Full text of DOI:10.1080/10473289.2000.10464135

This article was downloaded by: [Illinois Wesleyan University]
On: 06 October 2014, At: 07:56
Publisher: Taylor & Francis
Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer
House, 37-41 Mortimer Street, London W1T 3JH, UK
Journal of the Air & Waste Management Association
Publication details, including instructions for authors and subscription information:
http://www.tandfonline.com/loi/uawm20
A Life-Cycle Inventory Model of Municipal Solid
Waste Combustion
Kenneth W. Harrison a , Robert D. Dumas a , Morton A. Barlaz a & Subba R. Nishtala b
a Department of Civil Engineering , North Carolina State University , Raleigh , North
Carolina , USA
b Center for Environmental Analysis, Research Triangle Institute , Research Triangle
Park , North Carolina , USA
Published online: 27 Dec 2011.
To cite this article: Kenneth W. Harrison , Robert D. Dumas , Morton A. Barlaz & Subba R. Nishtala (2000) A Life-
Cycle Inventory Model of Municipal Solid Waste Combustion, Journal of the Air & Waste Management Association, 50:6,
993-1003, DOI: 10.1080/10473289.2000.10464135
To link to this article: http://dx.doi.org/10.1080/10473289.2000.10464135
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained
in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no
representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose
of the Content. Any opinions and views expressed in this publication are the opinions and views of the
authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should
not be relied upon and should be independently verified with primary sources of information. Taylor
and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses,
damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection
with, in relation to or arising out of the use of the Content.
This article may be used for research, teaching, and private study purposes. Any substantial or systematic
reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any
form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://
www.tandfonline.com/page/terms-and-conditions

TECHNICAL PAPER
Harrison, Dumas, Barlaz, and Nishtala
ISSN 1047-3289 J. Air & Waste Manage. Assoc. 50:993-1003
Copyright 2000 Air & Waste Management Association
A Life-Cycle Inventory Model of Municipal Solid
Waste Combustion
Kenneth W. Harrison, Robert D. Dumas, and Morton A. Barlaz
Department of Civil Engineering, North Carolina State University, Raleigh, North Carolina
Subba R. Nishtala
Center for Environmental Analysis, Research Triangle Institute, Research Triangle Park, North Carolina
ABSTRACT
through com bustion (16%), recycling (23%), and com post-
ing (4%).1 MSW generation is an inevitable consequence
of hum an activity, and its m anagem ent has received in-
creased attention in the past decade as society attem pts to
m an age th is waste in a m an n er th at is both econ om ical
an d protective of th e en viron m en t. Th e n um ber of com -
m un ities th at offer curbside program s for th e separate
collection of recyclables and yard waste has increased, thus
decreasin g th e m ass of waste th at m ust be buried in lan d-
fills or burn ed in com bustion facilities, with con sequen t
m an agem en t of th e resultan t ash . In addition , con sider-
ation of th e en viron m en tal im plication s of waste disposal
is becom in g a factor in th e developm en t an d packagin g
of con sum er products.2
Evaluation of altern ate strategies for m un icipal solid waste
(MSW) m an agem en t requires m odels to calculate en vi-
ron m en tal em ission s as a fun ction of both waste quan -
tity an d com position . A m eth odology to calculate waste
com pon en t-specific em ission s associated with MSW com -
bustion is presen ted h ere. Th e m eth odology con siders
em ission s at a com bustion facility as well as th ose avoided
at an electrical en ergy facility because of en ergy recov-
ered from waste com bustion . Em ission factors, in un its of
kg pollutan t per m etric ton MSW en terin g th e com bus-
tion facility, are calculated for CO2-biom ass, CO2-fossil,
SOx, HCl, NOx, dioxin s/furan s, PM, CO, an d 11 m etals.
Water em ission s associated with electrical en ergy offsets
are also con sidered. Reduction s in en viron m en tal em is-
sions for a 500-m etric-ton-per-day com bustion facility that
recovers en ergy are calculated.
Th e objectives of solid waste m an agem en t (SWM)
program s th at in clude com postin g, recyclin g, an d, in
som e cases, com bustion with en ergy recovery are to de-
crease societal depen den ce on lan dfills an d to con serve
n atural resources th rough m aterial an d en ergy recovery.
Given th e geograph ical variation in th e availability of
recyclin g m arkets an d n um erous oth er location -specific
con sideration s, th e design of SWM strategies th at are
efficien t with respect to m aterial an d en ergy con serva-
tion requires a site-specific evaluation of m ultiple SWM
altern atives. For exam ple, en ergy recovery in a waste-to-
en ergy (WTE) facility m ay represen t an efficien t way to
recover th e en ergy value of m an y recyclables wh ile dis-
placin g som e fossil fuel utilization . Th us, th e ben efits of
WTE facilities sh ould be com pared to th e ben efits of
con vertin g recyclables to n ew products.
INTRODUCTION
Recen t estim ates in dicate th at 208 m illion ton s of m u-
n icipal solid waste (MSW) are gen erated an n ually in th e
Un ited States.1 Approxim ately 57% of th is waste is buried
in a san itary lan dfill, an d th e rem ain der is m an aged
IMPLICATIONS
Life-cycle analysis provides an analytical framework for
comparing the environmental emissions associated with
alternate waste management strategies. This paper pre-
sents a methodology for the development of a life-cycle
inventory of MSW combustion as a function of both waste
quantity and composition. In combination with data on
other solid waste management processes, these results
can be used to evaluate the environmental emissions as-
sociated with alternate integrated solid waste manage-
ment strategies. These combustion life-cycle inventory
results quantify the benefits of recovering electrical en-
ergy from MSW, which will also be useful in comparing
alternate solid waste management strategies.
To evaluate th e en viron m en tal burden s of SWM
strategies, m odels are required th at can calculate th e
en ergy con sum ption an d en viron m en tal em ission s for
each un it process th at m ay be used in th e solid waste
system , in clu din g collection , separation , recyclin g,
treatm en t, an d lan dfill processes. Th ese un it process
m odels th en can be in tegrated in to a larger m odel to
com p are en ergy u se an d en viron m en tal em ission s
Volume 50 J une 2000
Journal of the Air & Waste Management Association 9 9 3

Harrison, Dumas, Barlaz, and Nishtala
across a large n um ber of tech n ically feasible altern ate
SWM strategies.3,4
from waste com bustion was assum ed to be in th e form of
electrical en ergy. Th e em ission s avoided because of re-
duced electricity gen eration by a utility were subtracted
from th e com bustion facility em ission s to calculate th e
overall com bustion LCI.
Th e objective of th is paper is to presen t a m eth odol-
ogy to calculate th e life-cycle in ven tory (LCI) for MSW
com bustion . Th is m eth odology h as also been followed
to calculate th e LCI of oth er solid waste un it processes
for use in an SWM-LCI decision support tool th at is un -
der developm en t. 4 Th is tool h as th e capability to iden -
tify in tegrated SWM strategies th at are optim al with
respect to cost, en ergy con sum ption , or on e of eigh t en -
viron m en tal em ission s.4 Gen eral in form ation on LCI
an alysis is presen ted in th e n ext section , followed by a
description of th e system boun daries an d design basis
for th e com bustion LCI an alysis. Th e m eth odology used
to calculate each em ission an d en ergy recovery is th en
described. Fin ally, typical results are presen ted, alon g
with th e sen sitivity of th ese results to th e fuel m ix wh ich
are assum ed to be offset due to electrical en ergy recov-
ery from MSW com bustion .
Th e com bustion LCI is a fun ction of waste quan tity
an d com position . Th e assum ed waste com position an d
waste properties are presen ted in Table 1, an d results are
presen ted for a 500-m etric-ton -per-day (m Tpd) facility.
Alth ough a m ass burn com bustion facility is assum ed for
th is m odel, th e actual detailed design of th e facility is n ot
critical. As described in th e followin g section , th e m ajor
factors con trollin g en ergy production an d en viron m en -
tal em ission s are th e h eat rate, th e waste com position an d
quan tity, an d th e efficien cy of th e air pollution con trol
(APC) equipm en t. Th e APC equipm en t assum ed to be
presen t in cludes a spray dryer for acid gas con trol, in jec-
tion of activated carbon for m ercury con trol, in jection of
am m on ia (or urea) for NOx con trol by con ven tion al se-
lective n on -catalytic reduction , an d a fabric filter for PM
con trol. After APC, th e flue gas is released to th e atm o-
sph ere. Th e default values used in th is paper are based on
a m odern com bustion facility in com plian ce with MSW
com bustion facility regulation s.8 Th e m ajor in put param -
eters th at ch aracterize th e com bustion system are sum -
m arized in Table 2. Altern ate values m ay be used to
represen t oth er scen arios.
BACKGROUND ON LIFE-CYCLE
INVENTORY ANALYSIS
An LCI represen ts a com pilation of a specific set of in puts
an d outputs associated with a product or process. LCI
an alysis m ay be used to evaluate th e en viron m en tal im -
pacts of a process, to evaluate areas wh ere th e process can
be im proved to m in im ize en viron m en tal em ission s, an d
to com pare a process with an equivalen t process, such as
a com parison of waste-to-en ergy an d lan dfills for MSW
m an agem en t. In th is m an uscript, th e LCI con cept is ap-
plied to MSW com bustion . In th e MSW com bustion LCI,
a set of en viron m en tal em ission s plus en ergy recovery
associated with waste com bustion are quan tified. Th e es-
sen tial feature of LCI m eth odology is an attem pt to th or-
ough ly con sider all aspects of a process. In th e con text of
MSW com bustion , LCI m eth odology requires th at in ad-
dition to an in ven tory of th e direct em ission s from a com -
bustion facility th at recovers en ergy, an in ven tory of th e
avoided em ission s at a power plan t (in cludin g associated
steps for fuel extraction an d tran sportation ) sh ould also
be in cluded. Gen eral in form ation on LCI m eth odology
as it can be applied to MSW m an agem en t5 an d to product
life cycles6 h as been presen ted previously.
Th e com bustion LCI sh ould in clude th e LCI of all
con sum able m aterials associated with facility operation ,
in cludin g th e m aterials used for APC: lim e, am m on ia (or
urea), an d activated carbon . However, wh ile we were able
to acquire LCI data for lim e an d am m on ia, LCI data for
activated carbon were un available.
The total quantity of ash generated is calculated from
the ash content of the MSW plus a fraction of the combus-
tible fraction of each component that does not burn be-
cause of inadequate mixing (Table 2). In addition, the lime
and activated carbon added for APC are included in the to-
tal quantity of ash produced. No differentiation is m ade
between bottom ash and fly ash. The LCI associated with
ash transportation, management, and disposal is considered
separately.12 Man y com bustion facilities recover ferrous
m etal from bottom ash with a m agnet. The com bustion
LCI accounts for the mass of ferrous metal recovered, which
reduces total ash generation. The LCI of ferrous m etal re-
covery is addressed in separate process m odels, which con-
sider its tran sportation to a m an ufacturin g facility an d
account for the difference between the production of fer-
rous m etal from virgin and scrap m aterials.4,13
SYSTEM BOUNDARIES AND DESIGN BASIS
Th e com bustion LCI m odelin g in cludes all activities as-
sociated with operatin g a com bustion facility on ce waste
is received. Th e LCIs of waste collection an d ash m an age-
m ent and disposal were considered in separate m odels that
were integrated into the overall decision support tool. It
was assum ed that em issions associated with construction
of the com bustion plant were not significant; these em is-
sions were not considered in the LCI. Energy recovered
Th e LCI param eters con sidered in clude gaseous an d
liquid releases as well as solid waste an d en ergy con sum p-
tion . Alth ough it is assum ed th at th ere are n o water re-
leases or solid waste production oth er th an ash at th e
9 9 4 Journal of the Air & Waste Management Association
Volume 50 J une 2000

Harrison, Dumas, Barlaz, and Nishtala
Ta ble 1 . Waste composition and physical properties.
MSW
Compositiona
Moisture Contentb
(% by wet weight)
Heating Valueb
(Btu/wet kg)
Ash Contentb
Component
(% by wet weight)
(% of dry weight)
Leaves
5.6
9.3
3.7
6.7
2.1
1.3
1.7
2.2
18.2
0.4
0.5
0.4
9.9
1.5
3.2
0.9
0.5
3.9
1.6
1.0
0.7
4.9
7.5
12.3
60.0
60.0
60.0
6.0
5.0
6.0
6.0
6.0
6.0
2.0
2.0
2.0
2.0
3.0
3.0
2.0
2.0
2.0
2.0
2.0
2.0
70.0
20.0
20.0
5722
5722
14,608
16,590
15,168
13,888
11,850
13,367
14,220
41,111
41,111
41,111
31,022
662c
6.3
6.3
Grass
Branches
6.3
Old newsprint
Old corrugated cardboard
Office paper
1.5
5.0
6.0
Old magazines
3rd class mail
Other paper
23.3
6.0
6.0
HDPE - translucent
HDPE - pigmented
PET
0.4
0.4
0.4
Other plastic
10.0
97.0
100.0
100.0
100.0
98.9
98.9
98.9
100.0
5.0
Ferrous cans
Other ferrous
0
Aluminum cans
Other aluminum
Glass - clear
0
0
185c
Glass - brown
Glass - green
Other glass
185c
185c
0
Food waste
3953
8072
0
Miscellaneous - combustible
Miscellaneous - non-combustible
6.0
100.0
aAdapted from reference 1; bAdapted from reference 7; cEnergy value attributable to labels.
actual com bustion facility m odeled, th ese param eters are
included because such releases are associated with the elec-
trical en ergy offset an d APC m aterial production . All val-
u es rep resen t th e m ass of m aterial released to th e
en viron m en t after treatm en t.
(PCDD/F), PM, CO, an d 11 m etals. Fossil an d biom ass CO2
em ission s are calculated separately to facilitate use of th e
results for an im pact assessm en t in wh ich th ese CO2
sources m ay be treated differen tly. Th e m eth odology used
to calculate an d allocate en ergy recovery an d each em is-
sion is described in th is section .
Th e LCI of waste com bustion is calculated from th e
sum of th e calculated em ission s associated with th e com -
bustion of each MSW com pon en t listed in Table 1. Th e
allocation of the LCI on a com ponent-specific basis is criti-
cal so th at th e in tegrated SWM-LCI m odel can be used to
com pare waste m an agem en t scen arios in wh ich specific
waste com pon en ts are eith er buried in a lan dfill, burn ed
for en ergy recovery, com posted, or recycled. Th e m eth -
odology used to calculate and allocate em issions from each
part of th e com bustion LCI is described in th e followin g
section .
Ta b le 2 . Summary of major default parameters characterizing combustion facility
operation.
Parameter
Value
Units
Reference
Facility capacity factora
Heat rate
1.0
18,000
7.1
no units
Btu/kWh
Lime input
kg lime/mT MSW
kg ammonia/mT MSW
kg carbon/mT MSW
no units
9
Ammonia input
Activated carbon input
Ferrous recovery rate
Unburned waste
1.5
10
11
0.4
90%
5
CALCULATION OF COMBUSTION LCI
% of combustible waste not
burned because of
incomplete combustion
Th e com bustion LCI con siders th e offsets associated with
en ergy recovery, com bustor stack em ission s, an d th e LCI
of the lim e and am m onia consum ed during stack gas treat-
m en t. Th e com bustor stack em ission s calculated in clude
CO2-biom ass, CO2-fossil, SOx, HCl, NOx, dioxin s/furan s
aFor this exercise, it was assumed that the combustion facility was operating at the design
capacity of 500 mTpd 100% of the time. In practice, a 500-mTpd facility would handle
less than 500 mTpd on an annual average because of downtime for maintenance.
Volume 50 J une 2000
Journal of the Air & Waste Management Association 9 9 5

Harrison, Dumas, Barlaz, and Nishtala
En er gy Recover y
Table 4. The energy and em issions associated with the ex-
traction and transportation of fuels for energy generation
are accounted for in the values presented in Table 4. The
sensitivity of overall com bustion LCI results to the NERC
grid selected is explored later in the paper.
Th e efficien cy of en ergy recovery is defin ed by a h eat rate
(Btu/kWh ) th at relates th e en ergy of th e com busted MSW
(Btu) to th e production of 1 kWh electrical en ergy ex-
ported from a WTE facility to th e electrical grid (after th e
h ouse load h as been m et). Th e export of electrical en ergy
from a WTE facility results in a decrease in th e am oun t of
electricity gen erated by a utility an d a correspon din g de-
crease in em ission s from th e utility’s electrical gen eratin g
plants. These avoided utility em issions are subtracted from
th e em ission s associated with waste com bustion to calcu-
late th e overall com bustion LCI. Th e en ergy th at is recov-
ered is calculated as th e sum of th e en ergy attributable to
each waste com pon en t based on its en ergy con ten t an d
th e facility h eat rate (Tables 1 an d 2). Th us, wh ere em is-
sions are avoided, the avoided em issions are allocated only
to th ose waste com pon en ts with en ergy con ten t.
Ta ble 4 . Emissions offsets due to electricity generation in the SERC region.14,a
LCI Parameter
kg/kWh
Gaseous emissions
Biomass CO
1.3E-04
9.5E-01
6.3E-03
7.7E-05
3.6E-03
no data
2.7E-04
1.2E-03
2.1E-03
7.6E-07
1.8E-04
no data
no data
no data
no data
no data
no data
no data
4.1E-08
no data
no data
no data
2
Fossil CO
2
SO
x
HCl
NO
x
PCDD/F
CO
The m ix of fuels used to generate electricity at a utility
and the m ix of fuels for which generation is avoided when
energy is recovered from MSW can be specified by the user.
Default values are provided for the national electrical en-
ergy grid and for the nine North Am erican Electric Reli-
ability Coun cil (NERC) electrical en ergy grids.14 Table 3
presents the default fuel m ixes for four NERC grids. For
this paper, the fuel m ix of the Southeastern Electric Reli-
ability Council (SERC) is used, and it is assum ed that the
com bustion of coal and natural gas are avoided in propor-
tion to their use when energy is recovered from MSW. This
em ission avoidance schem e is based on the assum ption
that new electrical energy generation of the type usually
produced (coal and natural gas) would not occur in response
to new electricity generation from MSW. Based on these
assum ptions, the em issions that are avoided as a result of
energy recovery from MSW com bustion are presented in
PM
CH
4
NH
3
Hydrocarbons
As
B
Cd
Cr
Cu
Hg
Ni
Pb
Sb
Se
Zn
Liquid emissions
Dissolved solids
Suspended solids
8.1E-04
6.7E-04
7.9E-07
1.1E-05
5.1E-05
2.1E-08
3.6E-08
2.9E-12
4.7E-06
3.6E-08
2.7E-12
1.3E-08
1.8E-01
10.6
Ta ble 3 . Fuel mix used for electrical energy generation and energy offset calculation.
b
Energy
Source
Use for Electrical Energy Generationa
Fuels Used to
Calculate Energy
Emission Offsetsb
BOD
c
COD
c
c
c
SERC
ECARc ERCOT
NPCC
Fe
NH
3
Cd
Coal
56.8
0.27
5.26
2.94
28.7
6.03
0
90.91
0.24
0.12
0.34
7.72
0.68
0
46.87
0.05
0.09
38.62
14.03
0.34
0
19.55
0.41
95.1
0
Hg
Distillate oil
Residual oil
Natural gas
Nuclear
P O
5
2
13.58
11.83
37.86
16.73
0.04
0
Cr
4.9
0
Pb
Zn
Hydroelectric
Wood
0
Solid waste
Energy (Btu)
0
aThe fuel mixture used for electrical energy generation.14 Units are percent of total generation
within region; bThe hypothetical composition of the mixture of fuels not used when electrical
energy is recovered from MSW in the SERC region; cSERC, East Central Area Coordination
Agreement, ElectricReliabilityCouncilofTexas, NortheastPowerCoordinatingCouncil(NPCC).
aData are mathematically derived from a series of calculations, and the number of
significant figures likely exceeds the precision of the data; bBOD = biochemical oxy-
c
gen demand; COD = chemical oxygen demand.
9 9 6 Journal of the Air & Waste Management Association
Volume 50 J une 2000

Harrison, Dumas, Barlaz, and Nishtala
Ca r b on Diox id e Em ission Fa ct or
data), an d ch em ical form ulas for specific plastics. Th e
use of eq 1 is illustrated for old corrugated cardboard
(OCC).
Emissions of CO2 (fossil and biomass derived) are calculated
based on a stoichiometric equation for waste combustion
Th e elem en tal an alysis of OCC on a dry an d ash -
free basis is 46.9% C, 6.6% H, 46% O, 0.0009% N, 0.2%
Cl, an d 0.3% S. Th e stoich iom etric form ula for OCC, as
calculated from th is an alysis, is C3.91H6.605O2.88N0.0000643
Cl0.00439S0.009345, wh ich h as a m olecular weigh t of 100.
Based on eq 1, th e CO2 em ission factor for th e com bus-
tion of on e m ole of dry, ash -free OCC is 172.04 g/m ole.
To express th is em ission factor based on th e m an n er in
wh ich OCC is typically received at a com bustion facil-
ity, it m ust be corrected for its m oisture con ten t, its ash
con ten t, an d th e am oun t of OCC th at does n ot burn
because of in com plete com bustion . As presen ted in
Tables 1 an d 2, th e default ash an d m oisture con ten ts
for OCC are both 5%, an d it is assum ed th at 5% of th e
com bustible m aterial does n ot burn because of in com -
plete com bustion . Th us, 85.74 g of dry, ash -free OCC
will burn per 100 g of wet OCC en terin g a com bustion
facility, an d th e em ission factor can be expressed as 147.5
g CO2 em itted per 100 g wet OCC th at en ters th e com -
bustion facility. As OCC origin ates from plan t-derived
carbon , th is OCC is classified as CO2-biom ass. CO2 em is-
sion factors for each waste com pon en t are sum m arized
in Table 5.
C H N S O Cl +α O + 3.78N + wH O →
(
)
c
h
n
s
o
l
2
2
2
h
l
n
cCO2 +
+ w − H2O + sSO2 + 3.78α + N2 +
2
2
2
o
w
h
w
l
+
+α + − c −
−
+
− s O2 + lHCl
2
2
4
2
4
(1)
wh ere α is th e n um ber of m oles of air supplied; w is th e
n um ber of m oles of water en train ed in th e fuel; an d c,
h, n, s, o, an d l are th e n um ber of m oles of each ele-
m en t in on e m ole of th e com bustible fraction of each
waste com pon en t.
Th ere are several assum ption s im plicit in th e use of
eq 1 for calculatin g both CO2 em ission factors an d, as
described below, for calculatin g th e total stack gas flow
rate. In usin g eq 1, it is assum ed th at all fuel-boun d N is
con verted to N2, th at all fuel-boun d S is con verted to
SO2, th at ash is in ert, an d th at th e volum e of CO an d
NOx is n egligible in calculatin g th e total flue gas vol-
um e. Elem en tal an alysis data were adopted from several
sources, in cludin g publish ed values,15 m easured values
for C an d N on som e com pon en ts (Barlaz, un publish ed
Ta ble 5 . Flue gas production and emission factors for CO , SO , HCl, NO , PCDD/F, CO, and PM (kg pollutant/mT waste component as received).a
2
2
x
Controlled Emissions (kg pollutant/mT waste component as received)
Flue Gas
Volume
Biomass CO Fossil CO
SO
HCl
NO (as NO)
PCDD/F
CO
PM
2
2
2
x
MSW
Component
(dscm at 7%
O /mT as received)
2
Leaves
Grass
Branches
Old newsprint
OCC
2569
2388
2569
6082
5637
4899
3365
4261
4900
14,871
14,871
7771
12,932
182
0
0
0
78
78
78
0
6.4E + 2
5.9E + 2
6.4E + 2
1.6E + 3
1.5E + 3
1.2E + 3
8.6E + 2
1.1E + 3
1.2E + 3
0
0
0
0
0
0
0
0
0
2.2E-1
2.0E-1
2.2E-1
5.2E-1
4.8E-1
4.2E-1
2.9E-1
3.7E-1
4.2E-1
1.3E + 0
1.3E + 0
6.7E-1
1.1E + 0
1.6E-2
0.0E + 0
0.0E + 0
0.0E + 0
6.7E-3
6.7E-3
6.7E-3
0.0E+0
1.8E-1
4.7E-1
0
1.0E-1
9.7E-2
1.0E-1
2.5E-1
2.3E-1
2.0E-1
1.4E-1
1.7E-1
2.0E-1
6.1E-1
6.1E-1
3.2E-1
5.3E-1
7.4E-3
0.0E + 0
0.0E + 0
0.0E + 0
3.2E-3
3.2E-3
3.2E-3
0.0E+0
8.5E-2
2.2E-1
0
5.2E-1
4.8E-1
5.2E-1
1.2E + 0
1.1E + 0
9.8E-1
6.8E-1
8.6E-1
9.8E-1
3.0E + 0
3.0E + 0
1.6E + 0
2.6E + 0
3.7E-2
0.0E + 0
0.0E + 0
0.0E + 0
1.6E-2
1.6E-2
1.6E-2
0.0E+0
4.2E-1
1.1E+0
0
3.3E-8
3.1E-8
3.3E-8
7.9E-8
7.3E-8
6.4E-8
4.4E-8
5.5E-8
6.4E-8
1.9E-7
1.9E-7
1.0E-7
1.7E-7
2.4E-9
0.0E + 0
0.0E + 0
0.0E + 0
1.0E-9
1.0E-9
1.0E-9
0.0E+0
2.7E-8
7.1E-8
0
3.2E-1
3.0E-1
3.2E-1
7.6E-1
7.0E-1
6.1E-1
4.2E-1
5.3E-1
6.1E-1
1.9E + 0
1.9E + 0
9.7E-1
1.6E + 0
2.3E-2
0.0E + 0
0.0E + 0
0.0E + 0
9.8E-3
9.8E-3
9.8E-3
0.0E+0
2.6E-1
6.8E-1
0
6.2E-2
5.7E-2
6.2E-2
1.5E-1
1.4E-1
1.2E-1
8.1E-2
1.0E-1
1.2E-1
3.6E-1
3.6E-1
1.9E-1
3.1E-1
4.4E-3
0.0E + 0
0.0E + 0
0.0E + 0
1.9E-3
1.9E-3
1.9E-3
0.0E+0
5.0E-2
1.3E-1
0
Office paper
Old magazines
3rd class mail
Other paper
HDPE - translucent
HDPE - pigmented
PET
Other plastic
Ferrous cans
Other ferrous
Aluminum cans
Other aluminum
Glass - clear
Glass - brown
Glass - green
Other glass
0
2.9E + 3
2.9E + 3
2.1E + 3
2.7E + 3
0
0
0
4.8E+1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1.7E + 1
1.7E + 1
1.7E + 1
0
5.0E + 2
1.3E + 3
0
Food waste
Miscellaneous -combustible
Miscellaneous - non-combustible
2,089
5,457
0
aData are mathematically derived from a series of calculations, and the number of significant figures likely exceeds the precision of the data.
Volume 50 J une 2000
Journal of the Air & Waste Management Association 9 9 7

Harrison, Dumas, Barlaz, and Nishtala
Em ission Fa ct or s for SO2, H Cl, NOx ,
Diox in s/ Fu r a n s, CO, a n d P M
results in 29.35 m oles of flue gas per 100 g of dry ash -free
OCC, or 5637 dscm per m T OCC at stan dard tem perature
an d pressure. Com pon en t-specific flue gas flow rates were
calculated usin g th is m eth odology, an d th e results are
presen ted in Table 5.
Th e em ission s of SO2, HCl, NOx, dioxin s/furan s (PCDD/
F), CO an d PM are assum ed to occur at th e regulated val-
ues presen ted in Table 6. Th ese values m ay overestim ate
actual em ission s, based on th e data for som e m odern WTE
facilities also presen ted in Table 6. Th e m odel user m ay
specify stack gas con cen tration s to reflect an altern ate
scen ario, with em ission s eith er h igh er or lower th an th e
regulated values. Because th e regulated pollutan t em is-
sion values are in un its of m ass per volum e of flue gas at
7% O2, th e volum e of flue gas produced durin g th e com -
bustion of each MSW com pon en t is required.
Th e com pon en t-specific flue gas flow rates (Table 5)
an d th e assum ed em ission factors (Table 6) were th en
used to calculate em ission factors for SO2, HCl, NOx,
PCDD/F, CO, an d PM. Th ese results are sum m arized in
Table 5. Th us, em ission s of th ese pollutan ts are effec-
tively allocated based on th e volum e of flue gas attrib-
uted to a waste com pon en t.
Th e m oles of dry flue gas (G) m ay be calculated by
sum m in g th e term s on th e righ t side of eq 1 (excludin g
H2O), as sh own in eq 2
Met a ls Em ission s Fa ct or s
Em ission factors were developed for 11 m etals, including
As, B, Cd, Cr, Cu, Hg, Ni, Pb, Sb, Se, and Zn. The am ount of
a m etal that volatilizes and escapes through APC equip-
m ent is a com plex function of how the m etal is incorpo-
rated in a m aterial, th e tem peratures attain ed durin g
com bustion, and other physical and chem ical factors. Un-
fortunately, because of our lim ited understanding of these
factors, a m echanistic m odel of com ponent-specific m etal
release could not be developed with sufficient accuracy.
There is one study in which an attem pt was m ade to corre-
late m etals em issions to inlet waste com position.17 How-
ever, relationships between m etals em issions and the input
waste com position were not statistically significant, due in
part to insufficient variation in waste com position during
the study period. Thus, the approach adopted for this model
was selected in consideration of insufficient statistical and
mechanistic information and the desire to do more than
assume that metals emissions vary with mass input rate only.
Th e m eth odology presen ted h ere is based on th e as-
sum ption th at th e un con trolled m ass em ission rate of a
m etal is directly proportion al to its in put to a com bus-
tion facility. First, un con trolled em ission factors are de-
veloped based on published em issions data.17 These m etals
em ission s are th en reduced by treatm en t efficien cies to
calculate m etals em ission s to th e en viron m en t. Th e m eth -
odology is illustrated for Pb in office paper an d th en gen -
eralized to all m etals and all waste com ponents using m etal
an d com pon en t-specific in form ation .
o
h
5l
n
G = + 4.78α −
+
+
(2)
2
4
4
2
Th e m oles of air added (α) are calculated by solvin g for
th e value of α th at results in 7% oxygen in th e flue gas
GO
= 7%
(3)
G
wh ere G0 is th e m oles of oxygen in th e dry flue gas based
on th e stoich iom etric coefficien t for oxygen in eq 1
o
h
l
GO =
+α − c −
+
− s
(4)
2
4
4
Solvin g eqs 3 an d 4 sim ultan eously results in eq 5 for α
α = −0.699o +1.50c + 0.35h − 0.244l +1.50s + 0.053n
(5)
Th us, for an MSW com pon en t with a kn own elem en tal
an alysis, α an d th en G m ay be calculated. For OCC, th is
Ta ble 6 . Regulated and actual emissions for combustion facilities.
Pollutant
Standarda
Actual Performanceb
Unitsc
CO
100
13
26
4.5
4.0
8.0
8.9
136
ppmv
ng/dscm
mg/dscm
ppmv
PCDD/F
PM
In th e em ission s tests reported by Ch an dler,17 office
paper was reported to m ake up 2.69% of th e waste in put
to th e com bustor on a wet-weigh t or as-received basis an d
to con tain 4.5 m g Pb/wet kg. Th us, office paper was re-
spon sible for th e in put of 0.121g of Pb per m T of waste,
an d th e total waste stream was calculated to con tain 188
g Pb/m T. Th e un con trolled em ission s flow rate for Pb was
th en calculated as th e product of th e Pb con cen tration at
the inlet to the APC equipm ent and the com bustion offgas
flow rate at th is poin t. Th e average un con trolled em is-
sion flow rate was 4.8 g Pb/m in , wh ich correspon ds to a
24
SO
30d
25d
150
2
HCl
ppmv
NO
ppmv
x
aReference 8; bPerformance data for combustion facilities with a spray dryer, fabric filter,
selective non-catalytic reduction, and carbon injection;16 cAll concentration levels re-
ported in the table are corrected to 7% O , dry basis; dThe regulations allow a combus-
2
tion facility to either control emissions by a specified percentage (80% for SO , 95% for
2
HCl) or to meet a specific concentration standard. The combustion LCI model is based
on the concentration standard.
9 9 8 Journal of the Air & Waste Management Association
Volume 50 J une 2000

Harrison, Dumas, Barlaz, and Nishtala
Pb em ission of 9.86 g/m T of waste burn ed at a waste in -
put of 0.487 m T/m in over th e 5-day test.
white unglued, and (3) colored unglued. One uncontrolled
em ission factor for ONP was calculated from th e weigh ted
average of Ch an dler’s th ree categories. Fin ally, a rem oval
efficien cy (user in put) was applied to th e release rate for
each m etal to calculate th e m etal release to th e en viron -
m en t th at could be attributed to in dividual waste com -
pon en ts (Table 8).
As described above, th e Pb in put was 188 g Pb/m etric
ton of waste, wh ich m ean s th at 0.052 g Pb were released
from th e waste to th e APC equipm en t per g Pb in itially
presen t in th e waste. As calculated above, th e office paper
con tributed 0.121 g of Pb/m T of waste burn ed, wh ich re-
sults in a Pb em ission factor of 6.34 m g Pb/m T of waste,
or, sin ce a m T of waste con tain ed 26.9 kg of office paper,
a Pb release rate of 234 µg/kg of office paper. Th is value
represen ts th e release rate of Pb from office paper to th e
APC equipm en t. Th e rem ain in g Pb partition s to th e bot-
tom ash . Th is procedure was applied to each m odeled
MSW com pon en t for 11 m etals, an d th e results are sum -
m arized in Table 7.
In the United States, em issions of Cd, Hg, and Pb are
regulated, and the m axim um lim its are 0.02, 0.2, and 0.08
m g/dscm at 7% O2.8 The m ethodology described here has
the potential to predict em issions in excess of these values.
To evaluate the potential for this to occur, the com bustion
LCI was calculated with a num ber of plausible waste m ix-
tures, and in no case were em issions standards violated.
However, the potential for a m odeled em ission in excess of
a regulated value m ust be considered if the regulatory lim it
changes or if additional m etals are regulated.
In th ose cases wh ere th ere was n ot a on e-to-on e cor-
respon den ce between th e waste com pon en ts reported by
Ch an dler17 an d th ose used for th is m odel, som e judgm en t
was used. For exam ple, th ere is on ly on e category for old
n ewsprin t (ONP) in th is study, wh ile ONP was presen ted
in th ree categories by Ch an dler: (1) glued, (2) black an d
Con su m p t ion of Ma t er ia ls for AP C
Lim e, am m onia (or urea), and activated carbon are all used
for APC, an d th eir default con sum ption rates are all quite
Ta ble 7 . Uncontrolled metal emission factors (kg pollutant/mT waste component as received).a
MSW Component
As
B
Cd
Cr
Cu
Hg
Ni
Pb
Sb
Se
Zn
Leaves
1.3E-5
1.3E-5
1.6E-6
1.2E-6
6.4E-3
6.4E-3
2.7E-4
1.1E-4
7.3E-4
7.3E-4
1.3E-4
1.2E-5
5.5E-4
5.5E-4
1.3E-4
2.9E-4
1.5E-4
1.5E-4
9.6E-6
3.9E-6
6.9E-4
6.9E-4
2.0E-4
1.0E-3
4.0E-4
4.0E-4
1.8E-4
5.0E-4
8.1E-3
8.1E-3
3.3E-3
3.4E-4
2.3E-4
2.3E-4
3.4E-5
9.9E-6
1.3E-7
1.3E-7
7.5E-8
1.9E-7
8.5E-3
8.5E-3
2.9E-3
4.8E-4
Grass
Branches
Old newsprint
Old corrugated
cardboard
1.1E-6
2.3E-6
1.4E-6
7.1E-7
1.6E-6
2.5E-6
2.1E-6
6.0E-5
8.8E-7
1.6E-6
1.4E-6
1.6E-6
1.1E-6
1.6E-6
1.6E-6
1.6E-6
1.1E-6
1.6E-6
3.8E-5
2.7E-5
7.4E-5
4.6E-4
1.2E-4
6.0E-5
8.0E-5
2.5E-4
3.6E-4
1.2E-4
2.3E-3
1.2E-4
1.0E-3
1.2E-4
1.2E-4
1.2E-4
1.0E-3
1.2E-4
1.2E-5
1.2E-5
1.2E-5
4.9E-5
4.6E-5
1.8E-5
2.1E-4
4.9E-6
3.5E-4
4.6E-5
6.5E-4
4.6E-5
4.5E-4
4.6E-5
4.6E-5
4.6E-5
4.5E-4
4.6E-5
9.7E-6
1.8E-5
7.0E-6
4.7E-5
8.7E-5
6.2E-5
1.8E-4
3.1E-4
8.1E-5
8.7E-5
9.0E-5
8.7E-5
8.4E-5
8.7E-5
8.7E-5
8.7E-5
8.4E-5
8.7E-5
6.4E-7
1.7E-6
2.1E-6
8.6E-6
4.1E-6
6.7E-6
5.1E-6
9.9E-6
5.1E-6
4.1E-6
6.6E-6
4.1E-6
5.6E-6
4.1E-6
4.1E-6
4.1E-6
5.6E-6
4.1E-6
4.9E-5
1.5E-4
1.5E-4
9.8E-5
2.6E-4
1.5E-4
2.0E-4
2.0E-4
9.8E-5
2.6E-4
9.8E-5
2.6E-4
9.8E-5
2.6E-4
2.6E-4
2.6E-4
9.8E-5
2.6E-4
6.4E-5
1.3E-4
7.3E-5
2.4E-5
1.6E-4
2.2E-4
1.3E-4
1.4E-5
1.2E-4
1.6E-4
1.4E-4
1.6E-4
1.3E-4
1.6E-4
1.6E-4
1.6E-4
1.3E-4
1.6E-4
2.0E-4
2.4E-4
1.3E-4
2.6E-7
1.9E-3
1.6E-4
1.2E-2
1.7E-2
3.2E-3
1.9E-3
3.2E-3
1.9E-3
3.2E-3
1.9E-3
1.9E-3
1.9E-3
3.2E-3
1.9E-3
6.6E-6
1.0E-5
5.3E-6
1.3E-7
3.8E-5
2.1E-4
2.2E-5
2.2E-6
2.3E-4
3.8E-5
7.7E-4
3.8E-5
4.1E-4
3.8E-5
3.8E-5
3.8E-5
4.1E-4
3.8E-5
7.5E-8
4.7E-7
2.1E-7
2.4E-7
2.0E-7
1.9E-7
5.6E-8
1.9E-8
9.4E-8
2.0E-7
9.4E-8
2.0E-7
9.4E-8
2.0E-7
2.0E-7
2.0E-7
9.4E-8
2.0E-7
2.3E-4
4.8E-3
1.9E-4
2.0E-3
1.5E-3
6.4E-4
1.9E-3
4.8E-3
3.3E-3
1.5E-3
2.2E-3
1.5E-3
2.9E-3
1.5E-3
1.5E-3
1.5E-3
2.9E-3
1.5E-3
Office paper
Old magazines
3rd class mail
Other paper
HDPE - translucent
HDPE - pigmented
PET
Other plastic
Ferrous cans
Other ferrous
Aluminum cans
Other aluminum
Glass - clear
Glass - brown
Glass - green
Other glass
Food waste
Miscellaneous -
combustible
Miscellaneous -
non-combustible
8.8E-7
1.1E-6
3.6E-4
1.0E-3
3.5E-4
4.5E-4
8.1E-5
8.4E-5
5.1E-6
5.6E-6
9.8E-5
9.8E-5
1.2E-4
1.3E-4
3.2E-3
3.2E-3
2.3E-4
4.1E-4
9.4E-8
9.4E-8
3.3E-3
2.9E-3
aData are mathematically derived from a series of calculations, and the number of significant figures likely exceeds the precision of the data.
Volume 50 J une 2000
Journal of the Air & Waste Management Association 9 9 9

Harrison, Dumas, Barlaz, and Nishtala
Ta ble 8 . Metals removal efficiencies in air pollution control equipment.
Ta ble 9 . LCI for lime and ammonia production.a,b
Pollutant kg/mT Lime Manufactured
Pollutant
Removal Efficiency (%)
Reference
kg/mT Ammonia
As
B
99.9
76.5
99.7
99.3
99.6
92.7
96.6
99.8
96.7
92.9
99.7
18
17
18
18
18
16
18
18
17
17
17
Gaseous emissions
Biomass CO
4.8E-02
1.3E + 03
3.7E + 00
1.2E-06
1.3E + 00
no data
2.1E + 00
5.6E + 03
8.6E + 01
2.5E-02
9.1E + 00
no data
2
Cd
Cr
Cu
Hg
Ni
Fossil CO
2
SO
x
HCl
NO
x
PCDD/F
CO
Pb
Sb
Se
Zn
3.5E-01
2.7E + 00
9.5E-01
2.0E-04
3.0E-01
1.5E-04
no data
2.8E + 01
5.6E-01
1.7E + 01
4.6E + 00
3.3E + 01
no data
PM
CH
4
NH
3
Hydrocarbons
As
B
no data
sm all (Table 2). Neverth eless, th eir m an ufacture sh ould
be con sidered in th e LCI for com pleten ess. At th e tim e of
th is work, LCI data were available for lim e an d am m on ia
but n ot for activated carbon . Th e LCI for lim e an d am -
m on ia production is sum m arized in Table 9. Th is LCI in -
clu des both th e p rodu ction p rocess an d em ission s
associated with th e production an d con sum ption of fuel
for lim e an d am m on ia m an ufacturin g. All LCI param eters
associated with lim e an d am m on ia con sum ption were
allocated even ly by m ass across all MSW com pon en ts.
Given th e sm all am oun t of activated carbon con sum ed,
th e absen ce of LCI data on activated carbon is n ot ex-
pected to h ave a sign ifican t im pact on th e results. Th e
effect of lim e an d am m on ia on th e overall com bustion
LCI is evaluated with th e m odel results.
Cd
5.0E-05
3.1E-04
no data
no data
Cr
no data
Cu
no data
Hg
4.3E-06
2.1E-04
1.9E-05
7.3E-07
8.0E-07
no data
no data
Ni
no data
Pb
2.5E-05
no data
Sb
Se
no data
Zn
no data
Liquid emissions
Dissolved solids
Suspended solids
BOD
1.1E + 00
4.3E-02
1.2E-03
1.6E-02
1.9E-02
3.9E-03
2.1E-02
5.9E-05
5.2E-05
4.0E-09
1.9E-03
5.0E-05
1.5E-08
1.7E-05
8.3E + 01
5.1E + 06
1.3E + 02
4.2E-01
2.8E + 00
9.0E + 00
2.3E + 00
3.4E-03
1.9E-02
8.8E-02
6.0E-03
4.7E-07
1.7E-03
6.0E-03
5.4E-08
2.1E-03
3.0E + 02
5.1E + 07
COD
Oil
H SO
2
4
Fe
MODEL RESULTS AND SENSITIVITY ANALYSIS
The LCI of a WTE com bustion facility that can process 500
m Tpd is presented in Table 10. Model results are based on
the waste com position and default param eters presented
throughout this paper. The results in Table 10 are divided
into three com ponents: (1) waste com bustion, (2) electri-
cal en ergy offsets, an d (3) APC m aterial con sum ption .
Where no data were available for any one com ponent, the
sum was not reported, to em phasize that the absence of
data does not necessarily m ean that the correct value is
zero. Energy offsets are included in Table 10 as negative
n um bers to in dicate th at th e en ergy offsets represen t
avoided em issions. As a result of these offsets, the total LCI
is negative for several param eters. For air em issions, the
contribution of lim e and am m onia to the overall LCI was
generally m inim al, with the exception of airborne am m o-
nia due to em issions during the am m onia production pro-
cess. For m ost wastewater em issions, the contributions of
lim e and am m onia proved m ore significant.
NH
3
Cd
Hg
P5O
2
Cr
Pb
Zn
Solid waste
Energy (Btu)
aLCI data for lime and ammonia were provided by Franklin Associates and Ecobalance
Inc., respectively; bData are mathematically derived from a series of calculations, and
the number of significant figures likely exceeds the precision of the data.
sufficien t flexibility to represen t a ran ge of scen arios. For
exam ple, if a facility does n ot in ject activated carbon for
Hg con trol, th en th e Hg rem oval efficien cy (Table 8) could
be decreased. Sim ilarly, if the facility to be represented does
not recover energy, then the heat rate could be set to a
very high num ber to trivialize the energy output. To illus-
trate the sensitivity of the m odel to the electrical energy
By ch an gin g user in puts th rough th e spreadsh eet-like
in terface, th e user of th e in tegrated SWM-LCI m odel h as
1 0 0 0 Journal of the Air & Waste Management Association
Volume 50 J une 2000

Harrison, Dumas, Barlaz, and Nishtala
Ta ble 1 0 . Combustion LCI for SERC region.a,b
gen eration fuel m ix, th e com bustion LCI was cal-
culated for th ree addition al electrical en ergy
grids—ECAR, ERCOT, an d th e North east Power
Coordin atin g Coun cil (NPCC)—as described in
Table 3. Th ese region s were selected because th ey
vary widely in th e ratio of coal to n atural gas used
for electrical en ergy gen eration , wh ich in turn
im pacts th e fuels used for en ergy offsets. Th e LCI
results for PM, CO2-fossil, an d Pb based on th e
differen t electrical en ergy gen eratin g region s are
com pared in Figure 1.
Annual Emissions (kg/year)
WTE Facility
Energy Offsets
APC LCI
Total
Gaseous emissions
Biomass CO
1.2E + 8
5.6E + 7
6.3E + 4
3.0E + 4
1.5E + 5
9.6E-3
9.3E + 4
1.8E + 4
2.7E + 2
0
-1.4E + 4
-1.0E + 8
-6.7E + 5
-8.2E + 3
-3.8E + 5
no data
6.5E + 2
3.2E + 6
2.8E + 4
6.8E + 0
4.2E + 3
0.0E + 0
8.1E + 3
3.6E + 3
5.8E + 3
1.3E + 3
9.4E + 3
1.9E-1
1.2E + 8
-4.2E + 7
-5.8E + 5
2.2E + 4
-2.3E + 5
2
Fossil CO
2
SO
x
HCl
NO
x
PCDD/F
CO
To in terpret Figure 1, recall th at for th e sce-
n arios m odeled h ere, electric gen eration offsets
will occur in proportion to th e relative con tribu-
tion of coal an d n atural gas to electricity gen era-
tion in a specified generating region. For exam ple,
th e NPCC region al gen eration com prises 19.6%
coal an d 11.8% n atural gas. Wh ile th is represen ts
on ly 31.4% of total NPCC electricity gen eration ,
com bustion offsets are attributed on ly to th ese
two fuel types. Th erefore, th e offset for 1 kWh of
MSW com bustion gen eration elim in ates em is-
sion s associated with 0.62 kWh gen erated from
coal com bustion an d 0.38 kWh gen erated from
n atural gas com bustion .
-2.9E + 4
-1.3E + 5
-2.2E + 5
-8.1E + 1
-2.0E + 4
no data
7.2E + 4
-1.1E + 5
-2.2E + 5
1.2E + 3
-1.0E + 4
PM
CH
4
NH
3
Hydrocarbons
0
As
1.1E-1
7.2E + 1
7.6E-1
8.2E-1
3.9E + 0
7.4E + 0
2.4E + 0
4.0E + 0
1.7E + 0
3.5E-1
2.0E + 1
B
no data
0.0E + 0
6.4E-2
Cd
no data
Cr
no data
4.0E-1
Cu
no data
0.0E + 0
5.5E-3
Hg
no data
Ni
no data
2.7E-1
Pb
-4.3E + 0
no data
3.1E-2
-2.9E-1
Sb
9.4E-4
Se
no data
1.0E-3
Zn
no data
0.0E + 0
PM offsets are n egative for all region s sh own
Liquid emissions
Dissolved solids
Suspended solids
BOD
in Figure 1, sin ce com bustor PM em ission s per
kWh are quite low com pared to th ose from coal
gen eration . In th e SERC an d ECAR region s, PM
offsets are sim ilar (Figure 1), even th ough th eir
use of coal is quite differen t, at 56.8 an d 90.9%,
respectively. Th is is because th e use of n atural gas
for electricity gen eration is quite low in both re-
gion s (2.9% SERC an d 0.3% ECAR). Th us, wh en
n orm alized to coal an d n atural gas on ly, th e off-
set fractions are nearly 100% coal for both regions.
In addition , PM offsets are stron gly govern ed by
th e coal offset sin ce th e total PM em ission (pre-
com bustion an d com bustion ) is 1.3 kg/kWh for
coal an d on ly 0.002 kg/kWh for n atural gas.
The CO2 offsets for the four electrical genera-
tion regions are m ore nearly equal than the PM
offsets (Figure 1). This is due to the one order of
m agnitude difference in CO2 em issions associated
with 1 kWh of generation from coal (982 kg/kWh)
and natural gas (62.3 kg/kWh) versus the four or-
ders of m agnitude difference in PM em issions for the two
fuel types. The CO2 offsets for the four regions are all nega-
tive, although there are large CO2 em issions associated with
1 kWh of generation from MSW com bustion. The em is-
sions reported in Figure 1 represent CO2-fossil; however, a
significant part of the CO2 em itted from MSW com bustion
is from the oxidation of carbon in paper products, which
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-8.6E + 4
-7.1E + 4
-8.5E + 1
-1.2E + 3
-1.5E + 3
-1.0E + 3
-5.4E + 3
-2.2E + 0
-3.9E + 0
-3.1E-4
3.7E + 4
1.7E + 2
7.7E + 2
2.5E + 3
6.6E + 2
5.9E + 0
3.2E + 1
2.4E + 1
1.7E + 0
1.3E-4
-4.9E + 4
-7.1E + 4
6.9E + 2
1.3E + 3
-8.5E + 2
-1.0E + 3
-5.4E + 3
2.2E + 1
-2.2E + 0
-1.7E-4
COD
Oil
Sulfuric acid
Iron
Ammonia
Cadmium
Mercury
Phosphate
Chromium
Lead
-5.0E + 2
-3.9E + 0
-2.9E-4
3.0E + 0
1.7E + 0
3.5E-5
-5.0E + 2
-2.2E + 0
-2.5E-4
Zinc
-1.3E + 0
-1.9E + 7
-1.1E + 12
5.8E-1
-7.5E-1
Solid waste
Energy (Btu)
1.9E + 5
3.8E + 10
-1.9E + 7
-1.1E + 12
aResults are based on a 500 mT/day facility; bData are mathematically derived from a series of calcula-
tions, and the number of significant figures likely exceeds the precision of the data.
is considered CO2-biom ass and is not included in the fossil
CO2 offset calculations depicted in Figure 1.
For Pb air em ission s, th e tren d for th e ERCOT an d
NPCC region s differs from th e tren d for th e SERC an d
ECAR region s (Figure 1). Th e gaseous Pb em ission from
coal gen eration (4.3 × 10-5 kg/kWh ) is two orders of m ag-
n itude h igh er th an th at for n atural gas gen eration (2.7 ×
Volume 50 J une 2000
Journal of the Air & Waste Management Association 1 0 0 1

Harrison, Dumas, Barlaz, and Nishtala
lim itation s associated with th is ap-
plication of LCI to waste m an age-
m en t. Th is p ap er h as d escribed
several assum ption s related to th e
com bustion process an d electrical
en ergy gen eration associated with
th e com bustion m eth odology. In
addition , wh ere un iform data for a
specific param eter are n ot available
across all SWM altern atives (e.g.,
PCDD/F em ission s from a lan dfill
flare), m an agem en t altern atives
can n ot be com pared on th e basis of
th at param eter.
It m ust also be n oted th at th e
overall LCI does n ot address th e lo-
cation of specific em ission s th at will
im pact local air quality. As presented
in Table 10, th e operation of a WTE
facility results in a n et decrease in
th e em ission s of a n um ber of pol-
lutan ts. However, in m an y cases, th e
n egative values presen ted in Table
10 represen t th e sum of positive val-
ues associated with th e com bustion
facility and larger negative values as-
sociated with electrical en ergy off-
sets. Where the locations of the WTE
facility an d th e avoided electrical
en ergy gen eration are n ot in th e
sam e airsh ed, th e global ben efit of
overall reduced em ission s is in con -
trast to in creased em ission s in th e
airsh ed en com passin g th e WTE fa-
Figure 1 . Sensitivity analysis using different regional electrical grids. Data represent annual emissions
based on the combustion of 500 mTpd.
10-7 kg/kWh ). In con trast to th e lower PM em ission s from
MSW com bustors relative to coal on a per kWh basis, Pb
em ission s from MSW com bustion are relatively h igh such
th at th e two region s th at h ave n early 100% coal gen era-
tion in th e offset fuel defin ition (SERC an d ECAR) h ave
n egative offsets, wh ile th e two region s th at h ave approxi-
m ately 60% coal gen eration in th e offset fuel defin ition
(ERCOT an d NPCC) h ave positive offsets.
cility. Th e relation sh ip between global an d airsh ed-
specific em ission s h as been exam in ed for a series of SWM
strategies, an d it h as been sh own th at SWM strategies rep-
resen tin g global optim um solution s m ay actually decrease
air quality in th e local SWM region /airsh ed of in terest.19
Despite lim itation s associated with use of LCIs, th e
LCI m eth odology represen ts a fram ework for th e evalua-
tion of altern ate SWM strategies in wh ich a n um ber of
em ission s can be con sidered. Th e m eth odology described
h ere will be useful for quan tification of th e em ission s at-
tributable to com bustion an d for un derstan din g h ow th ey
com pare to altern ate processes such as recyclin g an d lan d-
fills for th e m an agem en t of solid waste.
DISCUSSION
Th e m eth odology presen ted h ere for calculation of th e
LCI of a com bustion facility is a useful first step in com -
parin g altern ate SWM strategies. In com bin ation with
process m odels of oth er parts of th e SWM system (collec-
tion , separation , m aterials recyclin g, com posting, and dis-
posal), the com bustion m odel can be used in an overall
SWM-LCI m odel to identify waste m anagem ent alterna-
tives that are optim al with respect to specific environm en-
tal em issions.3 However, it is im portan t to understan d th e
ACKNOW LEDGMENTS
Alth ough th e research described in th is article h as been
fun ded wh olly or in part by th e U.S. En viron m en tal Pro-
tection Agen cy (EPA) un der cooperative agreem en t No.
823052 to th e Research Trian gle In stitute (RTI) with a
1 0 0 2 Journal of the Air & Waste Management Association
Volume 50 J une 2000

Harrison, Dumas, Barlaz, and Nishtala
15. Tillm an , D.A. The Combustion of Solid Fuels & Wastes; Academ ic Press:
San Diego, CA, 1991; pp 236-237.
16. Mem oran dum : Sum m ary of Perform an ce Data, from Colleen Kan e,
U.S. En viron m en tal Protection Agen cy, to Walt Steven son , U.S. En vi-
ron m en tal Protection Agen cy, October 17, 1995.
subcon tract to North Carolin a State Un iversity, it h as n ot
been subjected to th e agen cy’s peer an d adm in istrative
review an d th erefore m ay n ot n ecessarily reflect th e views
of th e agen cy; n o official en dorsem en t sh ould be in ferred.
Th e support of Susan Th orn eloe, th e EPA project officer,
an d Keith Weitz, th e RTI project officer, is ackn owledged.
We also ackn owledge Ecobalan ce In c. for providin g som e
of th e LCI data, an d th e assistan ce of Kath i McBlief with
m an uscript preparation .
17. A.J. Ch an dler & Associates Ltd.; Com pass En viron m en tal In c.; Rigo
& Rigo Assoc., In c.; Th e En viron m en tal Research Group-Un iversity
of New Ham psh ire, Wastewater Tech n ology Cen ter. Waste Analysis,
Sampling, Testing and Evaluation (WASTE) Program: Effect of Waste Stream
Characteristics on MSW Incineration: The Fate and Behaviour of Metals.
The Final Report of the Mass Burn MSW Incineration Study (Burnaby,
B.C.), Vol. 2, Tech n ical Report, April 1993.
18. Em ission Test Report—Field Test of Carbon Injection for Mercury Con-
trol: Cam den Coun ty Mun icipal Waste Com bustor; EPA-600/R-93-
18; U.S. En viron m en tal Protection Agen cy, Office of Air Quality
Plan n in g an d Stan dards: Research Trian gle Park, NC, 1993.
19. Dum as, R.D. Ph .D. Dissertation , Departm en t of Civil En gin eerin g,
North Carolin a State Un iversity, Raleigh , NC, 1999.
REFERENCES
1. Characterization of Municipal Solid Waste in the United States: 1996 Up-
date; EPA/530-R-97-015; U.S. En viron m en tal Protection Agen cy, Of-
fice of Solid Waste: Wash in gton , DC, 1997.
2. Ress, B.B.; Calvert, P.P.; Pettigrew, C.A.; Barlaz, M.A. Environ. Sci.
Technol. 1998, 32, 821-827.
3. Solan o, E.S.; Ran jith an , S.; Barlaz, M.A.; Brill, E.D. In tegrated Solid
Waste Man agem en t Usin g a Life-Cycle Meth odology for Con sider-
in g Cost, En ergy, an d En viron m en tal Em ission s—1. A Math em atical
Model; ASCE J. Environ. Eng. 1999, subm itted for publication .
4. Weitz, K.; Nish tala, S.; Barlaz, M.A.; Th orn eloe, S.A.; Ham , R. Int. J.
Life-Cycle Assess. 1999, 4, 195–201.
5. Wh ite, P.R.; Fran kie, M.; Hin dle, P.; Integrated Solid Waste Manage-
ment: A Life-Cycle Inventory; Ch apm an & Hall, 1995.
6. Life-Cycle Assessm en t: In ven tory Guidelin es an d Prin ciples; EPA/600/
R-92/245; U.S. En viron m en tal Protection Agen cy, Office of Research
an d Developm en t: Wash in gton , DC, 1993.
7. Tch oban oglous, G.; Th eisen , H.; Vigil, S.A.; In tegrated Solid Waste
Man agem en t: En gin eerin g Prin ciples an d Man agem en t Issues;
McGraw-Hill, 1993.
8. Stan dards of Perform an ce for New Station ary Sources, Subpart Eb—
Stan dards of Perform an ce for Large Mun icipal Waste Com bustors for
wh ich Con struction Is Com m en ced after Septem ber 20, 1994 or for
wh ich Modification or Recon struction Is Com m en ced after Jun e 19,
1996; 40 CFR Part 60, Decem ber 19, 1995.
9. Mun icipal Waste Com bustors-Backgroun d In form ation for Proposed
Stan dards: 111(b) Model Plan t Description an d Cost Report; EPA-450/
3-89-27b; U.S. En viron m en tal Protection Agen cy, In dustrial Studies
Bran ch : Research Trian gle Park, NC, 1989.
10. NOx Con trol Tech n ologies Applicable to Mun icipal Waste Com bus-
tion ; EPA-600/R-94-208; NREL/TP-430-6742; U.S. En viron m en tal Pro-
tection Agen cy, Office of Research an d Developm en t: Wash in gton ,
DC, Decem ber 1994.
11. Wh ite, D. Radian Corp. Person al com m un ication , February 1996.
12. Sich , B; Barlaz, M.A. Process Model Documentation: Calculation of the
Cost and Life-Cycle Inventory for Waste Disposal in Traditional, Bioreactor
and Ash Landfills; Departm en t of Civil En gin eerin g, North Carolin a
State Un iversity: Raleigh , NC, 1999.
About the Authors
Kenneth W. Harrison is a doctoral candidate at North Caro-
lina State University (NC State), Department of Civil Engi-
neering, Raleigh, NC 27695; phone: (919) 515-4342; e-mail:
kharriso@eos.ncsu.edu. Robert D. Dumas recently com-
pleted his Ph.D. at NC State, and can be reached at
rddumas@bellsouth.net. Subba Nishtala is a research en-
gineer at Research Triangle Institute, Center for Environ-
mental Analysis, Cornwallis Road, Research Triangle Park,
NC 27709; phone: (919) 541-7448; e-mail: nsr@rti.org.
Morton A. Barlaz (corresponding author) is an associate
professor at North Carolina State University, Department of
Civil Engineering, North Carolina State University, Raleigh,
NC 27695; phone: (919) 515-7676; e-mail: barlaz@unity.
ncsu.edu.
13. Roy F. Weston , In c. Generic Life-Cycle Inventories for Virgin and Recycled
Steel; In tern al draft report prepared for th e Research Trian gle In sti-
tute, Research Trian gle Park, NC, 1999.
14. Dum as, R.D. Energy Consumption and Emissions Associated with Elec-
tric Energy Consumption as Part of a Solid Waste Management Life Cycle
Inventory Model; Departm en t of Civil En gin eerin g, North Carolin a
State Un iversity: Raleigh , NC, 1998.
Volume 50 J une 2000
Journal of the Air & Waste Management Association 1 0 0 3