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Life cycle assessment for optimising the level of separated collection

in integrated MSW management systems

L. Rigamonti *, M. Grosso, M. Giugliano

DIIAR Environmental Section, Politecnico di Milano, P.zza Leonardo da Vinci, 32 - 20133 Milano, Italy

a r t i c l e i n f o

Article history:

Accepted 7 June 2008Available online 5 August 2008

a b s t r a c t

This life cycle assessment study analyses material and energy recovery within integrated municipal solid

waste (MSW) management systems, and, in particular, the recovery of the source-separated materials

(packaging and organic waste) and the energy recovery from the residual waste. The recovery of mate-

rials and energy are analysed together, with the final aim to evaluate possible optimum levels of

source-separated collection that lead to the most favourable energetic and environmental results; this

method allows identification of an optimum configuration of the MSW management system.

The results show that the optimum level of source-separated collection is about 60%, when all the mate-

rials are recovered with high efficiency; it decreases to about 50%, when the 60% level is reached as a

result of a very high recovery efficiency for organic fractions at the expense of the packaging materials,

or when this implies an appreciable reduction of the quality of collected materials. The optimum MSW

management system is thus characterized by source-separated collection levels as included in the above

indicated range, with subsequent recycling of the separated materials and energy recovery of the residual

waste in a large-scale incinerator operating in combined heat and power mode.

2008 Elsevier Ltd. All rights reserved.

1. Introduction

Life cycle assessment (LCA), originally developed for assessing

environmental impacts of products, processes and activities with

the so-called cradle to grave approach, has evolved in the last

few years toward extended applications related to a broader range

of human activities involving environmental interactions, such as

waste management, treatment and disposal operations. LCA is

becoming a tool commonly utilised for decisionmaking related to

alternative waste management strategies (Finnveden, 1999;

Rebitzer et al., 2004), but only a few studies have analysed munici-

pal solid waste (MSW) management from a systems perspective

(AEA, 2001; Eriksson et al., 2005; Heilmann and Winkler, 2005;

Profu, 2004; Thorneloe et al., 2005). The main conclusion of allthese studies is that reduced landfilling in favour of increased recy-

cling of energy and materials leads to lower environmental impact

and lower consumption of energy resources. On the basis of this re-

sult, we have analysed, from an energetic and environmental point

of view, materialand energyrecovery within integrated MSW man-

agement systems, with the final aim to evaluate possible optimum

levels of source-separated collection that lead to the most favour-

able energetic and environmental results. Trying thus to identify

an optimum configuration of the MSW management system, this

LCA study analyses together the recovery of source-separated

materials (i.e., the recycling of iron, aluminium, glass, paper, wood

and plastic, and the composting of food waste and green fraction)

and the high efficiency energy recovery from the residual waste

(i.e., the incineration with production of electricity and heat).

2. Methodology

In order to quantify the real energetic and environmental bal-

ance of the recycling of materials source-separated from MSW

and of the energy recovery from the residual waste, the technique

of LCA is used. This means taking into account that any recycling

activity influences the environment by consuming resources and

releasing emissions and waste streams, and by replacing conven-tional products from primary production, i.e., the production from

virgin raw materials. Moreover, the energy recovered from the

residual waste displaces the same quantity of energy produced in

conventional power plants and boilers fuelled with fossil fuels.

Standards ISO 14040 (2006) and ISO 14044 (2006) define the

four basic steps of the assessment procedure, well described and

commented in Rebitzer et al. (2004) and in Pennington et al.

(2004):

a. Goal and scope definition, which includes the preliminary

assumptions about the aim of the study, the functional unit

and the boundaries of the system.

0956-053X/$ - see front matter 2008 Elsevier Ltd. All rights reserved.doi:10.1016/j.wasman.2008.06.005

* Corresponding author. Tel.: +39 02 23996415; fax: +39 02 23996499.

E-mail address: [email protected] (L. Rigamonti).

Waste Management 29 (2009) 934944

Contents lists available at ScienceDirect

Waste Management

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / w a s m a n
mailto:[email protected]://www.sciencedirect.com/science/journal/0956053Xhttp://www.elsevier.com/locate/wasmanhttp://www.elsevier.com/locate/wasmanhttp://www.sciencedirect.com/science/journal/0956053Xmailto:[email protected]


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b. Life cycle inventory (LCI), which focuses on the quantification

of mass and energy fluxes.

c. Life cycle impact assessment (LCIA), where the environmental

impact of the activity is assessed with the use of impact

indicators.

d. Life cycle interpretation, which aims at evaluating possible

changes or modifications of the system that can reduce its

environmental impact.

The Simapro 7 software, developed by PR Consultants (2006a,

b, c), is used for the evaluation of the energetic and environmental

impacts of the various processing steps. Two characterisation

methods have been chosen: the cumulative energy demand

(CED) ( Jungbluth and Frischknecht, 2004) and the CML 2 (CML,

2001). The first one is used to calculate the total energy demand

of the activity under study. In fact, the CED method investigates

the energy use throughout the life cycle of the analysed system,

including direct as well as indirect consumptions of energy due

to, e.g., the production of additives or construction materials. The

CML 2 method, slightly modified in this study, is applied to evalu-

ate the environmental impacts. In particular, the following envi-

ronmental impact categories have been selected:

Global warming potential (GWP), which accounts for the emis-

sion of greenhouse gases; Human toxicity potential (HTP), which addresses a wide range

of toxic substances, including, in this study, the secondary par-

ticulate matter; Acidification potential (AP), which accounts for the emissions of

NOx, SOx and ammonia; Photochemical ozone creation potential (POCP), which accounts

for the substances that cause the photochemical ozone produc-

tion in the troposphere.

Finally, the effects of the variation of the most important input

parameters on the results are evaluated and discussed, and in par-

ticular (Rigamonti, 2007) the role of very high recovery of organicfractions, the effects of the possible decrease of the quality of the

recovered material when very high levels of source-separated col-

lection are pursued, and the effects of assuming different types of

conventional power plants for the evaluation of saved primary

energy.

3. Integrated MSW management systems analysed

Three MSW integrated management systems are analysed

(Fig. 1). They differ from each other in the quantities of waste sent

to material recovery and to energy recovery, based on three differ-

ent scenarios of source-separated collection (Table 1):

Scenario 35%, characterized by a source-separated collection ofabout 35%: this is the current target for Italy (year 2007), despite

the fact that the actual average of source-separated collection of

recyclables and compostable materials in 2005 was equal only

to 24.3% of the total Italian MSW production (APAT-ONR, 2006);

Scenario 50%, characterized by a source-separated collection of

about 50%: this level has been reached in recent years in some

provinces in the North of Italy (APAT-ONR, 2006); Scenario 60%, characterized by a source-separated collection of

about 60%: we have considered this as a reasonable target level

that can be reached in the medium term at the provincial scale

(at least in the North and Centre of Italy).

The composition of gross MSW was calculated based on several

analyses and represents the Italian average (Rigamonti, 2007). The

fractions collected separately are delivered to material recovery

processes, whereas the residual waste is destined to energy recov-

ery. Material recovery includes the recycling of packaging materi-

INCINERATOR:LARGE PLANT ONLY ELECTRICITY (substitution of a power plant fed

with a mix of fossil fuels / coal / natural gas)

LARGE PLANT CHP (substitution of boiler fed with natural gas + power

plant fed with a mix of fossil fuels / coal / natural gas)

SMALL PLANT CHP (substitution of boiler fed with natural gas + power


MSW

Steel

Aluminium

Glass

Paper

Wood

Plastic

RECYCLING(substitution of primary

production)

Green and foodwaste

COMPOSTING(substitution of peat and

mineral fertilizers)

Residual

waste

Source-separated

collection level of:

35%

50% 60%

INCINERATOR:LARGE PLANT ONLY ELECTRICITY (substitution of a power plant fed

with a mix of fossil fuels / coal / natural gas)

LARGE PLANT CHP (substitution of boiler fed with natural gas + power


SMALL PLANT CHP (substitution of boiler fed with natural gas + power


MSW

Steel

Aluminium

Glass

Paper

Wood

Plastic

RECYCLING(substitution of primary

production)

Green and foodwaste

COMPOSTING(substitution of peat and

mineral fertilizers)

Residual

waste

Source-separated

collection level of:

35%

50% 60%

Fig. 1. Integrated MSW management systems analysed.

Table 1

Scenarios analysed: quantity collected for each fraction, expressed in kg per tonne of

gross MSW produced

Fractions Scenario 35% Scenario 50% Scenario 60%

kg tMSW1 kg tMSW

1 kg tMSW1

Paper 103 191 191

Wood 14 16 21

Plastic 29 44 66

Glass and inert material 41 41 48

Metals without Al 8 13 13Aluminium 1 1 3

Food waste 69 115 160

Green waste 52 52 69

Other 31 31 31

Total collected 348 503 601

Total residual waste 652 497 399

L. Rigamonti et al./ Waste Management 29 (2009) 934944 935


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als (iron, aluminium, glass, paper, wood and plastic) and the com-

posting of food waste and green fraction.

4. LCA of material and energy recovery

For the packaging materials, we have assumed that 1 kg of sec-

ondary material (produced from recycled materials) displaces 1 kg

of the corresponding primary material (produced using virgin rawmaterials). In this sense, we do not consider the possible degrada-

tion of the material during the recycling process, which might lead

to the consequence that the quality of the secondary material is

worse than that of the primary material. Moreover, we do not con-

sider that the recycled material can also compete on the market

with materials of other types: for example recycled plastics can re-

place timber or concrete in structural items, as discussed by Ekvall

(2000) and by Ekvall and Finnveden (2001).

The compost obtained from food waste and green fraction is

used as a substitute for peat and mineral fertilizers (AEA, 2001;

Centemero and Caimi, 2002; Eriksson et al., 2005; Finnveden

et al., 2005; Sonesson et al., 2000). Moreover, the application of

compost as organic fertilizer promotes over time a build up of car-

bon in the soil that could prove to be a powerful sink ( Barth andFavoino, 2005). Linzner and Mostbauer (2005) tried to give an esti-

mation of this potential carbon sequestration. They concluded that

the sequestered amount of carbon is 213 or 133 kg CO2 eq. per t of

compost, in the hypothesis that the residual carbon after 50 years

is 40% or 25%, respectively, of the original amount. However, due to

the high uncertainty associated to these values, we have not in-

cluded the carbon sequestration contribution in our analysis.

The residual waste is sent to energy recovery in a waste-to-en-

ergy (WTE) plant. For the energetic and environmental balances,

we have assumed that the electricity produced from the incinera-

tor displaces the same quantity of electricity produced by the ther-

moelectric Italian mix, composed by coal at 20%, fuel oil at 20%,

natural gas at 20% and natural gas in a combined cycle at 40%.

When combined heat and power (CHP) operation is considered,

the heat produced displaces the same quantity of heat generated

by household boilers fed with natural gas (thermal efficiency =

87%).

4.1. LCA of material recovery

4.1.1. Inventory: material flows, energy consumptions and emissions

For the organic waste, data about emissions, energy consump-

tions and material flows have been gathered for the composting

activity and the production of peat and mineral fertilizers. We have

assumed that one can obtain 30 kg of compost starting from 100 kg

of food and green waste (CITEC, 2004), with an electrical consump-

tion of 50 kWh per tonne to be treated (Scaglia et al., 2004). Gas-

eous emissions are treated with biofilters. We have assumed that

34% of the produced compost is used in garden centres in substitu-

tion of peat, 62% in agriculture in substitution of mineral fertilizers

with the same content of nutrients (N, P and K) and 4% in environ-

mental restorations without substituting anything (Centemero,2006). Data about the production of peat and mineral fertilizers

were found in the Ecoinvent database (Swiss Centre for Life Cycle

Inventories, 2004).

For packaging materials, data about emissions, energy con-

sumptions and material flows have been gathered for both the pro-

duction from waste materials and from primary raw materials.

While the latter are easily available from the literature and from

international databases such as Ecoinvent and BUWAL250 (PR

Consultants, 2006d), the former were acquired mainly from direct

contacts with the operators of the most important recycling plants

Table 2

Energy consumptions for materials recycling, expressed per tonne of recycled material (R-material) produced (for wood expressed per m3 of particle board produced and for

plastic expressed per tonne of total plastic)

Steel recycling Energy consumptions per tonne of R-steel produced Source of the datab

Electrical energy (Pre-treatment) 71 kW h Plant

Electrical energy (Melting) 600 kW h Literature

Total energy 671 kW h (=6357 MJ)a

Aluminium recycling Energy consumptions per tonne of R-Al produced

Electrical energy (Pre-treatment) 69 kW h Literature

Electrical energy (Melting) 10 kW h Plant

Thermal energy (Pre-treatment) 845 MJ (from natural gas) Plant

Thermal energy (Melting) 4040 MJ (from natural gas) Plant

Total energy 5633 MJa

Glass recycling Energy consumptions per tonne of R-glass produced

Electrical energy (Pre-treatment) 18.4 kW h Plant

Thermal energy (Melting) 5460 MJ (from fuel oil) Literature


Paper recycling Energy consumptions per tonne of R-pulp producedElectrical energy 7 kW h Literature

Thermal energy 15 MJ (from diesel) Literature

Total energy 81 MJa

Wood recycling Energy consumptions per m3 of particleboard produced


Electrical energy (Production of particleboard) 95 kW h Literature

Thermal energy (Production of particleboard) 239 MJ from fossil fuel + 2147 MJ from wood Literature

Total energy 3627 MJ a

Plastic recycling Energy consumptions per tonne of total plastic


Electrical energy (Recovery) 278 kW h Literature

Thermal energy (Pre-treatment) 451 MJ (from diesel) Literature

Thermal energy (Recovery) 1840 MJ (from natural gas) Literature


a An average electrical efficiency equal to 38% is used for the conversion of kWh in MJ (IPPC, 2006).b Plant: data from direct contacts with the operators of the most important recycling plants located in the North of Italy; literature: data from literature.

936 L. Rigamonti et al./ Waste Management 29 (2009) 934944


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located in the North of Italy. In addition, the reference documents

on best available techniques (BAT), issued by the IPPC Bureau of

the European Union, were utilised as a source of information (IPPC,

2001a, b, c). A brief description of the recycling of each packaging

material is reported in the following paragraphs, including the ba-

sic data about mass balances and energy consumptions.

4.1.1.1. Steel. The reprocessing of scrap ferrous metal is a well-established industry. Households are a significant but relatively

minor source of ferrous scrap, mainly in the form of tin cans. Dur-

ing recycling, these components are first shredded and then a mag-

netic separator is used to remove impurities (typically paper,

plastics and non-ferrous metals) and to obtain separate ferrous

metals, cleaned at 9095% and ready to be sent to a steel smelter.

The selection efficiency is equal to 80%, whereas the electric arc

furnace efficiency, where the actual recycling takes place, is equal

to 84%. Energy consumptions are shown in Table 2; altogether, the

recycling requires 671 kW h per tonne of recycled steel.

The production of steel, both from virgin raw materials and

from scrap, releases air emissions that are taken into account in

the environmental assessment (IPPC, 2001a; ENEA, 2002).

4.1.1.2. Aluminium. Most of the aluminium in the MSW stream de-

rives from beverage cans. Magnetic and eddy current separation

techniques can be employed to effectively remove ferrous metal

from aluminium. The recovered aluminium undergoes a pre-treat-

ment of pyrolysis and then it is melted in a rotary kiln fed with nat-

ural gas. The recycled aluminium is produced in the form of ingots,

which are then sent to dedicated foundry for remelting.

The selection efficiency is equal to 95%, whereas the melting

efficiency is equal to 93%. The energy consumptions of the recy-

cling activities are showed in Table 2.

The production of aluminium, both from virgin raw materials

and from scrap, releases gaseous emissions that are taken into ac-

count in the environmental assessment. In particular, we have

used data from Ecoinvent database (Swiss Centre for Life Cycle

Inventories, 2004) and the reference document on BAT in thenon-ferrous metals industry (IPPC, 2001c) for emissions associated

with primary production. We have used data from a state-of-the-

art Italian plant, Ecoinvent database and ENEA (2002) for emissions

associated with secondary production.

4.1.1.3. Glass. The source-separated glass comes mainly in the form

of food and beverage containers. This fraction includes both col-

oured and clear glass bottles. Glass recycling involves different

activities such as manual selection, shredding, screening, magnetic

and non-magnetic separation to remove impurities and inert mate-

rials (ceramics and gravels) and to obtain a proper size distribu-

tion. The glass cullet is then delivered to a glass manufacturing

plant, where it is used in the production of new glass containers,

together with ordinary virgin raw materials (silica, calcium car-

bonate, sodium hydroxide, additives). The presence of cullet, which

is characterized by a lower melting temperature than virgin raw

materials, allows the glass furnace to be operated at a lower tem-

perature, thus leading to a significant savings of primary energy

(up to 20% when 80% of cullet is utilised in the kiln feeding).The selection efficiency is equal to 94%, while the melting effi-

ciency is equal to 100%. The energy consumptions of the recycling

activities are shown in Table 2. We have assumed that the furnace

would be fed with 83% of glass cullet and 17% of virgin raw mate-

rials, according to the current practice of the reference plants.

The production of glass, both from virgin raw materials and

from cullet, releases air emissions that are taken into account in

the environmental assessment (IPPC, 2001b; Ecoinvent database;

Glass Technology Services Ltd., 2004).

4.1.1.4. Paper. In this study, the production of pulp using recycled

paper is compared to the production of thermo-mechanical pulp

from wood. Virgin and recycled pulps are subsequently processed

in essentially comparable ways, and so this stage was not consid-

ered in the LCA. Moreover, we have not included the phase of

de-inking.

To produce the recycled pulp, the source-separated paper

undergoes a selection process, aimed to remove the impurities

(like pieces of plastic), and then is sent to the pulper, where other

residues are produced (ashes, sand and worn-out fibres). The over-

all activity has an average efficiency of 85.5%; the energy consump-

tions just for the selection are shown in Table 2 (Arena et al., 2004;

AmbienteItalia Comieco, 2003).

It is important to underscore that paper fibres degrade in the

recycling process, so they cannot be reused indefinitely.

4.1.1.5. Wood. Wood separated from MSW is mostly used for the

production of particleboard. With this aim, wood is first shredded,

then it undergoes a magnetic separation and finally it is reducedinto chips. The efficiency of this pre-treatment is equal to 85.5%;

the energy consumptions of the recycling activities are shown in

Table 2 (Fruhwald and Hasch, 1999).

In this study, the production of particleboard from wood

source-separated from MSW is compared with the production of

plywood from virgin material.

4.1.1.6. Plastic. Plastic materials include a wide range of different

polymers. In this study we have considered the mechanical recy-

cling of polyethylene terephthalate (PET), high density polyethyl-

ene (HDPE) and a mix composed by 57% low density

12.25% residues

100 plastic

20% residues

20% MIX

10% HDPE

50% PET

37.75% R-PET (75%)

9% R-HDPE (90%)

12% R- MIX (60%)

selection

recovery

recovery

recovery

Total residues = 41.25%

8% residues

1% residues

12.25% residues

100 plastic

20% residues

20% MIX

10% HDPE

50% PET

37.75% R-PET (75%)

9% R-HDPE (90%)

12% R- MIX (60%)

selection

recovery

recovery

recovery

Total residues = 41.25%

8% residues

1% residues

Fig. 2. Mass balance of plastic recycling.



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polyethylene (LDPE), 35% linear low density polyethylene (LLDPE)

and 8% polypropylene (PP).

The process of plastic recycling consists of separating the mixed

plastic materials in the three fractions, PET, HDPE and the mix,

using mainly near infra-red (NIR) detectors and manual sorting.

Then, each stream of plastic undergoes a series of treatments,

including pre-washing, manual separation, separation by X-ray

and metal detectors, grinding, filtration, washing, flotation, dryingand fine screening. At the end of the process, flakes or granules of

the recycled polymers (R-PET, R-HDPE and R-mix) are obtained.

The mass balance of plastic recycling is shown in Fig. 2. In this

study, we have considered a product called total plastic made of

R-PET (64.3%), R-HDPE (15.3%) and R-MIX (20.4%). The energy con-

sumptions for the production of 1 tonne of total plastic are re-

ported in Table 2 (Arena et al., 2003).

4.1.2. Results: recycling efficiencies

Table 3 summarizes selection and recovery efficiencies of the

materials analysed; the combination of these two values gives

the overall recycling efficiency.

The recycling of glass is the most efficient because, starting

from 100% of source-separated glass, it yields 94% of recycled glass.

It is followed by the recycling of aluminium, which has a yield of

about 88%. Composting is the least efficient material recovery pro-

cess; the yield of this process is only 30%.

4.1.3. Results: cumulative energy demand

The energy balance of material recovery is based on a compar-ison between the consumptions for recycling and those required

for the production from virgin raw materials. In particular, using

the CED characterization method, this consists in subtracting, for

each material, the energy consumption associated with the pro-

duction from virgin raw materials from that required by the recy-

cling processes. Both direct and indirect energy consumptions are

considered.

The results of this operation are shown in Table 4. The main

considerations that can be drawn are:

For all the materials analysed, energy consumption for the virgin

production is higher than for recycling; this means that recy-

cling always allows energy savings. The highest savings is related to the aluminium recycling; this

activity allows a savings of 187,834 MJeq per tonne produced

(corresponding to 165,951 MJeq per tonne collected). The second

process that allows a large energy saving is plastic recycling,

with 72,573 MJeq saved per tonne produced (equal to 42,637

MJeq per tonne collected). If we express the energy savings in relative terms, the recycling

of paper allows the highest savings, equal to 99%; this means

that the production of pulp from recycled paper requires only

1% of the energy necessary for pulp production from wood. This

is due to the fact that the energy consumptions for the growth

and maintenance of the forest and for the production of fibres

from wood are absent in pulp production from recycled paper.

Aluminium and plastic recycling allows significant savings too,

9491%. Finally, glass recycling and composting are the activi-

ties that allow for the lowest energy savings when comparedto the corresponding primary production.

4.1.4. Results: environmental impact indicators

Environmental assessment is performed with the same ap-

proach utilised for energetic balance: for each material, the emis-

sions released during the production from virgin raw materials

are subtracted from the emissions derived from the recycling pro-

cesses. The assessment follows an LCA approach, including both di-

rect and indirect emissions.

Results are reported in Table 5, and lead to the following

considerations:

All the packaging materials show negative values for all theimpact indicators; this means that the collection and recycling

of 1 tonne of each of these materials with its substitution for vir-

gin production is environmentally advantageous. The collection and recycling of aluminium is the process that

allows the highest environmental advantages, for all the ana-

Table 3

Recycling efficiency (found from the c ombination of selection and recovery efficiency)

for the materials analysed

Material Selection efficiency

(% in weight) (A)

Recovery efficiency

(% in weight) (B)

Recycling efficiency

(% in weight) (A B)

Steel 80 84 (melting

furnace)

67.2

Aluminium 95 93 (melting kiln) 88.35

Glass 94 100 94

Paper 85.5 100 85.5

Wood 85.5 100 85.5 (44.5 after

drying)

Plastic 80 73.5 58.75

Food and

green

wastes

80 37.5 (composting) 30

Table 4

Energy savings when recycling instead of producing starting from virgin raw

materials (values expressed: in MJeq per tonne produced, except for that of wood

which is expressed in MJeq per m3 of particleboard produced, as percentage and in

MJeq per tonne source-separated)

Material Saved energy

MJeq per

tonneproduced

% MJeq per

tonnesource-separated

Steel 27,176 81.2 18,275

Aluminium 187,834 93.5 165,824

Glass 6,424 36.1 7,231

Paper (pulp) 42,044 99.4 35,929Wood 29,438a 76.9 23,391

Plastic 72,573 91.4 43,170

Compost (from food

and green wastes)

1,080 41.0 324

a Expressed in MJeq per m3produced.

Table 5

Environmental impact indicators for material recovery (expressed per tonne of source-separated material)

Per 1 source-separated tonne Steel Aluminium Glass Paper Wood Plastic Food and green wastes

Global warming (kg CO2 eq.) 405 9855 722 557 166 1120 26.8

Acidification (kg SO2 eq.) 0.06 52 2.9 3.3 1.2 7.1 +0.07

Human toxicity (kg 1,4-DCB eq.) 247 47001 141 126 93 248 +5.6

Photochemical ozone creation (kg C2H4 eq.) 0.587 2.9 0.185 0.237 0.317 1.2 +0.025

Note: a negative value indicates an advantage for the environment whereas a positive value indicates a disadvantage.



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lysed impact indicators. The benefit in human toxicity is even

two orders of magnitude higher than that of plastic, iron and

paper, the other packaging materials whose recycling results

more convenient. This is mainly due to the avoided emissions

from electrolysis, a basic process in the primary aluminium pro-

duction, which is obviously not required when producing recy-

cled aluminium.

The composting of food waste and green fraction appears neu-tral from an environmental point of view.

4.2. LCA of the energy recovery from residual waste

4.2.1. Inventory and main hypotheses

The residual waste is sent to energy recovery in a waste-to-en-

ergy (WTE) plant, without any further pre-treatment. Strategies

based on the production of refuse derived fuel (RDF) and its subse-

quent combustion in a dedicated plant have not been considered

here because a previous study (Consonni et al., 2005a,b) demon-

strated that this is less efficient than the direct combustion of

residual waste from an energetic, environmental and economic

point of view.

The lower heating value (LHV) of the residual waste was calcu-lated based on the different levels of source separation hypothes-

ised for the various scenarios. This equals 10,249 kJ per kg,

10,090 kJ per kg and 10,393 kJ per kg for scenarios 35%, 50% and

60%, respectively.

We have considered three different WTE plants (Federambiente,

2005; Consonni et al., 2006):

a large plant, designed for a MSW management system of

about 1,200,000 inhabitants, producing only electricity (yearly

average net electrical efficiency = 28.8%) (LP);

a large plant, designed for a MSW management system of

about 1,200,000 inhabitants, operating in CHP mode (LP

CHP). We have assumed that the amount of steam sent to dis-

trict heating equals 30% of the total flow entering the steam

turbine (yearly average net electrical efficiency = 24.6%; yearly

average net thermal efficiency = 19.2%);

a small plant, designed for a MSW management system of

about 200,000 inhabitants, that produces electricity and heat

(SP CHP). We have assumed that the amount of steam sent to

district heating equals 60% of the total flow entering the steam

turbine (yearly average net electrical efficiency = 11.5%; yearly

average net thermal efficiency = 40.2%).

The three WTE plants are assumed to be representative of thestate-of-the-art for combustion, energy recovery and flue gas

treatment. The latter consists of a dry system that starts with

an electrostatic precipitator, followed by a scrubbing with sodium

bicarbonate and activated carbon, a fabric filter and a selective

catalytic reduction reactor fed with ammonia for the control of

nitrogen oxides. Stack concentrations are assumed to be the same

for all the three WTE plants (Table 6), and they comply with the

indication of the BAT Reference Document for waste incineration

(IPPC, 2006). As most recent incinerators have emissions that are

often significantly lower than those imposed by law, values in Ta-

ble 6 are based, rather than on current legislation, on direct mea-

surements carried out on state-of-the-art WTE plants operating in

Italy. Emission factors of fossil and non-fossil CO2 were calculated

based on the actual carbon content of the residual waste, by com-

bining the elementary composition of each fraction with the per-

centage of each fraction present in the residual waste. This actual

carbon content, which has been split between fossil (contained in

plastics) and biogenic (contained in the food waste, green frac-

tion, paper and wood), is equal to 294 kg, 288 kg and 296 kg per

tonne of residual waste of respectively scenario 35%, 50% and

60%.

As stated previously, the electricity produced from the WTE

plant displaces the same amount of electricity produced by the

thermoelectric Italian mix and the heat produced displaces the

same amount of heat generated by household boilers fed with nat-

ural gas. As the assumptions on the saved primary energy are al-

ways an important factor in LCA of waste management systems

(AEA, 2001; Bjrklund and Finnveden, 2005; Eriksson et al.,

2005; Finnveden et al., 2005; Moberg et al., 2005; Profu, 2004;Sonesson et al., 2000; Thorneloe et al., 2005), in the sensitivity

Table 6

Concentrations of the main pollutants at the stack of the WTE plant and emission factors expressed per tonne of residual waste for each scenario

Pollutants Concentrations (11% O2, dry gas) Emission factors

Scenario 35% Scenario 50% Scenario 60%

mg mn3 g t1 g t1 g t1

NH3 2 12.0 11.9 12.1

CO 10 60 59 61

PM10 2 12.0 11.9 12.1

HCl 2 12.0 11.9 12.1HF 0.2 1.20 1.19 1.21

N2O 2 12.0 11.9 12.1

TOC 3 18 18 18

NOX (as NO2) 50 301 296 303

SOX (as SO2) 2 12.0 11.9 12.1

lg mn3

lg t1 lg t1 lg t1

Cd 0.015 90 89 91

Hg 0.425 2555 2518 2576

Pb 0.5 3006 2963 3031

PAH 0.0025 15 15 15

ng I-TEQ m3n ng t1 ng t1 ng t1

Dioxin 0.01 60 59 61

kg t1 kg t1 kg t1

CO2 fossil 421 492 501

CO2 biogenic 656 563 585



7/11

-61

-378

-298-315

160

232 230

-143

-66-77

-413

-332-352

46

120

-194

-116-129

21

95

156

114

-67

8-1

89

-425

-325

-225

-125

-25

75

175


kgCO2eq.pertofresidualw

aste

mix Italy LP

coal LP

NGCC LP

mix Italy LP CHP

coal LP CHP

NGCC LP CHP

mix Italy SP CHP

coal SP CHP

NGCC SP CHP

Fig. 3. Variation of the Global warming indicator as a function of the kind of primary energy displaced by the electricity produced from the WTE plants (LP = large plant;

SP = small plant; CHP = plant operating in combined heat and power mode). Note: a negative value indicates an advantage for the environment whereas a positive value

indicates a disadvantage.

CUMULATIVE ENERGY DEMAND (MJeq t MSW-1

)

Large plant producing

only electricity

Large plant operating in a

CHP way

Small plant operating in a

CHP way

-5929

-9913-11304

-4961

-3765

-3135

-16000

-14000

-12000

-10000

-8000

-6000

-4000

-2000

0

35% 50% 60%

Energy recovery

Material recovery

-5929

-9913-11304

-5934

-4496

-3742

-16000

-14000

-12000

-10000

-8000

-6000

-4000

-2000

0

35% 50% 60%

Energy recovery

Material recovery

-5929

-9913-11304

-5428

-4117

-3429

-16000

-14000

-12000

-10000

-8000

-6000

-4000

-2000

0

35% 50% 60%

Energy recovery

Material recovery

:latoT:latoT:latoT

Scenario 35%: -10890 Scenario 35%: -11863 Scenario 35%: -11357



Fig. 4. Cumulative energy demand indicator for the three MSW management systems analysed and for the three types of WTE plant considered (the electricity produced from

the WTE plant displaces that produced by the thermoelectric Italian mix). Note: A negative value indicates an advantage for the environment whereas a positive valueindicates a disadvantage.



8/11

analysis we have considered two further hypotheses for the substi-

tution of electricity:

casecoal:the electricity producedfrom theWTE plant displaces

the same quantity of electricity produced by a conventional

power plant fed with coal (net electrical efficiency = 36.63%);

case NGCC: the electricity produced from the WTE plant dis-

places the same quantity of electricity produced by a combined

cycle power plant fed with natural gas (net electrical

efficiency = 55%).

Clearly these two cases are representative of the dirtiest and

of the cleanest ways of producing power from fossil fuels.

In the LCA, in addition to the emissions at the stack of the WTE

plants and to the avoided emissions due to the production of en-

ergy, we have considered emissions due to the production of steel

and concrete used in the construction of the plants, of reagents

used in the flue gas cleaning and of additives for inertisation of

fly ashes, together with the avoided emissions related to the recy-cling of steel and aluminium separated from the bottom ashes.

4.2.2. Results: cumulative energy demand and environmental impact

indicators

The CED of the three different types of WTE plants for the three

different scenarios is obviously negative (meaning a savings) due

to the energy produced by the combustion. The most convenient

option is, for all the three scenarios, the combustion of the residual

waste in a large plant operating in combined heat and power

mode.

Table 7

Environmental impact indicators for the three MSW management systems analysed and for the three types of WTE plant considered (the electricity produced from the WTE plant

displaces that produced by the thermoelectric Italian mix)

L arge plant prod ucing only e le ctricity L arge p la nt operat ing in a CHP wa y S ma ll p la nt operat ing in a CHP wa y

M E Total M E Total M E Total

Global warming (kg CO2 eq. tMSW1)

Scenario 35% 138 40 178 138 93 231 138 44 182

Scenario 50% 209 +7 202 209 33 242 209 +4 205

Scenario 60% 257 +2 255 257 31 288 257 0.4 257

Acidification (kg SO2 eq. tMSW1)

Scenario 35% 0.7 1.6 2.3 0.7 1.5 2.2 0.7 0.8 1.5

Scenario 50% 1.1 1.2 2.3 1.1 1.1 2.2 1.1 0.6 1.7

Scenario 60% 1.4 1.0 2.4 1.4 0.9 2.3 1.4 0.5 1.9

Human toxicity (kg 1,4 DCB eq. tMSW1)

Scenario 35% 71 91 162 71 95 166 71 84 155

Scenario 50% 101 74 175 101 77 178 101 69 169

Scenario 60% 183 62 245 183 65 248 183 58 240

Photochemical ozone creation (kg C2H4 tMSW1)

Scenario 35% 0.08 0.09 0.17 0.08 0.10 0.18 0.08 0.08 0.16

Scenario 50% 0.12 0.07 0.19 0.12 0.08 0.20 0.12 0.06 0.18

Scenario 60% 0.15 0.06 0.21 0.15 0.07 0.22 0.15 0.06 0.21

Note: M: contribute of material recovery; E: contribute of energy recovery. A negative value indicates an advantage for the environment whereas a positive value indicates a

disadvantage.

Global warming

-177

-202

-255

-193

-300

-250

-200

-150

-100

-50

0


Scenario 60%

organics

kgCO2eq.pertMSW

Fig. 5. Global warming indicator for the scenario 60% organics in comparison with that of the other scenarios (the WTE plant is the large one and produces only electricitythat displaces that produced by the thermoelectric Italian mix).

Table 8

Scenario 60% organics in comparison with the other scenarios already examined:

values indicate the percentage of collection on the total production of each fraction

Fractions Scenario

35%

Scenario

50%

Scenario

60%

Scenario 60%

organics

Paper 40 74 74 74

Wood 30 35 45 35

Plastic 20 30 45 30

Glass and inert

material

70.5 70.5 83 70.5

Metals without Al 40 61 61 61

Aluminium 14 19 45 19

Food waste 30 50 70 80

Green waste 60 60 80 90

Other 100 100 100 100

Total (% of

collection)

34.8 50.3 60.1 59.7



9/11

Fig. 3 reports the global warming indicator for the three scenar-

ios, the three WTE plants and the three different hypotheses about

the displaced electricity.

We can conclude that, even considering the other environmen-

tal indicators not shown here, the incineration with energy recov-

ery of the residual waste, in comparison with the production of the

same amount of energy from fossil fuels, is environmentally conve-

nient when the replaced electricity is produced from coal or from amix of fossil fuels (20% oil, 20% coal, 20% natural gas and 40% nat-

ural gas used in a combined cycle), whereas it is not environmen-

tally convenient when the displaced electricity is produced from

natural gas in a combined cycle plant.

5. LCA of the integrated MSW management systems

The combination of the LCA results obtained for material recov-

ery with those for energy recovery allows the calculation of the

LCA for the whole MSW management systems analysed. Fig. 4

and Table 7 show the calculated indicators for the three MSW

management systems analysed and for the three types of WTE

plants assumed, when the electricity produced displaces the pro-

duction of the thermoelectric Italian mix.For the three MSW management systems, all the impact indica-

tors have a negative value; this means that the MSW management

systems analysed are energetically and environmentally advanta-

geous in comparison with the conventional method of material

and energy production. In particular, the MSW management sys-

tem more convenient is the one characterized by a source-sepa-

rated collection of 60%.

6. Sensitivity analyses applied to the whole MSW management

system

6.1. The role of very high recovery of the organic fractions

The value of 60% of source-separated collection can be reachedby collecting the different fractions as reported in Table 1, but

there are obviously several other possibilities.

Table 8 reports the percentage of collection of each fraction that

was assumed in the analysis for the scenarios 35%, 50% and 60%

(columns 1, 2 and 3). In column 4, an alternative option of

source-separated collection is described (scenario 60% organics),

characterized by a very high yield of the food and green wastes.

Fig. 5 shows the variation of the global warming indicator

among the different scenarios; the trend is the same even for all

the other indicators, not shown here, whatever type of WTE plant

one considers. The results thus show that the new scenario 60%

organics is located between the scenario 50% and the scenario

35%. This means that a very high collection of the organic fractionsfor their composting is less advantageous than a recovery at aver-

age levels (scenarios 60% and 50%). A source-separated collection

of 50% appears then to be more advantageous than a source-sepa-

rated collection of 60%, when the latter is obtained due to a very

high efficiency recovery for food and green fractions at the expense

of the other materials.

6.2. Possible decrease of the quality of collected materials when very

high levels of source-separated collection are pursued

It is likely that the quality of the collected fractions decreases

when very high levels of source-separated collection are pursued.

This is due to the necessity of collecting a higher amount of mate-

rial, which might include fractions that are more contaminated or

associated with other components and so more difficult to be

recycled.

In this sensitivity analysis, the effects of thedecreaseof thequal-

ity of the collected material are examined for plastic that, among

the six packaging materials considered, is the one characterized

by the highest production of residues during the recycling process.

Table 9 shows, for each scenario analysed, the percentage of collec-

tion of plastic and the hypothesis about the production of residues

during its recycling (phases of selection and recovery). Moreover, a

newscenariois introduced; this is thesame as scenario 60%, butthe

residues produced during the selection of the collected plastic are

increased from 20% to 45%. Consequently, in this case, the total res-

idues from plastic recycling are 60% instead of 41%.

The LCA of this new scenario shows the energetic and environ-

mental benefits of the collection and of the following recycling de-crease (Table 10). In particular, this worsening is between 2%, for

human toxicity indicator, and 12%, for photochemical ozone crea-

tion indicator. Indeed, the scenario 60% plastic is less advanta-

geous than the scenario 50% in the indicators of cumulative

energy demand, acidification and photochemical ozone creation.

This means that reaching a source-separated collection of the

50% is more efficient than reaching a source-separated collection

of the 60%, if the latter implies a decrease of the quality of the col-

lected material.

This is even more true if we consider that this result were ob-

tained assuming the decrease in the quality of the collected plastic

only. The worsening of the impact indicators is more evident if we

assume the decrease in the quality of all the collected materials.

For example, if we assume that the selection efficiency of the pack-aging materials is the one reported in Table 3 reduced by 10% (25%

for plastic), the consequent worsening of the impact indicators is

between 11% (for acidification) and 24% (for human toxicity);

moreover, if the reduction of the selection efficiency is 20% (again

Table 9

Hypothesis on the increase of residues produced in plastic recycling (scenario 60%

plastic)

Scenario % of collection of plastic

(on the total of the

produced plastic) (Table 1)

Residues

from selection

Total recycling

residues (from

selection + recovery)

35% 20 20% 41%

50% 30 20% 41%

60% 45 20% 41%

60% plastic 45 45% 60%

Table 10

Variation of the impact indicators due to the decrease of the quality of the plastic collected (scenario 60% plastic) (the WTE plant is the large one and produces only electricity

that displaces that produced by the thermoelectric Italian mix)

Per t of MSW Scenario 35% Scenario 50% Scenario 60% (A) Scenario 60% plastic (B) D% (B-A)

CED MJ eq 10890 13678 14440 13542 6.2

Global warming kg CO2 eq 177 202 255 231 9.4

Acidification kg SO2 eq 2.31 2.32 2.38 2.23 6.3

Human toxicity kg 1,4-DCB eq 162 175 245 240 2.2

Photochemical ozone creation kg C2H4 eq 0.168 0.188 0.209 0.184 12



10/11

25% for plastic), the worsening of the impact indicators is between

15% (for acidification) and 30% (for human toxicity).

In this sense, a very high source-separated collection of the

packaging materials might be not so effective.

7. Conclusions

Fig. 6 shows, for all the MSW management systems analysed

(scenarios 35%, 50%, 60%, 60% organics, and 60% plastic), thevariation of the CED and of the global warming indicator with

the type of WTE plant considered when the electricity produced

displaces the production of the thermoelectric Italian mix. Scenar-

ios 60% organics and 60% plastic turn out to be worse than sce-

nario 50% for the CED indicator; moreover, scenario 60% organics

is worse than scenario 50% also for the GWP indicator.

We can thus conclude that the combination of the results for

material recovery and those for energy recovery together with

the indications of the sensitivity analysis allows the identification

of the optimum level of source separation, which is:

about 60%, when all the materials are recovered with high

efficiency (70% paper, 4050% wood, plastic and aluminium,

80% glass, 60% iron, 70% food waste, 80% green fraction);

about 50%, when the level of 60% is reached due to a very

high efficiency recovery for food waste and green fraction

(food waste 80% and green fraction 90%) at the expense of

the other materials, or when the level of 60% is reached due

to a high efficiency recovery of all the materials but with a

reduction of the quality of the collected materials.

Under the hypotheses considered, the optimum MSW manage-

ment system is thus characterized by a source separation level as

above indicated, with subsequent recovery of the separated mate-

rials and energy recovery of the residual waste in a large-scale WTE

plant operating in a combined heat and power mode. Moreover,

when a decision has to be made on how much to increase the over-

all source separation level in integrated waste management sys-

tems, the efficiency of energy recovery from residual waste plays

a major role in defining the optimum balancing between material

and energy recovery.

Acknowledgements

The authors wish to thank the operators of the recycling plants

that have supplied most of the primary data utilised in the analysis

and the packaging consortia (CiAl, CNA, CoReVe, Comieco, Corepla

and Rilegno) for their useful advice.

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-10890

-14440

-13678

-15046

-14409

-11863

-14031

-14733

-13451

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-160Scenario 35% Scenario 50% Scenario 60%

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LP LP CHP SP CHP

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