Alternative scenarios to meet the demands of sustainable waste management

Transcription

1 Journal of Environmental Management 79 (2006) Alternative scenarios to meet the demands of sustainable waste management M.D. Bovea a, *, J.C. Powell b a Department of Mechanical Engineering and Construction, Universitat Jaume I, Av. Sos Baynat s/n, E Castellón, Spain b CSERGE, School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, UK Received 2 November 2004; revised 9 June 2005; accepted 13 June 2005 Available online 3 October 2005 Abstract This paper analyses different alternatives for solid waste management that can be implemented to enable the targets required by the European Landfill and Packaging and Packaging Waste Directives to be achieved in the Valencian Community, on the east coast of Spain. The methodology applied to evaluate the environmental performance of each alternative is Life Cycle Assessment (LCA). The analysis has been performed at two levels; first, the emissions accounted for in the inventory stage have been arranged into impact categories to obtain an indicator for each category; and secondly, the weighting of environmental data to a single unit has been applied. Despite quantitative differences between the results obtained with four alternative impact assessment methods, the same preference ranking has been established: scenarios with energy recovery (1v and 2v) achieve major improvements compared to baseline, with scenario 1v being better than 2v for all impact assessment methods except for the EPS 00 method, which obtains better results for scenario 2v. Sensitivity analysis has been used to test some of the assumptions used in the initial life cycle inventory model but none have a significant effect on the overall results. As a result, the best alternative to the existing waste management system can be identified. q 2005 Elsevier Ltd. All rights reserved. Keywords: Sustainable waste management; Life cycle assessment; LCA 1. Introduction The European landfill directive (1999) and the Packaging and Packaging Waste Directive (1994) aim to reduce the amount of biodegradable municipal wastes going to landfill. In addition, in Spain the national waste strategy requires an increase in the household waste recycling and recovery rates, plus a special promotion of composting. Both of these measures require the development of different alternatives to improve the environmental performance of the current waste management systems in order to reach the targets required for both the European and Spanish legislation. The study focuses on the assessment of alternative solid waste management options that can be used in the Valencian Community, situated in the East Coast of * Corresponding author. Tel.: C ; fax: C addresses: bovea@emc.uji.es (M.D. Bovea), j.c.powell@uea. ac.uk (J.C. Powell) /$ - see front matter q 2005 Elsevier Ltd. All rights reserved. doi: /j.jenvman Spain, to comply with the legislation. The study area covers 23,255 km 2, with a population of approximately 4,200,000 people grouped in three provinces: Alicante, Valencia and Castellón, that jointly produce around 2,200,000 ton/year of municipal solid wastes. It has been estimated that by 2012, 2,384,467 ton of waste will be produced per year taking into account both permanent and seasonal population,since tourism is an important factor in this area (866,287, 1,204, 134 and 314,046 ton/year for Alicante, Valencia and Castellón, respectively). In order to manage the municipal solid wastes, the Valencian Community is divided into 27 management areas, where municipalities in each one apply the same waste management model. The Waste Integral Plan of the Valencian Community represents the main instrument to coordinate all the waste management activities focussed on the achievement of the legal targets in this region. It proposes several alternative waste management systems to the current model with the aim of increasing the reuse, recycling and valorisation of waste in order to reduce its environmental burdens and reach the legal targets. The aim is to limit the disposal

2 116 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) of waste in landfills to the waste fraction that cannot be valorised. To fulfil this objective, the different scenarios focus mainly on the development of the collection system to increase the amount of recyclable material collected, and the proposed treatment of the biodegradable fraction of the waste stream by composting. This study includes an environmental evaluation of each scenario using the Life Cycle Assessment (LCA) methodology. According to ISO (1997), an LCA is comprised of four major stages: goal and scope definition, life cycle inventory, life cycle analysis and interpretation of the results. The life cycle of municipal solid waste starts when a material becomes waste and ends when it becomes either a useful product, inert landfill material or an emission to either air or water (McDougall and Hruska, 2000). The Life Cycle Inventory (LCI) is the most time consuming stage of an LCA. Different LCI models for waste management have been developed to facilitate its application: Integrated Solid Waste (ISW) was developed by White et al. (1995) and improved by McDougall et al. (2001); the US Environmental Protection Agency has also developed a computer-based decision support tool to evaluate integrated municipal solid waste management strategies (Weitz et al., 1999); the WISARD (1999) (Waste Integrated Systems Assessment for Recovery and Disposal) software was developed by Ecobilan for the UK Environmental Agency to enable decision-makers to establish the best environmental options for managing waste; ORWARE (Organic Waste Research) is a computer based model to evaluate the organic and now also inorganic fractions in municipal wastes (Eriksson et al., 2002). Although these models can provide useful support in determining the Best Practicable Environmental Option (BPEO) they tend to lack flexibility. They are often country specific in that they can only be used for the types of waste management systems likely to be found in the country of origin. Therefore in this study, the software SimaPro 6 (2004) has been applied to model the different waste management scenarios. Although this software is product focused, there is greater flexibility to construct a transparent and flexible solid waste management model. All the data needed for the life cycle inventory (LCI) have been modelled as new material/process/transport/energy system/ waste treatment. The environmental results for this study are presented both globally for each scenario and separately, analysing the individual contribution of each unit process for each scenario. 2. Description of the scenarios The Waste Integral Plan in the Valencian Community proposes several alternatives to the current waste management system. They combine different levels of bring and kerbside systems, all of which require the householders to source separate recyclable materials from their residual waste (restwaste): Recyclable materials are taken to communal containers positioned at the side of the street. Depending on the separated fractions, different containers are available for glass, paper/cardboard and light packages (defined as mixtures of plastic, beverage tetra-bricks, aluminium foils and cans). This collection system has been called a bring system in this study. Residual wastes (or restwaste) are taken to street-side containers, situated at an approximate walking distance of m (very high density) and collected daily (7 days/week). This collection system has been called kerbside collection points in this study. Different combinations of these two schemes have been applied to create alternative scenarios to the baseline model. A generalisation of the existing waste management system acts as a baseline against which all other scenarios are compared. The proposed scenarios by the Waste Integral Plan of the Valencian Community are described in the following: 2.1. Scenario 0 (baseline) The baseline scenario reproduces the existing waste management strategy in most of the areas of the Valencian Community. A bring system (low density: 1 container per 1500 inhabitants) operates for recyclables (glass and paper/cardboard). The recyclable material (4 and 3% of paper/cardboard and glass, respectively) is sent directly to the reprocessing facility. Restwaste (93%) is collected from kerbside collection points and sent to a MRF where unsorted household waste is separated into different fractions. The residue from the MRF (55%) is sent to a landfill without energy recovery. The putrescible fraction (34.5%) from the MRF is sent to a composting facility, and the recyclable fractions (3.5%) are sent to a reprocessing facility. In this scenario a total of 10.5% of materials are recycled in addition to the material recovered for composting. See Fig Scenario 1/1v This scenario emphasises the recovery of the putrescible fraction. The household waste is source separated into three fractions: putrescible, restwaste and recyclable. The two first fractions are deposited in two different containers at kerbside collection points within a maximum walking distance of 50 m. The putrescible fraction (47%) is transported directly to a composting facility, while the restwaste (29%) is disposed of in a landfill site without energy recovery (scenario 1) or a landfill where landfill gas is collected and used for energy generation (scenario 1v). The source separated recyclable fractions, glass,

3 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) Bring system (7.0%) Paper/cardboard (4.0 %) Reprocessing (10.5%) Household waste (100%) Glass (3.0%) Ferro-metal (1.3%) Paper/cardboard (1.4%) Kerbside collection point (93.0%) Restwaste (93.0%) MRF Glass (0.4%) Plastic (0.4%) Compost+water (34.5%) Residue (55.0%) Compost (13.4%) Landfill without energy recovery (55.0%) (The percentages represent the proportion of the total household waste stream) Fig. 1. Flowchart of the baseline scenario 0. paper/cardboard and light packages, are deposited in separate bring containers (high density: 1 container per 600 inhabitants). Glass and paper/cardboard (7 and 10%, respectively) are sent to the reprocessing facility while light containers (7%) are sent to a MRF where are separated into five different fractions (plastic, ferro-metal, paper/cardboard, non-ferro metal and residue). The first four separated fractions (6.3%) are transported to the reprocessing facility and the residue (0.7%) to a landfill site with/without energy recovery. See Fig Scenario 2/2v This scenario emphasises the quality of the recovered materials, both organics and inorganics. The household waste is source separated into four fractions: putrescible, inorganic, restwaste and recyclable. The first three fractions are collected in three different containers at kerbside collection points. The final destination of the putrescible fraction (47%) is a composting facility. The inorganic fraction (25%) is sent to a MRF where Bring system (24.0%) Paper/cardboard (10.0 %) Glass (7.0%) Ferro-metal (1.7%) Paper/cardboard (0.7%) Reprocessing (23.3%) Light packages (7.0%) MRF Non ferro-metal (0.2%) Household waste (100%) Plastic (3.7%) Restwaste (47.0%) Residue (0.7%) Landfill with/without energy recovery (37.7%) Kerbside collection point (76.0%) Putrescible (29.0%) Compost facility Residue (8.0%) Compost+water (39.0%) Compost (19.0%) (The percentages represent the proportion of the total household waste stream) Fig. 2. Flowchart of the scenario 1/1v.

4 118 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) Household waste (100%) Bring system (24.0%) Paper/cardboard (4.0 %) Glass (3.0%) Non fermentable (25.0%) MRF Ferro-metal (2.3%) Paper/cardboard (7.0%) Glass (3.5%) Reprocessing (24.2%) Plastic (4.4%) Kerbside collection point (76.0%) Restwaste (21.0%) Residue (7.8%) Landfill with/without energy recovery (36.8%) Putrescible (47.0%) Compost facility Residue (8.0%) Compost+water (39.0%) Compost (19.0%) (The percentages represent the proportion of the total household waste stream) Fig. 3. Flowchart of the scenario 2/2v. recyclable recovered fractions (17.2%) are sent to the reprocessing facility while the residue of the MRF (7.8%) in addition to the residue of the composting process (8%) and the remaining restwaste (21%) is disposed in a landfill without energy recovery (scenario 2) or a landfill where landfill gas is collected and used for energy generation (scenario 2v). The recyclable fraction groups glass (3%) and paper/cardboard (4%) that are collected in separated containers in the bring system (low density: 1 container per 1500 inhabitants) and sent to the reprocessing facility. See Fig. 3. A comparison of the recovery fractions among the previously described scenarios is shown in Table 1. The residue is the fraction that is landfilled (without energy recovery (scenario 0, 1 and 2) or with energy recovery (scenario 1v and 2v)). Taking into account the composition of the total household waste reported in Table 2, the composition of the residue fraction can be calculated for each scenario. 3. Methodology The Life Cycle Assessment (LCA) methodology has been used to evaluate an environmental comparison of the alternative scenarios to the current waste management system. According to ISO (1997), an LCA comprises four major stages: goal and scope definition, life cycle inventory, life cycle analysis and interpretation of the results. The overall goal of the study is to evaluate the environmental performance of the current municipal solid waste management in comparison with some integrated alternatives in the area of the Valencian Community. The results of this study can be used as technical support during the decision-making processes. The function of the system under study is to manage household solid wastes in the area of study. The functional unit selected for the comparison of the alternative scenarios is the management of 1 ton of Table 1 Comparison of the recovery fractions for each scenario (in percentage, %) Scenario Recyclable material recovered Sent to compost Paper Glass Ferro metal Non-ferro Plastic Total metal Baseline /1v /2v Residue sent to landfill

5 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) Table 2 Composition of the total household waste and the residue obtained from each scenario, and density and water content of the different fractions obtained from wastes Household waste composition a (%) Residue composition Density b (kg/m 3 ) Water content b (%) Baseline (%) Scenario 1/1v (%) Scenario 2/2v (%) Metal Glass Paper/cardboard Plastic Putrescible Textil Other a Source: Ferrer et al. (2000). b Source: Tchoganouglus et al. (1993). household solid waste of the composition reported in Table 2. The Life Cycle Inventory (LCI) constitutes a detailed compilation of all environmental inputs (material and energy) and outputs (air, water and solid emissions) during each stage of the life cycle of the waste. An LCI has been completed for all the activities required to manage the waste from the time it leaves the household to its ultimate disposition: the bags and containers needed for the collection of the waste, the transport of the waste from the point of generation to the final destination, the management of the waste in a Transfer Station (TS) and/or in a Material Recovery Facility (MRF), the management of the waste in the landfill, the collection and treatment of the generated biogas (scenarios with energy recovery), the composting of the putrescible fraction and the recycling process of recovered fractions. The savings from energy generation from biogas, compost (avoiding fertilizers) and recycled material (avoiding virgin material) have also been included in the model. A description of those elements included in the model is detailed in Section 4. The phase of Life Cycle Impact Assessment (LCIA) aims to quantify the relative importance of all environmental burdens obtained in the LCI by aggregating them. According to ISO (2000), the general framework of an LCIA method is composed of several mandatory elements (classification and characterization) that convert LCI results to an indicator for each impact category, and optional elements (normalization and weighting) that lead to a unique indicator across impact categories using numerical factors based on value-choices. Finally, the results from the LCI and LCIA stages will be interpreted in order to select the best alternative scenario to the current waste management system (baseline). 4. Description of the LCI model This section describes the LCI model applied in this study, including the assumptions made for each element in the waste management system Waste bags Three different types of waste bags are considered for the kerbside collection systems: supermarket bags, medium sized bags and special bags with a closing system (Table 3). The manufacturing impacts arise from low density polyethylene (LDPE) production and from the energy needed for the foil extrusion (0.746 kw h/kg LDPE). The emission data is from BUWAL250 (1998). The impact produced by the supermarket bags has been not considered, since they are part of the waste before leaving the household. According to the average density of the total household waste ( kg/m 3 calculated from data in Table 2) and the average volume of waste in each bag calculated in Table 3, the number of bags needed for the kerbside collection has been estimated as bags/ton of waste (full bags are assumed) Waste containers Waste containers are considered for the kerbside collection and bring system. Table 4 shows the main characteristics of each container and the data source for the LCI. The number of containers has been estimated as an average of data from eight villages in the Valencian Community during 4 years ( ) (see Table 5). The average life span for each container has been assumed to be 5 years, plus an additional 10% of intentionally damaged containers per year due to vandalism. Table 3 Characteristics of waste bags (Ferrer et al., 2000) Bag weight (g) Use (%) Volume of waste (l) Supermarket bags Medium size bag Special bags with closing system Average 15.87

6 120 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) Table 4 Characteristics and LCI data considered for waste containers Volume (m 3 ) Weight (kg) Application LCI data Material/process Database Wheeled Mixed wastes (including fermentable) Injected HDPE BUWAL250 (1998) Idemat (1996) Igloo Recyclable glass Polyester IVAM (1998) Igloo Recyclable package (plastic, tetra-brick, tin, etc.) Galvanised steel IVAM (1998) Additional impact also arises from washing the containers. The water consumption for container washing has been estimated as 16.6 l/container, according to Baldasano et al. (2002). The frequency of washing depends on the waste fraction in the container. For containers collecting mixed wastes (including fermentable), the water consumption is assumed to be 250 l/year-container (Baldasano et al., 2002). For containers used to collect recyclable wastes, the assumption has been that they need half this washing frequency. However, the main impact from the container washing is due to the fuel consumption of the washing truck. The same fuel consumption as occurs for the waste collecting route has been assumed, the number of containers collecting mixed wastes and recyclable wastes being 300 and 150, respectively, washed per journey (Baldasano et al., 2002) Transport The collection system starts when the waste leaves the household. The transport of waste is considered in two stages. The first stage models the collection system, while the second stage models the transportation of the collected waste to the waste treatment facility. The collection model is based on data from Bjorklund et al. (2003), which includes the entire collection route, including stops and hydraulic work. No distinction is made between collection from different sources. Diesel consumption per ton of collected waste is reported in Table 6 according to the average distance driven per ton of collected waste. The impact due to transport other than collection is calculated using data from Finnveden et al. (2000). Three different types of routes (urban, rural and highway) with Table 5 Number of container needed per collected ton Type of container Bring Light packages 2.5 m 3 igloo 0.93 Paper/cardboard 3 m 3 galvanised 0.23 steel Glass 2.5 m 3 igloo 0.27 Kerbside collection 1.1 m 3 wheeled 0.03 No. container/ ton diesel trucks are available and different loads can be selected, as Table 7 shows. In both systems, the impact due to the thermal energy from diesel has been obtained from BUWAL (1998), assuming 45.4 MJ/kg of diesel. Data includes detailed emission data for heat production from diesel in Europe, including production and transport of primary energy sources and excluding the infrastructure of the energy systems. The characteristics of the transport for this application study, from collection to final treatment, are reported in Tables 8 and 9 (an empty return trip is assumed) Electrical energy The inventory data used for the generation of electrical energy corresponds to the primary energy structure used by Swiss Federal Institute of Technology (ESU-ETHZ) (Frischknecht et al., 1995). Table 10 shows the proportions of different fuels used to generate Spanish electricity for the year The life cycle inventory of each type of energy is sourced from BUWAL250 (1998). This average data was also used to calculate the emissions saved by energy displaced by energy from waste, i.e. landfill gas Transfer station (TS) Where the distance from the collection area to the waste treatment facility is large, a transfer station can be used to bulk up the waste for more efficient transport using a larger truck. Waste arriving at the transfer station in waste collection trucks (50 70% load) is discharged into 40 m 3 containers and bulked up to a full load with the aid of compacting equipment. Fuel consumption data for road transport shown in Table 7 have been applied. Table 6 Diesel consumption per ton of collected waste (adapted from Bjorklund et al. (2003)) Type of collection Diesel (MJ/ton) Waste collection, 1.1 km/ton Waste collection, 1.6 km/ton Waste collection, 3.3 km/ton Waste collection, 10 km/ton

7 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) Table 7 Fuel consumption during transport other than collection ( Finnveden et al., 2000) The impact due to the operation of the transfer station is mainly due to energy consumption during the transfer operation (1.298 kw h/ton), 2 and water consumption during the cleaning activities (6.47 l/ton). 2 It has been assumed that a transfer station is used in all the scenarios. See the Sensitivity analysis section to evaluate the effect that the exclusion of the transfer station has on the total environmental impact Material recovery facility (MRF) Mixed recyclables collected in the co-mingled containers arrive at the material recovery facility for sorting by manual and mechanical processes. The different fractions obtained from the sorting process are finally compressed in bales. Bales of recycled materials are transported to reprocessing facilities, while the residue material is transported to the landfill. The impact due to these operations is mainly due to the electrical energy consumption used by the sorting equipment and during the compressing bales production (5.9 kw h/ton), 2 and water normally consumed during cleaning activities (29.1 l/ton) Composting Diesel truck, urban MJ/ ton km Diesel truck, rural MJ/ ton km Medium sized truck (appr. 24 ton) Full load (14.0 ton) % load (9.8 ton) % load (8.4 ton) % load (7.0 ton) % load (5.6 ton) Heavy truck (appr. 40 ton) Full load (25.0 ton) % load (17.5 ton) % load (12.5 ton) Heavy truck (appr. 52 ton) Full load (32.0 ton) % load (22.4 ton) % load (16.0 ton) Diesel truck, highway MJ/ ton km Composting involves a net consumption of energy to produce a material used as an artificial fertilizer. According to Nilsson (1997), as reported in Finnveden et al. (2000), the energy consumption during the composting process is due to electricity (54.4 MJ/ton of input to the composting process) and the consumption of diesel in the wheel loader, mills and strainers 2 Personal communication. Table 8 Characteristics of the transport from the MRF to the reprocessing facility Type a (see Table 7) Distance (km, round trip) Ferro-metal Medium 25 75) 1200 Non-ferro metal Medium 25 75) 1200 Plastic Medium 25 75) 300 Paper/cardboard Medium 25 75) 300 Glass Medium 25 75) 600 a Nomenclature: medium/heavy truck (% load) (%urban %rural %highway). (555.5 MJ/ton of input to the composting process). Air emissions are 0.28 kg of NH 3 and kg of N 2 O per ton of input to the composting process. The organic material obtained from the composting process is used as a fertiliser. The avoided material is a chemical fertiliser containing an equivalent amount of nutrients (N and P). According to Finnveden et al. (2000), the nutrient content of the compost is 8.3 kg of N and 2.0 kg of P per ton of input to the composting process. It has been assumed in the model that there is 100% replacement of organic fertilizer based on the N and P content (see the Sensitivity analysis section to evaluate the effect that a change in this percentage has on the overall impact). This means that the emissions that are avoided by using compost instead of chemical fertilised are credited to the waste management system. The life cycle inventory for the chemical N and P fertilizer avoided is obtained from Idemat Database (1996) Landfill Depending on the scenario, three different waste streams are sent to the landfill: Residual waste or restwaste collected and landfilled directly. Sorting residues from waste sorting processes at MRFs. Residual material from composting processes. The landfilling process consumes energy in the form of vehicle diesel during the operations of disposal and the site itself. Solid wastes arriving directly at the landfill are assumed to have a fuel consumption of 6.72 MJ/ton of disposed waste (Rieradevall et al., 1997). The impact due to landfill gas and leachate generation has been considered for each waste fraction, as Table 11 shows and explained below. Landfill gas is only produced from the biodegradable fractions of the waste. According to McDougall et al. (2001), approximately 250 m 3 N of biogas is produced per ton of biodegradable organic waste (putrescible, paper and textile), while 100 m 3 N/ton of landfilled residues from composting process. A gas collection efficiency of 55% and a calorific value of the biogas of 19.5 MJ/m 3 is assumed

8 Table 9 Characteristics of the transport from collection to final treatment facility Scenario 0 Restwaste 1.1 km/ton Medium (70%) ( ) 3.3 km/ton Medium (60%) ( ) Glass 3.3 km/ton Medium (60%) ( ) Scenario 1/1v Restwaste 1.1 km/ton Medium (70%) ( ) Fermentable 1.1 km/ton Medium (70%) ( ) Paper/ cardboard 3.3 km/ton Medium (60%) ( ) Glass 3.3 km/ton Medium (60%) ( ) Light packages 3.3 km/ton Medium (40%) ( ) Scenario 2/2v Restwaste 1.1 km/ton Medium (70%) ( ) Fermentable 1.1 km/ton Medium (70%) ( ) Non fermentable Collection route From collection to TS From TS to landfill From TS to MRF/compost From MRF to landfill a From MRF to reprocessing From TS to reprocessing Type a Type b Distance c Type b Distance c Type b Distance c Type b Distance c Type b Distance c Type b Distance c Paper/cardboard Paper/cardboard 1.1 km/ton Medium (70%) ( ) 3.3 km/ton Medium (60%) ( ) Glass 3.3 km/ton Medium (60%) ( ) 40 Heavy (100%) ( ) 50 Medium 100 0) 5 e e 25 Medium 25 75) 25 Medium 25 75) 40 Heavy (100%) ( ) 40 Heavy (100%) ( ) Medium 100 0) 5 25 Medium 25 75) 25 Medium 25 75) 40 Heavy 50 50) 40 Heavy (100%) ( ) 40 Heavy (100%) ( ) 40 Heavy (100%) ( ) 50 Medium 100 0) 5 e e Medium 100 0) 50 Medium (70%) ( ) 5 5 e e 25 Medium 25 75) 25 Medium (70%) ( ) M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) Nomenclature: medium/heavy truck (% load) (%urban %rural %highway). a see Table 6 b see Table 7 c km, round trip d Only residue fraction. e Recyclable fractions (plastic, ferro metal, non-ferro metal, paper/cardboard) see Table 8.

9 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) Table 10 Reference combination of primary energies within the Spanish electricity grid in 2003 (Red Eléctrica Española, 2004) Primary energy % Lignite Coal Fuel oil 2.09 Natural gas Nuclear Hydropower (Rieradevall et al., 1997). If the biogas is collected to recover energy, electricity generation of and MJ/ton can be obtained from biodegradable organic waste and residues from composting, respectively. It is assumed that where energy recovery occurs it involves the burning of landfill gas in a gas engine to generate electricity, which is then exported to the grid. Table 12 reports the air emissions from landfilling, with and without energy recovery. 3 The emissions to the hydrosphere are related to the generation of leachate due to three different processes (see Table 11): Contribution to the leachate production originating from rain is assumed to be l/ton (Rieradevall et al., 1997). This value is considered to be equal for all the waste fractions. Contribution to the leachate production due to the water content of the waste is assumed to be 45% of the water content for each waste fraction. Deduction from the water which reacts with the biodegradable organic fraction (putrescible, paper and textile) is assumed to be 52.1 l/ton (Rieradevall et al., 1997). The composition of the leachate is reported in Table Recycling The recycling process is included within the boundaries of the waste management system. The environmental burden associated with the reprocessing of each of the recovered waste fractions has been calculated taking into account LCI data for the following processes: The impact due to the transportation of the recovered material from the collection or sorting facility to the reprocessing site. LCI data associated with transport are reported in Table 7. The potential saving (or addition) of energy consumption and emissions arising from the use of secondary instead of 3 The emitted CO 2 has been considered as a net contribution to the global warming. See Sensitive analysis section to evaluate the effect that the exclusion of the biological CO 2 has on the global warming category and on the overall impact. primary materials to manufacture new products. LCI data associated with this process have been obtained from McDougall et al. (2001), Table 22.7). The amount of primary material replaced by each ton of recycled product varies with each material and also depends on the quality of the recovered material going to reprocessing. The contamination ratios reported in Table 14 have been applied, assuming that recycled material performs equally well and can replace an equal quantity of virgin material. The residue from the recycling process is sent to a landfill. 5. Results 5.1. LCI results The LCI data described above have been applied to model the five alternative waste management systems proposed in Figs Table 15 shows which parts of the waste management system (kerbside/bring system) contribute most significantly to the main pollutants, before they are aggregated into impact categories LCIA results LCI results will be analysed at two levels: First, the emissions accounted for in the inventory stage have been arranged into impact categories according to CML (2001) to obtain an indicator for each category. Secondly, the weighting of environmental data to a single unit will be applied. A wide range of weighting methods exist and several reviews can be found in Baumann and Rydberg (1994), Eriksson et al. (1996), Giegrich and Schmitz (1996), Powell et al. (1997), Hertwich et al. (1997) or Dreyer et al. (2003). In compatibility with ISO (2000), four different impact assessment methods have been applied in order to select which alternative scenario has a better overall environmental performance: Eco-Indicator 95 (EI 95) method (Goedkoop, 1996), Eco-Indicator 99 (EI 99) method (Goedkoop and Spriensma, 2000), EPS (Environmental Priority System) method (Steen and Ryding, 1993; Steen, 1999a,b) and CSERGE (Powell et al., 2002). The results for impact categories and LCIA methods are given in global terms for each scenario and for each process within the scenarios. The latter is important in understanding the role that each process has on the overall environmental impact. The unit processes considered are: Collection: includes the environmental impact due to the waste bags, containers and transport related to the collection route.

10 124 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) Table 11 Data for landfill gas and leachate generation Landfill gas generation (N m 3 /ton) Leachate generation Restwaste and sorting residues Paper Glass Metal Plastic Textile Putrescible Others Residues from compost Contribution from rain (l/ton) Contribution from water content in waste (l/ton) Deduction from fermentation process (l/ton) Total (l/ton) TS-MRF: includes the impact from the transportation of waste to the transfer station and/or material recovery facility and the processing of the waste at the facility. Recycling: includes the impact from the material reprocessing and the saving from the avoided primary materials. Also includes the impact from the transportation to the reprocessing facility. Landfill without/with energy recovery: includes the impact due to the landfilling process without/with energy recovery. In the case of landfill with energy recovery, it includes the saving from electricity production. Composting: includes impacts due to the composting site and to the composting process. Includes the saving from avoided chemical fertilizer and impacts from transportation to the composting facility Analysis by impact categories The emissions accounted for in the inventory stage have been allocated into five impact categories: global warming, ozone layer depletion, photochemical oxidation, acidification and eutrophication, according to CML (2001). In addition an abiotic depletion impact category is used. The reference unit and the net contributions to each impact category that each scenario produces are reported in Table 16. The contributions to individual impact categories Table 12 Air emissions from landfilling (calculated from Rieradevall et al., 1997) Without energy recovery (mg/n m 3 ) CO CO 2 900,917 1,480,372 CH 4 383, ,400 NO x SO x C x H y With energy recovery (mg/n m 3 ) are also given in Fig. 4a f, analysed by each process during the life cycle of the waste. The contribution to the abiotic depletion impact category (Fig. 4a) is mainly due to the fuel consumption during the collection and transportation of the waste to the final treatment facility and slightly due to the recycling process. A small saving of biotic depletion is due to the avoided fertilizers during the composting process. Very little difference appears between baseline and alternative scenarios. A clear difference can be found in the global warming impact category with the alternative scenarios, achieving a reduction of %, compared to the baseline (Fig. 4b). In terms of absolute values, scenarios 1v and Table 13 Leachate composition (calculated from Rieradevall et al. (1997)) (mg/l leachate) COD BOD a Suspended solids N NH N-org 2.9 NO K PO 3K Cl K Na C K C Metals 46.7 a BOD produced only due to the fermentable organic fractions (putrescible, paper and textile). All other leachate components are assumed to arise equally from all of the waste fractions (McDougall et al., 2001). Table 14 Contaminating ratios applied during the recycling process (BUWAL250, 1998) Material loses (%) Paper Glass Ferrometal Non-ferro metal Plastic

11 Table 15 Contribution that each part of the waste management system for each scenario has to the most significantly pollutants Substance process a NH 3 (g) CO (g) CO 2 (kg) CH 4 (kg) N 2 O (g) NO x (g) PAH s (mg) Pb (g) SO x (g) Scenario 0 kerbside_restwaste 96.4 K K K bring_paper K K K bring_glass K0.26 K K57.94 Total 99.1 K K scenario 1 kerbside_fermentable kerbside_restwaste bring_glass K0.61 K K bring_paper K K K bring_packages K0.16 K K K K K K Total K K K K scenario 1v kerbside_fermentable K0.195 K K2.63!10 1 kerbside_restwaste K K0.339 K K2.04 K K2.62!10 2 bring_glass K0.607 K K1.35!10 2 bring_paper K K K4.67!10 2 bring_packages K0.169 K282 K275 K K K K1.05!10 3 Total 114 K192 K K K1.94!10 3 scenario 2 kerbside_fermentable K kerbside_nonfermentable 4.36 K252 K K K K kerbside_restwaste bring_paper K K K bring_glass K0.26 K K57.94 Total 115 K172 K K5.01 K K scenario 2v kerbside_fermentable K0.195 K K2.63!10 1 kerbside_nonfermentable 4.36 K252 K K K K1.24!10 3 kerbside_restwaste K K0.248 K K1.49 K K1.91!10 2 bring_paper K K K1.87!10 2 bring_glass K0.26 K K5.79!10 1 a According to Figs Total 115 K183 K K K1.70!10 3 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006)

12 126 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) Table 16 Net contributions to impact categories and absolute values according to each LCIA method, for each scenario Unit scenario 0 scenario 1 scenario 1v scenario 2 scenario 2v Impact category Abiotic depletion kg Sb equiv. 2.19!10 K1 2.16!10 K1 2.16!10 K1 2.24!10 K1 2.24!10 K1 Global warming kg CO 2 equiv. 7.66! !10 2 K1.04! !10 2 K1.10!10 2 (GWP100) Ozone layer kg CFC-11 equiv. 1.88!10 K5 1.55!10 K5 1.07!10 K5 1.32!10 K5 9.66!10 K6 depletion (ODP) Photochemical kg C 2 H 2 equiv. 1.97!10 K1 7.56!10 K2-1.94!10 K2 5.12!10 K2 K1.93!10 K2 oxidation Acidification kg SO 2 equiv. K2.13!10 K1 K1.82 K2.36 K1.65 K2.05 Eutrophication kg PO 4 - equiv. 3.14!10 K3 K1.13!10 K1 K1.44!10 K1 K1.18!10 K1 K1.41!10 K1 LCIA method EI 95 Points 0.13 K0.22 K0.42 K0.26 K0.40 EI 99 Points 4.81 K1.20 K3.69 K1.25 K3.11 EPS 2000 ELUs K3.71 CSERGE Euros K28.90 K43.00 K27.80 K v (with energy recovery) produce a net saving to this impact category, while the remaining scenarios produce a net contribution. The contribution to this category is mainly due to CO 2 and CH 4 emissions from landfill gas generation. Differences between scenarios with and without energy recovery are due to the reduction of methane emissions (45% is collected). This reduction compensates for the increase of CO 2 emissions due to the combustion of landfill gas in the gas engine to generate electricity. The savings are due to the recycling of the recovered materials and the displaced emissions from energy recovery, mainly due to the metal and plastic fraction. This saving is slightly higher in scenario 1/1v than in 2/2v, although no important differences can be found. A net contribution to the ozone layer depletion can be found for all scenarios (Fig. 4c), mainly due to emissions from transportation, both during collection and to the final treatment facility. Savings are due to the recycling of recovered fractions in all scenarios, and to the landfilling process in scenarios with energy recovery. Compared to the baseline, scenarios without energy recovery produce a reduction in the emissions of around 17.6 and 29.8% for scenarios 1 and 2, respectively, compared with 43.1 and 48.6% for scenarios with recovery energy, 1v and 2v, respectively. Landfill is the dominating process in the net contribution to the photochemical oxidation category. A reduction of the net contribution is achieved in scenarios with energy recovery, (Fig. 4d). Net savings are mainly due to the recycling process, where alternative scenarios achieve a clear advantage compared to the baseline. In terms of absolute values, scenarios with energy recovery produce a net saving, while a net contribution is realized for the remaining scenarios. Compared to the baseline, alternative scenarios without energy recovery achieve a reduction of around 61.6% for scenario 1 and 74.0% for scenario 2. This percentage increases to 110% in both scenarios with energy recovery (1v and 2v). Net savings of acidification emissions are attained by all scenarios, including the baseline (Fig. 4e). The net contribution to this impact category is dominated by the fuel consumption associated with the collection and transportation of waste to the final treatment facility and by ammonia emissions during the composting processes. The net savings are dominated by recycling for all scenarios and to a lesser extent by landfill in those scenarios with energy recovery. Compared to the baseline, a reduction of around 700% is achieved by scenarios without recovery energy, and about 900% for those with energy recovery. A similar situation occurs when the contribution to the eutrophication potential is analysed (Fig. 4f). A clear advantage can be found for all alternative scenarios compared to the baseline. The collection transport processes have a net contribution to this impact category, while landfill has a net contribution only in those scenarios without energy recovery. The remaining processes only include savings. To summarise, compared with the baseline, scenarios with energy recovery (1v and 2v) achieve greater improvements for all impact categories than scenarios without energy recovery (1 and 2). Scenario 1v is slightly better than scenario 2v in acidification and eutrophication categories, there being no differences in terms of global warming and photochemical oxidation. In the ozone layer depletion category scenario 2v is slightly better than scenario 1v Analysis by impact assessment methods As there are no criteria to select the best weighting method for waste management analysis, the four impact assessment methods cited above have been applied and tested in parallel to explore if the results differ. The figures reported in Table 16 have been obtained. As the objective of this project is to obtain the best alternative scenario to the current waste management

13 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) (a) 3.00E-01 abiotic depletion (b) 1.00E+03 global warming 2.50E E+02 kg Sb eq 2.00E E E E-02 kg CO2 eq 6.00E E E E E-02 sc0 sc1 sc1v sc2 sc2v 0.00E E+02 sc0 sc1 sc1v sc2 sc2v 1.00E E+02 (c) 2.50E-05 ozone layer depletion (d) 2.50E-01 photochemical oxidation 2.00E E-01 kg CFC-11 eq 1.50E E E E E-06 sc0 sc1 sc1v sc2 sc2v kg C2H2 eq 1.50E E E E+00 sc0 sc1 sc1v sc2 sc2v 1.00E E E E-01 (e) 1.00E+00 acidification (f) 1.00E-01 eutrophication 5.00E E-02 kg SO2 eq 0.00E E E E E+00 sc0 sc1 sc1v sc2 sc2v kg PO4 (3-) eq 0.00E E E E-01 sc0 sc1 sc1v sc2 sc2v 2.50E E E E-01 landfill composting recycling transport collection Fig. 4. Contribution to each impact category by each process during the life cycle of the waste. system (baseline), from an environmental point of view, the relative change (in percentage) compared to the baseline scenario (scenario 0) has been calculated and represented graphically in Fig. 5. Important quantitative differences appear when the relative change for each alternative scenario is compared to the baseline. However, a similar profile is obtained with the four impact assessment methods, and thus, the same rank order preference can be established. In general scenarios with energy recovery (1v and 2v) achieve significant improvements compared to the baseline, and scenario 1v achieves slightly better improvements than 2v for all impact assessment methods except for EPS 00, that obtains a similar result for both alternatives. Fig. 6a e shows the contribution (in percentage) of each process to the overall environmental impact for each of the impact assessment methods applied and for each scenario. In the baseline scenario, the impact is dominated by the landfilling process and, to a lesser extent, by the transport activities during collection and transfer to the final treatment of the waste. The alternative scenarios involve less landfill so this process is less significant, with the environmental benefits obtained by the recycling process becoming noticeably more

14 128 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) % improvement compared to baseline E'99I EPS'2000 EI'95 CSERGE sc 1 sc 1v sc 2 sc 2v important. Environmental benefits due to the composting process are not significant, since the main benefit has been included in the reduction of waste disposed in the landfill. The main differences between the impact assessment methods appears to be with EPS 00, that considers the landfilling process to be more important that the other methods. Major differences become visible when scenarios without energy recovery are compared to the corresponding scenarios with energy recovery. While Eco-Indicator 95, Eco-Indicator 99 and CSERGE obtain a net environmental benefit for recovery energy, EPS 00 obtains a net contribution to the total impact. 6. Sensitivity analysis Fig. 5. Range of percentage of improvement for each alternative scenario compared to the baseline scenario with different impact assessment methods. This section tests the robustness of the LCI model using sensitivity analysis. Several assumptions used in the LCI model concerning biological CO 2, the use of transfer (a) 100% 80% 60% 40% scenario 0 20% 0% 20% 40% EI'95 EI'99 EPS'00 CSERGE landfilling composting recycling TS-MRF collection (b) 80% scenario 1 (c) 60% scenario 1v 60% 40% 40% 20% 20% 0% 20% EI'95 EI'99 EPS'00 CSERGE 0% 20% 40% EI'95 EI'99 EPS'00 CSERGE 40% 60% 60% 80% 80% 100% (d) 80% scenario 2 (e) 60% scenario 2v 60% 40% 40% 20% 20% 0% 20% EI'95 EI'99 EPS'00 CSERGE 0% 20% 40% EI'95 EI'99 EPS'00 CSERGE 40% 60% 60% 80% 80% 100% Fig. 6. Comparison of the contribution to the total impact by each unit process for each impact assessment method.

15 M.D. Bovea, J.C. Powell / Journal of Environmental Management 79 (2006) stations, and displaced fertilizer, are varied to identify their influence on the results Exclusion of biological CO 2 in the landfill process The CO 2 in the atmosphere can be divided into biological CO 2 and fossil CO 2 depending on the origin. The LCI model applied for the landfilling process has assumed that the CO 2 produced during the landfilling process is biological CO 2, since landfill gas is produced just from the biodegradable fraction of the waste (putrescible, paper and textiles) at a rate of 250 m 3 /ton and from the residue from the composting process at a rate of 100 m 3 /ton. Several authors (Hauschild and Wenzel, 1997; Nielsen and Hauschild, 1998; Finnveden et al., 2000) consider that the biological CO 2 from the landfilling process does not need to be considered as a net contribution to the global warming impact category, since it can be considered as a natural process from the biodegradable fraction of wastes. Therefore in this sensitivity analysis, the effect of excluding the biological CO 2 from the landfilling process has been studied. Therefore in scenarios without energy recovery, CO 2 emissions have not been included, while in scenarios with energy recovery, just CO 2 emissions from the combustion process have been added to the inventory data (107, mg/m 3 ). As expected, the results (Table 17) indicate significant reductions in the contribution to the global warming category compared to the initial LCI model. The global warming indicator has an average reduction of around 25% compared to the initial LCI model, being higher for scenarios without energy recovery (24 and 33% for scenario 1 and 2, respectively) than in those with energy recovery (23 and 19% for 1v and 2v, respectively). In spite of the quantitative differences between results obtained with the four impact assessment methods, the same preference ranking among alternative scenarios, as previously obtained with the initial LCI model, can be established: scenarios with energy recovery (1v and 2v) achieve major improvements compared to baseline, with scenario 1v being better than 2v for all impact assessment methods except for EPS 00, that obtains better results for scenario 2v Exclusion of the transfer station in kerbside collection schemes The initial LCI model assumed that a transfer station is used for all the kerbside schemes and in all the scenarios, although the Waste Integral Plan established the use of a transfer station when the distance from the waste collection point to the next waste treatment facility is higher than 25 km. The effect of excluding the TS has been explored. It was assumed that the same collection truck transported the waste to the corresponding waste treatment facility (MRF or landfill, depending on the scenario). The environmental effects of waste transportation mainly involve the abiotic depletion and ozone layer depletion categories and on a minor scale, the acidification and eutrophication impact categories and global warming. A small increase is produced on the contribution to these impact categories when the TS is excluded from the initial LCI model. Absolute indicators for these impact categories and for the different LCIA methods applied in this study are reported in Table 17 for each alternative scenario, including the percentage difference from the initial LCI model. Table 17 Results of sensitivity analysis: environmental indicator and percentage of reduction compared to the initial LCI model Excluding biological CO 2 Excluding transfer station Fertilizer displacement Impact category LCIA method Impact category LCIA method Impact category LCIA method Global warming indicator Unit scenario 1 scenario 1v scenario 2 scenario 2v kg CO 2 equiv. 165 (K24.3%) K128 (K23.1%) 86.3 (K33.1%) K131 (K19.1%) Eco-Indicator 95 Points K0.27 (K4.5%) K0.45 (K1.2) K0.28 (K3.1%) K0.42 (K1.0%) Eco-Indicator 99 Pt K1.41 (K17.5%) K3.69 (K2.7%) K1.43 (K14.4%) K3.12 (K2.6%) EPS 00 ELUs 42 (K12.1%) 3.24 (K80.6%) 24.7 (K15.7%) K4.02 (K60.6%) CSERGE Euro K32.1 (K11.1%) K43 (K3.5%) K30.3 (K9.0%) K38.5 (K3.1%) Abiotic depletion kg Sb equiv (2.3%) (2.3%) (3.1%) (3.1%) Ozone layer kg CFC-11 equiv. 1.67!10 K5 (7.7%) 1.19!10 K5 (11.2%) 1.47!10 K5 (11.4%) 1.11!10 K5 (14.9%) depletion Acidification kg SO 2 equiv (0.5%) 2.34 (0.8%) 1.63 (1.2%) 2.03 (1.0%) Eutrophication kg PO 3K 4 equiv (2.7%) (2.8%) K0.114 (3.4%) (2.8%) Eco-Indicator 95 Pt 0.22 (0.9%) 0.41 (0.5%) 0.26 (1.1%) 0.40 (0.7%) Eco-Indicator 99 Pt 1.04 (13.3%) 3.54 (4.1%) 1.07 (14.4%) 2.92 (6.1%) EPS 2000 ELUs (0.6%) 3.59 (10.8%) (1.7%) 3.26 (12.1%) CSERGE Euros (1.4%) (0.7%) (1.4%) (1.0%) Abiotic depletion kg Sb equiv (10.2%) (10.2%) (9.8%) (9.8%) Acidification kg SO 2 equiv. K1.81 (0.5%) K2.35 (0.4%) K1.64 (0.6%) K2.04 (0.5%) Eutrophication kg PO 4 equiv. K (23.5%) K0.117 (18.8%) K (22.4%) K0.115 (18.4%) EI 95 Pt K0.22 (3.1%) K0.41 (1.7%) K0.25 (3.1%) K0.40 (2.0%) EI 99 Pt K1.01 (15.8%) K3.50 (5.1%) K1.06 (15.2%) K2.92 (6.1%) EPS 2000 ELUs (2.9%) 4.63 (42.9%) (4.8%) K2.33 (37.2%) CSERGE Euros K28.70 (0.7%) K42.80 (0.5%) K27.60 (0.7%) K38.10 (0.5%)