November 2014 I-1



# Appendix I: Illustrative Forestry and Agriculture C ase Studies Using a Retrospective Reference Point Basel ine

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 N 2 O 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 Sou theast. ........................................... .................................. I-3 Table I-3. Biogenic Attributes for the Southeast an d South Central Regions. .......................... ................... I-4 Table I-4. Increased Removals by Multiples of 1 Bil lion 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 Fore st Definition Case Study Sensitivity. ............. ........ I-9 Table I-8. Biogenic Attributes over Forest Inventor y Time Frames for the Temporal Scale Case Study. ............................................

................................................... ................................................... ..................... I-10 Table I-9. Biogenic Landscape Attributes: Logging R esidues 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 Sto ver 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 Sto ver in the Corn Belt with N 2 O Emissions......... I-15November 2014 I-2



## 1. Introduction
This appendix presents three illustrative case stud ies 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. N ested within each case study section are various sensitivity ana lyses. These analyses highlight the influence of alternative scenarios on the base case. The three i llustrative 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 equa tion from the main report:  	
  

       (EQ. I.1) This appendix uses the illustrative biogenic landsc ape attributes ( GROW , AVOIDEMIT

, and SITETNC

) as calculated using the retrospective reference poi nt 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). As sessment 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 CO 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 a lternative scenarios as sensitivities:

• A regional aggregation of roundwood in both the Sou theast (SE) and South Central (SC) regions;

• Increased roundwood removals, as reflected in incre ased 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 fores tland, all timberlands, private timberlands, all working timberlands, private working timberland s); 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. IfNovember 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 CO 2 , we end up with a PGE of 0.42 mmtCO 2 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 Sou theast.

Feedstock/Process P L Roundwood/EGU 1 1.1
This case study then uses the main biogenic assessm ent 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 geo graphic domain, the GROW terms for the SE region and the SC region were computed separately and as a n aggregated southern region to demonstrate the impact of using larger spatial scales to develo p the BAF estimates. Table I-3 contains the growth and removals values (from the 2010 FIA survey perio d, which includes data collected between 2006 and 2010) for private timberlands for the SE a nd 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 an d 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 r esults in a very slight change to the GROW term for the Southeast region, though overall growt h still exceeds removals in the combined region.


### Increased Removals Increased removal scenarios were analyzed for round wood in the SE region to demonstrate the potential impact of changing future roundwood harve sts as a biogenic feedstock on the assessment factor under the reference point baseline. This ana lysis changes the removals term in isolation and thus does not mimic growth responses associated wit h 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 increas ed 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 rem ovals. For GROW, the “REMOVALS – GROWTH” difference in Equation H.2 changes with greater rem ovals, 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 Bill ion 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 valu es 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 valu es 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 val ues 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 valu es 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 gen erate changes to the GROW term because removals increase while growth does not. Removals b egin to exceed growth—and result in a net atmospheric contribution of biogenic CO 2 emissions from our hypothetical EGU using roundwoo d—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 l evel (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 fact or 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 wi th and without certain variables in the equation, this analysis illustrates the relative importance o f 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 impa ct on the assessment factor.

     
        (EQ. I.8) Inserting the illustrative values for relevant equa tion 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 assess ment 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 refere nce 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 impa ct on the assessment factor.

     	
  

      (EQ. I.9) Inserting the illustrative values for relevant equa tion 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 referen ce period. 

### Working Forest Forest inventory estimates (such as growth and remo vals) can be expressed for different land areas or definitions of forest. In general, FIA distingui shes between forestland (all land covered with forest as defined by FIA) and timberland (forest me eting certain minimum productivity thresholds and not reserved from timber harvest by law). Fores t owned by public entities can be further differentiated from forest owned by private entitie s (because, for example, private timberland accounts for 98.8% of all removals or harvests with in 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 c riteria 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 definit ion of forest); 2. All timberlands (forest land above productivity thr esholds not reserved from harvest); 3. Private forest lands (#1 above for private ownershi ps); 4. Private timberlands (#2 above for private ownership s);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 scre ened 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 so utheastern U.S. FIA data from the 2010 survey period, we obtained different values for growth/rem ovals ratios as depicted in Table I-7. Table I-7. Biogenic Attributes for the Working Fore st 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 Timberlands 1 6.8 4.1 −0.66 0 −0.024 −0.76

1 Because the private “working forests” tend to incur harvests more frequently (they account for 91.6% o f harvest removals) and yet account for only 82% of growth, t he GROW term decreases as the land base used in the comput ation becomes more restrictive.

This section calculates one of the above alternativ e 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 proc esses, 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 so me due to changing rates of utilization and changing age-class distributions of forests. Becaus e of its small value and the potential for variatio n due to inventory methodology, SITETNC is held constant across the temporal scales evalua ted. 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 201 0. 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 fluctu ated from a minimum of 5,587 million cu ft/yr in 1986 to a maximum of 8,142 million cu ft/yr in 2 010—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% inc rease. The ratio of growth/removals has also fluctuated, decreasing from a maximum of 1.98 in 19 76 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, am ong other factors. Table I-8. Biogenic Attributes over Forest Inventor y 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 −0.94November 2014 I-11

Scenario 1: Changed Time Frame 1966–1976 Inserting the illustrative values for relevant equa tion 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 equa tion 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 equa tion 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 CO 2 emissions from a hypothetical electricity facility with an EGU that uses logging residues from the Pac ific Northwest as a biogenic feedstock. The case study illustrates how estimated values for biogenic attributes and facility-specific attributes wouldNovember 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) equati on term analysis (i.e., investigation of the impact of various terms on the final result as they are ad ded or subtracted from the assessment factor calculation); and (2) alternative fate (i.e., inves tigation of the impact of assuming either a decay o r combustion fate if the logging residues were not re moved as biogenic feedstock). As with the SE roundwood case study, feedstock carb on losses during storage, transport, and processing ( L ) are held constant at 1.1, feedstock carbon embodi ed in products ( P ) is also constant at 1, and leakage associated with feedstock product ion ( 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 CO 2 , we end up with a PGE of 0.42 mmtCO 2 for the hypothetical 30 MW plant. In Appendix H, SITETNC for logging residues in the Pacific Northwest was estimated as 1 mtCO 2 e 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 R esidues 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 equa tion terms into the equation results in:

   . 	      . %#  .   (EQ. I.15)
And the result is:

  .  	   For this application:

  . 	   Therefore:

BAF = NBE/PGENovember 2014 I-14

BAF = .  	   /0 . 	   BAF = 0.02
SITETNC equals 1 in the base case to represent a ton of lo gging 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 h ave 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 po ol long term. In other words, using logging residues that would have been left at the productio n site following a harvest would result in a loss (or emission) of the 2% of that feedstock that woul d have remained on site in the long run. 

## 4. Corn Stover in the Corn Belt
This case study calculates the net biogenic CO 2 emissions from a hypothetical electricity facility with an EGU that uses corn stover from the Corn Bel t as a biogenic feedstock. The case study illustrates how estimated values for biogenic attri butes, 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 inf luence of including fluxes of nitrous oxide (N 2 O) 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, c onverts 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 t he estimates presented in the roundwood and logging residue case studies to account for the low er carbon fraction in corn stover (0.44) compared with roundwood/logging residue (0.50). Con verting the 275,000 BDT of feedstock to carbon and converting the short tons to metric tonn es and carbon to CO 2 we end up with a PGE of 0.44 mmtCO 2 for the hypothetical 30 MW plant. In Appendix H, SITETNC for corn stover in the Corn Belt was estimated as +0.0026 mtCO 2 e per ton of feedstock removed. GROW is set to 0 because the ratio of net growth to rem ovals 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 Sto ver in the Corn Belt.

Feedstock/Region SITETNC GROW AVOIDEMIT Corn Stover/Corn Belt .0026 0 0November 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 v ariables on the assessment factor result, the assessment factor was calculated with and without c ertain 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 N 2 

### O Emissions In Appendix H, SITETNC for corn stover in the Corn Belt with N 2 O emissions was estimated as +0.0123 mtCO 2 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 Sto ver in the Corn Belt with N 2 O 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 N 2 O emissions changes can be found in Appendix H. 2 CO 2 equivalence is used for SITETNC as N 2 O emissions are converted to CO 2 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. Departm ent of Agriculture, Forest Service, Washington Office. 336 p.