an energy process-step model for manufacturing paper and paperboard

Energy Vol. 21, No. 7/S. pp. 667-681. 1996

!m60-5442(%)ooo16-3 Published by Elswier Science Ltd

Printed in #Great Britain 0360-SW!96 ‘il5.00 + 0.00

AN ENERGY PROCESS-STEP MODEL FOR MANUFACTURING PAPER AND PAPERBOARD

LUIS GIRALDG and BARRY HYMANt Department of Mechanical Engineering, Box 352600, University of Washington, Seattle, WA 98195-2603,

U.S.A.

(Received 5 December 1995)

Abstract-A process-step energy-consumption model for the production of paper and paperboard is presented. The model is consistent with data published by the U.S. Department of Energy’s 1991 Manufacturing Energy Consumption Survey (MECS). The applicability of the framework to other industries is discussed. Published by Elsevier Science Ltd.

INTRODUCTION

Process-step models of energy consumption in 108 manufacturing processes at the four-digit Standard Industrial Classification (SIC) level were developed at Drexel University based on data collected in 1976.’ Changes in technology, production practices, product composition and energy prices, coupled with the availability of new data sources indicate that it is timely to update and refine these models. A generic approach for constructing such energy process-step models that are calibrated with MEC!? data was recently described.3 The three main stages of model construction are: (i) construct an establishment-oriented end-use model of energy consumption using MECS data; (ii) convert the establishment- oriented energy consumption model to a product-oriented energy intensity model; (iii) ahocate the product-oriented end-use energy intensities among process steps.

We have selected the paper industry for the first application of this generic approach. In addition to a literature review and data analysis, we visited seven paper, paperboard and pulp mills in Washington State to gain further insights into the energy consumption characteristics of their manufacturing processes. We also conducted telephone interviews with specialists from trade associations and mill engin- eers from several other States. The first of the three stages of constructing a process-step energy intensity model for paper and paperboard is described elsewhere.4 This paper is devoted to the second and third steps of model construction.

Figure 1 is extracted from the end-use models for paper mills (SIC 2621) and paperboard mills (SIC 2631) developed in Ref. 4 using 1991 MECS data. Figure 1 combines Figs. 1 and 9 from Ref. 4 and focuses on end-use and intermediate conversion activities, omitting some of the details of specific fuel inputs and waste heat recovery.$ While non-electric contributions to individual end-uses were aggregated in Figs. 1 and 9 of Ref. 4 to simplify the graphical depiction, these contributions are shown separately for fuel, and steam and waste heat recovery in Fig. lc. The disaggregated values are obtained from Table 4 of Ref. 4 for SIC 2631 plus similar data for SIC 2621 from Table Cl.52 of Ref. 5. This disaggregation allows us to conduct a more detailed allocation of end-use consumption to process-steps later in this paper. Figure 2 is the counterpart of Fig. 1 for pulp mills (SIC 2611). Figures 1 and 2 are energy-consumption models of paper, paperboard, and pulp mills. Since some paper mills and paperboard mills also produce pulp, and some pulp mills also produce paper and paperboard, the second stage in model construction is to transform these establishment-oriented energy consumption models into product-oriented energy-intensity models.

tAuthor for correspondence. $The reasons for consolidating the data for paper mills and paperboard mills is discussed in the next section.

667

648 Lois Giido and Barry Hyman

I , I I i

SIanaId RCCOWSdW~HWl _________- FUCI

_---- &&j& -m-m-_- N atmnhdible~la

Fig. 1. Intermediate and end-use energy consumption in paper/paperboard mills ( lOI2 Btu).

PRODUCTORENTED ENERGYINTENSiTIES

Overall energy intensities

It was shown in Ref. 3 that the energy intensity of manufacturing a set of products in a set of industries can be estimated from

(0 = (Q)-‘(E) . (1)

An energy process-step model for manufacturing paper and paperboard

OmiteEloztricity

1 20.9

I - i

669

(b). C4mIribuIiom of inlamcdiatc enqzy fomg IO mdusg (d. -

Stcun and Recovued Waste Heat _ _ _ _ _ _ _ _ _ _ FUel

----- Electricity ------- N-butible-bles

Fig. 2. Intermediate and end-use energy consumption in pulp mills (IO’* Btu).

When used in conjunction with SIC codes, each element of the (E) and (Q) matrices has a subscript that identifies an industry by its four-digit SIC code. Each element of (I) and (Q) has a superscript that identifies a product by the four-digit SIC code of the industry for which that product is tbe primary output. We now construct (E) and (Q) associated with SIC 2611, 2621 and 263 1.

The (E) and (Q, matrices - the elements of (E) are obtained directly from Table A4 of the 1991 MECS as

E 26,, = 300 x 1012 Btu, E,,,, = 1,204 x 1012 Btu, E263, = 832 x lOI Btu . (2)

670 Luis Giraldo and Barry Hyman

Table 1. Physical measures of pulp, paper and paperboard output in 1991.

Product

Pulp Paper Paperboard

Output (1000 tons)

9,028 39,078 40,323

In order to construct (Q), we need data on the annual physical production of each product of interest, d&aggregated according to the industries in which those products are produced. First we develop estimates for the total 1991 production of pulp, paper and paperboard.

The 1991 data presented in Table 1 for physical measures of paper and paperboard production are taken directly from Ref. 6. However, the physical quantity of pulp production listed in Ref. 6 (63,818 x lo3 tons) includes not only pulp produced as a final product in pulp mills but also pulp produced as an intermediate product in integrated pulp-paper and integrated pulp-paperboard mills. Some of the pulp produced in these integrated mills is sold on the open market (market pulp) but most of it is retained within the mills and transformed into either paper or paperboard. To avoid double- counting in the next stage of our analysis, we want pulp production data for market pulp only.

The American Forest and Paper Association (AFPA)_F publishes comprehensive annual statistics for the pulp, paper and paperboard industries. ’ The values for 1991 paper and paperboard output in Tables II and III of Ref. 7 match those listed in Ref. 6. This establishes Ref. 7 as a credible source for market pulp data that is consistent with the paper and paperboard data in Ref. 6. However, the pulp production data in Ref. 7 (Table XXI B) is for wood pulp only. To justify using wood market pulp production data as a surrogate for total market pulp production, we need to examine the composition of the pulp product group (SIC 2611) in more detail.

Table 2 shows the five product classes in the pulp product group and their 1991 value of shipments.’ The first three product classes in Table 2 are wood pulp products; the last two are non-wood pulp products and mill by-products. These latter product classes include non-pulp products whose physical output is measured by volume so that data is incompatible with our physical measure for pulp output expressed in tons. Given the lack of physical output data for total market pulp production, we use market wood pulp data which accounts for 93% of the value of shipments of pulp products. Hence, the pulp output estimate we list in Table 1 is the value from Ref. 7 for market wood pulp.

We next identify the industries in which pulp, paper and paperboard are produced and the amounts of each product produced in each of those industries. The Benchmark Input-Output Accounts (hereafter referred to I-O data)9s lo* ‘i disaggregate the value of product shipments according to the industries that produce the product. The classification system used in the I-O accounts is keyed to the SIC system.

Using the I-O data to build (Q) presents two problems. First, our energy model is based on 1991 MECS data, but the most recent I-O data available is for 1987. We deal with this limitation by extrapol- ating from 1977, 1982, and 1987 I-O data to estimate 1991 va1ues.S Second, the I-O classification system was modified in 1987 and paper mills and paperboard mills (formerly treated separately) were combined into one classification code. With no additional information to disaggregate paper and paper-

Table 2. Pulp product class descriptions and value of shipments for 1991.

SIC 2611 Product Classes Description

Value of Shipments (millon $)

26111 Special alpha and dissolving wood pulp 904.6 26113 Sulfate wood pulp 4152.3 26114 Sulfite and other wood pulp 269.7 26115 Pulp, other than wood, and miscellaneous pulp mill byproducts 413.4 26110 Pulp mill products not specified by kind 1.2

tFormerly the American Paper Institute (API). *The I-O tables are calculated at five year intervals.

An energy process-step model for manufactming paper and paperboard 671

board output for 1987, we will develop our model from this point on for combined paper/paperboard output (SIC 2621131).

I-O data for the sources of pulp and paper/paperboard in 1977, 1982 and 1987 are presented in Table 3. The 1991 source estimates in Table 3 are taken from linear regression lines for 1977, 1982 and 1987 data extrapolated to 1991. In the parlance of Ref. 3, this set of products and industries is essentially complete, i.e. pulp and paper/paperboard mills account for 99.8% of pulp production and 99% of paper/paperboard production in 1977. The coverage is even better for 1982 and 1987.t

We use the percentages for 1991 in Table 3 and the production data from Table 1 to calculate the elements of (Q) ( 103 tons) as*

Q;;:: = 6112, Q$& = 2916, Q$;::‘31 = 1270, Q$;;::: = 78,131 . (3)

Consolidating the E2621 and Ezh3, values from Eq. (2) and inserting them with Eq. (3) into Eq. (l), we obtain

Pi’ = 44.0 x lo6 Btu/ton, P621’31 = 24.4 x 106 Btu/ton . (4)

Partial energy intensities Although Eq. ( 1) was derived for estimating overall energy intensities such as those given :in Eq. (4),

we will assume it is also valid for estimating what we call the partial energy intensities of specific energy forms, intermediate-uses, and end-uses.9 The assumption used in deriving Eq. (l), that the energy intensity of a product is independent of the industry in which it is made, is less likely to be valid for partial energy intensities, e.g., the energy intensity of steam for process heat. However, as a first effort to demonstrate the application of the general approach, we will assume that Eq. (1) is valid for any energy form and use included in Figs. 1 and 2.

However, if one of the industries in a product-industry set has zero energy consumption for a specific energy form, intermediate-use, or end-use and other industries in the same set have non-zero values for the same form or use, then obviously their partial energy intensities cannot be equal. Hence E@. (1) cannot be used for that form or use. In those cases, we calculate the non-zero partial intensity by dividing the energy consumed for that form or use by the total production of the product. Intensities calculated this way are marked with an asterisk in Fig. 3. Applying this procedure to each of the intermediate-uses and end-uses, we obtain the energy intensity diagram for paper/paperboard production shown in Fig. 3. We use these end-use energy intensities as control totals for our process-step model described in the next section.

Table 3. Sources of pulp and paper/paperboard.

Source (96)

Product Year Pulp Mills Paper/Paperboard Mills

Pulp 1977 73.5 26.5 1982 71.5 28.5 1987 69.3 30.7 1991 (est.) 67.7 32.3

Paper/Paperboard 1977 0.9 99.1 1982 1.4 98.6 1987 1.3 98.7 1991 (est.) 1.6 98.4

t&e Tables 1, 2 and 3 of Ref. 3 for detailed 1982 production data. $This step assumes that the price of a product ($/ton) is independent of the industry in which the product is produced. See

Ref. 3 for a more detailed discussion. #We aheady used Rq. (1) to calculate electricity intensities in Ref. 2.

En 21:718-K

672 Luis Girddo and Barry Hyman

steamndaawead w&e Hat -________- F&WI

----_ w -_-_-_a N ammbaibkramvabkl

Fig. 3. Energy intensities of papr/paperboatd intemxdiate-uses and end-uses (l@ Btuhon).

ENERGY PROCESS-STEP MODEL

General approach In stage (iii) of our model construction we identify the key energy-consuming process-steps and

apportion the end-use intensities in Fig. 3 among those process-steps. Several studies’** 13* I** Is* I6 besides Drexel have developed process-step model8 for energy consumption in paper/paperboard production. Different process-steps and base years are used and consumption data varies widely among those studies. Some studies report total energy consumption at each process step, others only include electricity con-

An energy process-step model for mantiactming paper and paperboard 673

sumption, while still others disaggregate it into electricity, fuel and thermal energy. It is not clear if energy for support services such as facility lighting is included in any of these studies.

We rely primarily on the Drexel study for the following reasons: (i) Drexel developed models for many industries so updating models for industries other than paper will be facilitated by the consistency among Drexel process-step representations; (ii) Drexel data is more detailed than other studies. Material and energy balances for every process step are included; (iii) Drexel methodological consistency across industries facilitates cross-industry comparisons; (iv) energy and material flows explicitly ex,clude non- process uses such as lighting and space heating.

We base our model on the Drexel models for paper/paperboard made in integrated mills (mills that produce pulp and paper/paperboard in the same facility).? The Drexel model for paper produced in integrated mills contains 22 process steps; the paperboard model contains the same steps except that the bleaching step is omitted. For this first effort to use MECS to calibrate a process-step model, we consolidate the Drexel process steps into a 1Zstep model shown in Fig. 4. In the following description of each step of our model, the corresponding step(s) in the Drexel model arc included in parentheses. This correspondence helps to clarify the subsequent comparison of our results with the Drenel results. Neither our model nor Drexel accounts for recycled paper as a source of pulp. Incorporating this and other process variations is reserved for subsequent refinements of the model.

Material Flow Model

An important aid to distributing end-use energy intensities among process steps is a material balance for each process step. Our material flow model focuses on fiber, water and chemicals associated with the recovery process. Estimates of moisture content (the percentage of water in pulp or stock on a weight basis) at each step are drawn from Ref. 12. We calculate material flows based on one ton of finished paper/paperboard. For convenience, we begin the calculations at the last process step (Step 12) and work backwards. The resulting material flows are summarized in Fig. 4.

(12) Finishing (calender; winding, cutting, trimming, banding) - finished paper and paperboard products have a 5% moisture content; (11) Drying (dryer) - since no fiber is added or lost in drying, and since the entering moisture content is 64%, the amount of water entering the drying step i:s 1.69 tons; ( 10) - Pressing (press section) - we proceed similar to Step 11. With the moisture content for stock entering the pressing step estimated at 88%, we calculate the incoming water as 6.97 tons; (!a) Forming (decker; forming section) - since both water and fiber are extracted (e, and ef) during this step, the material balance is more complicated. As shown in Fig. 5, the amounts of output water and fiber (0, and 0,) from the forming step are known from the calculated inputs to Step 10. The input to the forming step (i, and if> has a 99.5% moisture content and the fluid extracted during forming has a moisture content of 99.9%.

These relationships yield the following set of equations for the material flow in this process step:

L - ’ e,=6.97tons,ii-e~=0.95tons,i,lji.+lli=0.995,e,/(e,+e)=0.999

The solution to this set is if = 1.18 tons, er= 0.23 tons, i, = 234.34 tons, and ef = 227.37 tons; (8) Screen- ing (cleaner; screen; screening, knotting, beating) - similar calculations with incoming material at 98% moisture content and recovered material at 99.9% moisture content yield that the stock entering Step 8 contains 0.99 tons of fiber and 234 tons of water and the recovered material consists of 0.19 tons of fiber and 185.62 tons of water; (8a) Fiber and water recovery - this is not a separate step in our process-step model, i.e., we do not account for any energy consumed in this operation. It is included here only to complete the material flow model. Of the 227.37 tons of water extracted during the forming step, 185.62 tons are recovered and 41.75 tons are treated and disposed of as waste. As part of this operation, 0.04 tons of fiber are lost; (7) Bleaching (bleaching) - no significant changes in mass flows occur at the bleaching step; (6) Refining (refiner) - no significant changes in mass flows occur at the refining step; (5) Chemical recovery (multiple evaporator; recovery furnace; slaker; lime kiln) - pulping chemicals and combustible solids used in chemical pulping are recycled in this step. I3lack liquor

iWhile only 35% of mills are integrated, integrated mills account for 74% of shipments.”


1. Dcb&ng --) 0.6Obark

3.50 lo@

2. cxpping

3.50 dlipa

47.42 putping liqwx + wrtrr 3.Digalhrs *

‘--+.66makaupdKaliah+wata

49.17waw A J

1.7s @ia + fibw 5.cwuial -

w

4 - 0.4swatavapor

4.walhing - 1.21 black liquor

40.72 wata 0.99 fibar

I 1 6. Rtihimg

48.72 water 0.99 liba

7. Blcadhg ,

48.72 waia 0.99 fibar

II.saaeahg 4 racovec 0.19 fiba 185.62 + waw

&Fiiaad W-W

R wade: 0.04 fiber + 41.7s water

9. Fotming 4 m 0.23 fib + 227.37 w&r

6.97 wda 0.95 fibar

10. ReaBiq

Fig. 4. Process-step model and material flows for paper/paperboard production (tons).

4 JI ow- 6.97 o f ~0.95

Fig. 5. Material flow in the forming section (tons).

An energy process-step model for manufacturing paper and paperboard 675

is sent to evaporators to reduce moisture content and concentrated liquor is burned in a recovery boiler to produce steam. Green liquor, a combustion by-product, is converted into white liquor in a. lime kiln and used in the pulping process. Using data for the quantities of chemical recovery solids burned in Washington State mill~,‘~ and assuming that black liquor has 63% solids,13 we estimate the quantity of black liquor produced by those mills. This is divided by the total production of these mill~‘~ to obtain an average quantity of liquor produced per ton of product (see Table 4); (4) Washing (washing and filtering, washing and screening) - pulp leaving the digester is washed, cleaned and screened to remove cooking liquor, impurities, and small solid particles. The liquor to paper ratio obtained for all facilities listed in Table 4 is used for estimating the black liquor output in this step; (3) Digesting (digester, flash tank). The recovery factor (the percentage by oven dry weight of pulp obtained from wood) depends on the pulping process and the grade of product. Since the kraft process represents 91% of chemical pulping and 75% of all pulp?’ we use a recovery factor of 50%.2l Chips that enter the digester are composed of 50% water and 50% fiber and lignin;22 (2) Chipping (chipper) - we assume that all of the wood is converted to chips; (1) Debarking (barker; shredder). The amount of material removed during the debarking process ranges between 10% and 25% of total weight.23 We use an intermediate value of 15% of the total log weight (Ref. 1).

ALLOCATING END-USE ENERGY INTENSITIES TO PROCESS STEPS

There are 12 end-uses defined by MECS, including boiler fuel and fuel for non-steam forms of onsite power generation. We refer to the latter two as intermediate uses (see Figs. l-3) and do not allocate their energy intensities to process steps. Also, the bottom five MECS end-uses depicted in .Fig. 3c are facility-oriented and and we do not allocate the energy consumed for those end-uses among the process steps. Finally, energy consumed for the ‘Other Process Use’ end-use is not distributed among process steps since inadequate information is available to make the allocation. In the remainder of this section, we allocate the energy used by the remaining four MECS end-uses (process heating; process cooling and refrigeration; machine drive; electro-chemical processes) to each of the 12 process step:s indicated in Fig. 4. We perform this allocation separately for fuel, electricity and steam and recovered waste heat.

Fuel As indicated in Fig. 3, the only designated end-uses for direct fuel consumption are process heat and

machine drive. We allocate these end-use energy intensities to process steps as follows: Process heat - all direct fuel consumption for process heat is allocated to Step 5 - Chemical Recovery, where fuel is burned in a kiln to calcine limestone. Machine drive - gas and steam turbines are used in some paper/paperboard mills to drive machinery. The machines are usually coupled in the pressing and drying process steps, creating the opportunity to use a single direct-drive unit. We allocate fuel for machine drive to these two process steps on the basis of their relative material flows as indicated in Fig. 4 (73.3% to pressing and 26.7% to drying).

Electricity Electricity for the four designated end-uses is distributed among the process steps accorlding to the

following arguments: Process heat - radio frequency drying technologies are being more widely used

Table4. Black liquor production by paper/paperboard mills in Wash- ington State.

Facility

James River Corp. Longview Scott Paper Simpson Tacoma kraft Weyerhauser

Total

Black Liquor Produced (ton/day)

775.0 3248.0 913.0 592.3

2622.0

8150.3


in paper/paperboard manufacturing. This is modeled by allocating all electricity for process heat to the drying process step. Process cooling - electricity for process cooling end-use is allocated to chemical recovery to reflect that technologies utilizing freeze concentration of black liquor are replacing tra- ditional evaporators. Machine drive - we use the IMIS database” of end-use electricity consumption for four-digit SIC industries. Five IMIS end-uses (size reduction; liquid-solid separation; solid-solid separation; materials handling, fabrication) are components of the MECS machine drive end-use. According to IMIS, material handling is 37.8% of electric machine drive; we allocate this electricity to each process step in proportion to the mass flow of pulp or stock, water, and black liquor associated with that step as depicted in Fig. 4. IMIS data indicates that electricity for size reduction accounts for 33.7% of machine drive electricity and we allocate it to debarking, chipping, refining and pressing using Drexel data for the relative consumption of electricity among these process steps. This leads to assigning 14.9% of electricity for size reduction to debarking; 14.7% for chipping; 20.5% for refining; and 49.9% for pressing. All of the IMIS solid/solid separation end-use (5.7% of electric machine drive) is allocated to screening. The liquid/solid separation end-use is allocated to washing and the fabrication end-use is assigned to forming. Table 5 summarizes the relationship between electricity consumption in each IMIS machine drive end-use and the process steps. Electrochemical - electrochemical end- use is assigned to the bleaching process step to account for electrolytic dissociation of sodium chloride.

Steam and recovered waste heat To distribute steam for process heating among process steps, we use Drexel’s relative steam usage

among the process steps that utilize steam. This yields 22.8% of process steam allocated to digesting, 24.4% to chemical recovery, 12.5% for bleaching, and 40.3% for drying. Consumption of steam for machine drive is distributed among pressing and drying in the same manner previously described in the fuel allocation.

Summary allocation

The allocations discussed in this section are summarized in Table 6. Combining these allocations with the control totals dislayed in Fig. 3 leads to the process-step energy intensities shown in Fig. 6 for each of the 12 process steps in our model.

RESULTS

The process-step energy intensities in Fig. 6, together with the energy intensities of the intermediate- uses and the unallocated end-uses are listed in Table 7. Also shown in Table 7 are the energy intensities from the Drexel model.

Table 5. Allocation of electricity from IMIS machine drive end-uses to process steps (%).

IMIS Machine Drive End-Use

Process-steps Size Liquid-solid Solid-solid Materials

reduction separation separation handling Fabrication Total

Debarking 5.0 0.2 5.2 Chipping 4.9 0.2 5.1 Digesting 2.6 2.6 Washing 11.4 2.6 14.0 Chemical recovery 2.4 2.4 Refining 6.9 2.5 9.4 Bleaching 2.6 2.6 Screening 5.7 12.0 17.7 Forming 12.0 11.4 23.4 Pressing 16.9 0.4 17.3 Drying 0.2 0.2 Pishing 0.1 0.1

33.7 11.4 5.7 37.8 11.4 100.0

An energy process-step m&l for manufacturing paper and paperboard

Table 6. Allocation of energy from end-uses to process steps (%).

611

End-Use

Process steps

Process Heating Process Cooling and Refrigeration Machine Drive

ESctro- Chemical Plocesses

steam Electricity Fuel Electricity steam Electricity Fuel Electricity

Debarking Chipping Digesting Washing Chemical

recovery Refining Bleaching Screening Forming Pressing Drying Finishing

Total

5.2 5.1

22.8 2.6 14.0

24.4 100.0 100.0 2.4 9.4

12.5 2.6 109.0 17.7 23.4 13.3

13.3 17.3 26.7 40.3 100.0 26.7 0.2

0.1

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Net total energy intensity

Our result for the energy intensity of paper/paperboard products is given in Eq. (4) as 24.4 x 106 But/ton. We need to reconcile this value (which we call the net total energy intensity) with the sum of the partial intensities of our model listed in Table 7.

All of the fuel intensity total in Table 7 contributes to the net total energy intensity. However only part of the steam and electricity totals contribute to the net total energy intensity since the energy content of the combustible fuels that are converted on site to steam and electricity before being distributed to end-uses and process steps is already included in the fuel intensity term. To eliminate double counting, we can express the net total energy intensity as:

net total energy intensity = total fuel intensity + net steam intensity + net electricity intensity, (5)

where the total fuel intensity is given in Table 7 as:

total fuel intensity = 22.059 x 106 Btu/ton (6)

and the net steam intensity is given in Fig. 3b as:

net steam intensity = 0.560 . (7)

Since

net electricity = electricity (purchased - sold) + electricity from noncombustible renewables , (8)

Figs. 3a and 3b yield:

net electricity intensity = (2.092 - 0.363 + 0.106) x 106 Btu/ton = 1.836 x lo6 Btu/ton . (9)

Substituting Eqs. (6), (7), and (9) into Eq. (5) yields a net total energy intensity of 24.455, in agreement with the value given in Eq. (4).


: : 2.238 w :

7. Bm I ,o.L%!-,

I 1403 : ____r____)(

I I I I I :

~~_tc.L~

I I I I I :

~t_K!-\

: 0.415, I

I 10. Raing m -O,s41_4 , I------------- I I t I I

I__________________~&~ , I oos5 1 -A--,

I

Fig. 6. Process-step energy intensities for paper/paperboard production (106 BNhon).

Comparison with Drexel model Table 7 lists the Drexel energy intensities for SIC 262113 1, obtained by taking the production

weighted average of intensities for SIC 2621 and SIC 213 1 in 1976 (Drexel base year).? To avoid double counting, we apply EZq. (5). The Drexel total fuel intensity is given in Table 7 as:

total fuel intensity (kxel) = 31.852 x lo6 Btu/ton . (10)

The Drexel model does not consider net steam so

net steam intensity (Drexel) = 0 , (11)

tFrom Ref. 6, paper and paperboard production were 26,613 x lo3 tons and 28,439 x lOa tons, respectively, in 1976.


Table 7. Comparison of energy intensity results with Drexel model (I@ Btulton)

This Model Drexel Model

Steam Electricity Fuel Steam Electricity Fuel

Frocess steps Debarking Chipping Digesting Washing Chemical recovery Refining Bleaching Screening Forming Pressing Drying Finishing

Unallocated end uses Other process use Facility HVAC Facility lighting Facility support Onsite transportation Other non-process use

4.083

4.369

2,238

0.415 7.367

Subtotal 18.662

0.188 0.188

Subtotal 0.376 0.296

Intermediate uses Boiler Conventional electricity generation

Subtotal

Total 19.038

0.164 0.161 0.082 0.444 0.098 0.297 0.131 0.560 0.740 0.547 0.055 0.003 3.304

0.022 0.138 0.114 0.022

0.115

3.715

3.939

1.229 4.199

2.175

0.083 0.030 7.000

1.405 17.313

0.063 0.075

0.320 1.683

0.200 0.174 0.651 0.400 0.500 0.200 0.172 2.912 1.683

0.038 0.025 0.201

20.299 24.599+ 0.154 5.570

20.453 30.169

22.059 17.313 2.912 31.852

0.150 0.145

+ Of this amount, 18.364 x lo6 Btulton is black liquor consumed in a recovery boiler, and is represented in the Drexel model as the chemical recovery process step. We include it as part of the boiler intermediate use rather than as part of the chemical recovery process step to facilitate a more direct comparison with our results.

Neither does Drexel account for electricity sales or electricity generation from noncombustible renewables, so Eq. (8) reduces to net electricity = electricity purchased or net electricity = total electricity - on site electricity generation. Then net electricity intensity = total electricity intensity -on site electricity generation intensity? or

net electricity intensity (Drexel) = (2.912 - 1.857) x lo6 Btu/ton = 0.155 x lo6 Btu/ton . (12)

Substituting Eqs. (lo), ( 1 l), and ( 12) into Eq. (5) yields

net total energy intensity (Drexel) = (31.852 + 0.155) x lo6 Btu/ton = 32.909 x IO6 Btu/ton . (13)

Comparing Eq. (13) to Eq. (4) reveals that our model provides a substantially lower energy intensity than Drexel. This is expected, given the significant improvements in energy efficiency within SIC 26 since 1976. Our result is also lower than the 27.15 x lo6 Btu/ton for SIC 26 calculated using API data for 1991. An indication that API energy intensities tend to be on the high side is available from the

tThe intensity of onsite electricity generation for SIC 2621131 is calculated as a production weighted average of the Dmxel results for SIC 2621 and SIC 2631.

680 Luis Waldo and Barry Hytnan

1976 data where the API value of 35.5 x 106 Btu/ton for SIC 26 is higher than the Drexel energy intensity presented in Eq. (14).

With regard to key differences in the partial energy intensities between our model and Drexel, Table 7 shows we estimate considerably less fuel consumption for Boilers and for Conventional Electricity Generation. This reflects improvements in boiler efficiency and increased use of cogeneration since 1976. On the other hand, increased electrification is reflected in our higher electricity intensities for many process steps.

CONCLUSIONS

Our detailed model of energy consumption in manufacturing paper and paperboard is a major improvement over previous efforts at modeling energy usage patterns in paper and paperboard manufacturing. In particular, this is the first time that a detailed engineering-type process-step model has been calibrated with systematically collected data on energy forms and end-uses (MECS data). Our model is transparent since all data sources, estimation methods, and assumptions have been explicitly described to facilitate updates and refinements.

While we only used 12 process steps in our model compared to the 22 used in the Drexel model, our approach is an improvement over Drexel in that we incorporate non-process end-uses, cogeneration, conventional electricity generation using steam, and waste heat recovery, elements not present in the Drexel model.

There are several opportunities to refine our model. One area for future work is to estimate steam losses through pipe distribution systems rather than allocating all steam produced in boilers to the end- uses. Other opportunities for future work include: accounting for waste paper as a source of fiber, distinguishing between integrated and nonintegrated mills, adding combined-cycle as a congeneration mode, splitting several of the more aggregated process steps (especially chemical recovery) into a set of more specific steps and expanding the energy model to account for generation and disposition of waste products and environmental residuals.

The framework developed here can be used to model energy use in manufacturing other products and in other industries. The key steps for building such models are: (1) Use MECS data supplemented by information from literature and trade associations to construct an establishment-oriented energy end- use model (e.g., Figs. 1,2 and 9 of Ref. 4); (2) Use I-O and business statistics data to convert establishment-oriented energy end-uses to product-oriented energy intensities (e.g., Fig. 3); (3) Select process steps to include in the model (e.g., Fig. 4); (4) Build process-step material flow model (e.g., Fig. 4); (5) Establish relationships between end-use energy intensities and process steps (e.g., Table 6); and (6) allocate end-use energy intensities to process steps (e.g., Table 7).

A major constraint on further model development is the limitation of data sources. For instance, MECS is published every three years and I-O data is published every five years, so it is difficult to establish a common base year for a model. Also, the lag in publishing such data limits how current a model can be; the most recently available data for this study are from the 1991 MECS and the 1987 I-O surveys. Generally, development of these kinds of models requires that government data sources be supplemented by private-sector data sources. In this study, we relied primarily on the IMIS database developed by EPRI and annual product production data from AFPA. Trade associations for other industries may not be able to provide the required data.

Acknowledgement-This research was supported by Battelle Pacific Northwest Laboratory under Task Order 210457 and Bonne- ville Power Administration under Purchase Order DE-AP79-93BPO6172. Preparation of the manuscript was supported under Grant DE-FGO6-89ER-75522 or DE-FGO6-92RL-12451 with the U.S. Department of Energy. By acceptance of this article, the publisher acknowledges the U.S. Government’s right to retain a non-exclusive, royalty-free license in and to any copyright covering this paper.

REFERENCES

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NOMENCLATURE

(E) = the column matrix whose elements are Ei

Ej = energy consumed in industry i e = extracted material flow

(I) = the column matrix whose elements are P

P = energy intensity (energy consumed per unit of physical output) of product p

i = incoming material flow 0 = outgoing material flow

(Q) = the matrix whose elements are g Q$’ = amount of product p produced by

industry i.

Subscripts f=fiber w = water

an energy process-step model for manufacturing paper and paperboard

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