## November 2014 M-1



# Appendix M: Summary of Illustrative Forestry and Agriculture Results

Table of Contents

1. Retrospective Reference Point Baseline: Southeast R oundwood .......................................... ............... M-2
1.1. Key Insights from the Retrospective Reference Point Baseline Application to Southeast Roundwood .........................................

................................................... ................................................... ............ M-3
2. Future Anticipated Baseline: Southeast Roundwood ..

................................................... ........................... M-4 2.1. Key Insights from the Future Anticipate Bas eline Application to Southeast Roundwood .. M-6
3. Retrospective Reference Point Baseline: Pacific Nor thwest Logging Residues ........................... ... M-7
3.1. Key Insights from the Retrospective Reference Point Baseline Application to Pacific Northwest Logging Residues ........................

................................................... .............................................. M-8
4. Future Anticipated Baseline: Pacific Northwest Logg ing Residues ...................................... ............... M-8
4.1. Key Insights from the Future Anticipate Baseline Ap plication to Pacific Northwest Logging Residues ..........................................

................................................... ................................................... .................. M-9
5. Retrospective Reference Point Baseline: Corn Belt C orn Stover ........................................ ............... M-10
5.1. Key Insights from the Retrospective Reference Point Baseline Application to Corn Belt Corn Stover ............................................

................................................... ................................................... .................. M-10
6. Future Anticipated Baseline: Corn Belt Corn Stover

................................................... ............................ M-10
6.1. Key Insights from the Future Anticipate Baseline Ap plication to Corn Belt Corn Stover ............................................

................................................... ................................................... .................. M-12


# List of Tables Table M-1. Biogenic Assessment Factors Derived from a Reference Point Baseline for the Southeast Roundwood Case Study. .............................

................................................... ................................................... M-3 Table M-2. Biogenic Assessment Factors Derived from a Future Anticipated Baseline Approach for the Southeast Roundwood Case Study.................

................................................... ................................... M-5 Table M-3. Biogenic Assessment Factors Derived from a Reference Point Baseline for the Pacific Northwest Logging Residues Case Study. ............

................................................... .................................. M-7 Table M-4. Biogenic Assessment Factors Derived from a Future Anticipated Baseline Approach for the Pacific Northwest Logging Residues Case Study.

................................................... ........................ M-9 Table M-5. Biogenic Assessment Factors Derived from a Reference Point Baseline for the Corn Belt Corn Stover Case Study. ...........................

................................................... .................................................. M-10 Table M-6. Biogenic Assessment Factors Derived from a Future Anticipated Baseline Approach for the Corn Belt Corn Stover Case Study. .............

................................................... .................................... M-11 

# 1. Introduction
This appendix presents the application of the retro spective reference point and future anticipated baseline approaches to estimate illustrative biogen ic assessment factors ( BAF) for specific

## November 2014 M-2

feedstocks in specific regions. Although both basel ine methodologies produce illustrative assessment factors for the same feedstock-region co mbinations, the methods differ in structure, and the assumptions are not harmonized between the two methods.
Three case studies are presented below: Southeast r oundwood, Pacific Northwest logging residues, and Corn Belt corn stover. Both baselines are appli ed within specific case study constructs to generate illustrative values for the framework equa tion terms and assessment factors. Sensitivities to regional scale, feedstock demand, equation term impacts, and time frame were also estimated, and those results are included below.
This appendix uses examples from each baseline appr oach to produce illustrative equation term values for three of the landscape biogenic attribut e terms ( GROW, AVOIDEMIT , and SITETNC

) from the biogenic assessment factor equation as presente d in the main report (Part 2).
 = ()(	
 + 

 +  + 
) (  ) () (EQ. M.1) For simplicity, feedstock carbon losses during stor age, transport, and processing ( L ) are held constant at 1.1, feedstock carbon embodied in produ cts ( P ) is also constant at 1, and leakage associated with feedstock production ( LEAK ) is not calculated in the illustrative term calcul ations here. The BAF is calculated by dividing NBE by PGE : BAF = NBE/PGE (EQ. M.2) For both the retrospective reference point and futu re anticipated baseline approaches, the interpretation of the assessment factor is the same . The assessment factor represents the ratio of net biogenic emissions to potential gross emissions . In other words, the assessment factor reflects the extent to which biogenic CO 2 

## emissions from stationary source consumption are c ounterbalanced by landscape-level biological carbon cycle processes. For example, an assessment factor of 0.2 indicates that 80% of biogenic CO 2 

## emissions are counterbalanced by landscape-level carbon sequestration, a nd 20% contributes to atmospheric CO 2 

## concentrations. Similarly, a negative assessment fa ctor suggests a carbon sink (e.g., from improved carbon management on the landscape). That is, where the assessment factor < 0, additional biogenic feedstock consumption leads to a net incre ase in landscape-level carbon sequestration.


# 2. Retrospective Reference Point Baseline: Southeast Roundwood
In this section, results are generated using a retr ospective reference point baseline in which the net change in various carbon pools on the feedstock pro duction landscape between two points of time in the past to how these pools have changed over th at period. The values for this case study presented in Table M-1 represent the net biogenic C O 2 

## emissions from a hypothetical electricity facility with an electricity generating unit (EGU) that uses roundwood from the Southeast region as a biogenic feedstock. This case study also examines alternative scenarios as sensitivities evaluating the regional aggregation, roundwood removals level, BAF equation term inclusion, land base, and temporal scale.

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Table M-1. Biogenic Assessment Factors Derived from a Reference Point Baseline for the Southeast Roundwood Case Study.

Scenario Time

Scale Growth (billion cu ft) Removals

(billion cu ft) Growth to

Removals Ratio (GROW) (removals– growth)/ removals) Avoided

Emissions (AVOIDEMIT) (avoided long
term sequestration)/ ton removals Net Landscape

Emissions (SITETNC) (other site emissions)/ton removals Potential Gross

Emission (PGE) (million tCO 2 e) Assessment

Factor (BAF) 2

Southeast 2006

–

2010 7.6 0 4. 38

− 0.74 0

− 0.02 4 0.42

− 0.84

South Central 2006

–

2010 9. 58 5. 38

− 0.78 0

− 0.02 0 0.42

− 0.88

Combined SE/SC 2006

–

2010 17. 16 9. 76

− 0.76 0

− 0.02 2 0.42

− 0.86

SE x2 Increased Removals 2006

–

2010 7.6 0 5. 38

− 0.41 0

− 0.02 0 0.42

− 0.48

SE x3 Increased Removals 2006

–

2010 7.6 0 6. 38

− 0.19 0

− 0.0 17 0.42

− 0.23

SE x5 Increased Removals 2006

–

2010 7.6 0 9. 38 0.19 0

− 0.01 0 0.42 0.20

SE x10 Increased Removals 2006

–

2010 7.6 0 14. 38 0.47 0

− 0.0 07 0.42 0.51

Without Net Landscape Emissions 2006

–

2010 7.6 0 4. 38

− 0.74 0 NA 0.42

− 0.81

Change Time Frame 1 1966

–

1976 5.99 3.0 3

− 0.98 0

− 0.02 4 0.42

− 1.10

Change Time Frame 1977

–

1986 5. 59 3. 67

− 0.52 0

− 0.02 4 0.42

− 0.60

Change Time Frame 1987

–

1996 5.96 4. 46

− 0.34 0

− 0.02 4 0.42

− 0.40

Change Time Frame 1997

–

2006 7.3 1 4.3 1

− 0.70 0

− 0.02 4 0.42

− 0.79

1 

### The change in time frame sensitivities could only be conducted on timberlands, rather than all workin g lands (which is the land base used for all other assessment factor calculations above) because the FIA database only h ad information available this far into the past for timberlands.


# 2.1. Key Insights from the Retrospective Reference Point Baseline Application to Southeast Roundwood

• The current estimated assessment factor for Southea st roundwood is less than 0 at −0.84. Except in the increased removals sensitivities wher e timber removals are increased and eventually exceed growth (which is held constant), these assessment factors remain negative, indicating a net increase in landscape-le vel carbon sequestration.

• Aggregating to a larger region (Southeast and South Central) or removing site land use and management biogenic CO 2 

## change from the equation ( SITETNC ) has little impact on the assessment factor in this instance.

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• Although growth and removals have varied over the p ast half-century, the assessment factor would remain negative if calculated over dif ferent historical time periods.


# 3. Future Anticipated Baseline: Southeast Roundwood
The case studies presented in Table M-2 in this sec tion begin with regional biomass consumption trajectories from the AEO Reference case and then r equire an additional 1 million short dry tons of roundwood feedstock consumption in the Southeast. T his additional biomass requirement is phased in linearly, beginning with 250,000 short dr y tons in the 2015 simulation period, reaching 1 million tons in 2030. The feedstock requirement w as phased in over time under the conservative assumption that it could take time for a new facili ty or demand point to build up a steady supply source of one particular feedstock given regional m arket dynamics. The additional biomass requirement is then held constant for the remainder of the simulation horizon 1 

## and must be met by roundwood only.
Instead of calculating the net change in carbon poo ls on the landscape between two points in time, the future anticipated baseline approach calculates the cumulative net change between two alternative scenarios. The first row in Table M-2 l abeled “Incremental Demand vs. AEO Ref” presents the estimated “marginal” BAF as discussed in Appendix L. 2 

## The “AEO Reference case vs. Zero Biomass” results in the tables below compare t he AEO Reference case with a Zero Biomass scenario; thus, the values presented correspond to the “average” effects explained in Appendix L but include an L factor of 1.1. All other scenarios use the “averag e user” approach described in Appendix L, which takes the relative difference bet ween the Incremental Demand and Zero Biomass scenarios. Like the reference point section, this c ase study also examines alternative scenarios as sensitivities evaluating regional aggregation, roun dwood demand level, BAF equation term inclusion, land base, and temporal scale.
There are two primary differences in the presentat ion of biogenic assessment values in this appendix. The first difference is the use of the te rm “relative” to describe the fact that future anticipated baseline biogenic attribute term values are the difference between two alternative cases over a set time period. Relative growth , for example, is the difference between the Zero B iomass case and the alternate case in the sum of all tree carbon growth fluxes (in CO 2 

## ) for the 50-year period between 2010 and 2060. The second is that th e sensitivities related to increased roundwood use are based on incremental demand levels for the feedstock rather than the increased removals evaluated in the reference point sensitivities.

1 

### The 2012 Annual Energy Outlook projections do not extend past 2030 ; thus, biomass consumption shock is held constant after this simulation period.
2 

### Comparison of the 1 million ton increased feedstoc k consumption scenario to the AEO Reference baselin e scenario can be interpreted as the marginal effect of a new source of consumption that is fuel ed by a single feedstock, relative to the AEO Reference anticipated baseline.

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Table M-2. Biogenic Assessment Factors Derived from a Future Anticipated Baseline Approach for the Southeast Roundwood Case Study.

Relative Growth & Removals 3 Relative Carbon Fluxes Relative Annual Total Carbon Flux & Biogenic Emissions

Scenario Time

Scale Relative Growth (million tCO 2 e) Relative

Removals (million tCO 2 e) Relative

Net Growth (GROW) (relative growth– relative removals) (million tCO 2 e/ton biogenic feedstock use) Relative

Avoided Emissions (AVOIDEMIT) (million tCO 2 e/ton biogenic feedstock use) Relative Net

Landscape Emissions (SITETNC) (million tCO 2 e/ton biogenic feedstock use) Relative

Potential Gross Emissions (PGE) (sum of all relative carbon fluxes/50 years) (million tCO 2 e/year) Relative Net

Biogenic Emissions (NBE) (emissions from harvest & use of feedstock per year) (million tCO 2 e /year) Assessment

Factor (BAF) (ratio of net biogenic emissions to potential gross emissions)

Incremental Demand vs. AEO Reference 201 5

–

2060 - 15

- 10

- 0.36 0.00

- 0.04 1.4

- 1

- 0.43

AEO Ref vs. Zero Biomass 201 5

–

2060 − 22 27 0.01 0.00 0.00 12.1 0 0.01

Incremental Demand vs. Zero Biomass 201 5

–

2060 − 37 17

− 0.03 0.00 0.00 13.4 0

− 0.04

South Central 201 5

–

2060 − 75 18

− 0.19 0.00

− 0.05 6.2

- 1

− 0.26

Combined SE/SC 201 5

–

2060 − 112 35

− 0.08 0.00

− 0.02 19.6

- 2

− 0.11

SE x2 Incremental Demand 201 5

–

2060 − 51 94 0.06 0.00 0.03 14.8 1 0.10

SE x3 Incremental Demand 201 5

–

2060 − 51 26

− 0.03 0.00 0.15 16.2 2 0.13

SE x5 Incremental Demand 201 5

–

2060 33 27 0.06 0.00

− 0.02 18.9 1 0.05

SE x10 Incremental Demand 201 5

–

2060 − 15 141 0.10 0.00 0.15 25.8 6 0.27

Without Onsite Emissions Change 201 5

–

2060 − 37 17

− 0.03 0.00 0.00 13.4 0

− 0.03

Change Time Frame 201 5

–

2030 − 7 56 0.22 0.00 0.06 4.5 1 0.31

3 

### Note that CO 2 

### accounting is atmospheric so sequestration is nega tive and emission is positive. While the BAF value as calculated from the equations is technical ly equal to the sum of GROW, AVOIDEMIT, and SITETNC in the absence of losses ( L ), the BAFs shown above may be slightly as it is assumed that L= 1.1 . Furthermore, the values provided in the table are rounded to the nearest in teger or hundredth particularly in the AVOIDEMIT term, which was projected to have a very small magnitude for most c ase studies (0.003 or less).

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# 3.1. Key Insights from the Future Anticipated Baseline A pplication to Southeast Roundwood

• Because the future anticipated baseline compares al ternative scenarios instead of comparing two points in time, many of the variables have different interpretations than they do under the reference point baseline.

o Instead of representing forest growth between two p oints in time, Growth represents the relative difference in cumulative tr ee carbon growth fluxes in CO 2 

## between the two scenarios (in this case, the case s tudy incremental demand scenario and the Zero Biomass utilization case). Po sitive values represent net emissions from the landscape for the case study sce nario relative to the Zero Biomass utilization scenario. Negative values repre sent a net increase in sequestration on the landscape for the case study s cenario.

o Removals

similarly represent the relative difference in cum ulative tree carbon harvest in the two scenarios, with positive values representing an increase in harvest emissions (in CO 2 

## e) for the case study relative to the Zero Biomass utilization case.

o Instead of simply representing the ratio of growth to removals, the anticipated future baseline treats GROW as difference between growth and removals in order to represent relative net growth.

• The “Incremental Demand vs. AEO Ref” case represent s the marginal effect of additional roundwood consumption relative to the AEO reference case. This anticipated additional demand leads to investments in new and replanted tr ee stands early in the simulation horizon, which increases carbon sequestration overa ll and reduces total emissions relative to the AEO Reference Case, resulting in a negative BAF (-0.43).

• The increased demand scenarios represent increases in incremental demand relative to the 1 million tons of incremental demand in the Southea st case study scenario (i.e., because the case study has a 1 million ton increase in demand r elative to the AEO Reference, the “SE x2 Incremental Demand” case reflects a 2 million ton i ncrease). These sensitivities have little impact on the assessment factor, but it should be n oted that they are not directly equivalent to the increased removal scenarios in th e reference point baseline table (which increases total biomass removed from the regional l andscape proportionally to the increase biogenic feedstock demand).

o In the initial time periods, the net emissions flux es related to increased biogenic feedstock demand oscillate between positive and neg ative net emissions (note only cumulative values are included here, so this time p ath effect is not shown). These fluctuations occur as the market and related land u se activities adjust to increased demand levels (e.g., large volumes of new plantings in the initial periods).

## November 2014 M-7 o However, as markets and related land uses adjust to new demand levels over time, equilibrium is reached and the assessment factor tr ends down to hover around or at 0.

o Thus, increasing the demand for Southeast roundwood for bioenergy use in this specific case study, and almost all of the related sensitivities, results in a small or 0 assessment factor. 4



## • In the sensitivity that shortens the analysis time frame from 50 years (2015–2060) to 20 years (2015–2030), the assessment factor for Sou theast roundwood is 0.3, whereas the 50-year case study base case was 0.01. This shows t hat this baseline approach is quite sensitive to the analysis time frame chosen.


# 4. Retrospective Reference Point Baseline: Pacific Nor thwest Logging Residues
The values for this case study presented in Table M -3 represent the reference point-derived net biogenic CO 2 

## emissions from a hypothetical electricity facility with an EGU that uses logging residues from the Pacific Northwest region as a bio genic feedstock. This case study also examines an alternative scenario as sensitivity evaluating t he equation term inclusion.

Table M-3. Biogenic Assessment Factors Derived from a Reference Point Baseline for the Pacific Northwest Logging Residues Case Study.

Scenario Time

Scale Growth

(billion cu. ft.) Removals

(billion cu. ft.) Growth to

Removals Ratio (GROW) (removals– growth)/ removals) Avoided

Emissions (AVOIDEMIT) (avoided long term sequestration)/ ton removals Net

Landscape Emissions (SITETNC) (other site emissions)/to n removals Potential

Gross Emission (PGE) (million tCO 2 e) Assessment

Factor (BAF)

PNW 2006

–

2010 N/A N/A 0

− 0.98 1.0 0.42 0.02

Without Net Landscape Emissions 2006

–

2010 N/A N/A 0

− 0.98 NA 0.42

− 0.98

4 

### Emissions from land management ( SITETNC ) have minimal influence on the assessment factor r esult. Evidence for this can be seen where the value of SITETNC is not included in the calculation; the assessment factor for Southeast Roundwood remains the same.

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# 4.1. Key Insights from the Retrospective Reference Point Baseline Application to Pacific Northwest Logging Residues

• In this case study, it is assumed that logging resi dues have an alternative fate of decay on the forest floor, which would result primarily in e missions to the atmosphere. Because residues are not specifically cultivated but rather removed for bioenergy consumption, the assessment factor in this instance depends on the v alue of avoided emissions.

• Logging residues in this instance receive a slightl y positive assessment factor because when logging residues are left on the landscape, a small portion of carbon is retained in soil carbon. Removal of the logging residues, therefore, has a small negative impact on soil carbon levels.

• Very little data are available on logging residues removal volumes and related impacts on landscape emissions. Thus, emissions fluxes associa ted with land management changes ( SITETNC

) are considered 0 for logging residues under this baseline approach. Therefore, omitting this term in calculating an assessment fac tor has no impact. 

# 5. Future Anticipated Baseline: Pacific Northwest Logg ing Residues
The case study results from Table M-4 in this secti on begin with regional Biomass Consumption trajectories from the AEO Reference case and then r equire an additional 1 million short dry tons of logging residue feedstock consumption in the Pacifi c Northwest. The additional biomass requirement is phased in using the same method desc ribed in the roundwood case study section and likewise must be met by logging residues only.

The first row in Table M-2 labeled “Incremental Dem and vs. AEO Ref” present “marginal” BAF as discussed in Appendix L. The remaining results are cumulative relative to Zero Biomass baseline. The incremental demand scenario includes 1 million tons more logging residues from the Pacific Northwest demanded by 2030 than AEO Reference case.

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Table M-4. Biogenic Assessment Factors Derived from a Future Anticipated Baseline Approach for the Pacific Northwest Logging Residues Case Study.

Scenario Time

Scale Relative Growth &

Removals Relative Carbon Fluxes Relative Total Carbon Flux & Biogenic Emissions

Assessment Factor (BAF) (ratio of net biogenic emissions to potential gross emissions) Relative Growth (million tCO 2 e) Relative

Removals (million tCO 2 e) Relative Net

Growth (GROW) (relative growth– relative removals) (million tCO 2 e/ton biogenic feedstock use) Relative

Avoided Emissions (AVOIDEMIT) (million tCO 2 e/ton biogenic feedstock use) Relative

Net Landscape Emissions (SITETNC) (million tCO 2 e/ton biogenic feedstock use) Relative

Potential Gross Emissions (PGE) (sum of all relative carbon fluxes/50 years) (million tCO 2 e/year) Relative Net

Biogenic Emissions (NBE) (emissions from harvest & use of feedstock per year) (million tCO 2 e /year)

Incremental Demand vs. AEO Ref 2015

-

2060 15

- 1 0.21 0.00 0.09 1.4 0.4 0.33

AEO Ref vs. Zero Biomass 201 5

–

2060 − 13 1

− 0.14 0.00

− 0.02 1.7

- 0.3

− 0.1 8

Incremental Demand vs. Zero Biomass 201 5

–

2060 − 14 16 0.02 0.00 0.03 3.1 0.1 0.04

Without Net Landscape Emissions 201 5

–

2060 − 14 16 0.02 0.00 0.00 3.1 0.0 0.02



# 5.1. Key Insights from the Future Anticipate Baseline Ap plication to Pacific Northwest Logging Residues

• In the “Incremental Demand vs. AEO Ref” case, there is an increase in forest harvests to respond to the additional demand for forest residue s. This increase in harvest leads to a slight increase in net emissions and a resulting BA F of 0.33.

• In the “AEO Ref vs. Zero Biomass” case, a change in silviculture causes a response in Growth (probably for long-term stability of the market) bu t very little change in harvest because residues from existing harvest can be used to meet nearly all of the biogenic demand. This leads to negative values for both “relative net gro wth” and “relative net landscape emissions” terms and thus a negative assessment fac tor.

• In the incremental demand case, another million ton s of biogenic feedstock are used (nearly doubling AEO Reference demand levels), whic h leads to both an increase in harvest and a stronger silvicultural response (although mut ed by the higher harvest). Given the aggregate harvest of approximately 1 billion tons C O 2 

## e over the 2015 through 2060 time While the BAF value as calculated from the equations is technical ly equal to the sum of GROW, AVOIDEMIT, and SITETNC in the absence of losses ( L ), the BAFs shown above may be slightly as it is assumed that L= 1.1 . Furthermore, the values provided in the table are rounded to the nearest in teger or hundredth particularly in the AVOIDEMIT term, which was projected to have a very small magnitude for most c ase studies (0.003 or less).

## November 2014 M-10 period, the harvest increase of 16 million tons is relatively minor. This leads to positive yet small “relative net growth,” “relative net landscap e emissions,” and assessment factors.


# 6. Retrospective Reference Point Baseline: Corn Belt C orn Stover
The values for this case study presented in Table M -5 represent the reference point-derived net biogenic CO 2 

## emissions from a hypothetical electricity facility with an EGU that uses corn stover from the Corn Belt region as a biogenic feedstock. This case study also examines alternative scenarios as sensitivities evaluating N 2 

## O as well as equation term inclusion.
Table M-5. Biogenic Assessment Factors Derived from a Reference Point Baseline for the Corn Belt Corn Stover Case Study.

Scenario Time

Scale Growth (billion cu. ft.) Removals

(billion cu. ft.) Growth to

Removals Ratio (GROW) (removals– growth)/ removals) Avoided

Emissions (AVOIDEMIT)(avoided longterm sequestration)/ ton removals Net

Landscape Emissions (SITETNC) (other site emissions)/to n removals Potential Gross

Emission (PGE) (million tCO 2 e) Assessment

Factor ( BAF ) 1

Base Case 2006

–

2010 N/A N/A 0 0 0.0026 0.4 4 0.00 29

With N 2 O 2006

–

2010 N/A N/A 0 0 0.0123 0.4 4 0.01 35



# 6.1. Key Insights from the Retrospective Reference Point Baseline Application to Corn Belt Corn Stover

• In this case study, corn stover production for ener gy is not considered the motivation for crop production, and the “growth to removals ratio” is assumed to be 0. The assessment factor in this instance depend on the value of “avo ided emissions,” because the assumed alternate fate of these residues is to decompose or be burned onsite (results here are the former). Therefore, “avoided emissions” are equal t o 0.

• When N 2 

## O is included in the “net landscape emissions” calc ulation, the assessment factor is larger than when N 2 

## O is not included (meaning that only 90% of biogeni c CO 2 

## emissions out the stack are counterbalanced by feedstock grow th). This suggests that there are increases in the nitrogen fertilizer application to replenish soil nutrients that were lost by removing corn stover that would have otherwise deco mposed onsite.


# 7. Future Anticipated Baseline: Corn Belt Corn Stover

The first row in Table M-2 labeled “Incremental Dem and vs. AEO Ref” present “marginal” BAF as discussed in Appendix L. Remaining sensitivity resu lts are cumulative relative to Zero Biomass baseline. The incremental demand scenario includes 1 million tons more corn stover from the Corn Belt demanded by 2030 than the AEO Reference case.

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Table M-6. Biogenic Assessment Factors Derived from a Future Anticipated Baseline Approach for the Corn Belt Corn Stover Case Study.

Scenario Time

Scale Relative Growth &

Removals Relative Carbon Fluxes Relative Total Carbon Flux & Biogenic Emissions Assessment Factor (BAF) (ratio of
net biogenic emissions to potential gross emissions) Relative Growth (million tCO 2 e) Relative

Removals (million tCO 2 e) Relative

Net Growth (GROW) (relative growth– relative removals) (million tCO 2 e/ton biogenic feedstock use) Relative

Avoided Emissions (AVOIDEMIT) (million tCO 2 e/ton biogenic feedstock use) Relative

Net Landscape Emissions (SITETNC) (million tCO 2 e/ton biogenic feedstock use) Relative

Potential Gross Emissions (PGE) (sum of all relative carbon fluxes/50 years) (million tCO 2 e/year) Relative Net

Biogenic Emissions (NBE) (emissions from harvest & use of feedstock per year) (million tCO 2 e/year)

Incremental Demand vs. AEO Ref 2015

-

2060 NA NA 0 0 0.08 1.4 0.0\ 0,08

AEO Ref vs. Zero Biomass 201 5

–

2060 NA NA 0 0 0.27 0.8 0.2 0. 27

Incremental Demand vs. Zero Biomass 201 5

–

2060 NA NA 0 0 0.15 2.2 0.3 0.1 7

With N 2 O 201 5

–

2060 NA NA 0 0 0.15 2.2 0.3 0.17

Without Net Landscape Emissions 201 5

–

2060 NA NA 0 0 0.00 2.2 0.0 0.00



### While the BAF value as calculated from the equations is technical ly equal to the sum of GROW, AVOIDEMIT, and SITETNC in the absence of losses ( L ), the BAFs shown above may be slightly as it is assumed that L= 1.1 . Furthermore, the values provided in the table are rounded to the nearest in teger or hundredth particularly in the AVOIDEMIT term, which was projected to have a very small magnitude for most c ase studies (0.003 or less).

## November 2014 M-12



# 7.1. Key Insights from the Future Anticipate Baseline Ap plication to Corn Belt Corn Stover
In the “AEO Ref vs. Zero Biomass” scenario (with 1 million ton demand increase over the AEO Reference level), the cumulative assessment factor for corn stover is 0.17. This means that approximately 83% of additional biogenic feedstock consumption is replaced by carbon sequestration on the landscape.

• As “relative net growth” defaults to 0 for corn sto ver, the relatively large assessment factor is driven by “relative net landscape emissions.” Th is flux represents changes in agricultural and forestry land management in response to the lon g-term increase in the demand for corn stover biomass.

• The estimated BAF

under the “Incremental Demand vs. AEO Ref” case is smaller than the “Incremental Demand vs. Zero Biomass” case. This im plies that the marginal landscape emissions effect of increasing corn stover removals in isolation could be smaller than a total shift in biomass consumption in the Corn Belt (with multiple feedstocks used to meet the additional demand).

• Note that when the N 2 

## O flux is included, calculated “relative net landsc ape emissions” values increase slightly because of the additional corn stover demand, which increases corn production and nitrogen fertilizer use, thus increa sing N 2 

## O emissions relative to the Zero Biomass baseline.

• When “relative net landscape emissions” is not incl uded in the assessment factor, the resulting assessment factor is effectively 0, becau se the primary terms, “relative net growth” and “relative net landscape emissions,” are eliminated.