November 2014 I-1 

Appendix I: Illustrative Forestry and Agriculture Case 

Studies Using a Retrospective Reference Point Baseline 

Table of Contents 

1. Introduction .................................................................................................................................................................. I-2

2. Roundwood in the Southeast ................................................................................................................................. I-2

Base Case .............................................................................................................................................................. I-2

Regional Aggregation ...................................................................................................................................... I-3

Increased Removals ......................................................................................................................................... I-4

Equation Term Analysis ................................................................................................................................. I-7

Working Forest .................................................................................................................................................. I-8

Temporal Scale ................................................................................................................................................. I-10

3. Logging Residues in the Pacific Northwest .................................................................................................... I-12

Base Case ............................................................................................................................................................ I-13

4. Corn Stover in the Corn Belt ................................................................................................................................. I-14

Base Case ............................................................................................................................................................ I-14

NBE Results with N2O Emissions .............................................................................................................. I-15

5. References .................................................................................................................................................................... I-16

List of Tables 

Table I-1. Biogenic Landscape Attributes: Roundwood in the Southeast. .................................................... I-3

Table I-2. Process Attributes: Roundwood in the Southeast. ............................................................................. I-3

Table I-3. Biogenic Attributes for the Southeast and South Central Regions. ............................................. I-4

Table I-4. Increased Removals by Multiples of 1 Billion Cubic Feet. ............................................................... I-5

Table I-5. Biogenic Attributes for Term Analysis. ................................................................................................... I-7

Table I-6. Land Base Categorization for the Working Forest Definition Case Study. ............................... I-9

Table I-7. Biogenic Attributes for the Working Forest Definition Case Study Sensitivity. ..................... I-9

Table I-8. Biogenic Attributes over Forest Inventory Time Frames for the Temporal Scale Case 

Study. ....................................................................................................................................................................... I-10

Table I-9. Biogenic Landscape Attributes: Logging Residues in the Pacific Northwest. ....................... I-13

Table I-10. Process Attributes: Logging Residues in the Pacific Northwest. ............................................. I-13

Table I-11. Biogenic Landscape Attributes: Corn Stover in the Corn Belt. ................................................. I-14

Table I-12. Process Attributes: Corn Stover in the Corn Belt ........................................................................... I-15

Table I-13. Biogenic Landscape Attributes: Corn Stover in the Corn Belt with N2O Emissions......... I-15
November 2014 I-2 

1. Introduction 

This appendix presents three illustrative case studies to demonstrate how values for biogenic 

landscape and process attributes could be combined to calculate the net biogenic emissions (NBE) 

and biogenic assessment factor (BAF) using a retrospective reference point baseline. Nested within 

each case study section are various sensitivity analyses. These analyses highlight the influence of 

alternative scenarios on the base case. The three illustrative case studies and associated sensitivity

analyses focus on: 

• Roundwood in the Southeast; 

• Logging residues in the Pacific Northwest; and 

• Corn stover in the Corn Belt. 

These case studies use the biogenic assessment equation from the main report: 

  	
  

   (EQ. I.1)

This appendix uses the illustrative biogenic landscape attributes (GROW, AVOIDEMIT, and SITETNC) 

as calculated using the retrospective reference point baseline approach in Appendix H. 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 (both of these biogenic 

process attributes are discussed in Appendix G). Assessment of potential leakage effects associated 

with feedstock production (LEAK) is not included in this case study application. 

2. Roundwood in the Southeast 

This case study calculates 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: 

• A regional aggregation of roundwood in both the Southeast (SE) and South Central (SC) 

regions; 

• Increased roundwood removals, as reflected in increased removals in multiples of one 

billion cubic feet of removals (by 1, 2, 5, and 10); 

• Equation term analysis (i.e., investigation of the impact of removing terms on the 

assessment factor calculation); 

• Varied land bases in the Southeast (i.e., all forestland, all timberlands, private timberlands, 

all working timberlands, private working timberlands); and 

• A temporal scale analysis for all timberland. 

Base Case 

For all of the case study scenarios, it was assumed that the electricity facility has an output of 30 

MW, a capacity factor of 95%, and efficiency of 26% (consumes 1 bone dry ton [BDT] of roundwood 

per MWh of electricity produced), thus requiring an input of 250,000 BDT of roundwood per year. If 
November 2014 I-3 

we assume that 50% of the 250,000 BDT of feedstock is carbon and convert the short tons to tonnes 

and carbon to CO2, we end up with a PGE of 0.42 mmtCO2 for the hypothetical 30 MW plant. 

Table I-1. Biogenic Landscape Attributes: Roundwood in the Southeast. 

Feedstock/Region Growth (G) 

(cu ft/yr) 

Removals (R)

(cu ft/yr) GROW AVOIDEMIT SITETNC

Roundwood/Southeast 7.6 4.4 −0.74 0 −0.02 

Table I-2. Process Attributes: Roundwood in the Southeast. 

Feedstock/Process P L 

Roundwood/EGU 1 1.1 

This case study then uses the main biogenic assessment factor equation from the main report: 

  	
  

   (EQ. I.2) 

Inserting the illustrative values for the relevant equation terms, this equation is now: 

  . 	
.     .  .   

And the result is: 

  . !"	


For this case study application: 

  . 	
 

Therefore: 

BAF = NBE/PGE 

BAF = . !"	
/0. 	


BAF = . #

GROW is less than 0 because the Southeast is currently experiencing greater forest growth 

compared with removals. Because AVOIDEMIT is 0 in this application, and SITETNC has a small 

value, GROW is the driving factor and causes the BAF to be negative. 

Regional Aggregation 

To evaluate the sensitivity of estimates to the geographic domain, the GROW terms for the SE region 

and the SC region were computed separately and as an aggregated southern region to demonstrate 

the impact of using larger spatial scales to develop the BAF estimates. Table I-3 contains the growth 

and removals values (from the 2010 FIA survey period, which includes data collected between 

2006 and 2010) for private timberlands for the SE and SC regions and then for the South as a whole. 

The process attributes—P and L—remain the same as for the base case. 
November 2014 I-4 

Table I-3. Biogenic Attributes for the Southeast and South Central Regions. 

Feedstock/Region 

Growth (G) 

(billion 

cu ft/yr) 

Removals (R) 

(billion 

cu ft/yr) 

GROW AVOIDEMIT SITETNC

Roundwood/Southeast 7.60 4.38 −0.74 0 −0.024 

Roundwood/South Central 9.58 5.38 −0.78 0 −0.020 

Roundwood/Combined 

Southeast and South Central

17.16 9.76 −0.76 0 −0.022 

Inserting the illustrative values for the relevant equation terms into the main biogenic assessment 

factor equation from the main report, this equation is now: 

  . 	
. $    	.  .   (EQ. I.3) 

And the result is: 

  . !$	


For this case study application: 

  . 	
 

Therefore: 

BAF = NBE/PGE 

BAF = . !$	
/0. 	


BAF = 0.86

Combining the Southeast and South Central regions results in a very slight change to the GROW

term for the Southeast region, though overall growth still exceeds removals in the combined region. 

Increased Removals 

Increased removal scenarios were analyzed for roundwood in the SE region to demonstrate the 

potential impact of changing future roundwood harvests as a biogenic feedstock on the assessment 

factor under the reference point baseline. This analysis changes the removals term in isolation and 

thus does not mimic growth responses associated with land use change to meet increased demand 

or enhanced growth due to changes in management to accommodate increased removals. This 

variation represents the base case removals increased by different multiples of 1 billion cubic feet 

(Table I-4). In each case, GROW and SITETNC are calculated using the methods described in 

Appendix H, so the “REMOVALS” volume in the denominator of Equations H.2 and H.4 increases 

with each increased removal case. For SITETNC, the numerator of Equation H.4 stays constant, so 

the estimated ratio decreases with the level of removals. For GROW, the “REMOVALS – GROWTH” 

difference in Equation H.2 changes with greater removals, ultimately causing the sign of the GROW

term to switch from negative to positive. 
November 2014 I-5 

Table I-4. Increased Removals by Multiples of 1 Billion Cubic Feet. 

Region 

Growth (G)

(billion 

cu ft/yr) 

Incremental 

Removal 

Increases 

(cu ft) 

Removals (R)

(billion 

cu ft/yr) 

GROW AVOIDEMIT SITETNC BAF

Southeast 7.60 Base 4.38 −0.74 0 −0.024 −0.84 

Southeast 7.60 1 billion 5.38 −0.41 0 −0.020 −0.48 

Southeast 7.60 2 billion 6.38 −0.19 0 −0.017 −0.23 

Southeast 7.60 5 billion 9.38 0.19 0 −0.010 0.20 

Southeast 7.60 10 billion 14.38 0.47 0 −0.007 0.51 

The calculations below step through the equation to generate the BAF values in Table I-4. In the 

increased removal scenarios presented below, as the GROW term increases and everything else 

stays the same, the BAF increases. 

Scenario 1: Incremental Removals by 1 Billion 

One billion cubic feet increase: Inserting the values for L, P, and SITETNC into the equation results 

in: 

  . 	
−.  +  − .  .   (EQ. I.4) 

And the result is: 

  . 	


For this case study application: 

  . 	
 

Therefore: 

BAF = NBE/PGE 

BAF = . 	
/0. 	


BAF = −.48

Scenario 2: Incremental Removals by 2 Billion 

Two billion cubic feet increase: Inserting the values for L, P, and SITETNC into the equation results 

in: 

  . 	
−. % +  − .  .   (EQ. I.5) 

And the result is: 

  . 	


For this case study application: 

  . 	
 
November 2014 I-6 

Therefore: 

BAF = NBE/PGE 

BAF = . 	
/0. 	


BAF = −0.23

Scenario 4: Incremental Removals by 5 Billion 

Five billion cubic feet increase: Inserting the values for L, P, and SITETNC into the equation results 

in: 

  . 	
. % +  − .   .   (EQ. I.6) 

And the result is: 

  . #	


For this case study application: 

  . 	
 

Therefore: 

BAF = NBE/PGE 

BAF = . #	
/0. 	


BAF = 0.20

Scenario 5: Incremental Removals by 10 Billion 

Ten billion cubic feet increase: Inserting the values for L, P, and SITETNC into the equation results 

in: 

  . 	
.  + 	 − 	.   .   (EQ. I.7)

And the result is: 

  .  	


For this application: 

  . 	
 

Therefore: 

BAF = NBE/PGE 

BAF = .  	
/0. 	


BAF = 0.51

As shown in Table I-4 above, increased removals generate changes to the GROW term because 

removals increase while growth does not. Removals begin to exceed growth—and result in a net 

atmospheric contribution of biogenic CO2 emissions from our hypothetical EGU using roundwood—
November 2014 I-7 

when current removals are increased by more than 3.3 billion cubic feet. However, it should be 

noted that current removals are already at a high level (4.8 billion cu ft/yr) relative to net growth 

compared with other regions nationwide. 

Equation Term Analysis 

For the equation term analysis, the assessment factor was calculated using base levels of the 

biogenic landscape attributes (Table I-5) with and without certain equation variables (e.g., GROW

and SITETNC). As for the base case above, for roundwood, L = 1.1 and P = 1, while AVOIDEMIT is 

equal to 0. By calculating the assessment factor with and without certain variables in the equation, 

this analysis illustrates the relative importance of those terms. 

Table I-5. Biogenic Attributes for Term Analysis. 

Feedstock/Region Growth (G) 

(billion cu ft/yr)

Removals (R)

(cu ft/yr) GROW AVOIDEMIT SITETNC

Roundwood/Southeast 7.60 4.38 −0.74 0 −0.024 

Scenario 1: Without the GROW Term 

In this equation term analysis, GROW is excluded from the equation to evaluate its impact on the 

assessment factor. 

  

   (EQ. I.8) 

Inserting the illustrative values for relevant equation terms into this equation results in: 

  . 	
  .  .  

And the result is: 

  .  	


For this application: 

  . 	
 

Therefore: 

BAF = NBE/PGE 

BAF = .  	
/0. 	


BAF = 0.03

Excluding the GROW term results in an increase in the negative assessment factor compared with 

the base case because only the changes in non-tree pools represented in the SITETNC term are 

represented in the BAF. The resulting assessment factor remains negative, however, because the 

SITETNC term pools have been increasing through the reference period. 
November 2014 I-8 

Scenario 2: Without the SITETNC Term 

In this equation term analysis, SITETNC is excluded from the equation to evaluate its impact on the 

assessment factor. 

  	
  

 (EQ. I.9) 

Inserting the illustrative values for relevant equation terms into this equation results in: 

  . 	
.    .  

And the result is: 

  . !	


For this application: 

  . 	
 

Therefore: 

BAF = NBE/PGE 

BAF = . !	
/0. 	


BAF = 0.81

Excluding the SITETNC term also results in an increase in the assessment factor compared with the 

base case because only the changes in tree biomass pools that are represented in the GROW term 

are represented in the BAF. The resulting assessment factor remains negative because the GROW

term pools have been increasing through the reference period. 

Working Forest 

Forest inventory estimates (such as growth and removals) can be expressed for different land areas 

or definitions of forest. In general, FIA distinguishes between forestland (all land covered with 

forest as defined by FIA) and timberland (forest meeting certain minimum productivity thresholds 

and not reserved from timber harvest by law). Forest owned by public entities can be further 

differentiated from forest owned by private entities (because, for example, private timberland 

accounts for 98.8% of all removals or harvests within the Southeast). The land under consideration 

can be further restricted to the “working forest,” which can be defined as accessible lands not 

constrained by steep slopes or wet soils or other criteria that would serve to limit the ability of 

these lands to produce commercial wood fiber. 

For the purposes of this working forest analysis, GROW estimates are developed for six categories 

of land for the Southeast United States: 

1. All forest lands (all lands meeting the FIA definition of forest); 

2. All timberlands (forest land above productivity thresholds not reserved from harvest); 

3. Private forest lands (#1 above for private ownerships); 

4. Private timberlands (#2 above for private ownerships); 
November 2014 I-9 

5. Working timberlands (#2 above, further screened to eliminate steep slopes, wet soils, etc.); 

and 

6. Private working timberlands (#4 above, further screened to eliminate steep slopes, wet 

soils, etc.). 

These categories are summarized in Table I-6. 

Table I-6. Land Base Categorization for the Working Forest Definition Case Study. 

Land Base Public 

Lands 

Private 

Lands 

Reserved 

Land 

Low Productivity 

Land 

Steep Slopes, 

Hydric Soils, 

etc. 

All Forest Lands Yes Yes Yes Yes Yes 

All Timberlands Yes Yes No No Yes 

Private Forest Lands No Yes Yes Yes Yes 

Private Timberlands No Yes No No Yes 

All Working 

Timberlands 

Yes Yes No No No 

Private Working 

Timberlands 

No Yes No No No 

Applying these different land definitions to the southeastern U.S. FIA data from the 2010 survey 

period, we obtained different values for growth/removals ratios as depicted in Table I-7. 

Table I-7. Biogenic Attributes for the Working Forest Definition Case Study Sensitivity. 

Roundwood/Southeast 

Growth (G) 

(billion 

cu ft/yr) 

Removals (R)

(billion 

cu ft/yr) 

GROW AVOIDEMIT SITETNC BAF

All Forest Lands 8.24 4.43 −0.86 0 −0.022 −0.97 

All Timberlands 8.14 4.45 −0.83 0 −0.024 −0.94 

Private Forest Lands 7.6 4.4 −0.75 0 −0.022 −0.85 

Private Timberlands 7.6 4.4 −0.74 0 −0.024 −0.84 

All Working Timberlands 7.2 4.1 −0.74 0 −0.024 −0.84 

Private Working 

Timberlands1

6.8 4.1 −0.66 0 −0.024 −0.76 

1Because the private “working forests” tend to incur harvests more frequently (they account for 91.6% of harvest 

removals) and yet account for only 82% of growth, the GROW term decreases as the land base used in the computation 

becomes more restrictive. 

This section calculates one of the above alternative land base equation as an example, using the All 

Forest Land category. 

  	
  

   (EQ. I.10) 

Inserting the illustrative values for the relevant equation terms into this equation: 

  . 	
−. #$ +  − 	.  .   

And the result is: 
November 2014 I-10 

  . 	


For this application: 

  . 	


Therefore: 

BAF = NBE/PGE 

BAF = . 	
/0. 	


BAF = 0.97

Temporal Scale 

Because forest growth and removals are dynamic processes, the GROW term can be expected to 

change over time. Some of this change may be due to sampling error, some due to changes in 

inventory processes over long spans of time, and some due to changing rates of utilization and 

changing age-class distributions of forests. Because of its small value and the potential for variation 

due to inventory methodology, SITETNC is held constant across the temporal scales evaluated. To 

demonstrate the levels of change in GROW that have occurred in the past in these measures, we can 

use data from the periodic assessments of the U.S. forest land base conducted under the Resources 

Planning Act (RPA) by the USDA Forest Service. From Smith et al. (2009; tables 33, 34, and 35), 

growth, mortality, and removals data were extracted for the southeastern United States for RPA 

years prior to 2010, and FIA data were used for 2010. All estimates are based on all timberlands 

(see analysis for Working Forest in Section 2.5). 

Table I-8 shows that the growth estimate has fluctuated from a minimum of 5,587 million cu ft/yr 

in 1986 to a maximum of 8,142 million cu ft/yr in 2010—a 46% increase in the Southeast—while 

the removals estimate has fluctuated from a minimum of 3,031 million cu ft/yr in 1976 to a 

maximum of 4,449 million cu ft/yr in 2010—a 47% increase. The ratio of growth/removals has also 

fluctuated, decreasing from a maximum of 1.98 in 1976 to a minimum of 1.34 in 1996, followed by 

an increasing trend to 1.83 in 2010. As previously mentioned, growth/removals is expected to 

change over time for a variety of reasons and will reflect changing rates of roundwood utilization 

and changing age-class distributions of forests, among other factors. 

Table I-8. Biogenic Attributes over Forest Inventory Time Frames for the Temporal Scale Case 

Study. 

Roundwood/Southeast/

All Timberlands 

Growth (G)

(billion 

cu ft/yr) 

Removals (R)

(billion 

cu ft/yr) 

GROW AVOIDEMIT SITETNC BAF

1976 5.99 3.03 −0.98 0 −0.024 −1.10 

1986 5.59 3.67 −0.52 0 −0.024 −0.60 

1996 5.96 4.46 −0.34 0 −0.024 −0.40 

2006 7.31 4.31 −0.70 0 −0.024 −0.79 

2010 8.14 4.45 −0.83 0 −0.024 −0.94 
November 2014 I-11 

Scenario 1: Changed Time Frame 1966–1976 

Inserting the illustrative values for relevant equation terms into the equation results in: 

  . 	
−. %# +  − .  .   (EQ. I.11) 

And the result is: 

  . $	


For this application: 

  . 	
 

Therefore: 

BAF = NBE/PGE

BAF = . $	
/0. 	


BAF = −1.10

Scenario 2: Changed Time Frame 1977–1986 

Inserting the values for L and P into this equation results in: 

  . 	
−. " +  − .  .   

And the result is: 

  . "	


For this application: 

  . 	
 

Therefore: 

BAF = NBE/PGE 

BAF = . "	
/0. 	


BAF = −0.60

Scenario 3: Changed Time Frame 1987–1996 

Inserting the illustrative values for relevant equation terms into the equation results in: 

  . 	
−. ! +  − .  .   (EQ. I.12) 

And the result is: 

  . 	


For this application: 

  . 	
 
November 2014 I-12 

Therefore: 

BAF = NBE/PGE

BAF = . 	
/0. 	


BAF = −0.40

Scenario 4: Changed Time Frame 1997–2006 

Inserting the illustrative values for relevant equation terms into the equation results in: 

  . 	
−.  +  − .  .   (EQ. I.13) 

And the result is: 

  . !!	


For this application: 

  . 	
. 

Therefore: 

BAF = NBE/PGE 

BAF = . !!	
/0. 	


BAF = −0.79

Scenario 5: Changed Time Frame 2010 

Inserting the values into this equation results in:

  . 	
−. #! +  − .  .   (EQ. I.14)

And the result is: 

  . !%	


For this application: 

  . 	
 

Therefore: 

BAF = NBE/PGE

BAF = . !%	
/0. 	


BAF = −0.94

3. Logging Residues in the Pacific Northwest 

This case study calculates the net biogenic CO2 emissions from a hypothetical electricity facility

with an EGU that uses logging residues from the Pacific Northwest as a biogenic feedstock. The case 

study illustrates how estimated values for biogenic attributes and facility-specific attributes would 
November 2014 I-13 

be combined to calculate the NBE and BAF using a reference point baseline. This case study also 

examines alternative scenarios including (1) equation term analysis (i.e., investigation of the impact

of various terms on the final result as they are added or subtracted from the assessment factor 

calculation); and (2) alternative fate (i.e., investigation of the impact of assuming either a decay or 

combustion fate if the logging residues were not removed as biogenic feedstock). 

As with the SE roundwood case study, 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) values are not included in this case 

study application. 

 Base Case 

For all of the case study scenarios, it was assumed that the electricity facility has an output of 30 

MW, a capacity factor of 95%, and efficiency of 26% (consumes 1 BDT of roundwood per MWh of 

electricity produced ), thus requiring an input of 250,000 BDT of roundwood per year. If we assume 

that 50% of the 250,000 BDT of feedstock is carbon and convert the short tons to tonnes and 

carbon to CO2, we end up with a PGE of 0.42 mmtCO2 for the hypothetical 30 MW plant. 

In Appendix H, SITETNC for logging residues in the Pacific Northwest was estimated as 1 mtCO2e 

per ton of feedstock removed. GROW is 0 and AVOIDEMIT represents an alternative fate of 

decomposition on site. 

Table I-9. Biogenic Landscape Attributes: Logging Residues in the Pacific Northwest. 

Feedstock/Region GROW AVOIDEMIT SITETNC

Logging Residues/Pacific 

Northwest 

0 −0.98 1 

Table I-10. Process Attributes: Logging Residues in the Pacific Northwest. 

Feedstock/Process PRODC L 

Logging Residues/EGU 1 1.1 

Inserting the illustrative values for relevant equation terms into the equation results in: 

  . 	
  . %#   .   (EQ. I.15) 

And the result is: 

  .  	


For this application: 

  . 	
 

Therefore: 

BAF = NBE/PGE
November 2014 I-14 

BAF = .  	
/0. 	


BAF = 0.02

SITETNC equals 1 in the base case to represent a ton of logging residues being removed or emitted 

from the feedstock production site. As described in Appendix H, the AVOIDEMIT value of −0.98 

represents the percentage of emissions that would have occurred on the production site had those 

logging residues remained on site rather than been combusted at a stationary facility less the 2% 

that would have remained sequestered in the soil pool long term. In other words, using logging 

residues that would have been left at the production site following a harvest would result in a loss 

(or emission) of the 2% of that feedstock that would have remained on site in the long run. 

4. Corn Stover in the Corn Belt 

This case study calculates the net biogenic CO2 emissions from a hypothetical electricity facility

with an EGU that uses corn stover from the Corn Belt as a biogenic feedstock. The case study 

illustrates how estimated values for biogenic attributes, and process attributes would be combined 

to calculate the NBE and BAF using a reference point baseline. 

This case study also examines alternative scenarios including (1) equation term analysis (i.e., 

investigation of the impact of various terms on the final result as they are added or subtracted from 

the assessment factor calculation); and (2) the influence of including fluxes of nitrous oxide (N2O) at 

sites where corn stover is removed. 

 Base Case 

For all of the case study scenarios, it was assumed that the electricity facility has an output of 30 

MW per year, a capacity factor of 95% efficiency, converts 1.1 BDT of corn stover per MWh of 

electricity produced, and would consume an input of 275,000 BDT of corn stover per year. Note, 

this estimate of BDT has been revised upward from the estimates presented in the roundwood and 

logging residue case studies to account for the lower carbon fraction in corn stover (0.44) 

compared with roundwood/logging residue (0.50). Converting the 275,000 BDT of feedstock to 

carbon and converting the short tons to metric tonnes and carbon to CO2 we end up with a PGE of 

0.44 mmtCO2 for the hypothetical 30 MW plant. 

In Appendix H, SITETNC for corn stover in the Corn Belt was estimated as +0.0026 mtCO2e per ton 

of feedstock removed. GROW is set to 0 because the ratio of net growth to removals is 0. AVOIDEMIT

is also 0 because all emissions would have occurred anyway in the absence of residue removals. 

Therefore: 

Table I-11. Biogenic Landscape Attributes: Corn Stover in the Corn Belt. 

Feedstock/Region SITETNC GROW AVOIDEMIT

Corn Stover/Corn Belt .0026 0 0 
November 2014 I-15 

Table I-12. Process Attributes: Corn Stover in the Corn Belt 

Feedstock/Process P L 

Corn Stover/EGU 1 1.1 

To investigate the relative impact of each of the variables on the assessment factor result, the 

assessment factor was calculated with and without certain equation variables (i.e., SITETNC). 

Inserting the illustrative values for the relevant equation terms into the main biogenic assessment 

factor equation from the main report, this equation is now: 

  . 	
  . $   .   (EQ. I.16) 

And the result is: 

  .  !	


For this case study application: 

  . 	
 

Therefore: 

BAF = NBE/PGE 

BAF = .  !	
/0. 	


BAF = 0.0029

NBE Results with N2O Emissions 

In Appendix H, SITETNC for corn stover in the Corn Belt with N2O emissions was estimated as 

+0.0123 mtCO2 equivalent (e) per ton of feedstock removed.1,2 Once again, GROW is set to 0 because 

the ratio of net growth to removals is 0. AVOIDEMIT is also 0 because all emissions would have 

occurred anyway in the absence of residue removals. Therefore: 

Table I-13. Biogenic Landscape Attributes: Corn Stover in the Corn Belt with N2O Emissions. 

Feedstock/Region SITETNC GROW AVOIDEMIT

Corn Stover/Corn Belt .0123 0 0 

Inserting the illustrative values for the relevant equation terms into the main biogenic assessment 

factor equation from the main report, this equation is now: 

  . 	
  .  !   .   (EQ. I.17) 

And the result is: 

 

1

 A detailed methodology for estimating SITETNC for soil carbon and N2O emissions changes can be found in 

Appendix H. 

2

 CO2 equivalence is used for SITETNC as N2O emissions are converted to CO2 terms. 
November 2014 I-16 

  . $	


For this case study application: 

  . 	


Therefore: 

BAF = NBE/PGE 

BAF = . $	
/0. 	


BAF = 0.0135

5. References 

Smith, W.B., P.D. Miles, C.H. Perry, and S.A. Pugh. 2009. Forest Resources of the United States, 2007. 

Gen. Tech. Rep. WO-78. Washington, DC: U.S. Department of Agriculture, Forest Service, 

Washington Office. 336 p.