November 2014 M-1 

Appendix M: Summary of Illustrative Forestry and 

Agriculture Results 

Table of Contents 

1. Retrospective Reference Point Baseline: Southeast Roundwood ......................................................... 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 Baseline Application to Southeast Roundwood .. M-6

3. Retrospective Reference Point Baseline: Pacific Northwest 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 Logging Residues ..................................................... M-8

4.1. Key Insights from the Future Anticipate Baseline Application to Pacific Northwest Logging 

Residues .................................................................................................................................................................. M-9

5. Retrospective Reference Point Baseline: Corn Belt Corn 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 Application 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 retrospective reference point and future anticipated 

baseline approaches to estimate illustrative biogenic assessment factors (BAF) for specific 
November 2014 M-2 

feedstocks in specific regions. Although both baseline methodologies produce illustrative 

assessment factors for the same feedstock-region combinations, the methods differ in structure, 

and the assumptions are not harmonized between the two methods. 

Three case studies are presented below: Southeast roundwood, Pacific Northwest logging residues, 

and Corn Belt corn stover. Both baselines are applied within specific case study constructs to 

generate illustrative values for the framework equation 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 approach to produce illustrative equation term 

values for three of the landscape biogenic attribute terms (GROW, AVOIDEMIT, and SITETNC) from 

the biogenic assessment factor equation as presented in the main report (Part 2).

 = ()(	
 + 

 +  + 
)()() (EQ. M.1)

For simplicity, feedstock carbon losses during storage, transport, and processing (L) are held 

constant at 1.1, feedstock carbon embodied in products (P) is also constant at 1, and leakage 

associated with feedstock production (LEAK) is not calculated in the illustrative term calculations 

here. The BAF is calculated by dividing NBE by PGE: 

BAF = NBE/PGE (EQ. M.2)

For both the retrospective reference point and future 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 CO2 emissions from stationary source consumption are counterbalanced by landscape-level biological carbon cycle processes. 

For example, an assessment factor of 0.2 indicates that 80% of biogenic CO2 emissions are counterbalanced by landscape-level carbon sequestration, and 20% contributes to atmospheric CO2

concentrations. Similarly, a negative assessment factor 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 increase in landscape-level carbon sequestration. 

2. Retrospective Reference Point Baseline: Southeast 

Roundwood 

In this section, results are generated using a retrospective reference point baseline in which the net

change in various carbon pools on the feedstock production landscape between two points of time 

in the past to how these pools have changed over that period. The values for this case study 

presented in Table M-1 represent the net biogenic CO2 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. 
November 2014 M-3 

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 tCO2e)

Assessment 

Factor 

(BAF)2

Southeast 2006–

2010 

7.60 4.38 −0.74 0 −0.024 0.42 −0.84

South Central 2006–

2010 

9.58 5.38 −0.78 0 −0.020 0.42 −0.88

Combined SE/SC 2006–

2010 

17.16 9.76 −0.76 0 −0.022 0.42 −0.86

SE x2 

Increased 

Removals 

2006–

2010 

7.60 5.38 −0.41 0 −0.020 0.42 −0.48

SE x3 

Increased 

Removals 

2006–

2010 

7.60 6.38 −0.19 0 −0.017 0.42 −0.23

SE x5 

Increased 

Removals 

2006–

2010 

7.60 9.38 0.19 0 −0.010 0.42 0.20

SE x10 

Increased 

Removals 

2006–

2010 

7.60 14.38 0.47 0 −0.007 0.42 0.51

Without Net 

Landscape 

Emissions 

2006–

2010 

7.60 4.38 −0.74 0 NA 0.42 −0.81

Change Time

Frame1

1966–

1976 

5.99 3.03 −0.98 0 −0.024 0.42 −1.10

Change Time

Frame 

1977–

1986 

5.59 3.67 −0.52 0 −0.024 0.42 −0.60

Change Time

Frame 

1987–

1996 

5.96 4.46 −0.34 0 −0.024 0.42 −0.40

Change Time

Frame 

1997–

2006 

7.31 4.31 −0.70 0 −0.024 0.42 −0.79

1 The change in time frame sensitivities could only be conducted on timberlands, rather than all working lands (which is 

the land base used for all other assessment factor calculations above) because the FIA database only had 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 Southeast roundwood is less than 0 at −0.84. 

Except in the increased removals sensitivities where timber removals are increased and 

eventually exceed growth (which is held constant), these assessment factors remain 

negative, indicating a net increase in landscape-level carbon sequestration. 

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

management biogenic CO2 change from the equation (SITETNC) has little impact on the 

assessment factor in this instance. 
November 2014 M-4 

• Although growth and removals have varied over the past half-century, the assessment 

factor would remain negative if calculated over different historical time periods.

3. Future Anticipated Baseline: Southeast Roundwood 

The case studies presented in Table M-2 in this section begin with regional biomass consumption 

trajectories from the AEO Reference case and then require an additional 1 million short dry tons of 

roundwood feedstock consumption in the Southeast. This additional biomass requirement is 

phased in linearly, beginning with 250,000 short dry tons in the 2015 simulation period, reaching 

1 million tons in 2030. The feedstock requirement was phased in over time under the conservative 

assumption that it could take time for a new facility or demand point to build up a steady supply 

source of one particular feedstock given regional market dynamics. The additional biomass 

requirement is then held constant for the remainder of the simulation horizon1 and must be met by 

roundwood only. 

Instead of calculating the net change in carbon pools 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 labeled “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 the 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 “average user” approach described in 

Appendix L, which takes the relative difference between the Incremental Demand and Zero Biomass 

scenarios. Like the reference point section, this case study also examines alternative scenarios as 

sensitivities evaluating regional aggregation, roundwood demand level, BAF equation term 

inclusion, land base, and temporal scale. 

 There are two primary differences in the presentation of biogenic assessment values in this 

appendix. The first difference is the use of the term “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 Biomass 

case and the alternate case in the sum of all tree carbon growth fluxes (in CO2) for the 50-year 

period between 2010 and 2060. The second is that the 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 feedstock consumption scenario to the AEO Reference baseline scenario 

can be interpreted as the marginal effect of a new source of consumption that is fueled by a single feedstock, relative 

to the AEO Reference anticipated baseline. 
November 2014 M-5 

Table M-2. Biogenic Assessment Factors Derived from a Future Anticipated Baseline Approach for 

the Southeast Roundwood Case Study. 

Relative Growth & 

Removals3

Relative Carbon Fluxes

Relative Annual Total 

Carbon Flux & Biogenic 

Emissions 

Scenario Time 

Scale 

Relative 

Growth 

(million 

tCO2e) 

Relative 

Removals

(million 

tCO2e) 

Relative

Net 

Growth 

(GROW) 

(relative 

growth– 

relative 

removals) 

(million 

tCO2e/ton 

biogenic 

feedstock 

use) 

Relative 

Avoided 

Emissions 

(AVOIDEMIT)

(million 

tCO2e/ton 

biogenic 

feedstock 

use) 

Relative Net 

Landscape 

Emissions

(SITETNC) 

(million 

tCO2e/ton 

biogenic 

feedstock 

use) 

Relative 

Potential 

Gross 

Emissions 

(PGE) (sum 

of all 

relative 

carbon 

fluxes/50 

years) 

(million 

tCO2e/year)

Relative Net 

Biogenic 

Emissions 

(NBE) 

(emissions 

from harvest 

& use of 

feedstock 

per year) 

(million 

tCO2e /year)

Assessment 

Factor 

(BAF) (ratio 

of net 

biogenic 

emissions 

to potential 

gross 

emissions) 

Incremental 

Demand vs. 

AEO Reference 

2015–

2060 

-15 -10 -0.36 0.00 -0.04 1.4 -1 -0.43

AEO Ref vs. 

Zero Biomass 

2015–

2060 

−22 27 0.01 0.00 0.00 12.1 0 0.01

Incremental 

Demand vs. 

Zero Biomass 

2015–

2060 

−37 17 −0.03 0.00 0.00 13.4 0 −0.04

South Central 2015–

2060 

−75 18 −0.19 0.00 −0.05 6.2 -1 −0.26

Combined 

SE/SC 

2015–

2060 

−112 35 −0.08 0.00 −0.02 19.6 -2 −0.11

SE x2 

Incremental 

Demand 

2015–

2060 

−51 94 0.06 0.00 0.03 14.8 1 0.10

SE x3 

Incremental 

Demand 

2015–

2060 

−51 26 −0.03 0.00 0.15 16.2 2 0.13

SE x5 

Incremental 

Demand 

2015–

2060 

33 27 0.06 0.00 −0.02 18.9 1 0.05

SE x10 

Incremental 

Demand 

2015–

2060 

−15 141 0.10 0.00 0.15 25.8 6 0.27

Without Onsite 

Emissions 

Change 

2015–

2060 

−37 17 −0.03 0.00 0.00 13.4 0 −0.03

Change Time

Frame 

2015–

2030 

−7 56 0.22 0.00 0.06 4.5 1 0.31

 

3

 Note that CO2 accounting is atmospheric so sequestration is negative and emission is positive. 

 While the BAF value as calculated from the equations is technically 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 integer or hundredth particularly in the AVOIDEMIT term, which was 

projected to have a very small magnitude for most case studies (0.003 or less).
November 2014 M-6 

3.1. Key Insights from the Future Anticipated Baseline Application to 

Southeast Roundwood 

• Because the future anticipated baseline compares alternative 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 points in time, Growth

represents the relative difference in cumulative tree carbon growth fluxes in CO2

between the two scenarios (in this case, the case study incremental demand 

scenario and the Zero Biomass utilization case). Positive values represent net 

emissions from the landscape for the case study scenario relative to the Zero 

Biomass utilization scenario. Negative values represent a net increase in 

sequestration on the landscape for the case study scenario. 

o Removals similarly represent the relative difference in cumulative tree carbon 

harvest in the two scenarios, with positive values representing an increase in 

harvest emissions (in CO2e) 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 represents the marginal effect of additional 

roundwood consumption relative to the AEO reference case. This anticipated additional 

demand leads to investments in new and replanted tree stands early in the simulation 

horizon, which increases carbon sequestration overall 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 Southeast case study scenario (i.e., because the 

case study has a 1 million ton increase in demand relative to the AEO Reference, the “SE x2 

Incremental Demand” case reflects a 2 million ton increase). These sensitivities have little 

impact on the assessment factor, but it should be noted that they are not directly 

equivalent to the increased removal scenarios in the reference point baseline table (which 

increases total biomass removed from the regional landscape proportionally to the 

increase biogenic feedstock demand). 

o In the initial time periods, the net emissions fluxes related to increased biogenic 

feedstock demand oscillate between positive and negative net emissions (note only 

cumulative values are included here, so this time path effect is not shown). These 

fluctuations occur as the market and related land use 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 trends 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 Southeast roundwood is 0.3, whereas the 

50-year case study base case was 0.01. This shows that this baseline approach is quite 

sensitive to the analysis time frame chosen. 

4. Retrospective Reference Point Baseline: Pacific Northwest 

Logging Residues 

The values for this case study presented in Table M-3 represent the reference point-derived net 

biogenic CO2 emissions from a hypothetical electricity facility with an EGU that uses logging 

residues from the Pacific Northwest region as a biogenic feedstock. This case study also examines 

an alternative scenario as sensitivity evaluating the 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 

tCO2e) 

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 result. 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. 
November 2014 M-8 

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 residues have an alternative fate of decay on 

the forest floor, which would result primarily in emissions to the atmosphere. Because 

residues are not specifically cultivated but rather removed for bioenergy consumption, the 

assessment factor in this instance depends on the value of avoided emissions.

• Logging residues in this instance receive a slightly 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 associated with land management changes 

(SITETNC) are considered 0 for logging residues under this baseline approach. Therefore, 

omitting this term in calculating an assessment factor has no impact.

5. Future Anticipated Baseline: Pacific Northwest Logging 

Residues 

The case study results from Table M-4 in this section begin with regional Biomass Consumption 

trajectories from the AEO Reference case and then require an additional 1 million short dry tons of 

logging residue feedstock consumption in the Pacific Northwest. The additional biomass 

requirement is phased in using the same method described in the roundwood case study section 

and likewise must be met by logging residues only. 

The first row in Table M-2 labeled “Incremental Demand 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. 
November 2014 M-9 

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 

tCO2e) 

Relative 

Removals

(million 

tCO2e) 

Relative Net 

Growth 

(GROW) 

(relative 

growth– 

relative 

removals) 

(million 

tCO2e/ton 

biogenic 

feedstock 

use) 

Relative 

Avoided 

Emissions 

(AVOIDEMIT)

(million 

tCO2e/ton 

biogenic 

feedstock 

use) 

Relative 

Net 

Landscape 

Emissions

(SITETNC) 

(million 

tCO2e/ton 

biogenic 

feedstock 

use) 

Relative 

Potential 

Gross 

Emissions 

(PGE) 

(sum of all 

relative 

carbon 

fluxes/50 

years) 

(million 

tCO2e/year)

Relative Net 

Biogenic 

Emissions 

(NBE) 

(emissions 

from harvest 

& use of 

feedstock 

per year) 

(million 

tCO2e /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 

2015–

2060 

−13 1 −0.14 0.00 −0.02 1.7 -0.3 −0.18

Incremental 

Demand vs. 

Zero 

Biomass 

2015–

2060 

−14 16 0.02 0.00 0.03 3.1 0.1 0.04

Without Net 

Landscape 

Emissions 

2015–

2060 

−14 16 0.02 0.00 0.00 3.1 0.0 0.02

5.1. Key Insights from the Future Anticipate Baseline Application 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 residues. This increase in harvest leads to a 

slight increase in net emissions and a resulting BAF 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) but 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 growth” and “relative net landscape 

emissions” terms and thus a negative assessment factor. 

• In the incremental demand case, another million tons of biogenic feedstock are used 

(nearly doubling AEO Reference demand levels), which leads to both an increase in harvest 

and a stronger silvicultural response (although muted by the higher harvest). Given the 

aggregate harvest of approximately 1 billion tons CO2e over the 2015 through 2060 time 

 While the BAF value as calculated from the equations is technically 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 integer or hundredth particularly in the AVOIDEMIT term, which was 

projected to have a very small magnitude for most case 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 landscape emissions,” and assessment factors. 

6. Retrospective Reference Point Baseline: Corn Belt Corn 

Stover 

The values for this case study presented in Table M-5 represent the reference point-derived net 

biogenic CO2 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 N2O 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 tCO2e) 

Assessment 

Factor 

(BAF)

1 

Base Case 2006–

2010 

N/A N/A 0 0 0.0026 0.44 0.0029

With N2O 2006–

2010 

N/A N/A 0 0 0.0123 0.44 0.0135

6.1. Key Insights from the Retrospective Reference Point Baseline 

Application to Corn Belt Corn Stover 

• In this case study, corn stover production for energy 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 “avoided 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 to 0. 

• When N2O is included in the “net landscape emissions” calculation, the assessment factor is 

larger than when N2O is not included (meaning that only 90% of biogenic CO2 emissions 

out the stack are counterbalanced by feedstock growth). 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 decomposed onsite.

7. Future Anticipated Baseline: Corn Belt Corn Stover 

The first row in Table M-2 labeled “Incremental Demand vs. AEO Ref” present “marginal” BAF as 

discussed in Appendix L. Remaining sensitivity results 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. 
November 2014 M-11 

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 

tCO2e) 

Relative 

Removals

(million 

tCO2e) 

Relative 

Net Growth

(GROW) 

(relative 

growth– 

relative 

removals) 

(million 

tCO2e/ton 

biogenic 

feedstock 

use) 

Relative 

Avoided 

Emissions 

(AVOIDEMIT)

(million 

tCO2e/ton 

biogenic 

feedstock 

use) 

Relative 

Net 

Landscape 

Emissions

(SITETNC)

(million 

tCO2e/ton 

biogenic 

feedstock 

use) 

Relative 

Potential 

Gross 

Emissions 

(PGE) 

(sum of all 

relative 

carbon 

fluxes/50 

years) 

(million 

tCO2e/year)

Relative Net 

Biogenic 

Emissions 

(NBE) 

(emissions 

from harvest 

& use of 

feedstock 

per year) 

(million 

tCO2e/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 

2015–

2060 

NA NA 0 0 0.27 0.8 0.2 0.27

Incremental 

Demand vs. 

Zero Biomass 

2015–

2060 

NA NA 0 0 0.15 2.2 0.3 0.17

With N2O 2015–

2060 

NA NA 0 0 0.15 2.2 0.3 0.17

Without Net 

Landscape 

Emissions 

2015–

2060 

NA NA 0 0 0.00 2.2 0.0 0.00

While the BAF value as calculated from the equations is technically 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 integer or hundredth particularly in the AVOIDEMIT term, which was 

projected to have a very small magnitude for most case studies (0.003 or less).
November 2014 M-12 

7.1. Key Insights from the Future Anticipate Baseline Application 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 stover, the relatively large assessment factor 

is driven by “relative net landscape emissions.” This flux represents changes in agricultural 

and forestry land management in response to the long-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 implies 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 N2O flux is included, calculated “relative net landscape emissions” 

values increase slightly because of the additional corn stover demand, which increases corn 

production and nitrogen fertilizer use, thus increasing N2O emissions relative to the Zero 

Biomass baseline. 

• When “relative net landscape emissions” is not included in the assessment factor, the 

resulting assessment factor is effectively 0, because the primary terms, “relative net 

growth” and “relative net landscape emissions,” are eliminated.