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ORWARE—a simulation tool for waste management
Resources, Conservation and Recycling 36 (2002) 287–307
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ORWARE —a simulation tool for waste management O. Eriksson a,*, B. Frostell a, A. Bjo¨rklund a, G. Assefa a, J.-O. Sundqvist b, J. Granath b, M. Carlsson c, A. Baky d, L. Thyselius d a
Department of Industrial Ecology, Royal Institute of Technology (KTH), S-100 44 Stockholm, Sweden b Swedish En6ironmental Research Institute (IVL), P.O. Box 21060, S-100 31 Stockholm, Sweden c Department of Economy, Swedish Uni6ersity for Agricultural Sciences (SLU), P.O. Box 7033, S-750 07 Uppsala, Sweden d Swedish Institute of Agricultural and En6ironmental Engineering (JTI), P.O. Box 7033, S-750 07 Uppsala, Sweden Received 19 January 2001; accepted 2 March 2002
Abstract A simulation model, ORWARE (ORganic WAste REsearch) is described. The model is mainly used as a tool for researchers in environmental systems analysis of waste management. It is a computer-based model for calculation of substance flows, environmental impacts, and costs of waste management. The model covers, despite the name, both organic and inorganic fractions in municipal waste. The model consists of a number of separate submodels, which describes a process in a real waste management system. The submodels may be combined to design a complete waste management system. Based on principles from life cycle assessment the model also comprises compensatory processes for conventional production of e.g. electricity, district heating and fertiliser. The compensatory system is included in order to fulfil the functional units, i.e. benefits from the waste management that are kept constant in the evaluation of different scenarios. ORWARE generates data on emissions, which are aggregated into different environmental impact categories, e.g. the greenhouse effect, acidification and eutrophication. Throughout the model all physical flows are described by the same variable vector, consisting of up to 50 substances. The extensive vector facilitates a thorough analysis of the results, but involves some difficulties in acquiring * Corresponding author. Tel.: +46-8-790-93-31; fax: + 46-8-790-50-34 E-mail address: [email protected] (O. Eriksson). 0921-3449/02/$ - see front matter © 2002 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 1 - 3 4 4 9 ( 0 2 ) 0 0 0 3 1 - 9
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relevant data. Scientists have used ORWARE for 8 years in different case studies for model testing and practical application in the society. The aims have e.g. been to evaluate waste management plans and to optimise energy recovery from waste. © 2002 Elsevier Science B.V. All rights reserved. Keywords: Waste management; Material flow analysis; Systems analysis; Life cycle assessment; Simulation model; ORWARE
1. Introduction ORWARE (ORganic WAste Research) is a tool for environmental systems analysis of waste management. It is a computer-based model for calculation of substance flows, environmental impacts, and costs of waste management. It was first developed for systems analysis of organic waste management, hence the acronym ORWARE, but now covers inorganic fractions in municipal waste as well. ORWARE consists of a number of separate submodels, which may be combined to design a waste management system for e.g. a city, a municipality or a company. A first description of the ORWARE model was given by Dalemo et al. (1997). The ORWARE model has been developed in close cooperation between four different research institutions in Sweden, each of which has contributed specific skills and competence to the model: KTH— Royal Institute of Technology, IVL— Swedish Environmental Research Institute, JTI— Swedish Institute of Agricultural and Environmental Engineering and SLU— Swedish University for Agricultural Sciences.
1.1. Applications In the construction of different submodels, the waste management systems of Stockholm and Uppsala have been used as role models. In practice, however, the submodels are generic and may be modified to fit an arbitrarily chosen waste management system, or non-existing future waste management system. The model has been used by municipalities (Dalemo, 1996; Bjo¨ rklund et al., 1999, 2000a) and companies, e.g. Norsk Hydro (Dalemo et al., 1998) to compare organic and mineral fertiliser and by Birka Energi (Eriksson et al., 2000) to compare large-scale incineration with large-scale composting.
1.2. Other models During the last decade, a few models with similar scope as ORWARE have appeared. There is the Swedish model MIMES/Waste (Sundberg and Ljunggren, 1997). Two models have been developed in the UK; the integrated solid waste management (ISWM) model by Procter & Gamble (White et al., 1995), and a model developed by Ecobilan and funded by the UK Environment Agency (Aumoˆ nier and Coleman, 1997). The ISWM model forms the basis for a Canadian
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model funded by the Environment and Plastics Industry Council and the Cooperations Supporting Recycling (Mirza, 1998). In the US, a model has been developed by the Environmental Protection Agency (Weitz et al., 1999). The objectives of these models are similar, to go beyond limited local perspectives and evaluate environmental effects of waste management from a systems perspective. In doing this, the models have one functional unit in common; to handle and treat the waste generated in a certain area and time. All models describe input flows of waste in terms of waste fractions, with only minor differences in characterisation (mainly organics, metal, glass, plastic, paper, incineration ashes). Investment and running costs are also calculated by all models. The system boundaries differ somewhat with regard to the degree of inclusion of up-stream and down-stream processes, and whether multiple functional units are applied as defined in life cycle assessment (LCA) (ISO, 1997). The level of detail in the modelling of waste management processes also differ between the models, so that different degree of site-specificity is allowed, different amounts of data is required, and results of different level of detail can be retrieved from simulations. In addition, the models are developed for different regional characteristics, and will not easily allow adjustments to other regions.
1.3. Aims of the paper The objectives of this paper is to update the model description presented by Dalemo et al. (1997) by presenting the ORWARE model, or rather the approach used, as it looks today. The aim is also to briefly present some of the case studies performed with ORWARE and to point at further model development.
2. Methods and general description of the model All process submodels in ORWARE calculate the turnover of materials, energy and financial resources in the process (Fig. 1). Processes within the waste management system are e.g. waste collection, anaerobic digestion or landfill disposal. Materials turnover is characterised by the supply of waste materials and process chemicals, and by the output of products, secondary wastes, and emissions to air, water and soil. Energy turnover is use of different energy carriers such as electricity, coal, oil or heat, and recovery of e.g. heat, electricity, hydrogen or biogas. The financial turnover is defined as costs and revenues of individual processes. A number of submodels may be combined to a complete waste management system in any city or municipality (or other system boundary). Such a conceptual ORWARE model of a complete waste management system is shown in Fig. 2. At the top of the conceptual model in Fig. 2 there are different waste sources, followed by different transport and treatment processes. The solid line in Fig. 2 encloses the waste management core system, where primary and secondary wastes are treated and different products are formed. With primary waste is understood
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Fig. 1. Conceptual design of a process submodel in ORWARE. The submodel calculates flows of materials, energy and financial resources.
waste entering a treatment process from a waste source, while secondary waste is generated in a treatment process. Thus source separated organic waste is a primary waste, while incineration slag and flyash are secondary wastes.
Fig. 2. A conceptual model of a complete waste management system comprising a number of processes described by different submodels.
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Fig. 3. LCA in ORWARE takes into account core system as well as the up-stream and down-stream systems (Bjo¨ rklund and Bjuggren, 1998).
In the practical implementation of the ORWARE model, all submodels according to Fig. 3 have been modelled in the software MATLAB with its graphical interface Simulink (The Mathworks, Inc.). This allows the connection of different submodels as shown in Fig. 1 to any type of larger unit as shown in Fig. 2. In this way, any type of waste management system may be designed and analysed with the model.
2.1. Material flow analysis in ORWARE ORWARE may be described as a combination of material flow analysis (MFA) (Baccini and Brunner, 1991) and LCA (ISO, 1997). A MFA describes the static situation of different materials flows between different subsystems in a defined system. The model handles a large number of physical flows and may therefore be characterised as a multidimensional material and substance flow analysis (for substance flow analysis cf. van der Voet et al., 1995). Flows such as total solids and polycyclic aromatic hydrocarbons (PAH) as well as single elements such as chlorine and copper may be followed. In the current form of the model, it is possible to evaluate the results from over 50 parameters simultaneously. In practice, however, the amount of parameters that may contribute in a meaningful way is lower due to lack of data or poor data quality.
2.2. Life cycle assessment in ORWARE The MFA carried out in ORWARE generates data on emissions from the system, which is aggregated into different environmental impact categories. This makes it possible to compare the influence of different waste management system alternatives on e.g. the greenhouse effect, acidification, eutrophication and other impact categories. The system boundaries are of three different types; time, space and function. In
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an analysis of a certain system the temporal system boundaries vary between different studies (depends on scope) and also between different submodels. Most of the process data used are annual averages but for the landfill model and the arable land long-term effects are also included. There is a geographical boundary delimiting the waste management system as shown in Fig. 2, whereas emissions and resource depletion are included regardless of where they occur. The system boundaries in ORWARE are chosen with an LCA perspective, thus including in principle all processes that are connected to the life cycle of a product (in this case a waste management system). Our coverage of life cycle impacts covers raw material extraction, refinery, production and use. Construction, demolition and final disposal of capital equipment are not included regarding energy consumption and emissions but are included for economy. This is illustrated in Fig. 3, which shows how a core system (the waste management system) is enlarged in order to include relevant up-stream (e.g. energy generation) and down-stream (e.g. biogas usage) activities and processes. The core system of Fig. 3 corresponds to the part of the conceptual model shown within the solid line in Fig. 2. In ORWARE up-stream material flows, associated with the use of energy carriers in the core system, are included. In a similar way, down-stream flows associated with the spreading of organic fertiliser from biological treatment or biogas utilisation may be included in the analysis. The core processes cause emissions in a defined area while up-stream and down-stream processes may cause emissions at undefined locations. Another aspect of the LCA perspective in ORWARE is the use of functional units. In the ISO standard (ISO, 1997) a functional unit is defined as ‘the quantified performance of a product’. It is thus a measure of the function a product (or a system) is able to fulfil, and is important to define clearly in comparisons of different systems. The main function of a waste management system is to treat a certain amount of waste from the defined area. Other functions, e.g. providing different kinds of products that can be recovered from waste, are also possible. Today, many waste management systems provide energy supply in addition to waste treatment. In other cases, it provides fertiliser, or in most recent years recycled products or materials. In order to achieve a just comparison between different waste management alternatives, functions not present in a certain system have to be compensated for. The compensation of functional units in ORWARE is achieved by expanding the system boundaries to include different so called compensatory processes (Fig. 4). Compensatory processes also have up-stream and down-stream processes. Therefore, each treatment alternative in ORWARE has its own unique design of core system as well as different compensatory systems. This has been illustrated in Fig. 5. The total system comprises the waste management core system, the compensatory system and their related up-stream and down-stream systems. The compensatory system, up-stream and down-stream systems constitute the enlarged system in ORWARE. Either the waste management system or the compensatory system provides the functional units.
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Fig. 4. By expanding the analysis in LCA with a compensatory system, the comparison of different systems can be made more just (Finnveden, 1998).
2.3. Presentation of results in ORWARE Scenarios are often used when analysing different waste management alternatives with ORWARE. In each scenario the input of waste and output of functional units are constant while the design of the system varies. The scenarios are compared for different environmental impact categories, energy consumption and costs. The results are calculated for all parts of the waste management system and compensatory system, but may be analysed from different angles to reveal different interesting aspects of the system. Impact categories may be displayed for either the waste management core system or the total system. Interesting perspectives may be to analyse the relative contribution to total impacts of the waste management system and the compensatory system, or the relative significance of specific processes within the waste management system. It is also possible to display selected emissions like NO2 or substance flows like cadmium. The results may for instance
Fig. 5. Conceptual model of the total system in ORWARE (Eriksson and Frostell, 2000).
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Fig. 6. Results from ORWARE to illustrate presentation of results.
be presented in charts with bars for different treatment alternatives and different impact categories. An example of this is shown in Fig. 6. In Fig. 6 each bar corresponds to one treatment scenario and the sections of the bars represent different processes within the waste management system. In this case eutrophication from a study of hydrogen production from waste is shown. When trying to assess the total impact from an ORWARE simulation it can be difficult to prioritise between six and seven impact diagrams. One solution, which is sometimes used in LCA, is to aggregate impact categories into one unit. But the weighting factors used are often questioned because of the high degree of subjective valuation. One solution to this, which is currently used in ORWARE, is to present all impact categories in one radar diagram as shown in Fig. 7. Each axis represents one impact category and the values of each scenario are connected by a line. All values are normalised to the reference scenario (Incineration, heat), which represents an impact value of 1. In this way it is possible to compare different scenarios for different impact categories in the same diagram.
3. Submodels ORWARE consists of submodels for the core system of waste management and the compensatory system, and their respective up-stream and down-stream processes. The core and down-stream process submodels of the waste management system are unique for the ORWARE model and are presented in more detail while compensatory and up-stream are only described briefly. This documentation of the model is focused as it is implemented today. The models are continually restructured, extended and refined for the purpose of
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providing better results and adjustments to the scope of each study performed. This is an advantage in order to do an appropriate analysis but a disadvantage when it comes to perform an analysis within as short time as possible. A more detailed description of the different submodels including detailed data is available (in Swedish) in Sundqvist et al. (2000).
3.1. Waste sources and waste fractions Activities that generate waste are not included, but the model begins when waste is collected at the source. The sources that can be included are limited only by the availability of data on waste. The sources used so far are households, business and some special wastes from industries. The model handles solid waste, sewage (with/without urine separation) and urine. The household waste is divided into several fractions, e.g.: organic waste, non-combustible waste, combustible waste, cardboard, dry paper, diapers, rubber, laminate, glass, metal, HDPE and LDPE. These fractions (or other fractions according to data available from the inventory) can be combined into a waste stream from a waste source. Each fraction is characterised by a set of parameters describing the chemical composition of the waste, including: – Parameters of environmental relevance: heavy metals, NOx, SO2, HCl, PCB, dioxins, PAH, AOX, CH4, CO, CHX, CO2, BOD, COD, NH3/NH4, P, NO2 − / NO3 − , etc.
Fig. 7. Diagram showing all impact categories from ORWARE in one diagram. In this case the result for comparing incineration with anaerobic digestion of easy degradable organic waste in a Swedish municipality is shown.
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– Parameters of relevance to process performance: C, H, O, N, P, H2O, VS, energy, etc. – Parameters of economic relevance: CH4, N, P, etc. – Parameters that characterise the material recovery: paper, plastic, metals, etc.
3.2. Transports There are different types of vehicle submodels for different types of transports. For collection of waste there are back-packer and front-loader models. For transport of primary and secondary waste like flyash and slag there are three submodels: ordinary truck, truck and trailer and barge for transports at sea. Data on average load, average speed etc. are used as input in all transport submodels. The output is total energy consumption, time consumption and costs. Emissions are calculated from the energy consumption. The economical calculations for the transport models are based on costs for diesel fuel, wages for truck drivers and investment and maintenance costs for the trucks. The model calculates the time consumed and the wage cost is set accordingly. The transport submodel is further described in Sonesson (1996) and in Sonesson (1998).
3.3. Incineration The incineration submodel consists of three parts: pre-treatment, incinerator and air pollution control. The pre-treatment provides baling of the incoming waste which makes it possible to store waste and combust it later. In the incinerator the waste is combusted and the outputs are raw gas, slag and fly ash. The raw gas is led to the air pollution control and the clean gas is released as air emissions. A submodel for flue gas condensing is included which may be used for more efficient energy recovery. The condense water is cleaned before it is emitted. The energy recovered in this submodel is district heating and/or electricity. As for all submodels, site specific data are used as much as possible. When such data are missing, the attempt has been to use data from (1) comparable facilities, (2) other waste incinerators, or (3) reasonable assumptions. Emission factors are calculated from material balances over each process and are either product related (linearly dependant on the incinerated amount of the substance), process related (dependant on the amount of waste incinerated), or threshold related. The last category is modelled to generate a constant emission level depending on some threshold, defined as that legislative threshold values are always kept. This approach is realistic for emissions that are normally adjusted within very narrow limits, e.g. NOx. The reason is usually economic; threshold values must be kept, but further reductions would not be economically motivated. The costs for incineration can be set per kilogram waste treated or per kW h energy generated. The investment cost is set in relation to size of the incineration plant in terms of heat effect. The cost is higher for a combined heat and power
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plant (CHP) than for a heat plant. There are also maintenance costs and costa for additives, i.e. chemicals for air pollution control. The incineration submodel is further described in Bjo¨ rklund (1998).
3.4. Thermal gasification The thermal gasification submodel is primarily based on a pilot facility made by Thermoselect. At the cost of reduced overall energy efficiency, it is designed to minimize environmental impact. Pure oxygen is used instead of air for partial oxidation. This minimises gas volumes and increases the reaction temperature, which prevents formation of chloro-organic compounds. Pure oxygen is energy consuming, but avoiding inert gas load makes the product gas easier to clean and suitable for further processing to for instance hydrogen. High gas temperatures and long residence times in the reactor produce near equilibrium conditions in the syngas. Process heat is primarily supplied by internal heat recovery, but fuel is needed to produce an inert inorganic residual fraction. This model does not include any economy submodel. The thermal gasification submodel is further described in Bjo¨ rklund et al. (2000b).
3.5. Landfill The landfill submodel is divided into five different landfill types; mixed waste, biocell, sludge, fly ash and slag. The submodels are thought to work as Swedish ‘average landfills’, and the site specific adjustments are few. There is a possibility to adjust the efficiency of the landfill gas recovery as well as the type of leachate treatment used. Energy consumption in form of electricity and diesel oil is accounted for and product outcome is biocell. Energy is generated as heat and/or electricity from gas-fired engines, see the description of gas utilisation. Waste landfilled today will cause emissions during a long period of time. A dilemma is how to compare the emissions from the landfill with the instant emissions from the other processes in the system. Just to include instant landfill emissions would be to heavily underestimate the total impact. But if one tries to estimate the total emissions the uncertainty will be large and the time perspective will not be comparable to other processes. As a compromise the future impact from landfilling has been separated in two time periods, the definitions of which are a bit different between the different landfill types: (a) Sur6eyable time: The time until the most active processes in the landfill has ended and the landfill has reached a pseudo steady-state. For mixed waste, sludge and organic waste put in the biocell surveyable time is defined to last until the later part of the methane phase. That means a time frame of about 100 years for mixed waste and 10– 20 years for organic waste in a biocell. In the case of landfilled incineration ash and slag, the surveyable time corresponds to the time needed for highly soluble substances such as alkaline salts to leak out to a large extent.
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(b) Remaining time: The time until all material has been spread out in the environment through gas emissions, leaking, erosion and possible inland ices. The remaining time includes the emissions in a kind of worst scenario. The economy for the landfill is based on data for biocells which have been scaled with respect to the treatment capacity. Costs due to managing the landfill in terms of fuel for the compactor etc. is included. The landfill submodel (biocell not included) is further described in Bjo¨ rklund (1998), Appendix D and the biocell in Fliedner (1999).
3.6. Material recycling So far, submodels for recycling of plastics and cardboard have been developed. The models are based on specific Swedish plants. The model for plastic recycling represents recycling of polyethylene. Of the incoming plastics to the recycling plant, a certain amount is sorted out as reject. The plastic that is recycled gives rise to electricity consumption. The output from the model is emissions to water, waste in the form of sludge and finally plastic granules, which are assumed to replace virgin polyethylene. The cardboard recycling model is based on one of two Swedish cardboard recycling plants. The recycled cardboard needs 15% extra weight to replace virgin cardboard. The cardboard recycling plant give rise to emissions to water, energy related emissions to air, energy consumption and waste in form of biosludge and plastic reject. The material recycling submodel is further described in Sundqvist et al. (2000).
3.7. Anaerobic digestion The submodel for anaerobic digestion is suitable for a thermophilic or a mesophilic process. The model is based on a real treatment plant in Uppsala which is a continuous single stage mixed tank reactor (CSTR). The incoming material is cleared from plastic bags and metals and then fragmentised. The separation will result in a loss of organic material. After hygienisation at 70 or 130 °C the substrate is brought to the digester. The model automatically calculates the energy needed for hygienisation and digestion as well as need of water for adjustment of the TS. After the digestion step, the substrate passes through a heat exchanger and a dewatering equipment. The amount of gas generated is dependent on the composition of different organic compounds as fat, proteins, cellulose, hemicellulose, lignine, rapidly degradable carbohydrates and the retention time. The sludge from the digester is separated into a solid and a liquid phase in the dewatering process. The digestion residue is stored in large covered lagoons in solid or liquid phase. Electricity is consumed for mixing, pumping and drying. The submodel delivers sludge (dry or wet) for spreading and biogas to be combusted. Costs for anaerobic digestion are fixed or related to the treatment capacity. Costs for hygienisation, digester and storage are for example related to size but maintenance costs are almost fixed.
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A more detailed description of the model can be found in Dalemo (1996).
3.8. Composting Three different types of composting facilities are modelled: Large-scale reactor composting with/without gas cleaning Large-scale windrow composting with/without gas cleaning Small-scale composting in households The models are based on the assumption that the composts are well managed, i.e. no failures occur that will give rise to high emissions of methane and other products of anaerobic conditions. All leachate water is returned to the compost. The degradation process is the same for all three compost types except for the degradation speed. The emissions are theoretically the same. The different compost submodels generate the same composition of the compost product when processing the same type of waste. When it comes to energy consumption the reactor compost demands quite lot of electricity, whereas composting in private households does not need energy at all (just some physical power which is not accounted for). Windrow composting is slightly less energy consuming than the reactor compost. The large-scale composting has an option to clean the compost gas from ammonium, NH3, and nitrogen oxides, NOx. The cleaning equipment consists of a condensation step with recycling of condense liquid to the compost process and a biofilter consisting of mature compost. The nitrogen captured in the filter is returned to the mature compost. The reactor compost submodel also gives a possibility to recover some of the heat released during the degradation. For the windrow compost submodel there are costs for land, machinery and other costs related to treatment capacity. For a reactor compost the fixed part of the cost is higher and also extra costs for buildings. The model for home composting uses a cost per ton, which corresponds to investment, costs for the bin. Cost for the time consumed in the household composting is not included. A more detailed description of the model can be found in Sonesson (1996).
3.9. Sewage treatment The sewage treatment submodel consists of screen, sandtrap, pre-sedimentation, biological purification (activated sludge treatment) and chemical purification. The model offers the choice of including nitrogen purification in the activated sludge process. The sludge is thickened and then led out of the model (e.g. to the anaerobic digester). Energy is consumed as electricity for pumping waste water to the sewage plant, aeration and other use. The sewage treatment submodel is further described in Dalemo (1999).
3.10. Gas utilisation Two types of gases can be produced in the core system. From the landfill and the anaerobic digester methane gas is produced and from thermal gasification synthesis
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gas is produced. The biogas can be utilised in biogas vehicles (cars and/or busses), in a biogas combustion engine for generation of heat and/or power and also in a steam reforming process, which turns biogas into synthesis gas. The synthesis gas from steam reforming and thermal gasification can be further processed into hydrogen. The hydrogen can be used in fuel cell vehicles. The biogas needs to be cleaned from CO2 and comprimated before it can be used to fuel vehicles. This refining action needs electricity. The fact that the energy efficiency in lower for biogas vehicles is considered. The gas engine generates about 30% electricity and 60% heat, the remaining 10% is losses. Emissions are given in Dalemo (1996). Cleaning and refining of the biogas is modelled as a fixed cost and pipeline between digester and fuel station is included. The biogas vehicles are more expensive than ordinary vehicles which is accounted for. The cost for the gas combustion engine is fixed. Submodels for steam reforming and fuel cell vehicles are still lacking economy models. The steam reforming submodel includes all the units from biogas cleaning to a final purification using a pressure-swing adsorption (PSA) required to produce hydrogen from biogas. The submodel is primarily based on data and information from the literature with some validations using data from natural gas steam reforming plants elsewhere. The model calculates emissions from biogas cleaning, steam reformer, shift converter, and PSA and the electricity required for two compressors. The process heat for the endothermic reforming reaction is supplied by combusting part of the impure biogas and purge gas in a gas engine with a production of heat and electricity. This model does not include any economy submodel. Further description of the steam reforming submodel can be obtained in Assefa (2000). The data used in developing the model for fuel cell vehicles is based on what researchers predict accounting for various considerations of technical development in car design and fuel cell efficiency. Depending on distinct advances in different vehicle components, the choice of fuel economy would have a dramatic effect on the results from the model. The fuel economies for the fuel cell car and for the petrol car used in this model are 80 mpgeq (miles per gallon equivalent) and 50 mpg (miles per gallon) respectively. Due to lack of data on emissions of the future advanced vehicles, the same emission factors per MJ gasoline as for current vehicles is used. Further information and reference material on the fuel cell vehicle submodel can be found in Bjo¨ rklund et al. (2000b).
3.11. Spreading of residues The submodel for spreading of organic fertiliser is divided into three steps: calculation of spreading areas and transport distances, transport of residues from treatment plant to center of spreading areas and finally the spreading itself. The maximum spreading of residues per hectare is determined from its contents of
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phosphorus and nitrogen. The transport of the residue is performed by an ordinary truck, see description for the transport submodels. The distance to and the area of each spreading area is used as input data and the model calculates the total distance and energy consumption. Two different spreaders are modelled, one for liquid products and one for solid products. The model determines what kind of spreader is needed depending on the dry matter content. The spreading model calculates the emissions from the truck transport and the spreading procedure and also energy consumption for the vehicles. The economy model takes input data as time consumption and fuel consumption from the spreading submodel and calculates wage costs, fuel costs and investment costs for tractors and spreaders based on their leasing costs. The leasing costs are different for dry and wet spreaders. The spreading submodel is further described in Sundqvist et al. (2000).
3.12. Arable land The model calculates the emissions of nitrogen compared to use of mineral fertiliser. Thus, relative rather than absolute values are calculated as in the other submodels. Nitrogen is assumed to exist in three forms: ammonia, nitrate and organically bound. The model gives emissions from mineralisation of organically bound nitrogen during the first year after spreading and the long-term effects of mineralisation. The efficiency with which the crops use the organic fertilisers compared to the mineral fertilisers are 100% for phosphorus, 80% of the mineral nitrogen and 30% of the organically bound nitrogen. The emissions of laughing gas (N2O), nitrate (NO3) and ammonia (NH3) depend on the soil condition, the spreading conditions and climatic region which can be adjusted in the model. The arable land submodel is further described in Dalemo et al. (1998).
3.13. The up-stream and compensatory systems Often the compensatory system coincides with the up-stream process of waste management. For convenience, these systems are therefore described in the same section. For both compensatory and up-stream processes the production is traced back to the cradle, i.e. it includes the effects of raw material extraction, refinery, transports, and production. Energy consumption in each life cycle stage is expressed as primary energy resource. See each specific submodel section for detailed data. Generation of district heating can be included both as an up-stream process to waste management when needed in a waste treatment process, or as a compensatory process if necessary to fulfil a functional unit. Conventional district heating can be generated from biomass, oil or coal. The biomass fired heat production is assumed to come from a CHP fired with wood chips and a overall efficiency of 109% (based on lower heating value). The air emissions from the CHP are allocated the same for electricity and heat. The emissions from coal combustion use the same
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source as for electricity production from coal but with another degree of efficiency, see below. Like district heating electricity generation may be included as both an up-stream process to waste management or a compensatory process. It is possible to use one single source or a combination, a power mix. The different sources in the model are: biomass, hydropower, wind power, nuclear power, natural gases, oil and coal. Data on Swedish facilities are used except for the coal plant where data is used which describes the emissions from an average coal condense power station in Denmark. The degree of efficiency for condense power is 44% and for combined heat and power (when coal is used for heating purpose) 88%. The compensatory models for transports include submodels for diesel busses and petrol cars. The up-stream systems consider the extraction and refinery of the fuels while the core system of these compensatory processes deal with direct effects of operating the vehicles. The fuel consumption for the busses is 0.34 l/km and for the cars the same figure is 0.10 l/km. The submodels for compensatory production of mineral fertiliser covers production of nitrogen and phosphorus. Compensatory plastic production covers the process from virgin resources to plastic granules. The plastic is assumed to be manufactured outside Sweden and represents average European values. The transport of the plastic from Northern Europe to Sweden is included. The submodel for compensatory cardboard production from virgin resources includes forestry and felling, transport of biomass, and production of cardboard pulp. Only the part of the biomass used for cardboard production is accounted for, the rest of the biomass is assumed to be used for other purposes and are therefore not accounted for. The submodel of the compensatory system is further described in Sundqvist et al. (2000).
4. Examples of applications The applications of the models varies between large research projects, minor development studies and for educational purposes. The projects are often made in cooperation with municipalities or companies. Two examples of the latter are further described.
4.1. Comparison of organic fertilisers The aim of this project was to compare production and use of organic fertilisers with mineral fertilisers. Four scenarios were studied: use of mineral fertiliser and incineration of the waste, anaerobic digestion of waste and manure, windrow composting of waste and reactor composting of waste. The waste considered was easily degradable waste from the society, manure from farms and sludge from
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wastewater treatment. The sludge and the manure are directly spread on arable land in all scenarios except for the digestion scenario where the manure is also treated. The environmental and economic consequences were calculated for a large city region (the municipality of Uppsala) and a region with a small community (the municipality of Ystad). The scenarios were evaluated mainly from an environmental point of view with help of LCA methodology. The impact categories studied were global warming potential, eutrophication, acidification and fluxes of heavy metals. The categories of human toxicology and eco-toxicology to water and soil were also studied but the weighting factors and hence the results for these categories are somewhat more uncertain though. Some calculations of financial economy were also performed. Some of the overall conclusions were: Production of mineral fertiliser does not affect results significantly in the studied scenarios, both from the environmental and economic points of view. The waste treatment processes together with emissions from arable land dominate the environmental impact. The net gain of energy from the waste management significantly influences the environmental evaluation.
4.2. Comparison of composting and incineration The aim of this project was to compare large-scale composting with large-scale incineration. Four scenarios were studied: composting of all waste and sludge; mainly composting and a small part of anaerobic digestion; incineration of all waste and sludge; and mainly incineration composting with a small part anaerobic digestion of all waste and sludge. The waste considered was easily biodegradable waste from the society and sludge from waste water treatment. From the composting facility, some type of bio-pellets are spread in forest areas, and from anaerobic digestion the sludge is spread on arable land. The scenarios were evaluated mainly from an environmental point of view with help of LCA methodology. The impact categories studied were global warming potential, eutrophication, acidification, consumption of primary energy carriers, financial economy and environmental economy. Some overarching conclusions were: As long as the amount of heavy metals in society and especially in the food chain is as high as today, incineration combined with land filling of incineration residues is preferable to composting for more or less unsorted easily degradable waste. It is more favourable to dry and pelletise compost than spreading it directly thanks to a lower nutrient leakage in soil. This holds especially true if waste heat is used for drying. Anaerobic digestion and composting could be of great interest if organic waste is source separated.
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5. Discussion
5.1. Model credibility As in all other LCA models and similar tools, large amounts of data with varying quality are handled. It is by many means hard to evaluate the credibility (Bjo¨ rklund, 2000). Most important for the uncertainty is probably some model choices, e.g. compensatory heat etc., and system boundaries. Therefore each case study should include a sensitivity analysis of the most important parameters. The model is constantly verified by using it in cooperation with local participants and by checking the input data in comparison to the results. The ORWARE model has been thoroughly validated in its basic version and the adjustments have consequently been validated as they have been introduced. An improvement of the model would be to characterise and classify the data used, at least for the key parameters, in order to investigate the credibility more thoroughly.
5.2. Applicability The main purpose for the different projects with ORWARE has been to construct a reliable model. Another aim, which has not been fulfilled so far, is to build a user friendly computer program to come in use at the local authorities. To assist the model constructors, the model has been developed in cooperation with Swedish municipalities for the reason of real input data to the models. A second aim has therefore been to assess waste management in different municipalities and evaluate the waste management plans. Recently the model has been used to evaluate waste management related to energy generation. The result has been expressed in terms of energy consumption, environmental impact and economical costs. Another general purpose has been for education. During the years the model has been used for a couple of diploma theses. The students have constructed new submodels or used the model for a case study. This work has been very successful. A simpler version of ORWARE has also been developed in order to bring the knowledge from research to students. The education model has been used at the both universities involved with a good result. The students have studied with different treatment options and compared the results for different system boundaries. The third application has been to use it in research. Besides model construction and case studies of waste management systems a new purpose has recently been developed. The calculation tool has been used in integrated chain management to evaluate the merits and demerits of new technologies. An example of this is a diploma thesis where environmental consequences of turning biogas into hydrogen are estimated. By doing so, waste management can get a stronger connection to new technologies for environmentally sound transports. A lot of money is spent to develop the use of hydrogen for transport use and by linking the waste management to this field the eco-efficiency can be much higher than to use the biogas directly in
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the vehicles. Coming up is also a study of catalytical combustion which is linked to another research project developing the technology while ORWARE is used to evaluate the environmental profits of the new technology. In order to fit into the different needs from the different players it could be wise to develop different versions of the model. The most flexible one should be kept for research work but simpler versions could also find their customers.
5.3. Usefulness Coming back to friendliness to the user it must be declared that ORWARE is a research tool. It is a heavy duty to collect and connect all data needed and also to configurate the system as mentioned. It should rather be seen as a service than as a computer program. By several means waste management is a complex phenomenon and so is also systems analysis. There is always a struggle between being as site specific and detailed as possible and being easy understandable. This dilemma is not a state but a process. To become more user friendly without loosing too much of the flexibility is something to continue to work with. However, in many cases the results of a case study are not the most wanted. The process of getting different players to apply systems thinking is even more worth.
Acknowledgements Funding for the development of ORWARE was provided the Swedish Environmental Protection Agency (SEPA) during the period 1993–1997 through the Swedish Waste Research Council. During the years 1998 and 1999 further development has been financed by the Swedish National Energy Administration. A grateful acknowledge to the former participants of the ORWARE project group Magnus Dalemo, Ulf Sonesson, Thomas Nybrandt, Ha˚ kan Jo¨ nsson (still working with ORWARE for sewage applications) and Karin Melin (former Mingarini). Special thanks to Go¨ ran Finnveden at The Environmental Strategies Research Group (fms) for improvements of the methodology.
References Assefa G, Environmental Systems Analysis of Waste Management —Prospects of Hydrogen Production from Waste for Use in Fuel Cell Vehicles, Master of Science Thesis, Division of Industrial Ecology, Department of Chemical Engineering and Technology, Royal Institute of Technology, Stockholm, Sweden (ISSN 1402 –7615, TRITA-KET-IM 2000:03), 2000. Aumoˆ nier S, Coleman T. Life cycle assessment for waste management planning. Proceedings of Sardinia 97, Sixth International Landfill Symposium, Cagliary, Italy, CISA, 1997. Baccini P, Brunner PH. Metabolism of the anthroposphere. Berlin: Springer, 1991. Bjo¨ rklund A, Bjuggren C, Dalemo M, Sonesson U. Planning biodegradable waste management in Stockholm. J Ind Ecol 2000a;3(4):43 –58. Bjo¨ rklund A. Melaina, M. and Keoleian, G. 2000b. Hydrogen as a Transportation Fuel Produced from
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Integrated Gasification of Municipial Solid Waste: An Examination of Two Intergrated Technologies. International Journal of Hydrogen Energy 26 (2001) 1209 – 1221. Bjo¨ rklund A. Environmental systems analysis of waste management — Experiences from applications of the ORWARE model, Doctoral Thesis, Division of Industrial Ecology, Department of Chemical Engineering and Technology, Royal Institute of Technology, Stockholm, Sweden (ISSN 1402-7615, TRITA-KET-IM 2000:15), 2000. Bjo¨ rklund A, Dalemo M, Sonesson U. Evaluating a municipal waste management plan using ORWARE. Journal of Cleaner Production 1999;7(4):271 – 80. Bjo¨ rklund A. Environmental systems analysis of waste management with emphasis on substance flows and environmental impact, Licentiate Thesis, Division of Industrial Ecology, Department of Chemical Engineering and Technology, Royal Institute of Technology, Stockholm, Sweden (ISSN 14027615, TRITA-KET-IM 1998:16, AFR-Report 211), 1998. Bjo¨ rklund A, Bjuggren C. Waste modelling using substance flow analysis and life cycle assessment, paper 98-A431. Proceedings of the Air and Waste Management Association’s Annual Meeting, June 14 – 18, San Diego, CA, USA, 1998. Dalemo M. Environmental systems analysis of organic waste management —the ORWARE model and the sewage plant and anaerobic digestion submodels, Doctoral thesis, Department of Agricultural Engineering, Swedish University of Agricultural Sciences, Uppsala, Sweden (Agraria 146; AFR-Report No. 239), 1999. Dalemo M, Bjo¨ rklund A, Oostra H, Sonesson U. Systems analysis of nutrient recycling from organic waste. JTI report Kretslopp och avfall No. 15, Swedish Institute of Agricultural Engineering, Uppsala, Sweden), 1998. Dalemo M, Frostell B, Jo¨ nsson H, Mingarini K, Nybrant T, Sonesson U, et al. ORWARE — a simulation model for organic waste handling systems, part 1: model description. Resources, Conservation and Recycling 1997;21:17 – 37. Dalemo M. The ORWARE Simulation Model— Anaerobic Digestion and Sewage Plant Sub-Models, Licentiate Thesis, Department of Agricultural Engineering, Swedish University of Agricultural Sciences, Uppsala, Sweden (Report No. 216), 1996. Eriksson O, Frostell B. 2000. An approach to sustainability assessment of energy systems, Chapter 16 in ‘Building Sustainable Energy Systems –Swedish Experiences’ Swedish National Energy Administration ISBN 91-7332-961-4. Eriksson O, Assefa G, Frostell B, Kuttainen K. Kompostering eller fo¨ rbra¨ nning av husha˚ llsavfall i Stockholm. Stockholm, Sweden: Industriellt Miljo¨ skydd, KTH, 2000 in Swedish. Finnveden G. On the possibilities of Life-Cycle Assessment, Doctoral thesis in Natural Resources Management, Department of Systems Ecology, Stockholm University (fms Report No. 73, IVL Report No. a1199, AFR Report No. 222, ISBN 91-7153-815-1), 1998. Fliedner A. Organic Waste treatment in Biocells — a Computer-based modelling Approach. In: The context of environmental systems analysis, Master of Science Degree Thesis, Division of Industrial Ecology and Division of Land and water Resources, Royal Institute of Technology, Stockholm, Sweden (TRITA-KET-IM 1999:5), 1999. ISO. Environmental Management — Life Cycle Assessment —Principles and Framework. ISO 14040: 1997. Brussels, Belgium: European Committee for Standardisation CEN, 1997. Mirza R. A Life Cycle Inventory Tool for Integrated Waste Management: A Municipal Focus. Proceedings of the Systems Engineering Models for Waste Management International Workshop, 25 – 26 February, Go¨ teborg, Sweden, 1998. Sonesson U. Systems Analysis of Waste Management — the ORWARE Model, Transport and Compost Sub-Models, Doctoral thesis, Department of Agricultural Engineering, Swedish University of Agricultural Sciences, Uppsala, Sweden (Agraria 130), 1998. Sonesson U. The ORWARE Simulation Model-Compost and Transport Sub-Models. Licentiate Thesis, Department of Agricultural Engineering, Swedish University of Agricultural Sciences, Uppsala, Sweden (Report No. 215), 1996. Sundqvist J-O, Baky A, Bjo¨ rklund A, Carlsson M, Eriksson O, Frostell B, et al. Systems Analysis of Energy Recovery from Waste — Evaluation of Energy, Environment and Costs. Case study Uppsala, Swedish Environmental Research Institute, Stockholm, Sweden. (IVL report 1380), 2000.
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Sundberg J, Ljunggren M. Linking two modeling approaches for the strategic municipal waste management planning. The MIMES — Waste Model and LCA. Proceedings of the Air and Waste Management Association’s 90th Annual Meeting Exhibition, June 8 – 13, Toronto, Ontario, Canada, 1997. van der Voet E, Klein R, van Oers L, Huele R, Mulder P. Substance flows through the economy and the environment, part I: systems definition. Environ Sci Pollution Res 1995;2(2):89 – 96. Weitz K, Barlaz M, et al. Life cycle management of municipal solid waste. Int J LCA 1999;4(4):195 – 201. White PrR, Franke M, Hindle P. Integrated solid waste management. A life-cycle inventory. UK: Chapman and Hall, 1995.
www.elsevier.com/locate/resconrec
ORWARE —a simulation tool for waste management O. Eriksson a,*, B. Frostell a, A. Bjo¨rklund a, G. Assefa a, J.-O. Sundqvist b, J. Granath b, M. Carlsson c, A. Baky d, L. Thyselius d a
Department of Industrial Ecology, Royal Institute of Technology (KTH), S-100 44 Stockholm, Sweden b Swedish En6ironmental Research Institute (IVL), P.O. Box 21060, S-100 31 Stockholm, Sweden c Department of Economy, Swedish Uni6ersity for Agricultural Sciences (SLU), P.O. Box 7033, S-750 07 Uppsala, Sweden d Swedish Institute of Agricultural and En6ironmental Engineering (JTI), P.O. Box 7033, S-750 07 Uppsala, Sweden Received 19 January 2001; accepted 2 March 2002
Abstract A simulation model, ORWARE (ORganic WAste REsearch) is described. The model is mainly used as a tool for researchers in environmental systems analysis of waste management. It is a computer-based model for calculation of substance flows, environmental impacts, and costs of waste management. The model covers, despite the name, both organic and inorganic fractions in municipal waste. The model consists of a number of separate submodels, which describes a process in a real waste management system. The submodels may be combined to design a complete waste management system. Based on principles from life cycle assessment the model also comprises compensatory processes for conventional production of e.g. electricity, district heating and fertiliser. The compensatory system is included in order to fulfil the functional units, i.e. benefits from the waste management that are kept constant in the evaluation of different scenarios. ORWARE generates data on emissions, which are aggregated into different environmental impact categories, e.g. the greenhouse effect, acidification and eutrophication. Throughout the model all physical flows are described by the same variable vector, consisting of up to 50 substances. The extensive vector facilitates a thorough analysis of the results, but involves some difficulties in acquiring * Corresponding author. Tel.: +46-8-790-93-31; fax: + 46-8-790-50-34 E-mail address: [email protected] (O. Eriksson). 0921-3449/02/$ - see front matter © 2002 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 1 - 3 4 4 9 ( 0 2 ) 0 0 0 3 1 - 9
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relevant data. Scientists have used ORWARE for 8 years in different case studies for model testing and practical application in the society. The aims have e.g. been to evaluate waste management plans and to optimise energy recovery from waste. © 2002 Elsevier Science B.V. All rights reserved. Keywords: Waste management; Material flow analysis; Systems analysis; Life cycle assessment; Simulation model; ORWARE
1. Introduction ORWARE (ORganic WAste Research) is a tool for environmental systems analysis of waste management. It is a computer-based model for calculation of substance flows, environmental impacts, and costs of waste management. It was first developed for systems analysis of organic waste management, hence the acronym ORWARE, but now covers inorganic fractions in municipal waste as well. ORWARE consists of a number of separate submodels, which may be combined to design a waste management system for e.g. a city, a municipality or a company. A first description of the ORWARE model was given by Dalemo et al. (1997). The ORWARE model has been developed in close cooperation between four different research institutions in Sweden, each of which has contributed specific skills and competence to the model: KTH— Royal Institute of Technology, IVL— Swedish Environmental Research Institute, JTI— Swedish Institute of Agricultural and Environmental Engineering and SLU— Swedish University for Agricultural Sciences.
1.1. Applications In the construction of different submodels, the waste management systems of Stockholm and Uppsala have been used as role models. In practice, however, the submodels are generic and may be modified to fit an arbitrarily chosen waste management system, or non-existing future waste management system. The model has been used by municipalities (Dalemo, 1996; Bjo¨ rklund et al., 1999, 2000a) and companies, e.g. Norsk Hydro (Dalemo et al., 1998) to compare organic and mineral fertiliser and by Birka Energi (Eriksson et al., 2000) to compare large-scale incineration with large-scale composting.
1.2. Other models During the last decade, a few models with similar scope as ORWARE have appeared. There is the Swedish model MIMES/Waste (Sundberg and Ljunggren, 1997). Two models have been developed in the UK; the integrated solid waste management (ISWM) model by Procter & Gamble (White et al., 1995), and a model developed by Ecobilan and funded by the UK Environment Agency (Aumoˆ nier and Coleman, 1997). The ISWM model forms the basis for a Canadian
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model funded by the Environment and Plastics Industry Council and the Cooperations Supporting Recycling (Mirza, 1998). In the US, a model has been developed by the Environmental Protection Agency (Weitz et al., 1999). The objectives of these models are similar, to go beyond limited local perspectives and evaluate environmental effects of waste management from a systems perspective. In doing this, the models have one functional unit in common; to handle and treat the waste generated in a certain area and time. All models describe input flows of waste in terms of waste fractions, with only minor differences in characterisation (mainly organics, metal, glass, plastic, paper, incineration ashes). Investment and running costs are also calculated by all models. The system boundaries differ somewhat with regard to the degree of inclusion of up-stream and down-stream processes, and whether multiple functional units are applied as defined in life cycle assessment (LCA) (ISO, 1997). The level of detail in the modelling of waste management processes also differ between the models, so that different degree of site-specificity is allowed, different amounts of data is required, and results of different level of detail can be retrieved from simulations. In addition, the models are developed for different regional characteristics, and will not easily allow adjustments to other regions.
1.3. Aims of the paper The objectives of this paper is to update the model description presented by Dalemo et al. (1997) by presenting the ORWARE model, or rather the approach used, as it looks today. The aim is also to briefly present some of the case studies performed with ORWARE and to point at further model development.
2. Methods and general description of the model All process submodels in ORWARE calculate the turnover of materials, energy and financial resources in the process (Fig. 1). Processes within the waste management system are e.g. waste collection, anaerobic digestion or landfill disposal. Materials turnover is characterised by the supply of waste materials and process chemicals, and by the output of products, secondary wastes, and emissions to air, water and soil. Energy turnover is use of different energy carriers such as electricity, coal, oil or heat, and recovery of e.g. heat, electricity, hydrogen or biogas. The financial turnover is defined as costs and revenues of individual processes. A number of submodels may be combined to a complete waste management system in any city or municipality (or other system boundary). Such a conceptual ORWARE model of a complete waste management system is shown in Fig. 2. At the top of the conceptual model in Fig. 2 there are different waste sources, followed by different transport and treatment processes. The solid line in Fig. 2 encloses the waste management core system, where primary and secondary wastes are treated and different products are formed. With primary waste is understood
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Fig. 1. Conceptual design of a process submodel in ORWARE. The submodel calculates flows of materials, energy and financial resources.
waste entering a treatment process from a waste source, while secondary waste is generated in a treatment process. Thus source separated organic waste is a primary waste, while incineration slag and flyash are secondary wastes.
Fig. 2. A conceptual model of a complete waste management system comprising a number of processes described by different submodels.
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Fig. 3. LCA in ORWARE takes into account core system as well as the up-stream and down-stream systems (Bjo¨ rklund and Bjuggren, 1998).
In the practical implementation of the ORWARE model, all submodels according to Fig. 3 have been modelled in the software MATLAB with its graphical interface Simulink (The Mathworks, Inc.). This allows the connection of different submodels as shown in Fig. 1 to any type of larger unit as shown in Fig. 2. In this way, any type of waste management system may be designed and analysed with the model.
2.1. Material flow analysis in ORWARE ORWARE may be described as a combination of material flow analysis (MFA) (Baccini and Brunner, 1991) and LCA (ISO, 1997). A MFA describes the static situation of different materials flows between different subsystems in a defined system. The model handles a large number of physical flows and may therefore be characterised as a multidimensional material and substance flow analysis (for substance flow analysis cf. van der Voet et al., 1995). Flows such as total solids and polycyclic aromatic hydrocarbons (PAH) as well as single elements such as chlorine and copper may be followed. In the current form of the model, it is possible to evaluate the results from over 50 parameters simultaneously. In practice, however, the amount of parameters that may contribute in a meaningful way is lower due to lack of data or poor data quality.
2.2. Life cycle assessment in ORWARE The MFA carried out in ORWARE generates data on emissions from the system, which is aggregated into different environmental impact categories. This makes it possible to compare the influence of different waste management system alternatives on e.g. the greenhouse effect, acidification, eutrophication and other impact categories. The system boundaries are of three different types; time, space and function. In
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an analysis of a certain system the temporal system boundaries vary between different studies (depends on scope) and also between different submodels. Most of the process data used are annual averages but for the landfill model and the arable land long-term effects are also included. There is a geographical boundary delimiting the waste management system as shown in Fig. 2, whereas emissions and resource depletion are included regardless of where they occur. The system boundaries in ORWARE are chosen with an LCA perspective, thus including in principle all processes that are connected to the life cycle of a product (in this case a waste management system). Our coverage of life cycle impacts covers raw material extraction, refinery, production and use. Construction, demolition and final disposal of capital equipment are not included regarding energy consumption and emissions but are included for economy. This is illustrated in Fig. 3, which shows how a core system (the waste management system) is enlarged in order to include relevant up-stream (e.g. energy generation) and down-stream (e.g. biogas usage) activities and processes. The core system of Fig. 3 corresponds to the part of the conceptual model shown within the solid line in Fig. 2. In ORWARE up-stream material flows, associated with the use of energy carriers in the core system, are included. In a similar way, down-stream flows associated with the spreading of organic fertiliser from biological treatment or biogas utilisation may be included in the analysis. The core processes cause emissions in a defined area while up-stream and down-stream processes may cause emissions at undefined locations. Another aspect of the LCA perspective in ORWARE is the use of functional units. In the ISO standard (ISO, 1997) a functional unit is defined as ‘the quantified performance of a product’. It is thus a measure of the function a product (or a system) is able to fulfil, and is important to define clearly in comparisons of different systems. The main function of a waste management system is to treat a certain amount of waste from the defined area. Other functions, e.g. providing different kinds of products that can be recovered from waste, are also possible. Today, many waste management systems provide energy supply in addition to waste treatment. In other cases, it provides fertiliser, or in most recent years recycled products or materials. In order to achieve a just comparison between different waste management alternatives, functions not present in a certain system have to be compensated for. The compensation of functional units in ORWARE is achieved by expanding the system boundaries to include different so called compensatory processes (Fig. 4). Compensatory processes also have up-stream and down-stream processes. Therefore, each treatment alternative in ORWARE has its own unique design of core system as well as different compensatory systems. This has been illustrated in Fig. 5. The total system comprises the waste management core system, the compensatory system and their related up-stream and down-stream systems. The compensatory system, up-stream and down-stream systems constitute the enlarged system in ORWARE. Either the waste management system or the compensatory system provides the functional units.
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Fig. 4. By expanding the analysis in LCA with a compensatory system, the comparison of different systems can be made more just (Finnveden, 1998).
2.3. Presentation of results in ORWARE Scenarios are often used when analysing different waste management alternatives with ORWARE. In each scenario the input of waste and output of functional units are constant while the design of the system varies. The scenarios are compared for different environmental impact categories, energy consumption and costs. The results are calculated for all parts of the waste management system and compensatory system, but may be analysed from different angles to reveal different interesting aspects of the system. Impact categories may be displayed for either the waste management core system or the total system. Interesting perspectives may be to analyse the relative contribution to total impacts of the waste management system and the compensatory system, or the relative significance of specific processes within the waste management system. It is also possible to display selected emissions like NO2 or substance flows like cadmium. The results may for instance
Fig. 5. Conceptual model of the total system in ORWARE (Eriksson and Frostell, 2000).
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Fig. 6. Results from ORWARE to illustrate presentation of results.
be presented in charts with bars for different treatment alternatives and different impact categories. An example of this is shown in Fig. 6. In Fig. 6 each bar corresponds to one treatment scenario and the sections of the bars represent different processes within the waste management system. In this case eutrophication from a study of hydrogen production from waste is shown. When trying to assess the total impact from an ORWARE simulation it can be difficult to prioritise between six and seven impact diagrams. One solution, which is sometimes used in LCA, is to aggregate impact categories into one unit. But the weighting factors used are often questioned because of the high degree of subjective valuation. One solution to this, which is currently used in ORWARE, is to present all impact categories in one radar diagram as shown in Fig. 7. Each axis represents one impact category and the values of each scenario are connected by a line. All values are normalised to the reference scenario (Incineration, heat), which represents an impact value of 1. In this way it is possible to compare different scenarios for different impact categories in the same diagram.
3. Submodels ORWARE consists of submodels for the core system of waste management and the compensatory system, and their respective up-stream and down-stream processes. The core and down-stream process submodels of the waste management system are unique for the ORWARE model and are presented in more detail while compensatory and up-stream are only described briefly. This documentation of the model is focused as it is implemented today. The models are continually restructured, extended and refined for the purpose of
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providing better results and adjustments to the scope of each study performed. This is an advantage in order to do an appropriate analysis but a disadvantage when it comes to perform an analysis within as short time as possible. A more detailed description of the different submodels including detailed data is available (in Swedish) in Sundqvist et al. (2000).
3.1. Waste sources and waste fractions Activities that generate waste are not included, but the model begins when waste is collected at the source. The sources that can be included are limited only by the availability of data on waste. The sources used so far are households, business and some special wastes from industries. The model handles solid waste, sewage (with/without urine separation) and urine. The household waste is divided into several fractions, e.g.: organic waste, non-combustible waste, combustible waste, cardboard, dry paper, diapers, rubber, laminate, glass, metal, HDPE and LDPE. These fractions (or other fractions according to data available from the inventory) can be combined into a waste stream from a waste source. Each fraction is characterised by a set of parameters describing the chemical composition of the waste, including: – Parameters of environmental relevance: heavy metals, NOx, SO2, HCl, PCB, dioxins, PAH, AOX, CH4, CO, CHX, CO2, BOD, COD, NH3/NH4, P, NO2 − / NO3 − , etc.
Fig. 7. Diagram showing all impact categories from ORWARE in one diagram. In this case the result for comparing incineration with anaerobic digestion of easy degradable organic waste in a Swedish municipality is shown.
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– Parameters of relevance to process performance: C, H, O, N, P, H2O, VS, energy, etc. – Parameters of economic relevance: CH4, N, P, etc. – Parameters that characterise the material recovery: paper, plastic, metals, etc.
3.2. Transports There are different types of vehicle submodels for different types of transports. For collection of waste there are back-packer and front-loader models. For transport of primary and secondary waste like flyash and slag there are three submodels: ordinary truck, truck and trailer and barge for transports at sea. Data on average load, average speed etc. are used as input in all transport submodels. The output is total energy consumption, time consumption and costs. Emissions are calculated from the energy consumption. The economical calculations for the transport models are based on costs for diesel fuel, wages for truck drivers and investment and maintenance costs for the trucks. The model calculates the time consumed and the wage cost is set accordingly. The transport submodel is further described in Sonesson (1996) and in Sonesson (1998).
3.3. Incineration The incineration submodel consists of three parts: pre-treatment, incinerator and air pollution control. The pre-treatment provides baling of the incoming waste which makes it possible to store waste and combust it later. In the incinerator the waste is combusted and the outputs are raw gas, slag and fly ash. The raw gas is led to the air pollution control and the clean gas is released as air emissions. A submodel for flue gas condensing is included which may be used for more efficient energy recovery. The condense water is cleaned before it is emitted. The energy recovered in this submodel is district heating and/or electricity. As for all submodels, site specific data are used as much as possible. When such data are missing, the attempt has been to use data from (1) comparable facilities, (2) other waste incinerators, or (3) reasonable assumptions. Emission factors are calculated from material balances over each process and are either product related (linearly dependant on the incinerated amount of the substance), process related (dependant on the amount of waste incinerated), or threshold related. The last category is modelled to generate a constant emission level depending on some threshold, defined as that legislative threshold values are always kept. This approach is realistic for emissions that are normally adjusted within very narrow limits, e.g. NOx. The reason is usually economic; threshold values must be kept, but further reductions would not be economically motivated. The costs for incineration can be set per kilogram waste treated or per kW h energy generated. The investment cost is set in relation to size of the incineration plant in terms of heat effect. The cost is higher for a combined heat and power
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plant (CHP) than for a heat plant. There are also maintenance costs and costa for additives, i.e. chemicals for air pollution control. The incineration submodel is further described in Bjo¨ rklund (1998).
3.4. Thermal gasification The thermal gasification submodel is primarily based on a pilot facility made by Thermoselect. At the cost of reduced overall energy efficiency, it is designed to minimize environmental impact. Pure oxygen is used instead of air for partial oxidation. This minimises gas volumes and increases the reaction temperature, which prevents formation of chloro-organic compounds. Pure oxygen is energy consuming, but avoiding inert gas load makes the product gas easier to clean and suitable for further processing to for instance hydrogen. High gas temperatures and long residence times in the reactor produce near equilibrium conditions in the syngas. Process heat is primarily supplied by internal heat recovery, but fuel is needed to produce an inert inorganic residual fraction. This model does not include any economy submodel. The thermal gasification submodel is further described in Bjo¨ rklund et al. (2000b).
3.5. Landfill The landfill submodel is divided into five different landfill types; mixed waste, biocell, sludge, fly ash and slag. The submodels are thought to work as Swedish ‘average landfills’, and the site specific adjustments are few. There is a possibility to adjust the efficiency of the landfill gas recovery as well as the type of leachate treatment used. Energy consumption in form of electricity and diesel oil is accounted for and product outcome is biocell. Energy is generated as heat and/or electricity from gas-fired engines, see the description of gas utilisation. Waste landfilled today will cause emissions during a long period of time. A dilemma is how to compare the emissions from the landfill with the instant emissions from the other processes in the system. Just to include instant landfill emissions would be to heavily underestimate the total impact. But if one tries to estimate the total emissions the uncertainty will be large and the time perspective will not be comparable to other processes. As a compromise the future impact from landfilling has been separated in two time periods, the definitions of which are a bit different between the different landfill types: (a) Sur6eyable time: The time until the most active processes in the landfill has ended and the landfill has reached a pseudo steady-state. For mixed waste, sludge and organic waste put in the biocell surveyable time is defined to last until the later part of the methane phase. That means a time frame of about 100 years for mixed waste and 10– 20 years for organic waste in a biocell. In the case of landfilled incineration ash and slag, the surveyable time corresponds to the time needed for highly soluble substances such as alkaline salts to leak out to a large extent.
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(b) Remaining time: The time until all material has been spread out in the environment through gas emissions, leaking, erosion and possible inland ices. The remaining time includes the emissions in a kind of worst scenario. The economy for the landfill is based on data for biocells which have been scaled with respect to the treatment capacity. Costs due to managing the landfill in terms of fuel for the compactor etc. is included. The landfill submodel (biocell not included) is further described in Bjo¨ rklund (1998), Appendix D and the biocell in Fliedner (1999).
3.6. Material recycling So far, submodels for recycling of plastics and cardboard have been developed. The models are based on specific Swedish plants. The model for plastic recycling represents recycling of polyethylene. Of the incoming plastics to the recycling plant, a certain amount is sorted out as reject. The plastic that is recycled gives rise to electricity consumption. The output from the model is emissions to water, waste in the form of sludge and finally plastic granules, which are assumed to replace virgin polyethylene. The cardboard recycling model is based on one of two Swedish cardboard recycling plants. The recycled cardboard needs 15% extra weight to replace virgin cardboard. The cardboard recycling plant give rise to emissions to water, energy related emissions to air, energy consumption and waste in form of biosludge and plastic reject. The material recycling submodel is further described in Sundqvist et al. (2000).
3.7. Anaerobic digestion The submodel for anaerobic digestion is suitable for a thermophilic or a mesophilic process. The model is based on a real treatment plant in Uppsala which is a continuous single stage mixed tank reactor (CSTR). The incoming material is cleared from plastic bags and metals and then fragmentised. The separation will result in a loss of organic material. After hygienisation at 70 or 130 °C the substrate is brought to the digester. The model automatically calculates the energy needed for hygienisation and digestion as well as need of water for adjustment of the TS. After the digestion step, the substrate passes through a heat exchanger and a dewatering equipment. The amount of gas generated is dependent on the composition of different organic compounds as fat, proteins, cellulose, hemicellulose, lignine, rapidly degradable carbohydrates and the retention time. The sludge from the digester is separated into a solid and a liquid phase in the dewatering process. The digestion residue is stored in large covered lagoons in solid or liquid phase. Electricity is consumed for mixing, pumping and drying. The submodel delivers sludge (dry or wet) for spreading and biogas to be combusted. Costs for anaerobic digestion are fixed or related to the treatment capacity. Costs for hygienisation, digester and storage are for example related to size but maintenance costs are almost fixed.
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A more detailed description of the model can be found in Dalemo (1996).
3.8. Composting Three different types of composting facilities are modelled: Large-scale reactor composting with/without gas cleaning Large-scale windrow composting with/without gas cleaning Small-scale composting in households The models are based on the assumption that the composts are well managed, i.e. no failures occur that will give rise to high emissions of methane and other products of anaerobic conditions. All leachate water is returned to the compost. The degradation process is the same for all three compost types except for the degradation speed. The emissions are theoretically the same. The different compost submodels generate the same composition of the compost product when processing the same type of waste. When it comes to energy consumption the reactor compost demands quite lot of electricity, whereas composting in private households does not need energy at all (just some physical power which is not accounted for). Windrow composting is slightly less energy consuming than the reactor compost. The large-scale composting has an option to clean the compost gas from ammonium, NH3, and nitrogen oxides, NOx. The cleaning equipment consists of a condensation step with recycling of condense liquid to the compost process and a biofilter consisting of mature compost. The nitrogen captured in the filter is returned to the mature compost. The reactor compost submodel also gives a possibility to recover some of the heat released during the degradation. For the windrow compost submodel there are costs for land, machinery and other costs related to treatment capacity. For a reactor compost the fixed part of the cost is higher and also extra costs for buildings. The model for home composting uses a cost per ton, which corresponds to investment, costs for the bin. Cost for the time consumed in the household composting is not included. A more detailed description of the model can be found in Sonesson (1996).
3.9. Sewage treatment The sewage treatment submodel consists of screen, sandtrap, pre-sedimentation, biological purification (activated sludge treatment) and chemical purification. The model offers the choice of including nitrogen purification in the activated sludge process. The sludge is thickened and then led out of the model (e.g. to the anaerobic digester). Energy is consumed as electricity for pumping waste water to the sewage plant, aeration and other use. The sewage treatment submodel is further described in Dalemo (1999).
3.10. Gas utilisation Two types of gases can be produced in the core system. From the landfill and the anaerobic digester methane gas is produced and from thermal gasification synthesis
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gas is produced. The biogas can be utilised in biogas vehicles (cars and/or busses), in a biogas combustion engine for generation of heat and/or power and also in a steam reforming process, which turns biogas into synthesis gas. The synthesis gas from steam reforming and thermal gasification can be further processed into hydrogen. The hydrogen can be used in fuel cell vehicles. The biogas needs to be cleaned from CO2 and comprimated before it can be used to fuel vehicles. This refining action needs electricity. The fact that the energy efficiency in lower for biogas vehicles is considered. The gas engine generates about 30% electricity and 60% heat, the remaining 10% is losses. Emissions are given in Dalemo (1996). Cleaning and refining of the biogas is modelled as a fixed cost and pipeline between digester and fuel station is included. The biogas vehicles are more expensive than ordinary vehicles which is accounted for. The cost for the gas combustion engine is fixed. Submodels for steam reforming and fuel cell vehicles are still lacking economy models. The steam reforming submodel includes all the units from biogas cleaning to a final purification using a pressure-swing adsorption (PSA) required to produce hydrogen from biogas. The submodel is primarily based on data and information from the literature with some validations using data from natural gas steam reforming plants elsewhere. The model calculates emissions from biogas cleaning, steam reformer, shift converter, and PSA and the electricity required for two compressors. The process heat for the endothermic reforming reaction is supplied by combusting part of the impure biogas and purge gas in a gas engine with a production of heat and electricity. This model does not include any economy submodel. Further description of the steam reforming submodel can be obtained in Assefa (2000). The data used in developing the model for fuel cell vehicles is based on what researchers predict accounting for various considerations of technical development in car design and fuel cell efficiency. Depending on distinct advances in different vehicle components, the choice of fuel economy would have a dramatic effect on the results from the model. The fuel economies for the fuel cell car and for the petrol car used in this model are 80 mpgeq (miles per gallon equivalent) and 50 mpg (miles per gallon) respectively. Due to lack of data on emissions of the future advanced vehicles, the same emission factors per MJ gasoline as for current vehicles is used. Further information and reference material on the fuel cell vehicle submodel can be found in Bjo¨ rklund et al. (2000b).
3.11. Spreading of residues The submodel for spreading of organic fertiliser is divided into three steps: calculation of spreading areas and transport distances, transport of residues from treatment plant to center of spreading areas and finally the spreading itself. The maximum spreading of residues per hectare is determined from its contents of
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phosphorus and nitrogen. The transport of the residue is performed by an ordinary truck, see description for the transport submodels. The distance to and the area of each spreading area is used as input data and the model calculates the total distance and energy consumption. Two different spreaders are modelled, one for liquid products and one for solid products. The model determines what kind of spreader is needed depending on the dry matter content. The spreading model calculates the emissions from the truck transport and the spreading procedure and also energy consumption for the vehicles. The economy model takes input data as time consumption and fuel consumption from the spreading submodel and calculates wage costs, fuel costs and investment costs for tractors and spreaders based on their leasing costs. The leasing costs are different for dry and wet spreaders. The spreading submodel is further described in Sundqvist et al. (2000).
3.12. Arable land The model calculates the emissions of nitrogen compared to use of mineral fertiliser. Thus, relative rather than absolute values are calculated as in the other submodels. Nitrogen is assumed to exist in three forms: ammonia, nitrate and organically bound. The model gives emissions from mineralisation of organically bound nitrogen during the first year after spreading and the long-term effects of mineralisation. The efficiency with which the crops use the organic fertilisers compared to the mineral fertilisers are 100% for phosphorus, 80% of the mineral nitrogen and 30% of the organically bound nitrogen. The emissions of laughing gas (N2O), nitrate (NO3) and ammonia (NH3) depend on the soil condition, the spreading conditions and climatic region which can be adjusted in the model. The arable land submodel is further described in Dalemo et al. (1998).
3.13. The up-stream and compensatory systems Often the compensatory system coincides with the up-stream process of waste management. For convenience, these systems are therefore described in the same section. For both compensatory and up-stream processes the production is traced back to the cradle, i.e. it includes the effects of raw material extraction, refinery, transports, and production. Energy consumption in each life cycle stage is expressed as primary energy resource. See each specific submodel section for detailed data. Generation of district heating can be included both as an up-stream process to waste management when needed in a waste treatment process, or as a compensatory process if necessary to fulfil a functional unit. Conventional district heating can be generated from biomass, oil or coal. The biomass fired heat production is assumed to come from a CHP fired with wood chips and a overall efficiency of 109% (based on lower heating value). The air emissions from the CHP are allocated the same for electricity and heat. The emissions from coal combustion use the same
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source as for electricity production from coal but with another degree of efficiency, see below. Like district heating electricity generation may be included as both an up-stream process to waste management or a compensatory process. It is possible to use one single source or a combination, a power mix. The different sources in the model are: biomass, hydropower, wind power, nuclear power, natural gases, oil and coal. Data on Swedish facilities are used except for the coal plant where data is used which describes the emissions from an average coal condense power station in Denmark. The degree of efficiency for condense power is 44% and for combined heat and power (when coal is used for heating purpose) 88%. The compensatory models for transports include submodels for diesel busses and petrol cars. The up-stream systems consider the extraction and refinery of the fuels while the core system of these compensatory processes deal with direct effects of operating the vehicles. The fuel consumption for the busses is 0.34 l/km and for the cars the same figure is 0.10 l/km. The submodels for compensatory production of mineral fertiliser covers production of nitrogen and phosphorus. Compensatory plastic production covers the process from virgin resources to plastic granules. The plastic is assumed to be manufactured outside Sweden and represents average European values. The transport of the plastic from Northern Europe to Sweden is included. The submodel for compensatory cardboard production from virgin resources includes forestry and felling, transport of biomass, and production of cardboard pulp. Only the part of the biomass used for cardboard production is accounted for, the rest of the biomass is assumed to be used for other purposes and are therefore not accounted for. The submodel of the compensatory system is further described in Sundqvist et al. (2000).
4. Examples of applications The applications of the models varies between large research projects, minor development studies and for educational purposes. The projects are often made in cooperation with municipalities or companies. Two examples of the latter are further described.
4.1. Comparison of organic fertilisers The aim of this project was to compare production and use of organic fertilisers with mineral fertilisers. Four scenarios were studied: use of mineral fertiliser and incineration of the waste, anaerobic digestion of waste and manure, windrow composting of waste and reactor composting of waste. The waste considered was easily degradable waste from the society, manure from farms and sludge from
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wastewater treatment. The sludge and the manure are directly spread on arable land in all scenarios except for the digestion scenario where the manure is also treated. The environmental and economic consequences were calculated for a large city region (the municipality of Uppsala) and a region with a small community (the municipality of Ystad). The scenarios were evaluated mainly from an environmental point of view with help of LCA methodology. The impact categories studied were global warming potential, eutrophication, acidification and fluxes of heavy metals. The categories of human toxicology and eco-toxicology to water and soil were also studied but the weighting factors and hence the results for these categories are somewhat more uncertain though. Some calculations of financial economy were also performed. Some of the overall conclusions were: Production of mineral fertiliser does not affect results significantly in the studied scenarios, both from the environmental and economic points of view. The waste treatment processes together with emissions from arable land dominate the environmental impact. The net gain of energy from the waste management significantly influences the environmental evaluation.
4.2. Comparison of composting and incineration The aim of this project was to compare large-scale composting with large-scale incineration. Four scenarios were studied: composting of all waste and sludge; mainly composting and a small part of anaerobic digestion; incineration of all waste and sludge; and mainly incineration composting with a small part anaerobic digestion of all waste and sludge. The waste considered was easily biodegradable waste from the society and sludge from waste water treatment. From the composting facility, some type of bio-pellets are spread in forest areas, and from anaerobic digestion the sludge is spread on arable land. The scenarios were evaluated mainly from an environmental point of view with help of LCA methodology. The impact categories studied were global warming potential, eutrophication, acidification, consumption of primary energy carriers, financial economy and environmental economy. Some overarching conclusions were: As long as the amount of heavy metals in society and especially in the food chain is as high as today, incineration combined with land filling of incineration residues is preferable to composting for more or less unsorted easily degradable waste. It is more favourable to dry and pelletise compost than spreading it directly thanks to a lower nutrient leakage in soil. This holds especially true if waste heat is used for drying. Anaerobic digestion and composting could be of great interest if organic waste is source separated.
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5. Discussion
5.1. Model credibility As in all other LCA models and similar tools, large amounts of data with varying quality are handled. It is by many means hard to evaluate the credibility (Bjo¨ rklund, 2000). Most important for the uncertainty is probably some model choices, e.g. compensatory heat etc., and system boundaries. Therefore each case study should include a sensitivity analysis of the most important parameters. The model is constantly verified by using it in cooperation with local participants and by checking the input data in comparison to the results. The ORWARE model has been thoroughly validated in its basic version and the adjustments have consequently been validated as they have been introduced. An improvement of the model would be to characterise and classify the data used, at least for the key parameters, in order to investigate the credibility more thoroughly.
5.2. Applicability The main purpose for the different projects with ORWARE has been to construct a reliable model. Another aim, which has not been fulfilled so far, is to build a user friendly computer program to come in use at the local authorities. To assist the model constructors, the model has been developed in cooperation with Swedish municipalities for the reason of real input data to the models. A second aim has therefore been to assess waste management in different municipalities and evaluate the waste management plans. Recently the model has been used to evaluate waste management related to energy generation. The result has been expressed in terms of energy consumption, environmental impact and economical costs. Another general purpose has been for education. During the years the model has been used for a couple of diploma theses. The students have constructed new submodels or used the model for a case study. This work has been very successful. A simpler version of ORWARE has also been developed in order to bring the knowledge from research to students. The education model has been used at the both universities involved with a good result. The students have studied with different treatment options and compared the results for different system boundaries. The third application has been to use it in research. Besides model construction and case studies of waste management systems a new purpose has recently been developed. The calculation tool has been used in integrated chain management to evaluate the merits and demerits of new technologies. An example of this is a diploma thesis where environmental consequences of turning biogas into hydrogen are estimated. By doing so, waste management can get a stronger connection to new technologies for environmentally sound transports. A lot of money is spent to develop the use of hydrogen for transport use and by linking the waste management to this field the eco-efficiency can be much higher than to use the biogas directly in
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the vehicles. Coming up is also a study of catalytical combustion which is linked to another research project developing the technology while ORWARE is used to evaluate the environmental profits of the new technology. In order to fit into the different needs from the different players it could be wise to develop different versions of the model. The most flexible one should be kept for research work but simpler versions could also find their customers.
5.3. Usefulness Coming back to friendliness to the user it must be declared that ORWARE is a research tool. It is a heavy duty to collect and connect all data needed and also to configurate the system as mentioned. It should rather be seen as a service than as a computer program. By several means waste management is a complex phenomenon and so is also systems analysis. There is always a struggle between being as site specific and detailed as possible and being easy understandable. This dilemma is not a state but a process. To become more user friendly without loosing too much of the flexibility is something to continue to work with. However, in many cases the results of a case study are not the most wanted. The process of getting different players to apply systems thinking is even more worth.
Acknowledgements Funding for the development of ORWARE was provided the Swedish Environmental Protection Agency (SEPA) during the period 1993–1997 through the Swedish Waste Research Council. During the years 1998 and 1999 further development has been financed by the Swedish National Energy Administration. A grateful acknowledge to the former participants of the ORWARE project group Magnus Dalemo, Ulf Sonesson, Thomas Nybrandt, Ha˚ kan Jo¨ nsson (still working with ORWARE for sewage applications) and Karin Melin (former Mingarini). Special thanks to Go¨ ran Finnveden at The Environmental Strategies Research Group (fms) for improvements of the methodology.
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