regarding land use, crop mix, forest rotation

lengths, production practices, and others. Alterations in ambient ozone concentration levels will

therefore change the supply cur ves of U.S. agricultural and forest commodities, resulting in new

market equilibriums. Because both the changes in ozone concentrations and the distribution of

ozone

- sensitive crops and tree species vary spatially, there may be substantial differences in t he

net impacts across regions. There may also be distributional impacts as commodity production

shifts between regions in response to changes in relative productivity.

6A.1 Methodology

There are several alternative metrics used for assessing ozone concent rations (see Lehrer et

al. [2007] for more information). For this assessment, we are using the W126 metric, which is a

weighted sum of all ozone concentrations observed from 8 a.m. to 8 p.m available in 2025 and

2038. More specifically, we are using W126 o zone concentration surfaces generated using

enhanced Voronoi Neighbor Averaging (eVNA). W126 concentration surfaces based on meeting

the current ozone standard 1 

### were provided by EPA in the previous iteration of this project (2013)

served again as the basel ine for this analysis. According to information provided by EPA, the

eVNA W126 ozone surface is built from monitor data fused with Community Multiscale Air

1 The current primary and secondary ozone standards are 0.075 parts per mi llion (ppm) (or 75 parts per billion) based

on the a nnual fourth

- highest daily maximum 8

- hr concentration, averaged over 3 years . For the purposes of

calculating impacts on crop yields and forest growth rates, we used the W126 equivalent of the current sta ndard.

### 6A

- 2

Quality (CMAQ) model

- based gradient interpolations. The spatial resolution of the ozone

surface in A rcGIS Shapefile format is 12 km.

County

- level values were extracted from the eVNA W126 ozone surface using ArcGIS.

Only the ozone concentrations for the cropland and forestland portions of the W126 ozone

surface are used to derive the county

- level average crop and forest W126 ozone levels,

respectively. These weighting adjustments were made to better reflect the ozone concentration

that would affect the specific portions of each county containing forested land or cropland, rather

than basing county

- level e xposure on the ozone concentration across the whole county. Data

from the 2011 USGS National Land Cover Database (NLCD), updated from the previously used

2006 NLCD data are used to extract the cropland and forestland portions from the ozone surface

(Jin et al., 2013). The maps below demonstrate the change in forest and cropland area resulting

from updating the data from 2006 to 2011.

Table 6A

- 1. Comparison of Total Cropland and Forestland NLCD Area (sq m)

2006 NLCD 2011 NLCD % Increase

Cropland Area 1,730,787,687,000 1,786,333,937,400 3.21

Forestland Area 1,938,825,202,500 1,963,044,107,100 1.25



### Figure 6A

- 1

. Cropland Area (sq m) by County according to NLCD 2006 data

### 6A

- 3

Figure 6A

- 2. Cropland Area (sq m) by County according to NLCD 2011 data

Figure 6A

- 3. Forest Area (sq m) by County according to NLCD 2006 data

### 6A

- 4

Figure 6A

- 4. Forest Area (sq m) by County according to NLCD 2011 data

6A.1.1 Calculation of Relative Yield Loss

The median W126 ozone concentration response (CR) functions for crops and tree

seedlings in the 2007 EPA technical report (Lehrer et al., 2007 ) are used to calculate the RYLs

for crops and tree species under each ambient ozone concentration scenario used in this analysis.

Table 6A

- 1 presents the α and β parameters being used in the W126 ozone CR function for

different crops and tree species. The W126 ozone CR function is as follows: RYL = 1

−

e − ( W 126 α

⁄ ) β



### .

### 6A

- 5

Table 6 A

- 2. Parameter Values Used for Crops and Tree Species

α β

Crops

Corn 98.3 2.973

Sorghum 205.9 1.963

Soybean 110.0 1.367

Winter wheat 53.7 2.391

Potato 99.5 1.242

Cotton 94.4 1.572

Tree Species

Ponderosa 159.63 1.1900

Red alder 179.06 1.2377

Black cherry 38.92 0.9921

Tulip poplar 51.38 2.0889

Sugar maple 36.35 5.7785

Eastern white 63.23 1.6582

Red maple 318.12 1.3756

Douglas fir 106.83 5.9631

Quaking aspen 109.81 1.2198

Virginia pine 1,714.64 1.0000



### 6A.1.1.1 Relative Yield Loss for Crops

Specifically, for crops, we first calculate the FASOMGHG subregion RYLs for crops that

have W126 ozone CR functions using the subregion

- level, cropland

- based ozone concentration

values under each scenario. The FASOMGHG subregion

- level ozone concentration v alues are

initially calculated for all crops as the simple averages of the county

- level ozone concentration

values. For crops that do not have W126 ozone CR functions, we assign them W126 ozone CR

functions based on the crop proxy mapping shown in Table 6A

- 2

. This crop mapping was based

on the authors’ judgment and previous experience. 2 

### In addition, for oranges, rice, and tomatoes,

which have ozone CR functions that are not W126

- based (they are defined based on alternative

measures of ozone levels), we dire ctly used the median RYG values under the 13 ppm

- hr ozone

level reported in Table G

- 7 of Lehrer et al. (2007). More details on RYG are presented in further

subsections.

2 Also, note that FASOMGHG defines short

- rotation woody trees such as hybrid poplar and willow as crops. Ozone

impacts on short

- rotation woody trees were based on ozone RYLs for aspen.

### 6A

- 6

Table 6A

- 3. Mapping of Ozone Impacts on Crops to FASOMGH G Crops

Crops Used for

Estimating Ozone

Impacts FASOMGHG Crops

W126 Crops

Corn Corn

Cotton Cotton

Potatoes Potatoes

Winter wheat Soft white wheat, hard red winter wheat, soft red winter wheat, durum wheat,

hard red spring wheat, oats, barley, rye, sugar beet, grazing wheat, and improved

pasture

Sorghum Sorghum, silage, hay, sugarcane, switchgrass, miscanthus, energy sorghum, and

sweet sorghum

Soybeans Soybeans and canola

Aspen (tree) Hybrid poplar, willow (FASOMGHG places short

- rotation woody biomass

production in the crop sector rather than in the forest sector)

Non

- W126 Crops

Oranges Orange fresh/processed, grapefruit fresh/processed

Rice Rice

Tomatoes Tomato fresh/processed



### Moreover, for crops that have county

- level production data and W126 ozone CR functions

(including functions based on proxy crops), we updated the RYLs with production

- weighted

W126 values. The 2012 USDA Census of Agriculture (Ag Census) county

- level production data

are used to derive the weighted FASOMGHG subregio n RYLs, following Formula (6A .1).

wRYL ik 

### = Ozone CR Function k 

### ( ∑ Prod ijk ∗ W 126 ij j

∑ Prod ijk j 

### )

, (6A.1)

where i denotes FASOMGHG subregion, j indicates county, and k represents crop. Ozone

CR Function k 

### refers to the ozone concentration response function for crop k . Prod ijk 

### represents

the county

- level production level of crop k , and W126 ij 

### represents the cropland

- based ozone

value for county j in subregion i . Finally, wRYL ik 

### stands for the weighted FASOM GHG

subregion RYL for crop k . RYLs are calculated for each ozone concentration level being

considered.

### 6A

- 7

6A.1.1.2 Relative Yield Loss for Trees

The ozone CR functions for tree seedlings were used to calculate RYLs for FASOMGHG

trees over their whole life span. To derive the FASOMGHG region

- level RYLs for trees under

each ozone concentration scenario, we used FASOMGHG region ozone values and the ma pping

in Table 6A

- 3

.

Table 6A

- 4. Mapping of Ozone Impacts on Forests to FASOMGHG Forest Types

Tree Species Used for Estimating

Ozone Impacts FASOMGHG Forest Type FASOMGHG Region(s)

Black cherry, tulip poplar Upland hardwood SC, SE

Douglas fir Douglas fir PNWW

Eastern white pine Softwood CB, LS

Ponderosa pine Softwood PNWE, PNWW, PSW, RM

Quaking aspen Hardwood RM

Quaking aspen, black cherry, red maple,

sugar maple, tulip poplar Hardwood CB, LS, NE

Red alder Hardwood PNWE, PNWW, PSW

Red maple Bottomland hardwood SC, SE

Virginia pine Natural pine, oak

- pine, planted pine SC

Virginia pine, eastern white pine Natural pine, oak

- pine, planted pine SE

Virginia pine, eastern white pine Softwood NE

Note: CB = Corn Belt; LS = Lake States; NE = Northeast; PNWE = Pacific Northwest

— East side; PNWW = Pacific

Northwest

—

West side; PSW = Pacific Southwest; RM = Rocky Mountains; SC = South Central; SE = Southeast

.



### Specifically, the FASOMGHG region

- level RYLs are fi rst calculated for each tree species

listed in first column of Table 6A

- 3. Then, a simple average of RYLs for each tree species

mapped to a FASOMGHG forest type in a given region is calculated. The mapping of tree

species to FASOMGHG forest types is based on Elbert L. Little, Jr.’s Atlas of United States

Trees (1971, 1976, 1977, 1978 ). Note that crop RYLs are generated at the FASOMGHG

subregion level, whereas forest RYLs are calculated at the FASOMGHG region level, consistent

with the greatest level of regional disaggregation available for these sectors within

FASOMGHG.

### 6A

- 8

6A.1.1.3 Calcula tion of Relative Yield Gain

As described by Lehrer et al. (2007) , the RYL is the relative yield loss compared with the

baseline yield under a “clean air” environment. For implementation within FASOMGHG, we

calculate the RYG for crops and trees from moving between ambient ozone concentrations (i.e.,

RYG is calculated as a change in RYL when moving between scenarios).

Thus, to obtain the RYG for crops and trees under alternative ozone concentrations, we

need the RYLs under each s cenario. For example, to derive RYG under the current standard

75 ppb scenario relative to current conditions “currcond,” we use Formula (6A.2 ):

RYG 75 ppb 

### = 1

− RYL 75 ppb

1

− RYL currcond 

### − 1 = RYL currcond − RYL 75 ppb

1

− RYL cur rcond 

### (6A.2)

The FASOMGHG subregion

- level crop RYGs and the FASOMGHG region

- level tree

RYGs for changes associated with moving from one scenario to another were calculated for

additional comparisons in the same way.

6A.1.2 Conducting Model Scenarios in FASOMGHG

The current crop/forest budgets included in FASOMGHG are assumed to reflect

input/output relationships under current ambient ozone concentrations as these budgets are based

on historical data. To model the effects of changing ozone concentratio ns on the agricultural and

forest sectors, the following five scenarios were constructed and run through the model:

1. “Current Conditions” scenario, where no RYGs of crops and trees are considered

(assumed to be consistent with current ambient ozone conc entration levels);

2. 75 ppb scenario, where crop and forest yields are assumed to increase by the

percentages calculated in RYG 75ppb 

### , calculated relative to the current scenario;

3. 70 ppb scenario, using RYG 70ppb 

### , calculated relative to both current and 75 ppb

scenarios

4. 65 ppb scenario, using RYG 65ppb 

### , calculated relative to both current and 75 ppb

scenarios

5. 60 ppb scenario, using RYG 60ppb 

### , calculated relative to both current and 75 ppb

scenarios

### 6A

- 9

The time scope of the FASOMGHG model scenarios used f or these analyses is 2000

–

2050, solved in 5

- year time steps. 3 

### The crop and tree RYGs are introduced into the model

starting in 2025. During the time

- steps of 2025 and 2030, crop and tree RYGs are assumed to be

same as the RYGs in 2025. After 2040, RYGs rem ain constant at the RYGs obtained in 2038.

The special case is in 2035, for which the weighted average of RYGs in 2025 and 2038 (60% for

RYGs in 2025 and 40% for RYGs in 2038) are assigned to RYGs in 2035. Figure 6A

- 5 presents

the modeling process of simul ating ozone scenarios using FASOMGHG. The changes in crop

and tree yield growth potentially lead to new market equilibriums for agricultural and forestry

commodities, as well as land use changes between agricultural and forestry uses and

consequently GHG e missions and sequestration changes.

By comparing the market equilibriums under different scenarios, we can calculate the

welfare, land use, and GHG impacts of alternative ozone standards on the U.S. agricultural and

forest sector, including changes in consumer and producer welfare, land use allocation, and GHG

mitigation potential over time.

3 Because of terminal period effects, the model is run out to the 2050 time period, but only results through the 2040

model time period (representative of 2040

– 2044) are used in our analyses.

### 6A

- 10

Figure 6A

- 5. FASOMGHG Modeling Flowchart

6A.1.3 Data Inputs

In this section, we summarize the input data used in the FASOMGHG scenarios specified

for this assessment. Following the methods described above, we calculated W126 ozone

concentration levels by region and crop. Effects on crop yields and forest productivity were

calculated for each FASOMGHG reg ion. We present the values used as model inputs in tabular

and map format, with a primary focus here on comparison of the more stringent scenarios to the

current standard.

6A.1.3.1 Ambient Ozone Concentration Data

The county

- level forested and cropland W12 6 ozone values were aggregated at regional

and subregional levels, respectively.

### 6A

- 11

Table 6A

- 5. Forestland W126 Ozone Values under Alternative Scenarios

2025 2038

FASOMGHG Region C.C. a 75 ppb 70 ppb 65 ppb 60 ppb 75 ppb 70 ppb 65 ppb 60 ppb

CB 11.84 5.24 4.58 3.11 1.99 5.24 4.58 3.10 1.99

GP c 8.95 5.15 4.47 3.73 2.87 5.06 4.37 3.63 2.79

LS 6.33 2.83 2.71 2.23 1.83 2.83 2.71 2.23 1.83

NE 8.48 3.65 3.19 2.29 1.64 3.65 3.19 2.29 1.64

PNWE 5.55 2.24 2.24 2.22 2.19 2.16 2.14 2.10 2.06

PNWW 3.79 1.49 1.49 1.49 1.49 1.49 1.48 1.48 1.48

PSW 17.28 6.65 6.65 6.64 6.54 4.52 3.61 2.91 2.45

RM 13.36 7.32 7.29 6.83 5.75 6.69 6.57 6.08 5.07

SC 11.84 4.12 3.46 2.48 1.75 4.11 3.46 2.48 1.75

SE 13.10 3.03 2.81 2.26 1.82 3.03 2.81 2.26 1.82

SW a 10.03 6.08 4.58 3.43 2.47 6.04 4.55 3.40 2.44

a Current Conditions

b Current Standard

c GP and SW are modeled as agriculture

- only regions in FASOMGHG.

Note: CB = Corn Belt; GP = Great Plains; LS = Lake States; NE = Northeast; PNWE = Pacific Northwest

— East

side; PNWW = Pacific Northwest

— West side; PSW = Pacific Southwest; RM = Rocky Mountains; SC = South

Central; SE = Southeast; SW = Southwest

.



### Table 6A

- 5 displays the agricultural W126 ozone values at the subregion level. Similar to

the forest ozone values, the Pacific Southwest, South Central, Southeast, and Rocky Mountains

regions experience the greatest agricultural ozone reduction s under the 75 ppb scenario

compared with current conditions. The Corn Belt, Southwest, and Northwest regions also see

noteworthy agricultural ozone reductions.

### 6A

- 12

Table 6A

- 6. Cropland W126 Ozone Values under Modeled Scenarios

2025 2038

FASOMGHG Region Sub

- region C.C. a 75 ppb 70 ppb 65 ppb 60 ppb 75 ppb 70 ppb 65 ppb 60 ppb

CB Illinois, Northern 7.84 3.90 3.51 2.47 1.65 3.90 3.51 2.46 1.65

Illinois, Southern 11.46 6.54 5.79 3.86 2.38 6.53 5.79 3.86 2.38

Indiana, Northern 10.38 4.65 4.43 3.03 1.99 4.64 4.43 3.02 1.99

Indiana, Southern 13.13 6.66 6.40 4.22 2.54 6.65 6.40 4.22 2.54

Iowa, Central 5.71 2.79 2.46 2.06 1.65 2.79 2.46 2.06 1.65

Iowa, Northeast 6.23 2.69 2.42 2.02 1.67 2.69 2.42 2.02 1.67

Iowa, Southern 6.65 3.31 2.68 2.07 1.53 3.31 2.68 2.06 1.53

Iowa, Western 5.74 3.33 2.90 2.51 2.07 3.31 2.90 2.49 2.07

Missouri 11.50 5.17 4.01 2.76 1.81 5.17 4.01 2.76 1.81

Ohio, Northeast 12.71 5.34 5.08 3.51 2.35 5.34 5.08 3.51 2.35

Ohio, Northwest 12.07 5.89 5.65 3.88 2.54 5.88 5.65 3.87 2.54

Ohio, Southern 13.49 5.93 5.73 3.64 2.12 5.93 5.73 3.64 2.12

GP c Kansas 10.93 8.17 6.88 5.54 4.12 8.02 6.74 5.39 4.03

Nebr aska 8.87 5.81 5.27 4.41 3.24 5.65 5.12 4.26 3.13

North Dakota 4.46 3.03 3.00 2.86 2.72 3.03 2.96 2.86 2.69

South Dakota 5.66 3.73 3.50 3.12 2.68 3.67 3.43 3.09 2.62

LS Michigan 9.50 5.20 4.96 3.57 2.50 5.20 4.96 3.57 2.50

Minn esota 4.97 2.63 2.49 2.31 2.12 2.63 2.49 2.31 2.11

Wisconsin 7.02 3.04 2.85 2.25 1.78 3.04 2.85 2.25 1.78



### (continued)

### 6A

- 13 2025 2038

FASOMGHG Region Sub

- region C.C. a 75 ppb 70 ppb 65 ppb 60 ppb 75 ppb 70 ppb 65 ppb 60 ppb

NE Connecticut 11.90 4.53 3.69 2.71 1.85 4.53 3.69 2.71 1.85

Delaware 17.45 7.88 6.29 4.15 2.58 7.88 6.29 4.15 2.58

Maine 3.70 1.62 1.47 1.30 1.20 1.62 1.47 1.30 1.20

Maryland 17.20 7.37 5.88 3.77 2.29 7.37 5.87 3.77 2.29

Massachusetts 10.23 2.98 2.39 1.69 1.18 2.98 2.39 1.69 1.18

New Hampshire 5.84 1.99 1.73 1.32 1.06 1.99 1.73 1.32 1.06

New Jersey 16.70 6.95 5.42 3.49 2.19 6.93 5.42 3.49 2.19

New York 8.36 3.93 3.53 2.78 2.18 3.93 3.53 2.78 2.18

Pennsylvania 12.14 5.37 4.42 2.98 1.97 5.37 4.42 2.98 1.97

Rhode Island 11.72 4.47 3.71 2.69 1.85 4.47 3.71 2.69 1.85

Vermont 5.51 2.01 1.84 1.55 1.35 2.01 1.84 1.55 1.34

West Virginia 10.74 4.63 4.24 2.73 1.68 4.63 4.24 2.73 1.68

PNWE Oregon 6.66 2.64 2.64 2.62 2.55 2.53 2.48 2.43 2.35

Washington 4.96 1.79 1.79 1.79 1.78 1.78 1.78 1.77 1.77

PNWW 3.59 1.35 1.35 1.36 1.36 1.34 1.34 1.35 1.35

PSW California, Northern 21.86 9.61 9.61 9.58 9.49 6.20 4.54 3.21 2.35

California, Southern 21.46 12.49 12.48 12.43 12.31 6.20 5.52 4.82 4.23



### ( continued)

### 6A

- 14 2025 2038

FASOMGHG Region Sub

- region C.C. a 75 ppb 70 ppb 65 ppb 60 ppb 75 ppb 70 ppb 65 ppb 60 ppb

RM Arizona 13.53 9.63 9.63 9.17 7.91 8.24 8.11 7.51 6.24

Colorado 16.33 10.71 10.41 8.98 6.39 10.23 9.88 8.46 6.06

Idaho 12.75 5.05 5.04 4.79 4.15 4.62 4.57 4.30 3.75

Montana 6.61 3.25 3.25 3.15 3.00 3.16 3.16 3.09 2.89

Nevada 15.48 6.57 6.56 6.29 5.58 5.58 5.25 4.75 4.03

New Mexico 12.58 8.54 8.15 7.40 6.20 8.31 7.89 7.11 5.91

Utah 18.06 8.62 8.61 7.81 5.85 7.53 7.40 6.58 4.95

Wyoming 14.28 7.56 7.50 6.79 5.20 7.02 6.91 6.22 4.76

SC Alabama 13.16 2.89 2.70 2.29 1.91 2.89 2.70 2.29 1.91

Arkansas 12.30 4.81 3.76 2.57 1.71 4.81 3.76 2.57 1.70

Kentucky 13.79 5.59 5.35 3.52 2.16 5.59 5.34 3.52 2.16

Louisiana 9.59 4.62 3.58 2.66 1.95 4.62 3.58 2.66 1.95

Mississippi 11.21 3.32 2.75 2.11 1.55 3.32 2.75 2.11 1.54

Tennessee 15.55 4.57 4.22 2.85 1.83 4.57 4.22 2.85 1.83

Texas, East 9.92 5.67 3.88 2.79 1.99 5.64 3.87 2.77 1.98

SE Florida 9.16 2.95 2.86 2.76 2.60 2.95 2.86 2.76 2.60

Georgia 12.79 2.56 2.45 2.21 1.95 2.56 2.45 2.21 1.95

North Carolina 14.31 3.35 3.08 2.49 2.00 3.35 3.08 2.49 2.00

South Carolina 12.82 2.18 2.07 1.77 1.52 2.18 2.07 1.77 1.51

Virginia 12.62 3.95 3.47 2.35 1.59 3.95 3.47 2.35 1.59



### (continued)

### 6A

- 15 2025 2038

FASOMGHG Region Sub

region C.C. a 75 ppb 70 ppb 65 ppb 60 ppb 75 ppb 70 ppb 65 ppb 60 ppb

SW a Oklahoma 11.52 7.44 5.72 4.31 3.07 7.38 5.67 4.25 3.04

Texas, Central

Blacklands 9.17 5.45 4.06 3.05 2.18 5.43 4.05 3.03 2.16

Texas, Coastal Bend 7.24 5.23 4.13 3.24 2.44 5.23 4.12 3.23 2.42

Texas, Edwards

Plateau 9.02 6.38 5.24 4.28 3.38 6.32 5.17 4.20 3.31

Texas, High Plains 11.74 8.49 7.50 6.44 5.18 8.36 7.38 6.27 5.03

Texas, Rolling Plains 10.64 7.13 5.71 4.56 3.45 7.07 5.66 4.48 3.38

Texas, South 4.33 3.45 2.91 2.48 2.09 3.44 2.90 2.47 2.05

Texas, Trans Pecos 11.83 7.49 7.09 6.61 5.86 7.38 6.96 6.44 5.68

a Current Conditions

b Current Standard

c GP and SW are modeled as agriculture

- only regions in FASOMGHG.

### 6A

- 16

Figure 6A

- 6 presents the incremental ozone reductions under alternative 2038 ozone

standards with respect to the current 75 ppb standard. As the standard is tightened from the 70

ppb scenario to the 60 ppb scenario, the greatest ozone reductions are observed in the Pacific

So uthwest region. Central parts of the Rocky Mountains region extending into northern areas of

the Southwest and South central regions also see substantial ozone reductions. These ozone

reductions would affect the production of crops and timber that are susc eptible to ground

- level

ozone in these regions.

Figure 6A

- 6. Ozone Reductions with Respect to 75 ppb under Alternative Scenarios

### 6A

- 17

6A.1.3.2 Changes in Crop and Forest Yields with Respect to 75 ppb Scenario

Figures 6A

- 7 through 6A

- 12 display major crops’ RYGs under alternative ozone

standards scenarios at the FASOMGHG subregion level, with respect to the current 75 ppb

standard. These are the values that were directly incorporated into FASOMGHG to define the

scenarios modeled. Figures 6A

- 13 and 6A

- 14 displ ay changes in forest RYGs. As discussed

previously, the Rocky Mountains, Corn Belt, and parts of the southern regions of the United

States (e.g., within the Pacific Southwest, South Central, and Southeast regions) are shown to

experience the most significa nt further ozone reductions under the alternative policy scenarios.

Hence, one would expect to see the most sizable increases in RYGs for crops and tree species

grown in those regions. This finding is consistent with our calculations.

### 6A

- 18

Figure 6A

- 7. Perc entage Changes in Corn RYGs with Respect to the 75 ppb Scenario

### 6A

- 19

Figure 6A

- 8. Percentage Changes in Cotton RYGs with Respect to the 75 ppb Scenario

### 6A

- 20

Figure 6A

- 9. Percentage Changes in Potato RYGs with Respect to the 75 ppb Scenario

### 6A

- 21

Figure 6A

- 10. Per centage Changes in Sorghum RYGs with Respect to the 75 ppb Scenario

### 6A

- 22

Figure 6A

- 11. Percentage Changes in Soybean RYGs with Respect to the 75 ppb Scenario

### 6A

- 23

Figure 6A

- 12. Percentage Changes in Winter Wheat RYGs with Respect to the 75 ppb

Scenario

### 6A

- 24

Figure 6A

- 13. Percentage Changes in Softwood RYGs with Respect to the 75 ppb Scenario

### 6A

- 25

Figure 6A

- 14. Percentage Changes in Hardwood RYGs with Respect to the 75 ppb Scenario

### 6A

- 26

6A.2 Model Results

FASOM GHG was used to estimate the projected effects of alt ernative ozone

concentration standards on the U.S. agricultural and forestry sectors . As introduced earlier, t he

comparisons considered for this report focus on the differences between a scenario assuming

compliance with the existing 2008 standards (75 ppb) and scenarios in which three more

stringent ozone standards are met. Those three scenarios are 70 ppb, 65 ppb, and 60 ppb W126

values. Our analysis included changes to production, prices, forest inventory, land use, welfare,

and GHG mitigation potential associated with achieving each of the more stringent standards

.

6A.2.1 Agricultural Sector

Ozone negatively affe cts growth in many plants, leading to lower crop yields. In addition,

some crops are more sensitive to ozone than others, so the percentage changes in yield will vary

by crop and region. However, reducing ambient ozone concentrations would generally increa se

agricultural yields and total production, though the reductions in ozone concentrations that would

be achieved under a given standard vary across regions. Our analysis began by determining the

extent to which current yield loss es caused by ozone could b e reversed by reducing ozone levels.

Increased crop yields le a d to a greater available supply of most agricultural crops

, which in turn

tends to reduce market prices . There is also an overall tendency toward acreage shifting away

from ozone

- sensitive crops

. In general, i mpacts in the agricultural sector are relatively limited,

especially when compared with the forestry sector. By and large, more stringent standards led to

increased incremental impact s , but the additional impact in moving to increasingly str ingent

ozone standards was relatively small

.

6A.2.1.1 Production and Prices

Changes in U.S. agricultural production and prices were measured using Fisher i ndices

(sees Tables 6A

- 6 and 6A

- 7). 1 

### Both primary and secondary commodity production levels are

proj ected to increase by 2040 as a result of heightened productivity. Agricultural production

changes were generally relatively small across products, rarely exceeding an increase of 0.50%

with respect to the current standard and often changing by 0.02% or les s.

1 The Fisher price index is known as the “ideal” price index. It is calculated as the geometric mean of an index of

current pr ices and an index of past prices.

### 6A

- 27

Table 6A

- 7

. Agricultural Production Fisher Indices (Current conditions =100)

Sector Policy 2010 2020 2030 2040

Primary

Commodities

Crops 75 ppb 100.0 99.8 100.7 101.3

70 ppb 100.0 99.8 100.7 101.3

65 ppb 100.0 99.8 100.8 101.4

60 ppb 100.0 99.8 100.9 101.4

Livestock 75 ppb 100.0 99.9 100.2 100.3

70 ppb 100.0 99.9 100.2 100.3

65 ppb 100.0 99.9 100.2 100.4

60 ppb 100.0 99.9 100.2 100.5

Farm productsa 75 ppb 100.0 99.8 100.1 100.3

70 ppb 100.0 99.8 100.4 100.3

65 ppb 100.0 99.8 100.5 100.4

60 ppb 100.0 99.9 100.5 100.5

Secondary

Commodities

Processed 75 ppb 100.0 100.0 100.1 100.1

70 ppb 100.0 99.9 100.1 100.1

65 ppb 100.0 99.9 100.1 100.1

60 ppb 100.0 100.0 100.1 100.1

Meats 75 ppb 100.0 100.0 100.1 100.3

70 ppb 100.0 100.0 100.1 100.2

65 ppb 100.0 100.0 100.1 100.3

60 ppb 100.0 100.0 100.2 100.3

Mixed feeds 75 ppb 100.0 99.9 100.1 100.5

70 ppb 100.0 99.9 100.1 100.5

65 ppb 100.0 99.9 100.1 100.5

60 ppb 100.0 99.9 100.2 100.5

a Farm Products is the composite of Crops and Livestock.

### 6A

- 28

Table 6A

- 7

. Agricultural Price Fisher Indices (Current Conditions = 100)

Sector Policy 2010 2020 2030 2040

Primary Commodities

Crops 75 ppb 100.0 100.2 98.5 97.2

70 ppb 100.0 100.2 98.4 97.0

65 ppb 100.0 100.2 98.3 97.0

60 ppb 100.0 100.2 98.3 97.0

Livestock 75 ppb 100.1 101.4 99.2 99.9

70 ppb 100.6 102.2 100.3 97.0

65 ppb 100.1 102.2 100.6 97.0

60 ppb 100.1 101.8 100.4 97.0

Farm productsa 75 ppb 100.0 100.2 100.1 99.9

70 ppb 100.0 100.2 98.4 97.0

65 ppb 100.0 100.2 98.3 97.0

60 ppb 100.0 100.2 98.3 97.0

Secondary Commodities

Processed 75 ppb 100.1 100.3 98.8 98.3

70 ppb 100.1 100.3 98.6 98.2

65 ppb 100.1 100.3 98.2 98.0

60 ppb 100.1 100.3 98.2 97.9

Meats 75 ppb 100.1 99.8 100.1 99.9

70 ppb 100.1 99.8 100.1 99.9

65 ppb 100.1 99.8 100.1 100.0

60 ppb 100.1 99.8 100.1 100.0

Mixed feeds 75 ppb 100.1 99.7 98.2 99.3

70 ppb 100.1 99.7 98.1 99.5

65 ppb 100.1 99.7 97.4 99.3

60 ppb 100.1 99.7 97.5 99.5



### Increased production led to a general decline in market prices because the equilibrium

price adjusts to higher levels of supply. This result is consistent with expectations because higher

productivity leads to greater supply, which tends to decrease market prices. C hanges in price

were generally more pronounced than changes in production, with the largest decreases in the

### 6A

- 29

Farm Products, Livestock, and Processed categories. Agricultural prices tend to decline by a

greater percentage than production increases because t he demand for most agricultural

commodities is inelastic. 2 However, almost all declines in price were less than 2.0% of prices at

the current standards, and most were less than 0.5%.

6A.2.1.2 Crop Acreage

Crop acreage was projected to decline with the int roduction of the ozone standards because

additional productivity per acre reduces the demand for crop acreage. In aggregate, f armers will

be able to meet the demand for agricultural commodities using less land under scenarios with

lower ozone concentration s . Consistent with these expectations, the total cropped area is slightly

smaller for each model year in the alternative standard cases. However, land allocation also

depends on relative returns across various uses and is influenced by forest harvest timin g.

C hanges in land allocation between the agricultural and forestry sectors are discussed later in this

section.

Table 6A

- 8 provides projections of acreage in each of the major U.S. crops

, as well as

composites of all remaining crops and total cropland. Th e absolute change relative to the current

standard is presented for each alternative standard

. Larger changes occurred in sorghum acreage,

whereas only minor changes occurred in all other crops, leading to almost no net change in crop

acreage across all cr ops. This shift occurred largely because of differential crop sensitivity to

ozone concentrations. Note that the sum of the crop

- specific changes will not necessarily equal

the total changes shown in Table 6A

- 8 because some double

- cropping is reflected in the model

(e.g., soybeans and winter barley).

2 Demand elasticities are measures of the responsiveness of the quantity demanded to a change in price.

Commodities with inelastic demands are those where consumers change the quantity of a good they purchase by a

smaller percentage than the change in market price. Many food products fall into this category because they are

relatively low

- priced necessities.

### 6A

- 30

Table 6A

- 8. Major Crop Acreage, Million Acres

Crop Policy 2010 2020 2030 2040

Corn 75 ppb 91.2 85.8 77.4 70.9

Change with Respect to Current Standard

70 ppb 0.00 0.02 0.00

- 0.05

65 ppb 0.00 0.01 0.06

- 0.07

60 ppb 0.00 0.01 0.04

- 0.08

Soybeans 75 ppb 4.9 5.2 5.8 6.9

Change with Respect to Current Standard

70 ppb 0.00 0.00 0.00 0.00

65 ppb 0.00 0.00 0.00

- 0.03

60 ppb 0.00 0.00 0.00

- 0.03

Hay 75 ppb 43.7 41.1 41.7 42.0

Change with Respect to Current Standard

70 ppb 0.00

- 0.02 0.03 0.00

65 ppb 0.00

- 0.01 0.05

- 0.01

60 ppb 0.00 0.01 0.06

- 0.07

Hard Red

Winter Wheat 75 ppb 25.5 23.7 23.2 22.4

Change with Respect to Current Standard

70 ppb 0.00 0.00 0.00

- 0.06

65 ppb 0.00 0.00

- 0.06

- 0.11

60 ppb 0.00 0.00

- 0.03

- 0.10

Cotton 75 ppb 13.6 13.6 14.2 14.0

Change with Respect to Current Standard

70 ppb 0.00 0.00

- 0.04

- 0.01

65 ppb 0.00 0.00

- 0.05

- 0.01

60 ppb 0.00 0.00

- 0.04 0.00

Hard Red Spring

Wheat 75 ppb 13.5 12.9 13.4 13.0

Change with Respect to Current Standard

70 ppb 0.00 0.00 0.01 0.01

65 ppb 0.00 0.01

- 0.03 0.00

60 ppb 0.00 0.01

- 0.08

- 0.01

Sorghum 75 ppb 73.1 71.9 72.0 72.2

Change with Respect to Current Standard

70 ppb 0.00 0.20 0.02

- 4.88

65 ppb 0.00 0.24 0.02

- 4.90

60 ppb 0.00 0.26 0.09

- 4.89

SwitchGrass 75 ppb 0.1 0.1 0.1 0.1

Change with Respect to Current Standard

### 6A

- 31

Crop Policy 2010 2020 2030 2040

70 ppb 0.00 0.00 0.00 0.00

65 ppb 0.00 0.00 0.00 0.00

60 ppb 0.00 0.00 0.00 0.00

All Others a 75 ppb 352.2 366.7 355.8 340.0

Change with Respect to Current Standard

70 ppb 0.00 0.10 0.01

- 0.17

65 ppb 0.00 0.13

- 0.12

- 0.32

60 ppb 0.00 0.19

- 0.25

- 0.45

Total 75 ppb 5.6 5.4 4.6 4.0

Change with Respect to Current Standard

70 ppb 0.00 0.00 0.01

- 0.01

65 ppb 0.00

- 0.01 0.02 0.00

60 ppb 0.00

- 0.01 0.01 0.00

a Canola, durum wheat, fresh grapefruit, fresh orange, fresh tomato, grazing wheat, hybrid poplar, oats, potato,

processed grapefruit, processed orange, processed tomato, rice, rye, silage, soft red winter wheat, soft white

wheat, spring barley, sugar beet, sugarcane, sweet sorghum, winter barley.



### 6A.1.3 Forestry Sector

As with agricultural crops, ozone diminishes growth in most tree species, and our analysis

began by estimating how much of this diminished growth would be reversed under the more

stringent ozone standards. Impacts are significantly higher in the forestry sector, especially in

hardwood species and species more prevalent in the southern regions. Impacts are more

significant for southern regions because of the higher baseline ozone concentratio ns in the S outh

C entral and S outheast regions. Higher initial concentrations resulted in higher reductions to meet

the alternative standards and

, thus

, higher impacts to tree growth. This relationship also

contributes to the larger changes in the forestry sector as a whole.

6A.1.3.1 Production and Prices

Reducing ozone concentrations led to increased forest growth, which was reflected in

increased production in FASOMGHG. Some of the most substantial ozone standard impacts

occurred in saw log and pulp log h arvest quantities and prices. Compared with the current

standard, alternative standard cases had consistently higher production except for hardwood pulp

logs in 2030 and softwood pulp logs in 2040, where production increased only marginally and at

### 6A

- 32

times fe ll below the baseline estimates, especially in 2040. The most significant impacts

occurred in hardwood pulp logs, where harvests were projected to be more than 1% higher than

under the current standard level by 2040 for the 60 ppb concentration. There are some cases

where production of pulp logs and saw logs moved in opposite directions. There are two primary

explanations for these trends. The first is that as softwood saw log production expand s , the price

for softwood saw logs drop s, allowing processers to substitute saw logs for cases of production

in which pulp logs are traditionally u sed

. The second is that even when the primary log size

being harvested is pulp logs, saw logs will generally also be present because of natural variation

in tree growth rate s (and vice versa for harvest of saw logs). With higher growth rates, there

would tend to be more saw logs in stands harvested primarily for pulp logs over time.

The largest changes in production occurred at the 60 ppb level. Changes from the current

stan dard to 70 ppb were fairly small, but increased in 65 ppb, and changes were even larger in 60

ppb. Table 6A

- 9 presents these changes by major product.

The impact of policy intervention on timber market prices was more substantial than the

change in product ion in terms of percentage changes compared with the current standard.

Although increases in production of forest products did not exceed 1.5% compared with the

current standard, changes in price were as large as 12.8%. As with agricultural products, many

forest products have relatively inelastic demand so prices tend to change by a larger percentage

than quantities. Table 6A

- 10 lists absolute changes with respect to the current standard, whereas

Table 6A

- 11 lists the percentage change in forest product pri ces for each year, alternative

standard, and forest product.

Table 6A

- 9. Forest Products Production, Million Cubic Feet

Product Policy 2010 2020 2030 2040

Hardwood Saw logs 75 ppb 3,588 3,394 3,708 4,246

Change with Respect to Existing Standard

70 ppb 1 1 38 3

65 ppb 1 0 33

- 6

60 ppb 3 0 54

- 13

Hardwood Pulp logs 75 ppb 2,448 2,162 2,510 2,220

Change with Respect to Existing Standard

### 6A

- 33 70 ppb 2 1

- 29 3

65 ppb 3

- 2

- 29 14

60 ppb 10

- 1

- 40 25

Softwood saw logs 75 ppb 4,568 5,114 5,449 6,542

Change with Respect to Existing Standard

70 ppb

- 1 10

- 2 7

65 ppb 0 22 1 53

60 ppb 5 35 21 61

Softwood pulp logs 75 ppb 3,437 3,878 4,350 4,298

Change with Respect to Existing Standard

70 ppb 1

- 2 3

- 17

65 ppb 0 1 4

- 23

60 ppb 2 1 8

- 8



### Table 6A

- 10. Forest Product Prices, U.S. Dollars per Cubic Foot

Product Policy 2010 2020 2030 2040

Hardwood saw logs 75 ppb 0.80 0.89 0.58 0.33

Change with Respect to Existing Standard

70 ppb 0.00

- 0.01

- 0.01

- 0.02

65 ppb 0.00

- 0.01

- 0.02

- 0.03

60 ppb 0.00

- 0.01

- 0.03

- 0.04

Hardwood pulp logs 75 ppb 0.30 0.64 0.45 0.24

Change with Respect to Current Standard

70 ppb 0.00

- 0.01

- 0.01

- 0.01

65 ppb 0.00

- 0.01

- 0.03

- 0.02

60 ppb 0.00

- 0.02

- 0.04

- 0.03

Softwood saw logs 75 ppb 2.46 2.08 1.78 1.50

Change with Respect to Current Standard

70 ppb 0.00 0.00 0.00 0.00

65 ppb 0.00

- 0.01

- 0.01

- 0.02

60 ppb

- 0.01

- 0.02

- 0.02

- 0.04

Softwood pulp logs 75 ppb 1.49 1.33 1.47 1.14

Change with Respect to Current Standard

70 ppb 0.00 0.00 0.00 0.00

### 6A

- 34 Product Policy 2010 2020 2030 2040

65 ppb 0.00 0.00

- 0.01

- 0.02

60 ppb

- 0.01 0.00

- 0.03

- 0.05



### Table 6A

- 11. Forest Product Prices and Percentage Change, U.S. Dollars per Cubic Foot

Product Policy 2010 2020 2030 2040

Hardwood saw logs 75 ppb 0.80 0.89 0.58 0.33

% Change with Respect to Existing Standard

70 ppb

- 0.41%

- 0.75%

- 2.16%

- 5.07%

65 ppb

- 0.24%

- 1.00%

- 3.89%

- 9.11%

60 ppb

- 0.25%

- 1.22%

- 5.60%

- 11.36%

Hardwood pulp logs 75 ppb 0.30 0.64 0.45 0.24

% Change with Respect to Existing Standard

70 ppb 0.07%

- 0.96%

- 3.19%

- 5.15%

65 ppb 0.12%

- 1.92%

- 5.57%

- 10.53%

60 ppb

- 0.06%

- 2.87%

- 8.98%

- 12.75%

Softwood saw logs 75 ppb 2.46 2.08 1.78 1.50

% Change with Respect to Existing Standard

70 ppb 0.01%

- 0.17%

- 0.16%

- 0.13%

65 ppb 0.03%

- 0.27%

- 0.36%

- 1.08%

60 ppb

- 0.28%

- 0.97%

- 1.20%

- 2.65%

Softwood pulp logs 75 ppb 1.49 1.33 1.47 1.14

% Change with Respect to Existing Standard

70 ppb

- 0.05% 0.28%

- 0.28%

- 0.13%

65 ppb

- 0.18% 0.10%

- 0.76%

- 1.90%

60 ppb

- 0.57%

- 0.27%

- 1.87%

- 4.11%



### 6A.1.3.2 Forest Acres Harvested

Harvested acres are projected to decline in hardwoods as a result of higher productivity in

the policy cases. Conversely softwood acres harvested increases over time. The difference

between the hardwood harvested acres in th e current standard case and in the alternative

### 6A

- 35

standards widens from 2010 to 2040

, increasing to a difference of more than 4 % under the 60

ppb case

. The impact to total acres of softwood harvested shows a less uniform pattern, with the

largest impacts under the 65 ppb scenario, and an increase of up to 6% of harvested acres by

2040 compared to 2010. Table 6A

- 12 presents the model results for forest acres harvested.

Table 6A

- 12. Forest Acres Harvested, Thousand Acres

Product Policy 2010 2020 2030 2040

Total hardwood 75 ppb 14,923 11,701 12,277 13,138

Change with Respect to Current Standard

70 ppb 4 50

- 139

- 151

65 ppb 8 37

- 265

- 352

60 ppb 37 50

- 377

- 513

Total softwood 75 ppb 17,539 16,158 14,911 19,031

Change with Respect to Current Standard

70 ppb

- 11 35 47 106

65 ppb

- 13 107 223 361

60 ppb

- 2 142 328 314



### 6A.1.3.3 Forest Inventory

Under FASOM GHG definitions, existing inventory includes only trees that have been

standing since the initial model year of 2000. All trees planted since then, including both

reforestation and afforestation, are included in new inventory. The model projected significant

increase s in existing inventory for hard wood species under the current standard

, and consistent

with the increase in the acres harvested of softwood, the existi ng inventory of softwoods declines

through 2040 under the current standard

. The difference in responses is partially explained by

differential sensitivity to ozone between species. Hardwood species show a much higher

sensitivity to ozone levels and are thus modeled to respond more dramatically to reductions in

ozone concentration

.

Some relatively large differences between ozone standards occurred in the forest inventory

projections . For example, existing hardwood inventory was projected t o be 4.0 % small under the

60 ppb case than the 70 ppb case by 2040. New hardwood inventory is similarly sensitive

, with

### 6A

- 36

the model projecting a 2% de crease for th is same comparison. For new and existing inventory of

both hardwoods and softwoods, the largest impacts occurr ed at the 70 ppb standard. This type of

nonlinear response can occur because of differences in the relative impacts on alternative forest

and agricultural products that lead to land reallocation. Table 6A

- 13 presents the model results

for forest inventory.

Table 6A

- 13. Existing and New Forest Inventory, Million Cubic Feet

Product Policy 2010 2020 2030 2040

Existing Hardwood 75 ppb 281,924 273,055 292,685 306,296

Change with Respect to Existing Standard

70 ppb 0

- 64 1,983 4,998

65 ppb 0

- 138 5,974 14,937

60 ppb 0

- 278 8,896 22,548

Existing Softwood 75 ppb 184,828 153,771 135,137 133,794

Change with Respect to Existing Standard

70 ppb 0

- 19 185 494

65 ppb 0

- 38 683 1,583

60 ppb

- 6

- 77 1,059 2,553

New Hardwood 75 ppb 1,932 9,437 18,872 29,732

Change with Respect to Existing Standard

70 ppb 0

- 152

- 107 77

65 ppb 0

- 150

- 63 577

60 ppb 1

- 156 0 931

New Softwood 75 ppb 8,837 64,254 114,454 128,581

Change with Respect to Existing Standard

70 ppb 0

- 42

- 17

- 497

65 ppb 4 6

- 128

- 1,164

60 ppb 7

- 18

- 312

- 1,798



### 6A.1.4 Cross

- Sectoral Policy Impacts

One of the advantages of a model such as FASOMGHG for analysis of impacts on major

land

- using activities is the ability to account for shifts in land use. Differentiated impacts on

productivity across products will lead to changes in market prices and in the relative profitability

### 6A

- 37

of alternative land uses. In response, landowners will change their allocation of land across

different productive activities, wh ich will contribute to market impacts. In addition, these

changes in land use have implications for GHG emissions and other environmental impacts. In

this section, we discuss changes in land use, net GHG emissions, and producer and consumer

welfare across the agricultural and forest sectors.

6A.1.4.1 Land Use

FASOM GHG projected changes in eight land use categories: existing forest,

reforestation, afforestation, cropland, pasture, cropland pasture

, 3 

### and lands enrolled in the

Conservation Research Program (C RP)

. 4 

### The largest impacts under the current standard were

projected in afforestation. The general projected pattern under the alternative standards within

these categories was a decline in reforested area, afforested area, and cropland in 2030 and 2040,

co upled with increases in the pasture and cropland pastured areas

. There was no change in

acreage retained in CRP or rangeland

.

The incremental impact of more stringent ozone standards appears to be non

- linear in

some cases, especially in existing and refore sted areas. Existing forest exhibits a general decline

in the area under the 70 ppb scenario; in the 60 ppb scenario, however, there are small declines

through 2020, followed by large increases in 2030 and 2040. This is due to the different trends in

the hardwood and softwood species. Table 6A

- 14 presents the model results by major land use

type.

Table 6A

- 14. Land Use by Major Category, Thousand Acres

Product Policy 2010 2020 2030 2040

Existing forest 75 ppb 257,565 201,587 161,426 131,210

Change with Respect to Current Standard

70 ppb

- 7 82

- 113

- 269

65 ppb 0 0 0 0

60 ppb

- 2

- 84 159 691

Reforested 75 ppb 72,201 117,974 148,837 172,267

Change with Respect to Current Standard

3 Cropland pasture is managed land suitable for crop production (i.e., relatively high productivity) that is being u sed

as pasture

.

4 Rangeland estimates are also included, but rangeland is held fixed in FASOMGHG by assumption because it

cannot be allocated to any other use.

### 6A

- 38

Product Policy 2010 2020 2030 2040

70 ppb

- 10

- 7

- 56

- 189

65 ppb

- 16 52

- 212

- 878

60 ppb 28 107

- 267

- 1346

Afforested 75 ppb 14,086 10,886 6,404 11,474

Change with Respect to Current Standard

70 ppb 0 0

- 134

- 134

65 ppb 0 0

- 309

- 309

60 ppb 0 0

- 427

- 427

Cropland 75 ppb 311,713 313,325 304,227 292,678

Change with Respect to Current Standard

70 ppb 0 96

- 38

- 60

65 ppb 0 124

- 102

- 157

60 ppb 0 180

- 157

- 200

Pasture 75 ppb 84,280 85,049 86,133 82,571

Change with Respect to Current Standard

70 ppb 3

- 7 86 64

65 ppb 10

- 11 189 168

60 ppb 10 24 257 263

Cropland pasture 75 ppb 45,381 44,634 55,061 61,042

Change with Respect to Current Standard

70 ppb 0 1 29 51

65 ppb 0 1 161 216

60 ppb 0 6 235 277

Rangeland 75 ppb 302,210 301,104 300,049 299,039

Change with Respect to Current Standard

70 ppb 0 0 0 0

65 ppb 0 0 0 0

60 ppb 0 0 0 0

CRP 75 ppb 36,879 36,659 36,659 36,659

Change with Respect to Current Standard

70 ppb 0 0 0 0

65 ppb 0 0 0 0

60 ppb 0 0 0 0

### 6A

- 39

6A.1.4.2 Welfare

Welfare impacts resulting from the implementation of alternative standard levels

followed the same pattern between the agriculture and forestry sectors, al though it was more

pronounced in forestry. Consumer surplus typically increased in both cases as higher

productivity unde r reduced ozone conditions tended to increase total production and reduce

market prices. Because demand for most forestry and agricultural commodities is inelastic, there

are more instances in which producer surplus decline s. In some year/ozone concentration

combinations, the effect of fa lling prices on producer profits more than outweighs the effects of

higher production levels.

Percentage changes in agricultur al sector consumer and producer surplus between the

current standard and the alternative standards were relatively small in many cases

, with the

largest percentage change being a 5.8% decline in producer surplus in the 2040 model period.

However, the agricultural sector is a very large market, and even small percentage changes in

welfare can result in annualized values of tens or ev en hundreds of millions of dollars. Table 6A

15 provides consumer and producer surplus for the agricultural sectors under the current

standard, along with the change in surplus for each alternative standard

. There is considerable

variability in the magnitu de of consumer and producer impacts from year to year, which is not

surprising given the dynamic nature of the model and numerous adjustments taking place over

time in response to changes in net returns associated with alternative land uses.

Table 6A

- 15

. Consumer and Producer Surplus in Agriculture

, Million 2010 U.S. Dollars

Product Policy 2010 2015 2020 2025 2030 2035 2040

Consumer

Surplus 75 ppb 1,907,219 1,928,147 1,955,266 1,983,375 2,013,518 2,042,566 2,071,338

Change with Respect to Existing Standard

70 ppb 0 0 0 113 66 58

- 10

65 ppb

- 1 1 4 262 148 289 24

60 ppb 0 47 9 462 100 408 66

Producer

Surplus 75 ppb 718,105 824,802 815,996 865,123 817,707 874,549 908,352

Change with Respect to Existing Standard

70 ppb 1,202 2,454 1,796 609

- 1,144 675

- 52,504

65 ppb 216 530

- 407 1,174

- 2,933

- 39,605

- 10,211

### 6A

- 40 60 ppb

- 176 1,015

- 1,470 1,320

- 1,492

- 38,788

- 8,119



### The impacts of the scenarios with more stringent ozone standards w ere larger in the

forestry sector, with bigger increases in consumer surplus and greater declines in producer

surplus . Table 6A

- 16 presents the model results of the welfare analysis in the forestry sector.

Table 6A

- 16

. Consumer and Producer Surp l us in Forestry , Million 20 10 U.S. Dollars

Product Policy 2010 2015 2020 2025 2030 2035 2040

Consumer

surplus 75 ppb 715,634 760,957 801,653 819,407 867,332 885,687 926,837

Change with Respect to Current Standard

70 ppb 3 24,592

- 9

- 2 70 167 72

65 ppb 12 24,595 4 43 189 263 138

60 ppb 30 24,695 127 257 433 686 245

Producer

surplus 75 ppb 93,795 147,719 154,137 144,888 147,039 147,797 132,850

Change with Respect to Current Standard

70 ppb 1

- 24,614

- 28 94

- 24

- 152 8

65 ppb

- 5

- 24,621

- 73 291

- 111

- 86

- 35

60 ppb

- 57

- 24,727

- 261 135

- 471

- 503 37



### Because of the complex dynamics of the agriculture and forestry sectors and variability in

welfare impacts over time, it is often helpful to summarize the impacts in terms of annualized

values. Table 6A

- 17 and Table 6A

- 18 summarizes the annualized impacts of alternative ozone

standards on consumer and producer surplus in the agricultural and forestry sectors for 2010

–

2044 at a discount rate of 3% and 7% respectively. 5 

### The impacts of alternative s tandards on

consumer surplus are positive for each of the tighter standards for both agricultural and forestry

sectors, with the benefits increasing with more stringent requirements. For producer surplus, on

the other hand, annualized impacts are negative for all of the tighter standards for both

agriculture and forestry sector, becoming more negative as stringency is increased. Overall, total

5 Each model period in FASOMGHG is representative of the 5

- year period starting with that year, so results reported

for 2040 are representative of 2040

– 2044. Thus, we use values through 2044 in the annualization calculations.

### 6A

- 41

surplus declines for the agriculture sector while rises slightly for the forest sector across, leading

to a net dec rease for both sectors.

Table 6A

- 17

. Annualized Changes in Consumer and Producer Surpl us in Agriculture and

Forestry

, 2010

– 2044, Million 20 10 U.S. Dollars (3% Discount Rate)

Product Policy Agriculture Forestry Total

Consumer surplus 75 ppb 1,969,838 805,5 63 2,775,401

Change with Respect to Current Standard

70 ppb 28 4,552 4,580

65 ppb 86 4,592 4,678

60 ppb 132 4,744 4,877

Producer surplus 75 ppb 817,744 135,478 953,222

Change with Respect to Current Standard

70 ppb

- 3,601

- 4,534

- 8,135

65 ppb

- 5,035

- 4,524

- 9,559

60 ppb

- 4,741

- 4,684

- 9,425

Total surplus 75 ppb 2,787,582 941,041 3,728,623

70 ppb

- 3,573 18

- 3,555

65 ppb

- 4,949 68

- 4,882

60 ppb

- 4,608 60

- 4,548



### Table 6A

- 18

. Annualized Changes in Consumer and Producer Surpl us in Agriculture and

Forestry

, 2010

– 2044, Million 20 10 U.S. Dollars (7% Discount Rate)

Product Policy Agriculture Forestry Total

Consumer surplus 75 ppb 1,951,843 782,748 2,734,591

Change with Respect to Existing Standard

70 ppb 21 5,570 5,592

65 ppb 61 5,599 5,660

60 ppb 100 5,721 5,821

Producer surplus 75 ppb 800,022 130,681 930,703

Change with Respect to Existing Standard

70 ppb

- 945

- 5,561

- 6,506

65 ppb

- 2,719

- 5,555

- 8,273

60 ppb

- 2,635

- 5,694

- 8,328

Total surplus 75 ppb 2,751,865 913,429 3,665,294

### 6A

- 42 Change with Respect to Existing Standard

70 ppb

- 923 9

- 914

65 ppb

- 2,658 45

- 2,613

60 ppb

- 2,535 27

- 2,508



### 6A.1.4.3 Greenhouse Mitigation Potential

The capacity for both the agricultural and forest sectors to sequester carbon is enhanced

in each of the alternative standard cases, with increasing magnitude as p olicy stringency is

increased

. Although FASOM GHG projects fewer acres of forestland and total cropland, the

accelerated storage of carbon in trees and forest land and crop land soils outweighs any decline

from reductions in covered area. Carbon storage in both sectors is consistently higher in the

alternative standard cases, with the gap widening over time (see Figure 6A

- 15 for change in

forest carbon stock) . By 2040, the a g ricultural sector sequestered 0.01%~0.05% % more carbon

under the alternative standard cases and the forestry sector up to 0.5% more, resulting in gains of

more than 1,500 million metric tons CO 2 

### equivalent (MMtCO 2 

### e). Table 6A

- 19 presents carbon

sequestrati on projections under the current standard and changes under each alternative

standard

. 6 

### Note that negative values in the row for the current standard indicate sequestration or

carbon storage. Negative values in the change rows indicate that the alternative standard stores

more carbo n than the current standard (and vice versa for positive changes).

Notice that for the agricultural sector, the overall s tock of net GHG would decrease over

time in the baseline because cropping activities involve fertilizer and chemical usage, fossil

fuels, running machinery, livestock emissions from enteric fermentation and manure

management, and so forth

— all these GHG emi ssions are being released each year, while soil

carbon sequestration moves toward equilibrium within 25 years of a change in tillage. As soil

carbon reaches equilibrium, little additional sequestration is taking place each year but annual

emissions from ot her sources continue. Thus, over time, the annual emissions tend to outweigh

the increase in carbon stocked in agricultural soils, and net stock of GHG tends to become less

negative and eventually positive relative to the starting point. 7

6 These are total stocks of net GHG emissions over time, not annual emissions. If the total stock of GHG is

becoming more neg ative over time, more net sequestration is taking place than emissions. If the total stock of GHG

is becoming less negative or positive over time, emissions are greater than the increase in sequestration.

7 This change is consistent with the fact that U.S. agriculture is a net source of emissions on an annual basis. The

value of the total GHG stock associated with agriculture is starting at a negative value because of the FASOMGHG

convention of accounting fo r total carbon sequestration present in agricultural soils in the first year of the model run.

A large stock of carbon is sequestered, but it does not increase by much over time.

### 6A

- 43

Figure 6A

- 15. Carbon Storage in Forestry Sector, MMtCO 2 

### e

Table 6A

- 19. Carbon Storage, MMtCO 2 

### e

Product Policy 2010 2020 2030 2040 2010

- 2044

Agriculture 75 ppb

- 18,621

- 15,240

- 11,772

- 8,009

- 268,210

Change with Respect to Existing Standard

70 ppb 0

- 1

- 3

- 1

- 24

65 ppb 0

- 2

- 6

- 4

- 62

60 ppb

- 1

- 4

- 11

- 11

- 132

Forestry 75 ppb

- 73,321

- 74,338

- 77,963

- 81,063

- 1,533,424

Change with Respect to Existing Standard

70 ppb 1 51

- 100

- 259

- 1537

65 ppb 2 53

- 323

- 774

- 5207

60 ppb 12 94

- 465

- 1189

- 7739



### Changes in forestry sector carbon sequestration are largely driven by changes in forest

management, which include the increases in tree yield in the lower ozone environments. The

increased sequestration in this category outweighs losses in sequestration in the oth er major (84,000) (82,000) (80,000) (78,000) (76,000) (74,000) (72,000) (70,000)

2010 2015 2020 2025 2030 2035 2040

Base 75 ppb 70 ppb 65 ppb 60 ppb

### 6A

- 44

forestry categories: afforest ation and forest soil. Table 6A

- 20 presents the detailed changes in

forestry carbon sequestration.

Table 6A

- 20. Forestry Carbon Sequestration, MMtCO 2 

### e

Product Policy 2010 2020 2030 2040

Afforestation,

Trees 75 ppb

- 730

- 1594

- 963

- 1502

Change with Respect to Existing Standard

70 ppb 0 0 22 29

65 ppb 0 0 48 64

60 ppb 0 0 66 88

Afforestion, Soils 75 ppb

- 767

- 598

- 550

- 1018

Change with Respect to Existing Standard

70 ppb 0 0 11 11

65 ppb 0 0 27 27

60 ppb 0 0 37 37

Forest

Management 75 ppb

- 39827

- 37995

- 40023

- 39556

Change with Respect to Existing Standard

70 ppb 1 43

- 125

- 291

65 ppb 2 44

- 387

- 852

60 ppb 11 77

- 553

- 1298

Forest Soils 75 ppb

- 28320

- 27698

- 27243

- 27474

Change with Respect to Existing Standard

70 ppb 0 10 5 4

65 ppb 1 13 20 19

60 ppb 1 21 27 28



### 6A.2 Summary

Impacts to both sectors generally mirror one another, al though they are more prominent in

the forestry sector. Not only are tree species more responsive to changes in ozone, but the largest

reductions to meet the alternative standards will occur in regions with large forestry sectors:

S outh C entral, S outheast, and Rocky Mountains. Reductions in agricultural regions are

comparatively moderate. Productivity of both crops and forests is projected to increase at each of

the alternative standard levels. This increase in supply resulted in decreased prices for forest

products and agricultural commodities, which benefits consumer welfare while reducing

producer welfare. Unless there are significant changes to wood products markets in particular,

producers will be forced to sell at reduced prices to absorb the increased supply

. Nonetheless,

### 6A

- 45

gains to consumers become increasingly large with more stringent ozone standards. Gains to

agricultural producers in the most stringent case are associated with a decline in forestry returns

that results in a net shift in land use towa rd agriculture.

Increased productivity is also projected to affect land use both within and between the

agricultural and forest sectors. Within sectors, acreage is projected to shift from crops and tree

species that are more sensitive to ozone to those th at are less sensitive because productivity in the

former will be more substantially affected by reductions in ozone concentrations. For ozone

sensitive crops and species, producers are projected to require less land to produce at the same or

higher levels. Forest acreage in particular is projected to decline sharply, driven by declines in

both reforestation and afforestation.

Despite reductions in crop and forest area, carbon sequestration is expected to increase

over time, led almost entire ly by increased forest sequestration. Although there is less

reforestation and afforestation and lower sequestration in new inventory, the change is a result of

existing inventories becoming so much larger as trees grow faster. Lower sequestration in new

inventory is outw eighed by increased inventory in standing forests

, represented in the model as a

change in forest management.

Increased stringency in the ozone standard generally produces larger impacts on all of the

model outputs. However, the additional impact of movin g from the current standard to 65 ppb, or

to 60 ppb was sometimes marginal compared with changes occurring between the current

standard to 70 ppb. In particular, the impacts to the forestry sector, most notably in forest

inventories and the forest sector w elfare analysis, tended to increase at a decreasing rate after

meeting the 70 ppb standard.

The model results are subject to several limitations: First, the ozone concentration response

functions applied to crops and trees were using “median” parameters i n Lehrer et al. (2007)

— the

RYLs and RYGs calculated are thus “median” ones; second, the use of crop proxy mapping and

the forest

- type mapping due to incomplete data specified in Section 6.1 adds to the uncertainty of

these mode l results; third, the potential changes in tree species mixes within forest types due to

ground ozone

- level changes were not considered; and last, the international trade component in

FASOMGHG that assumes USDA

- based future projections under current condit ions may present

### 6A

- 46

another uncertainty for the model results, especially when soybeans and wheat are among the

major crop commodities for U.S. exports and have relatively large responses to changed ozone

environments.

6A.3 References

Jin, S., Yang, L., Danielson, P., Homer, C., Fry, J., and Xian, G. 2013. A comprehensive change detection method

for updating the National Land Cover Database to circa 2011. Remote Sensing of Environment, 132: 159

–

175.

Lehrer, J.A., M. Bacou, B. Blankespoor, D. McCubbin, J . Sacks, C.R. Taylor, and D.A. Weinstein. 2007. Technical

Report on Ozone Exposure, Risk, and Impact Assessments for Vegetation . EPA 452/R

- 07

- 002.

Little, E.L., Jr. 1971. Atlas of United States Trees, Volume 1, Conifers and Important Hardwoods . U.S. Depar tment

of Agriculture Miscellaneous Publication 1146, 9 p., 200 maps.

Little, E.L., Jr. 1976. Atlas of United States Trees, Volume 3, Minor Western Hardwoods . U.S. Department of

Agriculture Miscellaneous Publication 1314, 13 p., 290 maps.

Little, E.L., Jr . 1977. Atlas of United States Trees, Volume 4, Minor Eastern Hardwoods . U.S. Department of

Agriculture Miscellaneous Publication 1342, 17 p., 230 maps.

Little, E.L., Jr. 1978. Atlas of United States Trees, Volume 5, Florida . U.S. Department of Agricultur e

Miscellaneous Publication 1361, 262 maps.

U.S. Department of Agriculture, National Agricultural Statistics Service (USDA NASS). Various years. USDA

Agricultural Statistics (1990

– 2012) . Available at: http://www.nass.usda.gov/Publications/Ag_Statistics/

.

U .S. Department of Agriculture, Natural Resource Conservation Service (USDA NRCS). 2003. Annual NRI

— Land

Use . Available at: http://www.nrcs.usda.gov/technical/NRI

.