Life cycle assessment of urban waste management: Energy performances and environmental impacts. The case of Rome, Italy

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Waste Management 28 (2008) 2552–2564 www.elsevier.com/locate/wasman

Life cycle assessment of urban waste management: Energy performances and environmental impacts. The case of Rome, Italy Francesco Cherubini a,*, Silvia Bargigli b, Sergio Ulgiati b b

a Joanneum Research, Elisabethstraße 5, 8010, Graz, Austria Universita` degli Studi di Napoli ‘‘Parthenope”, Dipartimento di Scienze per l’Ambiente, Centro Direzionale, Isola C4, 80133 Napoli, Italy

Accepted 21 November 2007 Available online 29 January 2008

Abstract Landfilling is nowadays the most common practice of waste management in Italy in spite of enforced regulations aimed at increasing waste pre-sorting as well as energy and material recovery. In this work we analyse selected alternative scenarios aimed at minimizing the unused material fraction to be delivered to the landfill. The methodological framework of the analysis is the life cycle assessment, in a multi-method form developed by our research team. The approach was applied to the case of municipal solid waste (MSW) management in Rome, with a special focus on energy and material balance, including global and local scale airborne emissions. Results, provided in the form of indices and indicators of efficiency, effectiveness and environmental impacts, point out landfill activities as the worst waste management strategy at a global scale. On the other hand, the investigated waste treatments with energy and material recovery allow important benefits of greenhouse gas emission reduction (among others) but are still affected by non-negligible local emissions. Furthermore, waste treatments leading to energy recovery provide an energy output that, in the best case, is able to meet 15% of the Rome electricity consumption. Ó 2007 Elsevier Ltd. All rights reserved.

1. Introduction Humanity lives in a closed system, the Earth, where the amount of matter is almost constant and is continuously recycled among Biosphere, Lithosphere, Atmosphere and Hydrosphere by sun-powered and geothermal processes. The Earth is able to exchange a large amount of energy with the surrounding space, but only a little amount of matter. The continuous cycling of matter is therefore fundamental for the survival of the biosphere and humankind. The problem is that many chemicals and materials derived from human activities are not recyclable by natural processes in relatively short times and require additional technological processing. Such transformation processes (landfill, incineration, gasification, or recycling, among others) require energy.

*

Corresponding author. Tel.: +43 3168761327; fax: +43 3168761330. E-mail address: [email protected] (F. Cherubini).

0956-053X/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.wasman.2007.11.011

The present study focuses on the environmental assessment of selected solid waste management options that were proposed for the municipality of Rome, Italy. The city has an area of 1.29E+09 m2, 2.81E+06 inhabitants and a production of Municipal Solid Wastes (MSW) equal to 1.46E+12 g per yr. Pre-sorted wastes are not included in our figures, due to their relatively small amount, although the municipal waste management company, AMA, is displaying increasing efforts towards pre-sorting and recycling of still usable materials. The evaluation of MSW management of Rome is part of a larger project aimed at the study of material and energy performances and dynamics of selected Italian and international cities. Rome, the capital of Italy, is also the larger Italian urban system and was chosen as the starting point and reference case for further investigation of other Italian cities. Most MSW in Rome is currently disposed of in the landfill of Malagrotta (Rome), with no further sorting and/or thermal conversion. This short-sighted practice is likely to lead to exhaustion of the landfill area in a couple

F. Cherubini et al. / Waste Management 28 (2008) 2552–2564

of years and therefore is not sustainable. The aim of this paper is to compare selected waste disposal alternatives, highlighting those able to minimize the amount of waste and maximize material and energy recovery. 1.1. Scope of the assessment: the scenarios The applied life cycle assessment procedure (ISO 14040, 1997) is an internationally standardized method that is considered one of the most effective management tools for identifying and assessing the environmental impacts related to industrial processes and waste management options (Clift et al., 2000). In the present paper, the waste collection step is firstly investigated and, afterwards, the following four different scenarios are analyzed:  Scenario 0: Wastes are delivered to landfill without any further treatment (the present case of Rome).  Scenario 1: Part of the biogas naturally released by the landfill is collected, treated and burnt to produce electricity.  Scenario 2: A sorting plant at landfill site separates the organic and inorganic fractions. Ferrous components are also recovered and sent to recycling. Electricity, biogas (from anaerobic digestion) and compost are then produced.  Scenario 3: Wastes are directly incinerated to produce electricity with no further pre-sorting or pre-treating.

1.2. Zero emission/zero waste strategies Waste management strategies should aim at maximizing energy and material recovery while minimizing the final amount of waste delivered to landfill and the pollution related to all treatment and collection steps. These targets are only reachable by implementing waste minimization policies and waste pre-sorting practices, in conjunction with appropriate technological options within a zero emission/zero waste framework that emulates natural cycles and dynamics. Ecosystems recycle every kind of waste, and the concept itself of ‘‘waste” is no longer appropriate. The products from one component or compartment are always a useful resource for another component or compartment. Ecosystems self-organize in such a way that all available resources are utilized to the maximum possible extent and no unused resources are left.1

1

This may not be true for each individual process over a short time scale, but depends on the spatial and time window of interest as well as on the number of interacting processes. For example, fossil fuels (reduced carbon) can be considered as the waste of photosynthesis, a process where production is slightly larger than consumption (respiration). Instead, on the larger geological scales these materials are also cycled by earth’s convective processes and are used for the global construction of earth crust. By extracting them, humans boost the process by returning carbon to the biosphere faster than it would have been via natural cycles.

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The detritus chain in ecosystems is a clear example of this statement. Human dominated systems should be reshaped according to the same principle, for maximum resource use and zero emissions (Pauli, 1998; Schnitzer and Ulgiati, 2007). Instead, in traditional linear production and consumption systems, resources are processed and passed on to the next step, and unused wastes are released to the environment. As a consequence, the energy and material cost of the product is higher and the efficiency is lower, and a higher emission load is imposed on the environment. Such systems are unlikely to develop maximumpower behaviour and therefore be successful in medium and long-term competition, when resources become scarcer. In an integrated zero emission/zero waste strategy, waste prevention should become a priority. Processes are reorganized and clustered in such a way that unused resources become the raw input to new production patterns. When resources become scarce, this behaviour translates into a selective advantage. While in conventional production the main resources are matter, energy and labour, zero-emission patterns rely to a larger extent on knowledge, i.e., on better information about the needs of and surpluses from each component as well as about technological tools for resource processing and exchange (Gravitis and Suzuki, 1999). 2. Method of analysis (Life cycle assessment – LCA) and system description The methodological framework used in this paper is an extended life cycle assessment, where several evaluation methods are jointly used in order to provide a set of complementary indicators at multiple scales, based on the same set of input data (Ulgiati et al., 2006). 2.1. The methodology for the assessment Generally speaking, all impact assessment methods can be divided into two broad categories: those that focus on the amount of resources used per unit of product (‘‘upstream” methods), and those that deal with the fate of a system’s emissions (‘‘downstream” methods). The former can provide invaluable insights into the hidden environmental costs and inherent (un)sustainability of even seemingly ‘‘clean” systems. On the other hand, downstream methods are often more closely related to the immediate perceived impact on the local ecosystem, and can unveil large differences between systems with similar upstream performance. It must be realised that in no circumstance can a single method be sufficient to provide comprehensive information on an environmental impact assessment, and that LCAs based on only one approach invariably end up providing partial and sometimes even counterproductive indications. A complete LCA should carefully rely on a selection of impact assessment methods, which account for both the

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upstream and the downstream categories. Early efforts of the scientific community in this direction can be recognised in the scientific literature (Ulgiati, 2000; Khan et al., 2002, among others). The Material Flow Accounting method (Schmidt-Bleek, 1993; Hinterberger and Stiller, 1998; Bargigli et al., 2005) aims at evaluating the environmental disturbance associated with the withdrawal or diversion of material flows from their natural ecosystemic pathways. In this method, appropriate material intensity factors (g/unit) are multiplied by each input, respectively, accounting for the total amount of abiotic matter, water, air and biotic matter directly or indirectly required to provide that very same input to the system. The resulting material intensities (MIs) of the individual inputs are then summed together for each environmental compartment (again: abiotic matter, water, air and biotic matter), and assigned to the system’s output as a quantitative measure of its cumulative environmental burden from that compartment (often referred to as ‘‘Ecological Rucksack”). The Embodied Energy Analysis method (Herendeen, 1998; IFIAS, 1974) deals with the gross (direct and indirect) energy requirement of the analysed system, and offers useful insight on the first-law energy efficiency of the analysed system on the global scale, taking into consideration all of the employed commercial energy supplies. In this method, all of the material and energy inputs to the analysed system are multiplied by appropriate oil equivalent factors (g/unit), and the cumulative embodied energy requirement of the system’s output is then computed as the sum of the individual oil equivalents of the inputs, which can be converted to energy units by multiplying by the standard crude oil equivalency factor of 41.860 J/g. The chosen cumulative indicator is the so-called ‘‘Gross Energy Requirement” (GER), expressing the total commercial energy requirement of one unit of output in terms of equivalent Joules of petroleum oil. The Emergy Accounting method (Brown and Ulgiati, 2004; Odum, 1988, 1996) also looks at the environmental performance of the system on a global scale, but this time also taking into account all of the free environmental inputs such as sunlight, wind, and rain, as well as the indirect environmental support embodied in human labor and services, which are not usually included in traditional embodied energy analyses. Moreover, the accounting is extended back in time to include the environmental work needed for resource formation (and consequent renewability). All inputs are accounted for in terms of their solar emergy, defined as the total amount of solar available energy (exergy) directly or indirectly required to make a given product or support a given flow, and measured in solar equivalent Joules (seJ). The amount of emergy that was originally required to provide one unit of each input is referred to as its specific emergy (seJ/unit) or transformity (seJ/J), and can be considered a ‘‘quality” factor which functions as a measure of the intensity of the support provided by the biosphere to the input under study. Likewise,

the specific emergy or transformity of the system’s output is calculated as the sum of the total emergy embodied in the necessary inputs to the system divided by the output mass or exergy. The total emergy requirement thus calculated can be interpreted as an indication of the total environmental service appropriation by the analysed human activity. In particular, while the total non-renewable emergy input to the system under study provides a quantitative estimate of global non-renewable resource depletion, the total renewable emergy requirement is a measure of all of the natural exchange-pool resources diverted from their natural pathways, and that can therefore no longer provide their natural ecosystemic functions. The ecological relevance of the emergy methodology was recently discussed in detail by Brown and Hall, 2004), where the scientific career of its founder, Odum, is illustrated. 2.2. System description The functional unit of the analysis is the amount of waste produced in a year (2003) by the city of Rome. The MSW elementary composition (i.e., the fraction of C, H, N, S and O) assumed for the assessment is derived from Sundqvist et al. (1997), while the waste type composition (i.e., kitchen garbage, paper, plastics. . .) comes from the environmental report of AMA, the company in charge of the disposal of waste in Rome (AMA, 2003). These results, shown in Table 1, can be considered typical for most European cities. As suggested in the ISO 14040 norms, after the goal and scope definition (discussed in the previous section), a detailed life cycle inventory (LCI) needs to be performed, in which mass and energy flows directly involved in the urban waste system are identified (see Table 2). Results from the LCI are then used for the upstream and downstream characterization of impacts (life cycle impact assessment phase – LCIA). If a process step has two or more co-products (i.e., the organic and inorganic waste fraction, as well as ferrous metals, which come out from the sorting plant of Scenario 2), an allocation of the material and energy flows based on the exergy content of the different output is applied. Liquid, solid and gaseous emissions were carefully evaluated and classified into impact categories in order to calculate indicators such as global warming potential (GWP), acidification potential (AP), and eutrophication potential (EP). The greenhouse gases considered as potential contributors to global warming are CO2, CH4, N2O; gases responsible for rain acidification are SO2, NOx, HCl, H2S, and HF; chemical compounds that contribute to aquatic system eutrophication are total-N and total-P (equivalency factors for each impact category are available in LCA, 1997). Within the ‘‘resource depletion” category, indicators such as material intensity factors (MIs) limited to abiotic and water demand, gross energy requirement (GER) and of emergy synthesis were accounted for. The ‘‘collection” step (data source: AMA, 2003) is assessed separately and it is assumed to be the same for

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Table 1 MSW composition Component

wt (%)

Moisture (%)

Ash (%)

C (%)

H (%)

N (%)

S (%)

0 (%)

Kitchen garbage Paper Cardboard Plastics Textiles Rubber Leather Wood Glass Ferrous metalsa Aluminiuma Other

49.5 12.0 6.8 22.9 2.4 0.3 0.3 1.3 1.5 1.9 0.9 0.2

70.0 10.2 5.2 0.2 10.0 10.0 10.0 1.5 2.0 2.0 2.0 3.2

5.0 6.0 5.0 10.0 2.5 78.0 60.0 2.4 98.9 90.5 90.5 68.0

48.0 43.5 44.0 60.0 55.0 10.0 8.0 49.4 0.5 4.5 4.5 26.3

6.4 6.0 5.9 7.2 6.6 2.0 10.0 5.7 0.1 0.6 0.6 3.0

2.6 0.3 0.3 0.0 4.6 0.0 0.4 0.2 0.1 0.1 0.1 0.5

0.4 0.2 0.2 0.0 0.2 0.0 11.6 0.0 0.0 0.0 0.0 0.2

37.6 44.0 44.6 22.8 31.2 10.0 10.0 42.3 0.4 4.3 4.3 2.0

a

Organic content is from coatings, labels, and other attached materials.

Table 2 Life cycle inventory of the main input flows to waste management options; amounts are normalized per g of waste Input flow (per g of waste)

Unit

Collection

REF

Scenario 0

1 Water from wells 2 Water from acqueduct 3 Natural gas 4 Electricity 5 Diesel 6 LPG 7 Gasoline 8 Plastics (black sacks) 9 Paper and cardboard 10 Chemicals 11 Lubricants 12 MSW containers (steel) 13 MSW containers (HDPE) 14 Trucks 15 Light duty vehicles 16 HDPE (pipes) 17 HDPE (landfill walls) 18 Clay (landfill walls) 19 Concrete 20 Steel 21 PVC reactors (H2S removal) 22 Iron sponge (H2S removal) 23 Copper cables 24 Polyethylene film 25 Urea (NH2CONH2) 26 Activated carbon 27 Ca(OH)2 28 CaO 29 Cement 30 Sodium silicate

g g g kWh g g g g g g g g g g g g g g g g g g g g g g g g g g

Useful output 31 Electricitya: gross net 32 Upgraded biogas 33 Compostable matter (d.m.) 34 Ferrous metals

kWh kWh J g g

Waste to landfill 35 Untreated waste 36 Heavy wastes 37 Ashes

g g g

6.48E 0.59 8.08E 6.28E 5.65E 2.10E 7.60E 3.75E 6.48E 7.74E l.31E 3.98E 8.65E 2.31E 5.34E

02 04 06 03 05 05 04 05 05 04 05 05 03 05

A A A A A A A A A A A A A A A

REF

1

REF

9.63E 07 6.24E 04

A A

5.31E 07 6.24E 04

A+C A

l.25E 04 6.06E 05 4.47E 02

B B B

l.25E 04 6.06E 05 4.47E 02

B B B

4.20E 07 l.45E 08 4.89E 07

B B C

8.05E 05 8.00E 05

1.00

2

REF

3

REF

0.10

D+G

0.16

G

l.98E 03 8.16E 05 3.79E 04

G+E D+E E

6.01E 05 6.68E 05 l.57E 04

B G

9.83E 7.26E 6.83E l.77E

06 03 03 03

B B F+H F+H

l.33E 9.80E 6.87E 5.62E

05 03 04 04

B B F F

l.76E l.60E 6.44E l.34E l.72E l.34E 7.25E 8.05E

05 04 04 03 03 02 04 04

G+H G G G G G G G

3.00E 2.50E 3.20E 2.50E l.35E l.50E

03 03 03 02 02 03

G G G G G G

7.67E 04 6.85E 04 2.55E+03 0.12 2.80E 02

6.61E 04 5.94E 04

1.00 3.73E 02 0.12

0.22

A = Rapporto ambientale AMA (2003); B = Sundqvist et al. (1997); C = Kohl and Nielsen (1997); D = Caputo and Pelagagge (2002); E = Berglund and Borjesson (2006); F = Consonni et al. (2005); G = Arena et al. (2003); H = Bjorklund et al. (2001). a The electrical demand of Scenario 1, 2 and 3 is fully provided by the electricity produced by the corresponding scenario.

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the four scenarios. Waste collection in Rome is based on heavy duty diesel-fuelled trucks which pick up the unpre-sorted wastes from large MSW containers located at the sidewalk and/or roadside of the whole city area. The reason why the collection is separately analysed is that it can be significantly different from city to city and therefore might hide the real results of the analysis of waste management strategies. By splitting the collection and the treatment steps, results are more likely to be comparable with and applicable to other urban systems. Usually, the output of a scenario is composed of two types of energy (electricity and/or biogas); we consider that part of this amount is used as a feedback for internal energy consumption within the landfilling/waste treatment facility. Regarding global impact indicators (i.e., GWP and AP), when one of the scenarios has an energy output the net results are shown. Environmental benefits derived from the recycled material (ferrous metals and compostable matter) are not accounted for, due to the uncertainty of available data. Scenario 0: the landfill. Wastes are collected and buried in a monitored landfill. For more information about a landfill system, see Sundqvist et al., 1997. In this system the organic fraction of waste undergoes decomposition in anaerobic conditions, releasing the so-called ‘‘landfill gas”. This is mainly composed of CH4 (58%) and CO2 (41%), but it may also contain traces of H2S, HCl, HF and other chemical compounds. On a yearly basis, a methane production of 140 m3 per ton of landfilled waste is estimated (Sundqvist et al., 1997), generating a CH4 emission of 2.04E+08 m3 at atmospheric pressure and density (2003 data). Fifty percent of the biogas is assumed to be collected by pipes and burnt in flares to convert CH4 into CO2(mainly). Such a CO2 emission from landfill gas flaring is quantified but it is not accounted for in the GWP because it does not have a fossil origin (it comes from the organic fraction, because plastic does not decompose); the remaining 50% of landfill biogas is assumed to be directly released to the atmosphere. Other basic assumptions regarding landfill activities (Scenarios 0 and 1) are:  Three percent of the total sulphur disposed of to landfill in 1 yr is released to atmosphere as H2S (Nielsen and Hauschild, 1998);  The main emissions released from biogas combustion in flares are CO, NO2, HCl, HF (emission factors: 800, 100, 12 and 0.02 mg/m3, respectively (White et al., 1999)) and dioxins (emission factors from USEPA, 1995);  The main emissions freely released from the landfill together with biogas (CH4 and CO2) are CO, HCl and HF (emission factors: 13, 65 and 13 mg/m3, respectively (White et al., 1999));  Heavy metals released to atmosphere are only mercury (Hg) and cadmium (Cd), the most volatiles (Sundqvist et al., 1997);

 Leachate emission (and its composition) is averaged from several data reported by Kylefors, 2003. According to such assumptions, the airborne emissions due to combustion processes directly or indirectly involved in the system are evaluated (as well as for Scenarios 1–3):  Emissions from spontaneous landfill fires (CO2, CO, NOx, and dioxins among others (Sundqvist et al., 1997)); regarding dioxins, HPA and PCB emissions, since they are mostly absorbed to the particle matters, they fall down to the ground close to the point from where they are emitted, and then only 35% of this amount is treated as emission.  Emissions released from the combustion of fossil fuels (natural gas, diesel, gasoline, liquid propane gas): CO2, CO, NOx, PM10, SO2, CH4, N2O (EPA, 1996) and dioxins (USEPA, 1995). Emission factors for transportation fuels can be found in APAT (1999).  Emissions for electricity production required to feed the system; the Italian electric supply mix was considered (coal 14.2%, oil 30.8%, natural gas 34.8%, hydro 16.6%, other renewable 3.6%).  Emissions for production and delivering of the input flows required by the system.  All dioxin and furan emissions are referred to g of 2,3,7,8-TCDD with apposite equivalent factors (USEPA, 1995). In this scenario, the most relevant input flows are clay and earth for landfill walls (Table 2). Scenario 1: landfill with biogas recovery. The biogas naturally released from the landfill is collected (about 50% of the total), treated (in PVC reactors in order to remove H2S with iron sponge) and burnt (in situ) in order to produce electricity. The remaining biogas fraction is burnt in flares (25%) or released to the atmosphere (25%). As mentioned for the previous scenario, also in this case the CO2 released by biogas combustion was not accounted for as contributing to the GWP (however, it was included among the local emissions). The total energy content of the collected biogas is estimated to be 3.12E+09 MJ, thanks to its lower heating value (LHV) equal to 17.73 MJ/m3 (Conte, 2001). The biogas is burnt in turbines with a 28% efficiency to produce 2.43E+08 kWh of electricity per year. Emission factors for the combustion of biogas are: NOx 349.56 mg/m3; CO 120.95 mg/m3; PM10 2.68 mg/m3; SO2 6.83 mg/m3; H2S 0.51 mg/m3; HCl 3.97 mg/m3; and HF 1.00 mg/ m3(Conte, 2001). Material inputs for biogas collection and use can be considered negligible in terms of mass contribution compared to the clay and earth for the landfill walls (as indicated in Table 2). Scenario 2: MSW sorting plant. This scenario (see Fig. 1) relies on a sorting plant (for information on the sorting plant, see Caputo and Pelagagge, 2002) that is able to separate the waste mass into its main components; the organic is separated from the inorganic fraction (the main flows), as

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Fig. 1. Diagram of the main steps involved in Scenario 2.

well as the ferrous metals and the heavy fraction of the waste (such as inerts and building materials) from the rest of the waste. The organic fraction is essentially made of kitchen garbage (about 50% of the original MSW weight) while mainly plastics, paper and cardboard, wood, textiles and rubber constitute the inorganic fraction.2 The organic fraction is then delivered to another plant where, after an enrichment in solid content from 7% to 10% (optimum percentages according to Berglund and Borjesson, 2006), undergoes to anaerobic digestion in order to produce biogas (70% CH4 and 30% CO2), with an average yield of 3.74E+03 MJ/ton of organic waste treated (Berglund and Borjesson, 2006). This means a total biogas production of 2.19E+09 MJ. Afterwards, biogas is upgraded by removing H2S and by increasing the percentage of CH4 up to 97% in order to be used as a substitute for natural gas. The energy demand of this step is equal to the 11% of the energy content of the biogas produced (Berglund and Borjesson, 2006). The digestate, i.e., the residue of the anaerobic digestion that remains inside the reactor, must be treated for removal of pathogenic microorganisms and used as fertilizer. The inorganic fraction of the waste is delivered to an RDF (refuse derived fuel) production plant where 7.83E+08 kg of RDF bricks (mainly made of 41% paper, 24% plastics, 12% cardboard) are produced. RDF bricks are finally burnt in an incineration plant to generate electricity. Generally, it is preferable to burn RDF than untreated wastes. In fact, RDF has a higher heating value, a more homogeneous chemical composition, an easier storage and handling ability and smaller emission factors. The combustion of RDF bricks, having a lower heating value of 17 MJ/kg (Arena et al., 2003), delivers 1.33E+16 J of energy, that is in turn converted to about 1.11E+09 kWh of electricity with an average efficiency of 30%. The emission factors assumed for the combustion of RDF bricks can be found in Consonni et al. (2005). Finally, the heavy 2 Cellulosic material is not inorganic matter, but since it cannot be fermented (cellulose and hemicellulose do not depolymerize in the anaerobic condition required for biogas production), it is stored with the inorganic fraction of the waste to be burnt (via RDF).

fraction of waste and ash (from RDF combustion as well as from flue gas treatment) are disposed of in the landfill. Ferrous metals are recovered and delivered to recycling facilities. For this scenario, the most relevant input flows are the equipment for the flue gas cleaning system (urea, activated carbon, CaO, Ca(OH)2) and the energy consumption for the biogas enrichment (see Table 2). Transportation of the intermediates from one plant to another, and finally to the landfill, was also accounted for. The assumptions made for the transportation are: round trip of 50 km, diesel consumption of 0.125 L/km, truck capacity of 64 tons and average speed of 35 km/h. Scenario 3: direct incineration. Wastes are directly transported to the incineration plant to be burnt in order to recover electricity with no pre-treatment/sorting (further information about incineration plant in Ruth, 1998). Untreated/non-differentiated wastes have a LHV of 8.85 MJ/kg (Arena et al., 2003) and in our case study can generate 12.9 GJ of energy. This energy is converted to 9.67E+08 kWh of electricity at 27% efficiency. The bottom ashes and the flue gas treatment ashes are delivered to the landfill. The most relevant input is the equipment for the flue gas cleaning system (urea, activated carbon, CaO, Ca(OH)2). The transportation of ashes to the landfill was also evaluated, at the same transport conditions of Scenario 2. Emission factors for MSW incineration come from Sundqvist et al., 1997. 3. Results and discussion 3.1. Material flow accounting (MFA) Table 3 shows the MFA performance parameters for the collection step and for each of the different scenarios investigated. The main products of each scenario are listed in the second column. The fourth column indicates the abiotic material intensity of products, i.e., the amount of abiotic matter (minerals, soil, fuel, etc.) degraded or diverted in order to provide that product/service, measured as gab/unitprod. Similarly, the fifth column indicates the total amount of water diverted from its natural course in support of the process (gwater/unitprod). The latter indicator is

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Table 3 Performance indicators according to material flow accounting (MFA) method Process

Producta

Unit

MFA Abiotic MI gab/unit

Water MI gwt/unit

Collectionb

Concentrated waste

g

0.05

1.22

Scenario 0

Landfilled waste

g

0.24

0.03

Scenario 1

Landfilled waste Electricity produced from biogas

g kWh

0.24 1899

0.02 0.82

Scenario 2

Landfilled waste Electricity produced from RDF Biogas (>97% CH4) Ferrous metals g

g kWh g 0.13

0.30 334 1.14 1.00

2.09 2398 8.06

Scenario 3

Landfilled waste Electricity produced from incineration

g kWh

0.36 552

1.04 1578

a Total amount of product is not indicated, because focus is placed on input material flows per unit of output. In each scenario, the amount of landfilled waste as well as its physical–chemical state can be different. b Waste collection is a common phase for all Scenarios. It is therefore evaluated separately, as a preliminary step.

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% Scenario 3

Scenario 2

Scenario 1

0% Scenario 0

becoming increasingly telling in times of water shortage worldwide. The contribution of the collection step must be added to each scenario for complete results. Therefore, Table 3 must be read as follows: to dispose of wastes within Scenario 2, for example, 0.3 g of abiotic materials are used up, i.e., the disposal of 1 g of waste in the city of Rome requires the production, somewhere in the world, of 0.3 g of further material waste. This is an additional ‘‘hypercycle” of waste production that can be only broken by means of appropriate waste prevention policies. Furthermore, Scenario 2 is able to add (or combine) to the waste disposal service, electricity and biogas (>97% CH4) production, exploiting the valuable content of the waste. Waste management options of Scenarios 0 and 1 show similar results for the abiotic material intensities, while Scenarios 2 and 3 are characterized by the highest values. Similarly, the water MI factors represent the water demand of each process, i.e., the amount of water used up to feed the process and provide the service (and that cannot be used elsewhere). These MFA indicators suggest a priority: improving waste disposal and conversion technologies would help in saving significant amounts of water and abiotic matter. Concerning the material intensities for electricity production, 334 g of abiotic matter is required to produce 1 kWh of electric energy in Scenario 2 (and 55 gab for Scenario 3). These values are lower than those for electricity from coal, 5137 gab, and comparable, at least in Scenario 2, to the electricity from oil and natural gas, respectively 349 and 274 gab (Hinterberger and Stiller, 1998). Even the enriched biogas (97.3% CH4) has a material intensity very close to that for natural gas, 1.22 gab (Hinterberger and Stiller, 1998). Fig. 2 complements data from Table 3 by showing the amount of waste delivered to the landfill, as a percentage of total waste collected. Despite the fact that none of the investigated scenarios are able to avoid landfilling, the strongest mass reduction (up to 80% less waste to final disposal) and change in waste composition and reactivity

Fig. 2. Amount of final wastes delivered to landfill for each scenario, as percentage of total waste collected.

takes place in Scenarios 2 and 3. In fact, it is extremely important to point out that only inert or burnt materials which do not undergo further decomposition are landfilled; they will not cause any release of CH4 and other landfill gas to the atmosphere (an idea of their magnitude for untreated waste is given in Section 2.2 – Scenario 0), although they still result in the presence of heavy metals in the leachate. 3.2. Gross energy requirement (GER) The GERs of the analysed scenarios are compared in Table 4, while Table 5 shows the possible contribution of each scenario’s energy output to the energy demand of Rome (city energy requirement: electricity 2.91E+16 J/yr, natural gas 4.51E+16 J/yr, energy for transports 1.38E+17 J/yr; source: Statistical Yearbook of Rome, 2003).

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Table 4 Performance indicators according to GER (gross energy requirement) method Producta

Process

Unit

GER Energy ind (J/unit)

c

Collection

Scenario 0

Landfilled waste b

Concentrated waste

g

720.76

Energy ine (J/unit)

g

53.51

Scenario 1

b

Landfilled waste Electricity from biogas collected Energy output: 288 J/gwaste treated Energy efficiency (Eout/Ein): 13%

g kWh

2.15E+03 2.67E+07

12.67 871.08

Scenario 2

Landfilled wasteb Electricity from RDF Biogas (>97%CH4) Ferrous metals Energy output: 5014 J/gwaste treated Energy efficiency (Eout/Ein): 52%

g kWh g g

9.71E+03 1.38E+07 3.79E+03 2.06E+01

66.80 5.06E+05

Scenario 3

Landfilled wasteb Electricity from incineration Energy output: 2140 J/gwaste treated Energy efficiency (Eout/Ein): 22%

g kWh

9.52E+03 1.60E+07

673.94 1.13E+06

a b c d e

Total amount of product is not indicated, because focus is placed on input energy per unit of product and output energy per unit of waste treated. In each scenario, the amount of landfilled waste as well as its physical-chemical state can be different. Waste collection is a common phase for all Scenarios. It is therefore evaluated separately, as a preliminary step. Including the energy content of the waste. Without the energy content of the waste (for biogas the energy content of the waste is not yet exploited).

Table 5 Energy output and Rome energy demand

Electricity produced (kWh) Biogas produced (J) Electricity out/electrical demand of Romea Biogas (97% CH4) out/gas demand of Rome Possible % of renewable energy in Romeb Energy out/energy for transport in Rome a b

Scenario 1

Scenario 2

Scenario 3

1.17E+08

9.98E+08 3.72E+15 15.47% 8.24% 6.22% 5.30%

8.67E+08

1.81% 2.97% 0.30%

13.44% 4.24% 2.26%

Electricity from hydroelectric plants and other renewable energies not accounted. Including electricity from hydroelectric plants and other renewable sources.

Column 4 of Table 4 indicates that to dispose of 1 g of waste within Scenario 0, about 53.5 J of energy must be used up. In Scenario 2, this value increases to 9.7 kJ, while approximately 14 MJ of energy must be invested in order to generate 1 kWh of electricity, also including as input energy the energy content of the waste itself (RDF, in this case). Since wastes can be assumed as a renewable source and therefore not included as an energy cost, these figures decrease to 66.8 J per g of waste disposed of and to 0.5 MJ per kWh of electricity produced (fifth column of Table 4). In this way, Scenario 1 requires less energy per gram of waste than Scenario 0, thanks to the feedback of electricity produced from the collected biogas. These indicators also put into evidence that Scenario 2 requires about 20% more non-renewable energy (mainly fossil) than Scenario 0 for providing the same service, i.e., the waste disposal, but it is also able to release 5 kJ of energy (electricity and biogas) per g

of waste treated, which can replace an equivalent amount of fossil energy. Therefore, it is important to relate the invested energy to the energy output delivered by the system (the parameter ‘‘energy output” Jout/gwaste treated of Table 4), by means of an energy recovering efficiency index (the ratio between the energy output and the total energy input, ‘‘Eout/Ein” – without including the collection phase). Based on the above data, it is possible to state that Scenario 2 appears as the best waste management option; it produces more than twice the energy output of Scenario 3 and has the highest energy recovery efficiency. The explanation for such a striking result is that this is the only scenario which takes into account both components of waste, the organic one, to produce biogas, and the inorganic one, to produce electricity via RDF combustion. Instead, Scenario 1 only exploits the organic part (landfill gas) and Scenario 3 the inorganic part (direct combustion).

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Table 6 Results of the emergy synthesis method System

Emergy demand with services (seJ/unit)

Emergy demand without services (seJ/unit)

Collection step (gwaste)

1.27E+08

6.25E+07

Scenario 0 (gwaste)

1.58E+08

1.56E+08

Scenario 1: Disposed waste (gwaste) Electricity (kWh)

1.54E+08 5.36E+05

1.52E+08 5.28E+05

Scenario 2: Disposed waste (gwaste) Electricity (kWh) Upgraded biogas (g) Ferrous metals (g)

1.22E+08 2.28E+04 1.66E+04 9.34E+07

1.16E+08 2.24E+04 1.60E+04 6.48E+07

Scenario 3: Disposed waste (gwaste) Electricity (kWh)

1.83E+08 8.56E+04

1.81E+08 8.44E+04

Table 4 also shows that in the present situation of Rome (collection + Scenario 0), the collection step is more energy intensive than landfilling (due to the diesel consumed by trucks); therefore, embodied energy analysis points out a different priority than the one highlighted by MFA: to minimize the fuel consumption of the collection step. Again, this is another proof of the need for simultaneous and integrated application of different methods to the same process, not to hide some aspects of its dynamics. Finally, a comparison among the energy demand for the production of 1 kWh of electricity from different sources can also be performed. The energy requirements per kWh of electricity produced from Scenarios 1, 2 and 3 are shown in the fourth and fifth columns of Table 4; these values are comparable with the energy demand for electricity production by conventional sources, as oil (1.24E+07 J/kWh), coal (1.21E+07 J/kWh), natural gas (9.50E+06 J/kWh) and hydro (4.72E+06 J/kWh) (Frischknecht et al., 2003). Table 5 shows that Scenario 2 could meet an important fraction of Rome energy demand (15.47% of electricity and 8.24% of natural gas) and would contribute to reach a target of 6.22% of total city energy consumption (electricity, heating and transport) met by means of renewable sources (also including the contribution of hydroelectricity). If only the transport sector is taken into consideration, its renewable energy fraction could be equal to 5.3%, very close to the EU target of 5.75%, which must be achieved by the year 2010. This seems to be the only way to meet such a target without importing palm oil from Asia or bioethanol from Brazil, given the low production of biofuels in Italy and their very difficult (if not impossible) implementation in the short term. 3.3. Emergy synthesis Table 6 shows results from emergy synthesis. The indicator chosen (among others available) is the ‘‘emergy inten-

sity”, i.e., the demand for direct3 and indirect4 environmental support per unit of waste treated or unit of electricity generated. The emergy cost per gram of waste collected is much lower than the cost per gram of waste processed, in each of the four scenarios investigated. This is because of the relatively low emergy demand for machinery and fuel compared to the much larger demand for landfill construction (clay, concrete) in Scenarios 0 and 1, as well as for power machinery in Scenarios 2 and 3. However, since emergy also accounts for the environmental support to economic factors, the collection step is the one with the largest emergy investment (labor of drivers and services for fuel). Scenario 2 has the lower specific emergy per unit of disposed waste because it reduces the amount of waste sent to the landfill, and as a consequence a much smaller landfill is required. However, the emergy cost for the several disposal systems is on the same order of magnitude, and the different performance of the four scenarios is mainly based on the quantity and quality of co-products they are able to supply. The specific emergy of electricity produced can be compared to that of common fossil fuel plants and hydro (Brown and Ulgiati, 2004), as shown in Fig. 3. Emergy synthesis clearly highlights the benefit of recycling. In fact, by assigning zero emergy (i.e., zero additional environmental support) to the waste as such (Brown and Ulgiati, 2004), the emergy cost to be accounted for is only related to the additional effort for collection and processing. Due to the fact that the emergy cost of recycled material is low compared to the emergy cost of new purchased input flows, the emergy intensities of the electricity produced in Scenarios 2 and 3 are the lowest, even compared with the emergy intensity of hydro-electricity. Therefore, recycling is a rewarding practice requiring the least environmental support. 3 4

That directly goes into the product/service or its manufacturing. That makes the input available to be exploited by the process.

F. Cherubini et al. / Waste Management 28 (2008) 2552–2564 6.E+05

Table 8 Comparison among airborne emissions at a local scale

5.E+05

Specie (g)

Seen. 0

Seen. 1

Seen. 2

Seen. 3

CO2 CO NOx PM10 SO2 CH4 N20 HC1 HF H2S Hg Pb Cd Cu Zn Ni Cr Dioxins TCDDeq HPA

3.15E+11 1.60E+08 2.45E+07 1.13E+05 1.13E+08 7.55E+10 n.a. 4.80E+07 4.58E+06 1.60E+08 2.81E+01 5.54E+02 3.51E+00 3.53E+02 9.07E+02 3.87E+01 1.00E+02 0.24 1.01E+02

3.95E+11 7.38E+07 6.27E+07 5.02E+05 1.14E+08 3.78E+10 5.27E+03 2.75E+07 8.10E+05 8.02E+07 2.81E+01 5.54E+02 3.51E+00 3.53E+02 9.07E+02 3.87E+01 1.00E+02 0.35 1.01E+02

6.51E+11 3.92E+07 5.43E+08 7.83E+06 3.13E+07 1.30E+05 2.35E+07 2.74E+07 2.74E+06 n.a. 3.92E+04 3.88E+05 3.92E+04 n.a. n.a. n.a. n.a. 0.19 n.a.

1.44E+12 2.11E+09 1.09E+09 2.60E+07 8.10E+08 2.01E+04 1.17E+08 1.61E+08 n.a. n.a. 1.46E+06 7.81E+04 4.81E+05 4.81E+04 1.24E+05 4.90E+03 1.31E+04 1.38 1.38E+04

4.E+05 SeJ/J

2561

3.E+05 2.E+05 1.E+05

Hydro

Nat. gas

Oil

Coal

Scen. 3

Scen. 2

Scen. 1

0.E+00

Fig. 3. Comparison among specific emergies (which reflect the environmental support) for the production of electricity using different sources.

3.4. Emissions at the global and local scales The environmental performances of each scenario (expressed as global warming potential, acidification potential, eutrophication potential and dioxin emission) are depicted in Table 7. Such values refer to the larger global scale, while Table 8 shows the estimated airborne emissions at the plant local scale. The results of Table 7 are calculated according to a ‘‘netemission” approach: ‘‘Total emission of each scenario” minus ‘‘Avoided emissions thanks to the use of the energy output of that scenario”. For Scenario 0, net and gross emissions coincide because no useful outputs are provided. Instead, if electricity is produced, we consider that it replaces the electricity derived from the Italian electric grid while, as far as the production of biogas (>97% CH4) is concerned, a fraction of it replaces the diesel fuel required by the collection trucks (9%) and the rest (91%) is used as a substitute of natural gas. It is also noteworthy that the impacts of Scenarios 0 and 1 are strongly affected by the emission of landfill gases as CH4 (equal to 90% of GWP for the first scenario and about 30% for the second), H2S, HCl and others, originated by the anaerobic decomposition of landfilled organic waste. The global warming potential of the landfill scenarios is even higher than the impact

Table 7 Impact categories of collection phase and investigated scenarios System

Collection Scenario 0 Scenario 1 Scenario 2 Scenario 3

Net impacts GWP kt CO2

AP t SO2

EP t NO3

209 1910 868 345 224

319 546 186 441 780

n.a. 126 126 n.a.a n.a.a

Dioxins g TCDD 0.01 0.24 0.29 0.28 0.92

a For these scenarios landfilled wastes are without a significance organic content.

of the direct waste incineration (Scenario 3). This is due to the fact that Scenarios 2 and 3 deliver burnt-inorganic wastes to the landfill, which do not decompose further and do not give rise to organic emissions (i.e., methane and acid gases to the atmosphere and P- and N-compounds to water bodies). However, they still contribute metals to the leachate. Therefore, from a greenhouse gas emission and eutrophication point of view, burning seems to be better than burying. In fact, the main problem is that landfill is not an isolated system and it is not inert at all, but it should be considered as a chemical reactor which remains active for thousands of years. All the outcoming chemicals will inevitably pass through the landfill system and will disperse to the surrounding environment, causing both air and water/soil pollution, as indicated by the eutrophication potential in Table 7 (no eutrophication potential is calculated for Scenarios 2 and 3 because the landfilled wastes do not have a significant organic content). In order to avoid/minimize the environmental impacts, a landfill needs to be monitored for centuries. Concerning the present situation of Rome (Scenario 0), collection has a lower impact than disposal; hence, the priority is to improve the technology of disposal rather than the collection modalities. Moreover, Table 7 highlights that Scenario 2 is the best waste management option since it has a negative value for the GWP, the AP and dioxin emissions. Its implementation would therefore help in reducing the greenhouse gas effect, acid rains and dioxin emissions. These benefits are possible thanks to the generation of electricity and biogas that save the use of fossil fuels. The difference in dioxins emissions between Scenarios 2 and 3 is due to the fact that in Scenario 3 there is a co-firing of inorganic materials (including Cl-rich plastics) and organic matter. Such conditions favours the formation of dioxins (in Scenario 2, instead, only the inorganic fraction of the waste is burnt).

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Despite the large-scale results, local emissions (in which emissions for the supply of electricity and goods as well as benefits from electricity and/or biogas production are not taken in account) show a different trend. Table 8 shows the main local airborne emissions related to direct combustion in a plant or landfill site. At the local scale, the landfillbased Scenarios 0 and 1 have the lowest emission values for all chemicals except CH4 and H2S, while Scenarios 2 and 3 have larger emissions since they involve a combustion step. As a consequence, there is a conflict between the global and local results: what is positive at the global scale (Scenario 2) is not such at the local scale. 4. Waste management scenarios within the ‘‘zero waste’’ concept Results from the investigated scenarios for urban waste management show interesting technological and energy options. However, none of these options can fully provide a safe waste disposal strategy or an appropriate resource management pattern for full recovery of available resource potential of the un-pre-sorted wastes. Concerning pollution problems, it does not appear that they can all be solved by any of the investigated options. Due to unsolved problems (higher costs or unabated local pollution), the social acceptance of these strategies is still uncertain, in spite of several positive aspects pointed out by our assessment. The simple hierarchy pyramid shown in Fig. 4 is the classic view of ‘the desirability’ of waste management activities. The strength of the waste management hierarchy depiction is to show which practices are the more easily implemented and which are the most desirable. The figure emphasizes the opportunities that could be had by moving the management of a particular waste up the pyramid. In Italy, the un-pre-sorted waste management is placed in the bottom and the present paper has the aim to take it up to the upper levels of the pyramid. Zero emissions/zero waste strategies are often criticized for being an utopistic target. This may be true if we only

consider zero emission strategies as a simple refinement of past actions. Past eco-efficiency strategies, based on improved management of resources, are certainly capable of decreasing the environmental load but they always face technological, economic and social constraints, hard to overcome. ‘‘Zeroizing emissions will not be the outcome of an ongoing continuous development of minimization. Zeroizing needs radical breakthroughs, a shift from individual technologies to the system’s level! There is a need to combine newness and originality with a reference to sustainability’s mosaic. The creative process needed does not only include the – often seemingly intuitive – proposing of new ideas, but also the analytic consideration of the problem as well as the choice of fittest ideas and the establishing of the implementation strategy” (Schnitzer and Ulgiati, 2007). In the light of the required creative process, it must be underscored that the described waste management scenarios represent a gradual technological improvement which does not solve the problem but provides better knowledge about it. Scenarios 0 and 1 are set in the bottom of the pyramid, while Scenario 3 is just a step above, in the ‘‘treatment with energy recovery” section. Scenario 2 is the only one that tries to move up to the upper levels of the pyramid, since it lies in between the ‘‘treatment with energy recovery” and ‘‘recycle” sections: it produces electricity and biogas but it also recovers ferrous metals and compostable matter. Even if Scenario 2 could gradually approach the upper levels of the pyramid by means of technological improvement and material and energy efficiency, there is a level where technology seems unable to provide the basis for further steps. If we remain trapped within a purely technological improvement strategy, ‘‘zero waste/zero emissions” may appear an unreachable target. Thus, in order to solve the issue of waste disposal, we should not rely only on building new technologically advanced treatment plants, but we should implement waste prevention policies, based on the higher levels of the pyramid (‘‘Recycle” and ‘‘Reuse”), as well as on redesigning our production and consumption patterns towards the ideal condition of waste prevention, waste reuse or recycling as well as waste valorisation as new resource flows. This would also prevent us from being trapped in the hyper-cycle of generating wastes in order to dispose of the existing wastes. 5. Conclusions

Fig. 4. The waste management hierarchy.

A life cycle assessment of collection and different waste disposal strategies such as landfilling with (Scenario 1) and without (Scenario 0) landfill biogas exploitation, sorting plant to produce electricity via RDF and biogas via anaerobic digestion (Scenario 2), and waste incineration (Scenario 3), was performed by means of a multi-method multi-scale approach. Selected impact indicators calculated for the assessment lead to the following conclusions:

F. Cherubini et al. / Waste Management 28 (2008) 2552–2564

 Material flow accounting: The disposal of 1 g of waste requires the production of about 0.3 g of further waste as abiotic matter (the case studies range between 0.24 gab of Scenario 0 to 0.36 gab of Scenario 3). This calls for waste prevention policies in order to stop such an additional cycle of waste production. Furthermore, none of the selected scenarios are able to completely avoid the landfill, although in Scenarios 2 and 3 a reduction up to 80% can be achieved, together with a change in waste composition.  Gross energy requirement: The scenarios able to minimize the landfill (2 and 3) require a 20% increase of fossil energy consumption for the disposal of waste. However, they can provide a consistent energy output that, in Scenario 2, could meet 15.5% of the Rome electrical demand and 8.2% of the natural gas consumption (replaced by the upgraded biogas).  Emergy synthesis: The main result pointed out by the emergy synthesis is that recycling is a rewarding practice: the electricity production from waste combustion requires less environmental support than hydropower.  Global and local emissions: Landfilling is the most polluting waste management option (concerning GWP, AP and EP) at the global scale, since it is strongly affected by many different emissions (CH4, H2S, HCl, N and P inorganic compounds. . .) originated from the anaerobic condition within the system. Furthermore, a landfill needs to be monitored for a relatively long time period in order to minimize its environmental impact. Nevertheless, a conflict arises when local emissions are assessed, because Scenarios 2 and 3 – in spite of their large-scale benefits – show the highest emissions at the plant scale. An overall interpretation of these indicators suggests the landfill systems (Scenarios 0 and 1) as the worst waste management options. Results also show that a sorting plant coupled with electricity and biogas production (Scenario 2) is very likely to be the best option for waste management, despite the non-negligible problem of local emissions (NOx, PM10, heavy metals, HPA, among others). Furthermore, in Scenario 2 and, to a smaller extent, Scenario 3, a non-negligible amount of energy becomes available, in spite of an increase of fossil fuel energy input of about 20%, while waste residues to be landfilled are minimized and inerted. Therefore, if we truly have to choose only among the assessed options, even the incineration alternative (Scenario 3) would appear to be better than landfilling (Scenarios 0 and 1), also from an environmental impact point of view. However, none of the investigated scenarios are able to completely avoid the construction of a landfill. This aspect urgently calls for a breakthrough improvement: finding a convenient way for reuse of bottom and fly ashes which are now delivered to the landfill. If environmental problems must be solved step by step (due to technological, economic and social constraints),

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