HOLIWAST - Deliverable D3-2 Description of …infoterre.brgm.fr/rapports/RP-55006-FR.pdfHOLIWAST -...

HOLIWAST - Deliverable D3-2 Description of simulators of the present state of MSW in

three casesFinal Report

BRGM/RP-55006-FRJuly, 2007

Holiwast Deliverable 3-2

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PRIORITY [policy-oriented research priority SSP/8.1]

SPECIFIC TARGETED RESEARCH OR INNOVATION PROJECT

HOLIWAST

Holistic assessment of waste management technologies.

Contract number: 006509

Deliverable n°D3-2

Description of simulators of the present state of MSW in three cases

Due date of deliverable: 1st August 2006

Actual submission date: 1st July 2007

Start date of project: 1st August 2005 Duration: 2 years

Organisation name of lead contractor for this deliverable: BRGM

Revision: final

Project home page: http://holiwast.brgm.fr

Project co-funded by the European Commission within the Sixth Framework Programme (2002-2006)

Dissemination Level PU Public PP Restricted to other programme participants (including the Commission Services) RE Restricted to a group specified by the consortium (including the Commission Services) RE CO Confidential, only for members of the consortium (including the Commission Services)

Research European Commission


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Key words : Simulation, waste management, Katowice, Turin, Tollose Authors: MICHEL, P., MENARD, Y., VILLENEUVE, J. (2007) – HOLIWAST deliverable 32, Description of simulators of the present state of MSW in three cases. BRGM/RP-55006-FR, p.96, ill.26.

© BRGM, 2007, this document cannot be reproduced without formal authorisation of BRGM.


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SUMMARY

This report presents an assessment of three waste management systems build in part upon the methodological know-how acquired in the course of the AWAST FP5 project. Because it allows a global synthesis of large amounts of information on waste streams and waste transformation processes, the AWAST simulator is used to compare the different integrated management schemes. Three contrasted situations have been considered: a large city, a medium-sized agglomeration, a sparse rural area. Apart from the contrasting situations the case studies are also complementary in terms of the geographic location: Italy (Turin), Poland (Katowice) and Denmark (Tølløse).

The simulations consider the current situation as a reference to evaluate scenarios applying best available technologies. The results of the scenarios are presented in Deliverable 3-3.

The current situation of the waste management is presented in terms of matter and energy "flows" circulating between "processes". It supplies particularly the flows of matter output from the system into the environment. It also supplies the costs associated to the operations and the economical value of the different flows.

In the frame of Holiwast, the simulator has been used for its ability to support the analysis of experimental data. Data were collected using questionnaires, interviews of persons in charge of waste management. The use of this “process modelling” oriented approach helps to qualify these data, using them to calculate coherent material balances, to determine operational performance parameters of treatments, and to fill the gaps using default values.

The results of the simulators representing the current situation in the 3 cases are detailed in 3 separate chapters. Included are: matter balance, off-gas, land use, energy balance, costs.

The 3 cases are not compared in this report. The comparison of scenarios/cases will be the purpose of Deliverable 3.4.


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CONTENTS

1.� FRAME OF THE CASE STUDIES ............................................................................................9�

1.1.� REASONS FOR THE CASE STUDIES ........................................................................................9�1.2.� CASE STUDIES WITHIN THE PROJECT ....................................................................................9�

2.� THE SIMULATION TOOL........................................................................................................11�

2.1.� COMPONENTS OF THE SIMULATOR ......................................................................................11�2.1.1.� Flowsheet. ..............................................................................................................12�2.1.2.� Phase model. .........................................................................................................13�2.1.3.� Models ....................................................................................................................15�2.1.4.� Algorithms...............................................................................................................15�

2.2.� PROCESS MODELS.............................................................................................................16�2.2.1.� Functions of the process models ...........................................................................16�2.2.2.� Collection................................................................................................................18�2.2.3.� Transport ................................................................................................................20�2.2.4.� Transfer station ......................................................................................................22�2.2.5.� Sorting plant ...........................................................................................................23�2.2.6.� Incineration .............................................................................................................25�2.2.7.� Composting ............................................................................................................29�2.2.8.� Landfill ....................................................................................................................32�

2.3.� METHODOLOGY OF A SIMULATION STUDY ............................................................................39�

3.� SYSTEM DEFINITION.............................................................................................................41�

3.1.� THE ADMINISTRATIVE LIMITS AND THE SYSTEM BORDERS .....................................................41�3.2.� THE INDICATORS AND THE STREAMS DEFINITIONS ................................................................41�3.3.� IMPORTS AND ALLOCATION OF PRESSURES AND OUTPUTS....................................................42�

4.� KATOWICE CASE STUDY......................................................................................................43�

4.1.� METHODOLOGY .................................................................................................................43�4.1.1.� Data collection........................................................................................................43�4.1.2.� Data treatment........................................................................................................45�

4.2.� WASTE MANAGEMENT SYSTEM OF KATOWICE .....................................................................46�4.3.� WASTE GENERATED...........................................................................................................46�4.4.� WASTE TREATMENT DETAILS ..............................................................................................47�

4.4.1.� Collection................................................................................................................47�4.4.2.� Sorting plant ...........................................................................................................48�4.4.3.� Mechanical biological treatment plant (MBT) .........................................................48�4.4.4.� Incineration .............................................................................................................48�4.4.5.� Results....................................................................................................................49�

5.� TURIN CASE STUDY..............................................................................................................55�


5.2.� WASTE MANAGEMENT SYSTEM OF TURIN ............................................................................57�5.2.1.� General information................................................................................................57�

5.3.� WASTE GENERATED...........................................................................................................59�5.4.� WASTE TREATMENT DETAILS ..............................................................................................61�

5.4.1.� Collection................................................................................................................61�5.4.2.� Sorting plant ...........................................................................................................63�5.4.3.� Results....................................................................................................................64�

6.� TØLLØSE CASE STUDY ........................................................................................................69�


6.2.� WASTE MANAGEMENT SYSTEM OF TØLLØSE........................................................................71�6.3.� WASTE GENERATED...........................................................................................................72�6.4.� WASTE TREATMENT DETAILS ..............................................................................................73�

6.4.1.� Collection................................................................................................................73�


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6.4.2.� Biological treatment................................................................................................73�6.4.4.� Results....................................................................................................................75�

7.� CONCLUSION.........................................................................................................................82�

LIST OF FIGURES

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1. FRAME OF THE CASE STUDIES

1.1. Reasons for the case studies

The Holiwast project aims at:

1) providing a multidisciplinary (environmental, economic, social) comparison of different waste management technologies;

2) identifying how the most appropriate technologies can be implemented within an integrated waste management framework, for different socio-economic contexts;

3) evaluating the opportunity of policy instruments for promoting these technologies and support decision-makers in waste management.

These two last objectives set the assessment of technologies in the global context of real waste management systems. So far, the main decision criteria for qualifying the “best available technology” (BAT) may be not only a comparison of different installations made to identify the “best achievable” criteria (emissions for example), but also reflect the influence of the global organisation (emissions depend on what remains in the “residual waste”).

The case studies are based on real data matched with the respective social-cultural frame conditions. The approach sets in a first attempt the “zero point” conditions of the studied case, and in these conditions, it is further extrapolated what could be the advantage of introducing a “BAT”. The building of scenarios to be simulated for diffusion of waste treatment technologies and management practices, and assessment of the economic and social consequences will give support for selection of the most promising technologies (best practice).

One of the last goals is also the assessment and evaluation of various policy instruments pertaining to waste including the achievement of the respective parts of the waste management hierarchy with regard to material-oriented waste policy/legislation

1.2. Case studies within the project

Holiwast is built on 6 technical work packages.

The first (WP1) evaluates the existing policy instruments related to waste management in terms of their effectiveness in reducing environmental impacts, reflecting upon the waste management hierarchy. The second (WP2) lists effective but low-cost waste treatment technologies that are currently adopted or planned including an evaluation of current optimised schemes for source separation. It singles out other technologies (“emerging” technologies) for which application, albeit not diffused yet, may be considered as “mature” and whose diffusion may be fostered by relevant EU or country-specific legislation and strategies. These two work-packages are mainly “individual” assessments, concentrating on a “one by one” evaluations. Anyway, to cope with the number of “individuals”, the case studies serve as a guide starting with policies and technologies used in the present situation and examining its potential improvements.


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The aim of the three following work packages (WP3 to WP5) is to complete and extend these assessments by putting technologies in a real context. This broader approach will help measuring the costs/benefits, costs/effectiveness and socio-economic consequences of pushing (integrating) BAT in an existing waste management system, thus moderating (or enhancing) the individual technologies criteria with criteria due to the elements of the context. These work-packages focus on 3 case studies to be simulated for three contrasting “regions” in Europe, based on real, available data, and only complemented by default values from literature and research studies.

Three contrasted situations have been considered: a large city, a medium-sized agglomeration, a sparse rural area. Apart from the contrasting situations the case studies are also complementary in terms of the geographic location: Italy (Turin), Poland (Katowice) and Denmark (Tølløse).

The assessment of the three cases build in part upon the methodological know-how acquired in the course of the AWAST FP5 project. Because it allows a global synthesis of large amounts of information on waste streams and waste transformation processes, the AWAST simulator is used to compare the different integrated management schemes at the scale of a city or a rural area. The simulations (WP3) consider the current situation as well as scenarios applying best available technologies (based on findings of WP2). The case studies will include the assessment of environmental efficiency (WP4) and the economic and social consequences in case of diffusion of certain waste treatment technologies (WP5).

The three work-packages WP3, WP4 and WP5 are soundly interlinked.

WP6 represents the synthesis of findings but has a much broader scope. The findings are expressed in a decision aid tool for waste policy making, particularly in the field of promoting the BAT, not specific of the cases studied. So even if the case studies represent the major part of the work, they are only intended to supply examples derived from real contrasted situations to feed the design of the final decision aid tool.


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2. THE SIMULATION TOOL

The AWAST simulator was issued from the AWAST 5th FP project. It is based on process analysis, including energetic and economic aspects, of the whole management system: collection, transport, recycling, biological treatment, thermal treatment and landfill. The software allows to adapt best practices and to build strategies for sustainable municipal solid waste management, disposal and reuse in cities or rural areas. This tool, thanks to its flexibility and adaptability to the local context, enables cities and industrial operators throughout the European Community to:

� evaluate the present situation in terms of waste processing efficiency and cost, energetic balance, residual streams, etc;

� accompany, control and re-orient the choices;

� define and plan sustainable degrees of progress;

� improve the implementation of the concept of integrated municipal solid waste management.

With the simulator, WP3 initiates the assessment with the scope definition, the model calibration and the simulation of the real cases in Poland, Italy and Denmark. The simulations of optimised situations using BAT are done for the three cases.

2.1. Components of the simulator

A simulator basically allows getting a representation of a given situation in terms of matter and energy "flows" circulating between "processes". By changing some key parameters of the system (either in input flows or in processes), it calculates the new material and energy balances. It supplies particularly the flows of matter output from the system into the environment. Additionally, the simulator supplies the costs associated to the operations and the "value" of the different flows.

The simulator does not integrate in itself the interpretation of its results. It remains an advanced calculator containing functions that can manipulate experimental data, calculate coherent material balances, sizes and settings of unit-operations, simulate plant operation and display results in tables and graphs.

The AWAST simulator combines the following elements:

The flowsheet describes the system in terms of successive unit operations and material streams. This flowsheet can reflect various scenarii so they can be compared against given criteria. It takes into account numerous system features to describe the physical (sorting plant) as well as functional (sorting of glass) elements.

The phase model describes the materials handled by the system (raw waste, products, reagents, water, etc.) so that unit operations and plant performance, products and reagents quality (grades and undesirable element level) can be evaluated. The description of the phases is critical for analysing and optimising the system, as it imposes the type and quantity of data necessary to feed the simulator. For real applications, it has to be simple enough to face the general lack of data, but complete enough to be able to handle the available data. This statement reinforces the vital importance of procedures to acquire field data, including sampling protocols.

Mathematical models for each unit operation (collection, transport, biological treatments, thermal treatments, landfills) formalises the current scientific knowledge about the unit operation, and its level of complexity depends on the data available and the


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targeted objectives (i.e. flowsheeting, unit operation sizing, or optimisation). The model parameters - dimensions, settings and calibration factors - are set to “default values” and can be calculated or validated from field data. The models can evolve as the knowledge on the processes improves without prejudice to the simulator structure. Short description of the models is given in paragraph 2.2.

A set of algorithms for data reconciliation, model calibration, unit operation sizing, full material balance calculation, power consumption and costs calculation is interfaced with a set of data representation tools. As a result, the plant simulator constitutes a highly efficient communication vector between the different actors who play a part in the system operation and evolution.

2.1.1. Flowsheet.

The flowsheet is a drawing of waste flows circulating through “operations” of waste management. In the example depicted in Figure 1 below, mixed waste goes to incineration, biowaste to composting, separate collections to a sorting plant, bulky waste to landflill. This is a rather common situation that is often translated in statistics as “% of waste generated” to “Treatment”. This figure shows nevertheless that these statistics should account the following factors:

• Feed to incineration is augmented by sorting plant refuse and composting plant refuse,

• Feed to landfill is augmented by incineration refuse, • Separate collection do not provide feed to recycling (existence of a refuse), • Different modes of separate collection may have different performance for

recycling.

Figure 1: Example of flowsheet within waste simulator


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a) This very simple example raises the following remark: the tons treated are not the tons generated, therefore leading to problems for “allocating” treatment performances per ton generated.

In order to sort out this problem, the indicators concerning material balance used further in this report are defined as:

• Recycling (matter) = output from sorting plants + mono-product selective collections directly send to recycling + all metals extracted in plants

• Recycling (organic) = home composting + all inputs to composting plants – refuse of composting plants

• Waste to Energy = all inputs to thermal treatments with energy recovery (incl. refuses from other plants) – bottom ashes – fly ashes

• Re-use of bottom ashes = used bottom ashes

• Disposal = waste generated – matter recycling – organic recycling – waste to energy – re-use of bottom ashes.

b) There may be several inputs to treatments, therefore leading to detailed investigations for each treatment; and as far as refuse from previous treatment is identified as feed of another, it leads to a “chain of performances”. In the example, the refuse of the sorting plant may be highly calorific and if sorting performance (expressed as the quantity of refuse) varies from 5 to 30% of sorting plant input, this leads to a change in the incineration performance (kWh/t). As well, sorting performance may also depend on the collection performance per mode of collection (expressed as the quantity of impurities in the collected streams). One difficulty in building the flowsheet of a real system is to represent that dependence tree which is difficult to get from global data (as those obtained from the above described indicators) or from operations reports (as they do not necessarily reflect the “allocation” of performances to the flows taken into account in the flowheet.

c) Another point concerns the level of “aggregation” in the representation. This is particularly linked to collection, but may also be considered for treatments. Collection of mixed waste in the above example is represented as “one” operation. In most cases, this collection is made at different frequencies for different zones (6 days per week in the city centre, twice a week in the suburbs,…). As well, separate collection may be implemented in many different ways (either bring or door to door collection, either for individualised materials as “plastics” or for multi-materials as “packaging”. Another dimension appears with the operator of collection: several operators (public or private) may share the territory (on the administrative area of Katowice, not less than 17 operators were identified). It is often a practical decision (depending on available data and budget of the study) and expert decision (depending on the potential interest of complexity) to aggregate in a single operation the complexity of real operations.

As a whole, the flowsheet drawing is one of the most difficult task of the simulator building. It often brings a rather complex graph which is difficult to understand (at least at decision level) which contains “simple enough” representation of operations to be fed by field data and “complex enough” to be able to account for interactions between operations.

2.1.2. Phase model.

The phase model is a qualitative description of data that are figured out in the flows. These data are used by models for the calculations of matter transformations. The phase model for waste management in Holiwast is heritated from the AWAST project in which was considered the possibility to have in one flow 3 phases (waste, water, gas). The


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waste phase is described by 4 size classes and 9 components, each component being further subdivided in 20 substances (using the terminology of MFA1) (see Figure 2).

Figure 2: Example of the table description of the phase waste in AWAST simulator (the components are wood, paper, glass, Fe metals, NFe metals, plastics, textiles, biowaste, others ; the substances are H, Cfossil, Corg, N, O, S, Cl, F, P, Fe, Al, Pb, Zn, Cd, Hg, Cr, As, Cu, H20, others)

The water phase contains the components that may appear in the system as reagents (i.e. Ca(OH)2, CaCO3, NaOH, ACTIVATED C, COKE, NH3/SNCR, NH3/SCR, CaCl2, CaSO3, WATER). The gas phase is mainly described by components that appear in emissions (i.e. O2, H2O, CO org., CO fossil, CO2 org., CO2 fossil, CH4, NO2, SO2, F2, Cl2, HCl, Cd, Hg, Ni, Pb, Zn, Dioxins, N2). All these components (in the water and gas phases) are also described by chemical elements identical to those of the waste components in order to be able to make material balances at the level of elements.

This phase model rather complete was defined during AWAST because most of the data to be supplied are “accessible” in most countries at national level. Each input stream of the simulator is supplied using this description. Nevertheless, the description of waste according to this frame is seldom possible using local data. It was established during AWAST some default values of all these arrays for the most frequently encountered waste flows. These are called the “waste matrices”. These cover “residual or mixed waste”, separately collected: glass, metal, biowaste, paper, plastic, textile, batteries, bulky waste, chemicals, end of life vehicles, WEEE, fluorescent tubes, medicines, and: oil and fat, road waste collected by sweepers, sewage sludge, sewer waste, cemetery waste, garden and park waste, manually collected road waste, market waste.

In most cases, only quantities are known at local level. Sometimes mixed waste composition is available. In fact, the standard practice of simulator build up is to “input” the waste matrix in all drawn flows and to “complete” the data set with known flowrates and compositions.

Input flows are the only ones necessary to describe quantitatively to run the simulator. If other flows are known (as it is generally the case for treatment products), they are used to adjust the models. The next paragraph introduces both concepts of “direct” and “reverse” simulation.

1 MFA – AWAST DeliverableXXXX


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2.1.3. Models

The models constitute the main added value of the simulator. They are described in details in the next paragraph.

2.1.4. Algorithms

Direct simulation.

AWAST is powered by a direct sequential algorithm which chains the process models one after each other. To simplify, the simulator calls the first model’s routine, feed it with inputs, the model calculates the outputs (dotted flows in the Figure 3), then the simulator calls the second model, etc. When all the models have been called, all flows have been calculated. This run is named “iteration”. The simulator proceeds with iterations until a convergence criteria is reached (sum of the squares of the differences between flows of two successive iterations < small value).

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Figure 3: Principle of direct simulation: continuous lines represent “input data” ie input flows and process models, dotted lines represent “results of calculations” ie output flows.

Reverse simulation.

When it happens that both input and output flows of an operation (a process) are known, reverse simulation helps to “adjust” the model of that operation so that when this model is used in the direct mode, its calculated outputs are as close as possible to the initial output data.

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Figure 4: Principle of reverse simulation: continuous lines represent “input data” ie input and output flows, dotted lines represent “adjusted models”.

Reverse simulation is not systematic. It is made for models which need adjustments and if all necessary data are available.


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It remains nevertheless a means to adjust general models with local data, giving as a result models keeping their predictive power but adapted to a specific situation.

Both direct and reverse simulations are used in the frame of “simulation methodologies”. The methodology for the Holiwast case studies is presented later in this chapter.

2.2. Process models

2.2.1. Functions of the process models

The process models have three functions:

� knowing the input flow and process parameters, they calculate the output flows,

� they calculate the energy consumption and production,

� they calculate the production costs.

These three aspects are interlinked: energy production depends on waste composition; costs depend on plant size and tons treated. As explained in deliverable 3.1, the models of waste management operations in AWAST introduce some understanding of main phenomena occurring so that their results may be less dependant on “mean data”. The challenge is to be as close as possible to “real” operations, using as less as possible “field data”, but anyway being able to beneficiate from them when available. To compensate the general lack of field data, and also from the poorness of the state of the art in understanding macro-phenomena of operations, default values are used.

Operation

Matter model

Feed(*) Outputs (*)

Energy modelFuel

Emissions to air(*)

Cost model Private costs

ElectricitySteam

Emissions to water(*)

Emissions to soil(*)

Local economicdata

ElectricitySteam

Operation parameters•Mandatory•Optional

Land use

Water(*)Air (*)

Inputs Outputs

Adjustment parametersAWAST default values

Operation

Matter model

Feed(*) Outputs (*)

Energy modelFuel

Emissions to air(*)

Cost model Private costs

ElectricitySteam

Emissions to water(*)

Emissions to soil(*)

Local economicdata

ElectricitySteam

Operation parameters•Mandatory•Optional

Land use

Water(*)Air (*)

Inputs Outputs

Adjustment parametersAWAST default values

(*) refers to quantity and composition data.

Figure 5: Main functional areas of a process model.


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Principle of the models.

The “operation” area contains the scientific knowledge on process operation: it represents the “engine” that transforms inputs into outputs. In AWAST, this engine seeks to be as predictive as possible. As explained in D3-1, the mathematical representation of an operation remains to date limited to (by) an efficiency criteria resulting from a compromise between “use” and “efforts”. Ideally, the operation model should be able to predict all outputs just knowing for example the input flowrate. This is the common approach of many tools developed in recent years relying on strong databases of the so-called “transfer coefficients” or ratios per functional unit. When applied to real case situation, this approach is often misleading and is not able to reproduce real data. Most studies and data on plants performances show very wide intervals in all aspects of operation (matter, energy, costs). Among the numerous reasons for this failure, a main weakness is the lack of “explanation” of process performances in matter balance, energy balance and costs related to input flows characteristics, process design and process operation.

The “matter model” tends as far as possible to deduce outputs (output flows and emissions) from input and process characteristics. In most models, it is based on two fundamental representations of phenomena: separation based on physical characteristics (size, density, etc) and transformation based on “reactions” including either components or chemical elements. The matter model addresses “main” phenomena for which results are easily measurable and data are easily obtained from operator’s data. As an example, composting is represented by a “reaction” transforming a proportion of carbon in each (dry) waste category into CO2. This proportion is given as a “default value” of an “operation parameter”. If the quantity of compost in output is known, the default value may be adjusted to consider local performance. At the moment, the model is not advanced enough to predict the transformations of Hydrogen and Nitrogen and their split between gaseous and liquid emissions. For the concern of providing emission data, the matter model uses “default values” of typical emissions compositions.

The “energy model” treats both consumption and production. In most operations where no energy production is made, the model basically calculates the emissions due to the combustion of fuel and reports the electricity and steam consumptions given in model’s inputs. When these consumptions are not given in inputs from plant data, default values are used. Concerning energy production, two routes are well developed in the models: heat exchange in the boiler of an incineration plant, completed by turbine/alternator group if electricity is produce, and combustion of biogas coming from anaerobic digestion or landfill. In both cases, energy production is treated by the energy model according to information supplied by the mater model (quantity of heat or quantity and composition of biogas). Emissions to air are treated for incineration by the matter model and for biogas combustion by typical emission data supplied in the “default values”.

The land use is deduced from the matter model in the landfill operation model. In general, the land occupation of an operation is related to the capacity trough a non linear relation. The land occupation per ton treated tends to decrease when capacity increases. To date, this relation is not established with confidence. The default value is supplied in most models as a specific ratio in m2/t of capacity, giving more an order of idea than a precise value. The land use is calculated as the land occupation divided by the life time of the plant.

The “cost model” is an attempt to introduce in waste management the concepts of chemical engineering for calculation of production costs. This concept is based on a precise terminology of cost items, on an inventory of the pieces of equipment, their size and price according to the plant capacity, on an inventory of all consumptions (labour, energy, reagents, maintenance) according to the tons treated and at last on the accounting for all surroundings (administration, sales of products, cost of residues,…). During AWAST project, the cost models were established by statistical analysis of questionnaires collected on existing plants. Coefficients relating investment/capacity, maintenance/investment, labour and energy/tons treated, etc. were determined.


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As in all statistical approach, the field of validity of these coefficient remains the field on which they were determined (mainly French, German, Norwegian, Austrian data), leaving poor chance for precision when trying to extrapolate. In Holiwast, the Polish and Italian cases needed adjustments of the models coefficients.

Use of the models.

A number of parameters concerning the operation are mandatory: they must be fed to the “operation parameters” from field data. To collect these data, a questionnaire has been set up for each operation. Examples of these questionnaires received from Katowice are given in annex1. They require for precise technical information and must be filled by the plant operator. Data from questionnaires are used in the simulators when available. If no field data is available, the mandatory parameters for an operation are “transposed” from a similar (or supposed so) case already modelled in AWAST.

For a better appreciation of the results presented in next chapters, the following paragraphs review the models used in the simulators for case studies and give details about the share of results obtained by “modelling” and “literature data”.

2.2.2. Collection

The definition of a model able to represent a complete collection scheme in the varying situations that can be met in Europe has been a real challenge. The organisation of the numerous parameters necessary to describe the different collection areas and mode, but also the design of an interface with default values in databases and appropriate interaction with the user has led to a specific model structure. The collection model can be used either to assess performance criteria for a given situation (as the amount of waste collected per loader per working hour for each waste flow), or to assess the means necessary to achieve a new collection objective (as the number and type of containers, the number and type of vehicles and workers to collect a new flow)2

Outputs.

One output flow corresponds to feed flows.

Emissions to water and soil.

None.

Emissions to air.

They are deduced from the fuel consumption.

Knowing the kilometres, the type(s) of vehicle(s) and fuel(s), the emissions are calculated by default for the existing situation using the following CORINAIR data:

2 Villeneuve, J., Michel, P., Ménard, Y., Fehringer, R., Brandt, B., Daxbeck, H., (2003) AWAST Deliverables D25, D26, D27, D28: Documented models for predicting material, energy and economic balance for all channels, http://awast.brgm.fr


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Type: Truck 1, 16 t Consumption Emissions CO2 CO HC Particles SOx NOxUrban slow (l/100km) 20 (g/km) 671.67 18.8 2.75 0.95 0.91 8.7Urban fast (l/100km) 15 (g/km) 671.67 18.8 2.75 0.95 0.91 8.7Road (l/100km) 12 (g/km) 576.45 7.3 0.76 0.82 0.76 7.4Highway (l/100km) 16 (g/km) 472.53 4.2 0.6 0.66 0.62 6Type: Truck 2, 30 t CO2 CO HC Particles SOx NOxUrban slow (l/100km) 25 (g/km) 1097.05 18.8 5.8 1.6 1.46 16.2Urban fast (l/100km) 20 (g/km) 1097.05 18.8 5.8 1.6 1.46 16.2Road (l/100km) 15 (g/km) 1005.4 7.3 2.6 1.4 1.31 14.8Highway (l/100km) 20 (g/km) 904.96 4.2 2.3 1.25 1.18 13.5Exhaust fumes for boat CO2 CO HC Particles SOx NOx

(goe/t/km) 6 (g/kg fuel) 4186 28.57 7.14 3.1 2.3 50Exhaust fumes for train CO2 CO HC Particles SOx NOx

(goe/t/km) 10 (g/kg fuel) 796 4.4 1.79 0.58 0.63 8.88 Table 1: typical air emission data used in the collection and transport models

Energy and fuel consumption.

Basically, the idea is to gather precise enough data on the area, the waste flow(s) to collect and the collection mode and organisation to calculate the number of vehicles and containers required, the time necessary and the kilometres driven. This part of the calculation is aimed at supplying plausible results in case no field data are given. Field data are often difficult to get, either because the company is private or because municipal workers may not be specifically identified, depending of the accounting system. This part of the model calculates (or uses if known) the collection efficiency in t/h or t/km. This information is often the key point of the “plausible” economic balance of collection.

The energy consumption is calculated from the heating value of the different fuels:

Vol.mass(g/l) LHV (MJ/l)Super 750 32.02Diesel 835 35.35Gas 1.28 0.0377GPL 1.28 0.105

Table 2: Low heating value of different fuels

Costs.

Knowing the number of vehicles and time, the number of employees is calculated. The costs are assessed using economic data (salaries, costs of containers, vehicles…). They are calculated by a “cost model” designed during the AWAST project3 4.

The costs models generally relate investment cost to capacity and operating costs to tons treated. They are made of a number of “parameters” giving typical relations between costs items (maintenance is a percentage of Investment for example). Practically, these parameters have default values but may be adjusted to fit with real data.

For collection, the basic cost calculation is the following:

3 André Le Bozec (2003) Deliverable 6: Methodology for the determination of production costs and full costs of Municipal Solid Waste treatments, http://awast.brgm.fr, 4 André Le Bozec (2003) Deliverable 5&7: Costs models for each municipal solid waste process, http://awast.brgm.fr


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The so-called “cost factors” are typically adjustment variables and can be used to fit real costs data. This adjustment has been necessary for all three case studies.

2.2.3. Transport

For each flow of material transported, the ‘transport model’ calculates the total distance to be covered for different types of travels (urban, road, motorway) and the corresponding fuel consumption.

The model can use different constraints to calculate the fuel consumption and the atmospheric emissions. These constraints are:

� the frequency (trips/year);

� the storing capacity at the transfer station (tons);

� the type of truck.

The emissions to air of transports is rapidly evolving. The regulations allowing to control the atmospheric pollution due to gases emitted by vehicles concern both the direct emissions and the directives aimed at defining the fuel quality, particularly on their sulphur and lead content (85/210/CEE, 93/12/CE and 98/70/CE).

The regulations on direct gaseous emissions concern all types of vehicles. Particularly applying to trucks are the directives 88/77/CEE, 91/542/CEE, 96/01/CE , 99/96/CE, 2001/27/CE, also belonging to respectively Euro 1, 2, 3, 4, 5 standards. These standards set limits for CO, Hydrocarbons, NOx, particles.

On the mean time, numerous national and European studies have been conducted to measure the real gaseous emissions on vehicles in use and fed a database on the “emissions of vehicles in real use”.


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The analysis of these data supplied the emissions factors of each category of vehicle. The synthesis of this work is presented in the MEET5 project and its results have contributed to the development of the COPERT III6 methodology. This methodology allows the modelling and calculation of mean road transport emissions using a number of parameters as the age of vehicles, the type of trip, the distance, the fuel, etc.

Using this methodology, the INRETS has published a report7 that give emissions values for trucks and a forecast of these values according to regulations in use and vehicles in use in which references for data have been used for AWAST in scenario evaluations.

So for existing situations, the values used are those supplied in Table 1 and for scenarios, the values are shown in the following tables.

Fuel CO NOx COV PM CO2

Unit t t t t t million t 1970 5 400 155 78 937 254 837 60 440 19 079 17 1975 6 528 586 88 625 318 677 70 175 21 896 20 1980 7 354 814 93 350 369 584 76 356 23 381 23 1985 7 504 938 89 733 385 534 75 524 22 881 23 1990 8 645 255 97 530 453 186 84 507 25 307 27 1995 8 164 522 80 458 390 212 71 563 21 604 26 2000 9 386 389 62 109 309 233 58 105 14 468 30 2005 10 810 329 47 016 238 731 45 245 8 823 34

2010 11 732 916 35 483 173 191 33 175 4 245 37 2015 12 421 625 30 578 115 611 25 464 2 024 39 2020 13 143 478 30 174 93 671 23 351 1 279 42 2025 13 938 881 31 794 91 852 24 078 1 228 44

Table 3: Emissions from road transport – trucks (1/3)

SO2 Cd Cu Cr Ni Se Zn

Unit t kg kg kg kg kg kg 1970 4 291 54 54 268 375 54 5 364 1975 5 194 65 65 325 454 65 6 492 1980 5 857 73 73 366 512 73 7 321 1985 5 981 75 75 374 523 75 7 477 1990 6 895 86 86 431 603 86 8 619 1995 6 524 82 82 408 571 82 8 155 2000 5 655 94 94 471 660 94 9 424 2005 872 109 109 545 763 109 10 895

2010 237 119 119 593 830 119 11 852 2015 251 126 126 628 879 126 12 563 2020 266 133 133 665 931 133 13 298 2025 282 141 141 705 987 141 14 104


5 MEET : Methodology for calculating transport emissions and energy consumption - DG Transport, Commission Européenne - 1999

6 COPERT III : Computer Programme to calculate Emissions from Road Transport - Methodology and emission factors Leonidas Ntziachristos and Zissis Samaras, ETC/AEM, With contributions from: S. Eggleston, N. Gorißen, D. Hassel, A.-J. Hickman, R. Joumard, R.Rijkeboer, L. White and K.-H. Zierock - November 2000 7 Directives et facteurs agrégés d’émission des véhicules routiers en France de 1975 à 2025, Charlotte Hugrel, Robert Joumard, INRETS, Rapport LTE n° 0611, Juin 2006


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CH4 COVNM N2O

Unit t t t 1970 334 4 855 60 1975 372 5 411 66 1980 332 4 833 59 1985 278 4 030 53 1990 220 3 169 51 1995 168 2 403 51 2000 125 1 778 52 2005 103 1 464 56

2010 97 1 385 61 2015 100 1 431 67 2020 0 0 0 2025 0 0 0


In the model, these data are converted to g/l of fuel consumed.

The data from Table 1 identifies different emissions regimes for different types of trips (urban slow, urban fast, road, motorway whereas the above data show the evolution of emissions with time. The simulations combine both approaches. The reference data for existing situation are taken for year 2000 (assuming a mean age of vehicles of 5 years).

The cost calculation is done using a ratio in euro/(ton.km) given by the user.

2.2.4. Transfer station

The main aim of the model is to calculate the costs. It is designed from a publication from ADEME and uses data supplied in the guide for revision of departmental plans (http://www.ademe.fr/collectivites/Dechets-new/Politique-planif/Plans/Guide.htm) Outputs:

Same as inputs. Emissions to water and soil.

Not significant.

Emissions to air.

They are deduced from the consumption of fuel (Table 1). Energy consumption

Energy consumption on a transfer station is mainly due to loaders fuel consumption and compaction equipment. Plant data from Wisard software report the following values:

Unit Chosen Min MaxFuel l/t 0.5 0.2 0.91Electricity kWh/t 1.5 0.5 49 Table 6: Energy consumption per ton of input waste on a transfer station

Land use

The default value used in the model is deduced from the above mentioned ADEME publication: the surface area of the transfer station is 1 m2/t.


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The lifespan of the station is considered to be 15 years. For a 20000 t/year station, the default value for the land use is 1300 m2/year. Private costs

Reference values are: Investment: 1000 k€/20000t Operation: 16 €/t Yearly cost per ton for a 20000 t/year transfer station: 19 €/t It is to be noted that costs expressed in €/t strongly depend on plant capacity and tonnage treated. The model expresses the following type of relation:

Transfer station

0

20

40

60

80

100

120

140

160

180

200

0 10000 20000 30000 40000 50000 60000 70000 80000 90000 100000

t/year

€/t

Figure 6. Specific treatment cost for a typical transfer station

2.2.5. Sorting plant

Outputs

The model is essentially a splitter were a recovery from the total input per waste category is defined for each output (Figure 7).

Figure 7: example of split coefficients of input to each output (1=refuse, 2=paper, 3=glass,

4=metals, 5=plastics)


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The model further calculates the number of belts necessary to achieve the sorting of the different input flows according to the Eco-emballages method8 and advices the user on plant design and capacity. Emissions to water and soil.

Not significant.

Emissions to air.

They are deduced from the consumption of fuel (Table 1). Energy consumption

Energy consumption of the sorting plant is due to loaders fuel consumption and electricity consumption by equipment. Plant data from Wisard software report the following values used as default values in AWAST, unless the user specifies different ones:

Unit Chosen Min MaxFuel l/t 1.7 0.3 6Electricity kWh/t 22 3 22

Table 7: Energy consumption per ton of input waste on a sorting plant

Land use

The default value used in the model is 2 m2/t for a small plant (<6000 t/year) and 1 m2/t otherwise. These values correspond to real plants in France. Private costs

The cost model for a sorting plant is built on a typology of plants depending on capacity and mechanisation level:

Capacity: Mechanisation level (*):Min t/year Max t/year 1 2 3 4

3000 13000 10000 2 2 2

10000 23000 3 3 323000 60000 3 3 460000 4 4 4 4 .

(*) 1=only manual sorting, 2 = one sorting equipment (overband), 3 = Overband + one pre-sorting equipment, 4 = one or several mechanical sorting equipment

Figure 8: type of sorting plant.

For each type of plant, different default values of coefficients are used in the calculation of cost components. The structure of the model is:

• TCC = Total capital cost = Cfc (investment cost) + Cnid (capital not invested directly in the plant: Land, working capital, start up)

o Investment cost: Cfc = IEC (installed equipment cost) + ODC (Other direct costs: building, civil engineering, roads, networks) + IPC (Indirect costs: studies, supervision of works)

• Investment cost is calculated as: Cfc = k.IEC

8 Concevoir, construire et exploiter un centre de tri, Eco-Emballages, Janvier 2002


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• Operating cost: Cop = m(DC + M + IC) with: m = margin or overheads DC = Direct costs (personnel + electricity + supplies) M = Maintenance (repairs and renewal) IC = indirect costs (charges, insurance,…)

• Labour: L = Lsorters + Lothers

• DC = a.Labour, M = % of Investment, IC = %(DC+M)

• R = Revenues (sell of compost)

• CR - Management of residues

If D is the life time (years) of the plant, the final results are given as:

• Raw production costs = TCC/D + Cop

• Net production costs = TCC/D + Cop + CR - R

All coefficients (k, m, a, the different percentages) can be adjusted if precise information if known on an existing plant. Using default AWAST parameters, standard French wages for personnel, and considering of “type 3” plant, the cost model gives that relation:

Sorting plant - raw production costs

0

20

40

60

80

100

120

140

160

180

0 10000 20000 30000 40000 50000 60000

t/year

Euro

/t

Figure 9: raw production costs of a sorting plant using default values

In our case, the cost of Labour represents about 70% of the total cost. It the plant is of “type 4”, the total cost may be reduced between 10 and 20%.

2.2.6. Incineration

The incineration model is made of several unit operations presented in Figure 10.


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Figure 10: unit operations considered in the incinerator model

Depending on the objective of the study and the level of details of the available data, each unit operation may be adjusted. The following paragraphs present the approach used in Holiwast, mainly relying on “default” data. The model is shaped to calculate a precise material and substance balance. The use of default data nevertheless introduces a bias in the substance balance because emissions are calculated according to standards and not as a result of “reactions” representing the transformations of matter in all operations.

Outputs

The furnace is considered as a chemical reactor where waste is burned with air to produce bottom ash, gas and fly ash. The model differentiates the behaviour of each waste category, as shown in Figure 11. This makes the model sensitive to the waste composition.

F urnace

Boiler Turbine

Alternat or Electricit y

Bottom ashes

Steam Steam

Smoke t o gas treatment

Water + steam

Smoke Process water

Air

Waste

Gas treatment Water + reagents

Emissions to air

Water treatment Emissions to water

Filter cake


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Emissions to water

The default approach is to consider that the exhaust water is released into the environment and so far, complies with the standards of the water directive. The following values are taken into account:

Unit Default Min Max

Quantity l/t dry matter 500 400 1300

Component Unit Max valueOCD mg/l 125Hydrocarbons mg/l 10Phenols mg/l 0.1AOX mg/l 1F- mg/l 50As mg/l 0.1Cd mg/l 0.2Pb mg/l 0.5Cr (VI) mg/l 0.1Hg mg/l 0.05CN mg/l 0.1Heavy metals mg/l 15Solids mg/l 30

(*) Heavy metals = Al, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Sn, Zn Table 8: default values for emissions to water

The quantities come from the wizard database. The concentration limits come from the water directive.

Emissions to air

The emissions to air are the result of the gas treatment chain. The model considers the


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following steps: Electrostatic precipitator (ESP), spray tower, stack. The complete flowsheet of the incineration process is presented in Figure 12

Steamto environment

Fly ash to environment

Waste 2

Imported waste

Grosses Fe

Cake to environment

Waste1

Water to the environment

Scrap to environment

Reagents

Reagentaddition

Reagentaddition

Bottom ash to environment

Flue gas to environment

Water

Cake

Fly ashSteam

Bottom ash

Flue gas

Steam water

Combustion air

Water stock

pH regulationFilterpress

DecantationNeutralization

Bottom ash stock

OverbandMillScreen

Bottom ashcooler

Stack

Spray tower 1ESP

FurnaceTurbine-alternatorgroup

Plant Flowsheet of Project: Esp

1

2

3

4

56 7

8

9

1011

1213

14

15

16 17

18

19

20 21

22

23

24

25

26

27

28

29

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

2122

23

2425

26

27

28

29

30

31

32

33

34

35

36

37 38

39

40

41

42

43

4445

46

47

48 49

50 51

52

53

54

55

56

57

Figure 12: flowsheet of an incineration plant

As a result of the different steps of flue gas cleaning, the model calculates the composition of the emissions. It is nevertheless unable to predict the some emissions, particularly dioxins. To overcome this gap, the final stage (the stack) sets the emissions to standards limits of legislation if they are not specified by the user. These standard limits are as follows:

Component Unit Max valueDust mg/Nm3 10COT mg/Nm3 10HCl mg/Nm3 10HF mg/Nm3 1SO2 mg/Nm3 50NO2 mg/Nm3 200Cd mg/Nm3 0.05Hg mg/Nm3 0.05Sb+Pb+As+Cr+Co+Cu+Mn+Ni+V mg/Nm3 0.5Dioxins+Furanes ng/Nm3 0.1

Table 9: standard values for air emissions (incineration directive)


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Energy balance

Depending on the plant considered, the model can take into account the energy recovered in three different ways:

� Only the furnace with the calculation of mass transfer during combustion from the waste feed to the bottom ash and flue gas (including fly ash) outputs.

� Furnace and heat exchanger/boiler where the combustion energy is converted into steam energy through the heat exchanger/boiler device.

� Furnace and heat exchanger/boiler and turbine/alternator group where the steam energy is converted into mechanical energy through the turbine, and then in electrical energy through the alternator. The residual steam energy can be used into a heating circuit.

These calculations are based on a number of parameters given by the user (questionnaire) or by the database of default values: process water fed to the process, low heating value of each waste category, a set of temperature and pressure data in the boiler, in input and output of the smoke and the steam. The default values come from real plant data (Strasbourg and !vry incinerators).

The model does not calculate the fuel consumption. The default value issued from the Wisard database is 0.2 l/t of raw waste.

Land use

Referring to real case data for several 200000 t/year plants, the default value for land occupation used in the model is 0.2 to 0.25 m2/t. This value is divided by the life time of the plant to get a land use per year.

Private costs

The cost model is quite elaborated, made of 10 equations related to the different cost items (see AWAST deliverable 5&7), using basic local economic data (salaries, reagents, costs of electricity…) and 10 principal adjustment parameters.

Several confidential studies conducted with AWAST report a cost around 50 €/t for French incinerators above 200000 t/year. This cost includes: (investment+financial costs)/life time + operating costs + costs of the management of residues (bottom ash and filter cake) –receipts from reuse of bottom ashes – receipts from energy production. This cost excludes the land purchase. It appears that life time is an important parameter and that it is generally longer than “life time expectancy” foreseen in projects, as the plants are often subject to modernisation actions introducing different ratios on investment/life time.

2.2.7. Composting

During the AWAST project, extensive sampling campaigns have been done to collect the data necessary to feed a database of process models. The models concern biological degradation itself and all surrounding physical treatments. The approach was further improved to relate the emissions to degradation of organic matter using a simple description of main “reactions”.


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Some physical operations in pre or post treatment (trommel classification) were deeply investigated (Michel et al., 2003)9, but most of the models remain based on typical “transfer coefficients”.

Outputs

As in the incinerator model, the matter transformation is based on the concept of “chemical reactions” where a specified percentage of each category is reacting (Figure 13) and within each waste category, the substances are transferred from this reacting part to components of another phase (gas in this case).

Figure 13: unaltered part of waste categories

Chemical reaction from “waste” to “gas”

1 Corg ----> 1 CO2 org. 2 H ----> 1 H2O 2 O ----> 1 O2 1 H2O ----> 1 H2O

This simple “matter model” is used to calculate the quantity of compost produced and the quantity of CO2 and H20 produced in the air emissions. The percentages in Figure 13 are adjusted to real data (compost production).

Emissions to water

During composting operation, the leachate is generally re-circulated in the process. The composition of leachate according to wizard database is as follows:

Unit Default Min MaxCOD mg/l 572 50 1200Solids mg/l 205 110 337Heavy metals mg/l 0 0.4 0.68S mg/l 65 65 65P mg/l 3 0.8 7.8Cl mg/l 158 147 160N mg/l 40 30 45K mg/l 185 185 185Mg mg/l 3 3.3 3.3Ca mg/l 32 32 32

Table 10: typical leachate composition from composting

9 Michel, P., Villeneuve, J., Wavrer, Ph., Brochot, S., Morvan.B., Mallard.P. (2003) Aide au dimensionnement et à l'optimisation d'une installation de tri-compostage : modélisation des trommels., Déchets Sciences et Techniques, n° 29 pp. 3-7


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The leaks are treated before release in environment. The default values considered in the model are:

Unit Default Min MaxQuantity l/t Raw matter 1.5 1 3

Component Unit Default N Kjeldhal (g/t dry matter) 0.1P (g/t dry matter) 0.002K (g/t dry matter) 0.5

Table 11: emissions to water after leachate treatment

All other parameters are considered identical to those given in Table 8 (default values for emissions to water from incineration).

Emissions to air

The global air emissions are given by the matter model in terms of CO2org, H2O, O2. To complete these calculations, the following default data from CEMAGREF/ADEME study10 are used, except for NO2 where no data is reported in this study:

Component Unit Default Min MaxCH4 (g/t dry matter) 1905 476 9524CO2org (*) (g/t dry matter) 200000 110000 220000N20 (g/t dry matter) 323 16 403Nox(**) (g/t dry matter) 353NH3 (g/t dry matter) 1000 500 1000COV (g/t dry matter) 1500 300 3150

(*) this reference value is used to fit the other to CO2org calculation by the matter model (**) Ecoinvent data

Table 12: emissions to air from composting

Energy consumption

The fuel consumption originates from the CEMAGREF/ADEME study. The electricity consumption comes from the wizard database.

Unit Chosen Min MaxFuel l/t 4 1 6Electricity kWh/t 50 15 100

Table 13: energy consumption from composting

Land use

The default value for land occupation used in the model is 0.3 to 1 m2 per input ton, excluding the storage of compost. This value is divided by the life time of the plant to get a land use per year.

Private costs

The cost model is built on a typology of plants mainly related to the technology used for the fermentation phase.

10 Impacts environnementaux de la gestion biologique des déchets. Bilan des connaissances. Final report of the ADEME study n°0375C0081


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The investment cost, Cfc, is related to the cost of installed equipment (IEC) using the relation: Cfc = k.IEC.

Typical ratios for IEC given for specific capacity (IECr) are supplied in the model as well as default values of k (Table 14, Table 15).

Ratio k€/10000t IECr Min MaxSW - Static Windrow 301 189 412TW - Turned Windrow 578 458 698TW biowaste 525 366 684TW green waste 656 474 839RD - Rotating Drum 740 658 822EH - Enclosed Halls 1200 830 1560CR - Container Reactor 1680 1366 1994TR - Tunnel Reactor 590 103 1075

Table 14: typical values of installed equipment costs in k€/10 000t for a composting plant

k kmin kmaxSW - Static Windrow 2.2 1.4 2.9TW - Turned Windrow 2.5 2.2 2.8RD - Rotating Drum 1.8 1.6 1.9EH - Enclosed Halls 2.2 1.8 2.6CR - Container Reactor 4.1 3 5.3TR - Tunnel Reactor 1.2 1.17 1.2

Table 15: typical factor between installed equipment costs and investment costs

Operating costs take into account direct costs (DC = labour +energy), maintenance (M = % of investment costs) and indirect costs – charges, insurance,… (IC = % of investment). The specific consumptions of workers (technicians and administrative) and energy (electricity and fuels) are given per type of plant. The raw production cost is Investment/Life time + operating costs. The net production cost is decreased by the price of compost selling and increased by the price of management of residues. As a whole, many factors need to be adjusted to real cost data. If they are not available, the cost calculation remains at a level of precision of mean European values (typically 40 €/t as net production cost).

2.2.8. Landfill

From a critical review of existing models, a selection was made for the AWAST simulator based on a compromise between the “cost of use” of models (specific data requirement) and the associated level of accuracy obtained. Two models were fixed according to their use: a global assessment of a waste management system and the detailed assessment of a case study that requires some experimental data.

Both models include the following aspects, with a higher degree of precision for the second one:

� Atmospheric emission which contribute to the greenhouse effect

� Energy recovery from biogas

� Leachate infiltration to environment and its pollutant potential to groundwater

� Disposal costs (investments linked to landfill design, leachate and biogas treatment)


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Outputs

Apart from emissions, there is no output in terms of material flow.

Emissions to water

The modelling of the leachate generation is based on a hydrological balance to predict the water inflow, which enters in contact with waste, which involves rainfall, evapo-transpiration, run-off, type of surface sealing and water retention by the soil layer. From the water inflow, the leachate, which can be collected at the bottom of the landfill, is assessed based on the part which goes through waste rapidly along preferential paths, the part which is retained by waste and the water released by waste following a first order kinetic11. As default values for the estimation of leachate generation, several studies12 agree on around 20% of the rainfall during the cell exploitation and 0.2% when the cell is covered.

When enough data are available, the balance between water inflow and leachate collected may give and estimation on the infiltration in soil (leachate generated not collected) which may be one of the most serious emission in old landfills. When data are not available, the default assumption in the model is that the landfill has been operated according to the “best practices” and that there is no infiltration (all the leachate is collected).

To our knowledge, there is no reliable model to predict the composition of the leachate as also it varies with time. The model proposes an indicative range of values collected by ADEME13, given in Table 16.

There is anyway a regulatory obligation to treat the leachate before release to the environment or to a water treatment plant. In any case, the final emission to water must be within the limits given in Table 8.

��Guyonnet D. & AL. (1998) Accounting for water storage effect in landfill leachate modelling,

Waste Management and Research�12 AGHTM, 2000 La décharge a un avenir: le centre de stockage. Dossier AGHTM. TSM 2000;1:5-54

13 Les installations de stockage de déchets ménagers et assimilés, Techniques et Recommandations, ADEME Editions, Paris, 1998


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Parameter Unit Min MaxConductivity us/cm 1400 17100pH 3.7 8.8Eh mV -330 163Solids mg/l 550 2000COD mg/l O2 31 100000DBO5 mg/l O2 2 900000NTK mg/l 7 5000NH4 mg/l 2 3870NO2 mg/l 0 25NO3 mg/l 0 845PO4 mg/l 0.16 154K mg/l 2.8 3770Na mg/l 0 7700Ca mg/l 60 7200Mg mg/l 3 15600Cl mg/l 4.7 5000SO4 mg/l 1 3240Fe mg/l 0 5500Cu mg/l 0 10Cd mg/l 0.005 17Cr mg/l 0 18Ni mg/l 0.02 79Mn mg/l 0.06 1500Hg mg/l 0.0003 0.0012Pb mg/l ? 0.5Zn mg/l 0 1000As mg/l 5 1600

Table 16: limit values from literature of leachate composition.

Emissions to air

The modelling of the landfill gas generation is based the EMCON MGM model reviewed by Liberti (Liberti et al, 1993). Two separate equations are used to describe the gas generation rate (exponential rise and exponential decline). This model predicts the quantity of gaseous components resulting from organic carbon degradation, according to a given ratio CO2/CH4. A proportion of the gas generated is collected (see Figure 14) and either valorised, flared or vented out (if the flowrate is too small).

The emissions to air result of these 4 possible channels. Up to date, there is no simple and reliable model able to predict the composition of these emissions. The composition of the gas generated is varying over time14. Default values coming from literature review and measurements on sites have nevertheless been proposed by INERIS15,16 both for biogas (Table 17) and for combustion gases (Table 18).

14 Bockreis A., Steinberg I., (2005) Influence of mechanical-biological waste pre-treatment methods on the gas formation in landfills. Waste Management 25 (2005) 337-343. 15 Caractérisation des BIOGAZ – Bibliographie, Mesures sur sites, INERIS DRC-02-27158-AIRE-n°316b-JPo 16 Etude comparative des dangers et des risques liés au biogaz et au gaz naturel, INERIS-DRA n°46032, 2006 –JBr/biogaz/1


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�

��

��

��

Collectionand

extractionprocess

� ��

��

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Energyrecoveryprocess

Gas flarestacks

� ��

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Figure 14: biogas management in he landfill model

LiteratureMin Max

CH4 (%) 45 45 61CO2 (%) 32 39 55N2 (%) 17 0 31O2 (%) 2H2O (%) 4H2S (mg/m3) 20 0 2600Aromatics (mg/m3) 1Halogenated organics (mg/m3) 100Cl- (mg/m3) 45F- (mg/m3) 20S (mg/m3) 200Metals (mg/m3) 3 0 5

Measure

Table 17: Major components of landfill biogas

For combustion gases, limit emission values are imposed by legislation for major components17 and different types of installations < 20 MWth (Table 18). The value of 20 MWth corresponds to the transposition in France of the European legislation on large combustion installations18. For bigger installations, the text refers to a more general legislation19 concerning all combustion installations, telling that limit emissions values must be given on a case per case basis in the exploitation authorisation (Table 19). These limits must not exceed those allowed in Table 18.

17 Circulaire du 10 décembre 2003 relative aux Installations classées : installations de combustion utilisant du biogaz. 18 Directive 2001/80/EC of the European Parliament and of the Council of 23 October 2001 on the limitation of emissions of certain pollutants into the air from large combustion plants [Official Journal L 309 of 27.11.2001]. 19 Arrêté du 2 février 1998 relatif aux prélèvements et à la consommation d’eau ainsi qu’aux émissions de toute nature des installations classées pour la protection de l’environnement soumises à autorisation (JO du 3 mars 1998)


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Combustion equipment

O2 grade on dry basis (%) SO2 NOx Particles VOC CO

Boiler: 2 to 10 MWth 3 No limit 225 50 50 250Turbine: 2 to 20 MWth 15 No limit 225 150 50 300Engine: 2 to 20 MWth 5 No limit 525 150 50 1200Flare: 2 to 20 MWth 10 150All equipment < 2MWth No limit

Limit emission values (mg/m3)

Table 18: limit emission values for biogas combustion installations

Limit concentration (mg/m3) (**)

Dust kg/h =<1 100>1 40

CO No limitSO2 kg/h > 25 300NOx kg/h > 25 500N20 No limitHCl kg/h > 1 50HF g/h > 500 5COV kg/h > 2 110Cd g/h of (Cd+Hg+Tl) > 1 0.05Hg g/h of (Cd+Hg+Tl) > 1 0.05Tl g/h of (Cd+Hg+Tl) > 1 0.05Cd+Hg+Tl g/h of (Cd+Hg+Tl) > 1 0.1As+Se+Te g/h of (As+Se+Te) > 5 1Pb g/h > 10 1Mtx (*) g/h > 25 5(*) Sb+Cr+Co+Cu+Sn+Mn+Ni+V+Zn(**) O2 grade on dry basis (%) is set by the autorisation (indicative 11%)

Condition on flow

Table 19: Limit values for air emissions from installations concerned by environmental protection legislation

The global air emissions from the landfill model are calculated as the sum of contributions depicted in Figure 14. If no detailed information is given, the gas emitted represents 20% of the gas generated and a ratio “air/biogas” of 0.8 is considered for all combustion installation (including flares). The gas vented out corresponds to a limit flowrate of gas collected under which no combustion is possible (typically 20 Nm3/h). It represents the end of the biogas production curve (Figure 15).


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Years

Flow

rate

use

d (m

3/ho

ur)

Landfill gas flared (m3/h) Landfill gas valorised (m3/h)

Landfill gas vented out (m3/h) Min. capacity of landfill gas energy recovery system (m3/h)Nominal capacity of landfill gas energy recovery system (m3/h) Min. capacity of landfill gas flare system (m3/h)

First year of landfill

gas collection

First year of landfill gas flare operation

First year of landfill

gas energy recovery system

Last year of landfill

gas energy recovery system

Figure 15: typical use of biogas in the landfill model.

Energy consumption and production.

The energy production is calculated using the methane LHV of 36 MJ/Nm3. Using default values for biogas composition and air/biogas ratio, we get typically around 16 MJ/kg of biogas.

As most landfills are situated far from any heat network, the energy produced is considered to be electricity. The default values for efficiency are:

• Engine : 30% • Boiler + turbine : 15%

The consumption data come from the wizard database.

Unit Chosen Min MaxFuel l/t 0.75 0.5 1Electricity kWh/t 1.4 0.2 1.6

Table 20: Energy consumption in landfilling

Land use

The total surface area occupied by the landfill St is calculated by the model as the sum of:

• So surface area occupied by the cells. The number of cells is calculated as a function of capacity and the surface area of one cell uses the width of a cell (reference value: 25m), the length of a cell and the width of the dikes at the ground level (reference value: 7.0m),

• Sr surface area of roads: Sr � 0.1 So

• Sa surface area occupied by buildings and surrounding equipments: Sa � 0.05 So


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• Sl surface area occupied by leachate treatment installations: Sl � 0.015 So

• Sb non constructible zone (200 m around the landfill) Sb = 0.82 So + 34.6

The land use is a ratio of this total surface for a one year waste input.

Private costs

The cost model is well elaborated and accounts for all cost items linked to the landfill operation as shown in Table 21.

Cost items included

Investment costs (linked to capacity)

Storage: Engineering, land purchase, equipements, roads, civil works

Leachates: treatment installations

Biogas: treatment installations

Operating costs linked to tonnage treated

Storage: Site development (cells, coverage of cells at the end of exploitation), site management, salaries, monitoring,

Leachates: Collection system, operation, maintenance and analysis

Biogas: Collection system, operation, maintenance and analysis

Tax on polluting activities (if any)

Closure and post closure costs

Refitting of the site after closure + Long term survey of which : Survey management, Site supervision, Biogas analyses and treatment, Leachates analyses and treatment, Fence maintenance, Fence demolition at the end of the site life, Inclinometers, Aesthetic maintenance, Slopes stability measures, Topographic controls, Piezometers maintenance, Subterranean water analyses, Pollution events management

Receipts Sells of electricity

Table 21: costs items accounted for in landfill costs

Without field data on all cost items, the model can be adjusted to fit a cost given in Euro/ton.


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2.3. Methodology of a simulation study

The methodology of a simulation study with AWAST requires two steps: build a simulator of the existing situation and simulate scenarios (Figure 16).

Data collectionCharacterisation,

sampling11

Data treatment, M FAMaterial balance,

Data reconciliation

22

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

Tene

urs

MONS(en %)

Films > 5 mmx10

(en %)

Lourds > 5mm

(en %)

Inertes tot.(en %)

Hg(mg/kg sec)

Cd(mg/kg sec)

Ni(mg/kg sec)

Pb /10(mg/kg sec)

Cr/10(mg/kg sec)

Cu/10(mg/kg sec)

Zn/10(mg/kg sec)

OM Brutes - Qualité du compost (1 Double Tapis sélectionneur)

Crible 55%Crible 62%

Crible 76%NF Qualité A

CERAFEL

200

Scenarii,Simulations

55 � ��

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��

��

��

Build up and validationof the simulator

44

Adjustment of models,treatment ways, etc 33

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��

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sampling


sampling11


Data reconciliation

22 Data treatment, M FAMaterial balance,

Data reconciliation


Data reconciliation

22

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

Tene

urs

MONS(en %)

Films > 5 mmx10

(en %)

Lourds > 5mm

(en %)

Inertes tot.(en %)

Hg(mg/kg sec)

Cd(mg/kg sec)

Ni(mg/kg sec)

Pb /10(mg/kg sec)

Cr/10(mg/kg sec)

Cu/10(mg/kg sec)

Zn/10(mg/kg sec)




CERAFEL

200


55

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

Tene

urs

MONS(en %)

Films > 5 mmx10

(en %)

Lourds > 5mm

(en %)

Inertes tot.(en %)

Hg(mg/kg sec)

Cd(mg/kg sec)

Ni(mg/kg sec)

Pb /10(mg/kg sec)

Cr/10(mg/kg sec)

Cu/10(mg/kg sec)

Zn/10(mg/kg sec)




CERAFEL

200


55



55 � ��

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Build up and validationof the simulator

44Build up and validation

of the simulator

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Figure 16: Methodology of a simulation study

The first step is described in this report for the three cases. It relies on the analysis of data on all flows of the different operations in the system (collection and treatments). Missing data are filled in from databases of default values (on composition for example). Following the data analysis, models of the different operations are adjusted to reproduce data on flows, energy and costs. The adjusted models allow the assessment of real plants performances, the generation of data generally unavailable (material balance on each waste category and chemical element). This is what is called the “simulator of existing situation”, which supplies the description of all flows (including emissions), the energy consumptions and productions at each step of the system and the production costs (investments and operating costs).

In the second step, the scenarios are defined as well as the criteria for their assessment. This is the topic of deliverable 3-3.


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3. SYSTEM DEFINITION

3.1. The administrative limits and the system borders

The methodology of simulation as described above proposes in a first step to “adjust” each individual model of unit operation to real “field data” acquired on material flows, energy consumption, energy production, and costs. The chain of individual models through the “flowsheet” represents a “simulator” of the present system able to reproduce its global performance based as far as possible on field data.

The simulator proposes a detailed process approach that gives the material balance, the energy balance and the production costs. It is in no way a tool for providing a “Life cycle assessment” on a specific “product” or “service”. Speaking about emissions for example, the simulator may go until the final sinks, even if not included in the administrative boarders, but is not capable of dealing with avoided emissions. Speaking about recycling, the simulator does not include process models of the recycling industry, even if it could if the scope of the study was including process optimisation at that level.

Therefore, the simulator is mainly aimed at providing direct flows, energy and cost data for the waste management system (collection and treatments). For the purpose of “life-cycle thinking”, all upstream and downstream emissions (out of the defined limits of the processes chain represented) must be included with external data.

The system definition of the simulator consists in selecting the processes chain (flowsheet) that may be under control of local decisions and in selecting the characteristics of the flows (size distribution, components, chemical elements) that may give useful indicators for further evaluations carried out in subsequent work packages (see following paragraph).

It was previously discussed (during the kick-off meeting) that main waste streams causing problems and requiring decisions at local level are streams not covered by national legislation. The stress in Holiwast has been put on mixed waste, whether separate collection exists or not. It was thought appropriate to help decision on whether to implement or not separate collection, for which waste component, to which extend, and how depending on local conditions. The following streams participate to these potential choices for local communities: Mixed waste, Plastic, Metal, Mixed secondary materials, Glass, Paper, Composite packaging, Biowaste, Textile, Garden & park waste, Market waste, Batteries, Fluorescent tubes, Oil and fat, WEEE, Manually collected road waste.

3.2. The indicators and the streams definitions

The pilot studies on “Life Cycle Thinking in Municipal Waste Management in the Enlarged EU”, presented during the International Workshop of the JRC, Malta, November 10-11th 2005, were the starting point of the discussions on which streams were to be taken into account in the simulators and which indicators should be supplied for decision aid. Important methodological input and conclusions from the pilot studies were discussed in the frame of Holiwast workshop on indicators.

Previous work and evaluation of indicators clarify:

� the environmental pressures (in mass, surface area,… units)

� the mid-point indicators (calculated as equivalence to one reference pressure for the different impacts – as tCO2 eq.)

� the end-point indicator (calculated as a weighting of the above).


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The simulator contributing as a provider of primary “pressures”, the following list of was proposed as being the main ones for further elaboration of mid-point indicators: CO2, CH4, particulate matter (PM), land area, NOx, SO2, Ni, Zn, Cd, Hg, Pb, dioxins.

These pressures are extracted from the streams description (see paragraph 2.1.2) either from the components or from the substances.

3.3. Imports and allocation of pressures and outputs

Virtually all operations of waste management may have some “imports” – waste collected or treated which are not generated within the geographical area under study. The system definition of the case studies includes the operations leading to the “final sink” of the waste. Several flows are directed out of the geographical area to a treatment facility that receives other waste. In all cases, the emissions and outputs of the treatment, either located out of the administrative zone or inside, are considered according to the mass flow ratio between “waste generated” in the study zone and “imports” (Figure 17).

Operation

Imports

Waste generated

Emissions

Residues to otheroperation/final sink

Operation

Imports

Waste generated

Emissions

Residues to otheroperation/final sink

Figure 17: imports and allocation of outputs


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4. KATOWICE CASE STUDY

4.1. Methodology

4.1.1. Data collection

Most of the basic experimental data necessary for the case study was collected by GIG HOLIWAST partner.

The data for the year 2003 were collected. Most data concerning waste quantities were gathered in a complex drawing involving 18 collection companies, 21 treatment facilities including 15 landfills (Figure 18).

3 questionnaires were received from the main treatment facility of MPGK concerning the transfer station, the sorting plant and the composting plant. These questionnaires provide consumption of supplies and cost data which were used to adjust the simulator. Global cost data concerning collection and landfilling were supplied by GIG HOLIWAST partner. The cost models were adjusted with these global data.


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Resources (ENV) Emissions (Env.)

T- 80.92 MPGKiM Jasna


Resources (ENV) Emissions (Env.)3.08

Transport and collection 6.0217

20 02 01 biodegradable waste 3.0820 03 01 mixed municipal waste 6.02 112.5820 03 07 bulky waste 112.58

Total 121.68628.24

148.20

1 205.00

9 315.00

385.50

118.28

29.43

Resources (ENV) Emissions (Env.) 89.15

1 466.61Transport and collection

1 5 244.0020 03 01 mixed municipal waste 5 244.00

Total 5 244.00

35 528.97

T- 2Resources (ENV) Emissions (Env.) 445.26 LANDECO Landfill

112.06Transport and collection

2 123.3320 03 01 mixed municipal waste 40.07

Total 40.07 654.62

Resources (ENV) Emissions (Env.) 4 778.60

62.06Transport and collection

3 7 000.6420 03 01 mixed municipal waste 37.88 67 456.6315 01 06 mixed packaking 7.46

Total 45.34

Resources (ENV) Emissions (Env.) Resources (ENV) Emissions (Env.)Mixed packaging 5.86Insulation materials 0.27

Transport and collection Plastics 176.054 1.43 Sorting Plants Paper and cardboard 1 160.46

20 03 01 mixed municipal waste 603.88 T- 3 7 460.43 Mixed metals 3.93Total 603.88 3 430.33 Composting Plant Bulky waste 986.92

& Glass 185.330.23 Sortng Plant

Resources (ENV) Emissions (Env.)Katowice

Transport and collection 2.5 Compost 8 839.295 3 434.49 Composting Plants (2) Losses - vapors 8 328.41

20 02 01 biodegradable waste 30.35 46 522.58 Metals 465.2320 03 01 mixed municipal waste 1 466.61 Resources (ENV) Emissions (Env.)20 03 07 bulky waste 89.15

Total 1 555.76252.58

Resources (ENV) Emissions (Env.) 5 011.68T- 4 Non Compostable

Bie� Katowice 28 637.08Transport and collection

1220 02 01 biodegradable waste 124.7620 02 02 soils and stones 112.0620 02 03 other non-biodgradable waste 654.6220 03 01 mixed municipal waste 35 528.97 Resources (ENV) Emissions (Env.)20 03 02 waste from markets 445.2620 03 03 streat-cleaning residues 3 430.3320 03 07 bulky waste 4 778.60 593.36 T-2320 03 99 municipal wastes not otherwise specified 593.36 T-5 Zwirowa10 01 01 bottom ash, slag and boiler dust 62.06 40.07 Sosnowiec15 01 06 mixed packaging 0.2316 06 05 other bateries and accumlators 2.517 01 02 bricks 12 012.32 120.00

57 745.0736 122.33

Resources (ENV) Emissions (Env.) Resources (ENV) Emissions (Env.)

Transport and collection 603.886

20 03 07 bulky waste 30.16 T-6Total 30.16 Chorzów


Transport and collection Resources (ENV) Emissions (Env.)7

20 03 01 mixed municipal waste 937.24Total 937.24 T -7


Resources (ENV) Emissions (Env.)Transport and collection

20 03 01 mixed municipal waste 387.4820 01 39 plastics 020 01 01 paper and cardboard 53.16 T-115 01 06 mixed packaging 0.68 Czelad�16 03 06 other organic wastes 0.01 65.00 Ziele�17 01 07 bricks 65.0017 06 04 other insulation materials 0.34

Total 506.67 509.00



920 03 01 mixed municipal waste 59.27 30.16

Total 59.2737.88

Resources (ENV) Emissions (Env.) T-97.46 Recykling Wojkowice

T-9Transport and collection

10 59.2720 03 01 mixed municipal waste 12 360.00

Total 12 360.00 13.29



1120 03 01 mixed municipal waste 3 061.00 818.9620 02 03 other non-biodgradable waste 509.00 T -10

Total 3570 1.98 Knurów

980.00

1 856.00

0.68

0.34


T-8Resources (ENV) Emissions (Env.) MPGKiKM


1320 03 01 mixed municipal waste 628.24 T-1120 03 02 waste from markets 148.20 ZGK Bolesław

brique 17 01 02 bricks 0.00Total 776.44



1420 03 01 mixed municipal waste 652.35 T-1202 02 02 animal-tissue waste 0.0003 03 07 mechanicaly rejected from pulping of paper waste 0.0017 01 07 other mixed of concrete, bricks 98.3617 02 01 wood 66.4617 04 07 mixed metals 0.00

817.17

Resources (ENV) Emissions (Env.)Resources (ENV) Emissions (Env.)

Transport and collection15 1 945.00

20 03 07 bulky waste 13.29 T-13Total 13.29 COFINO Jastrzebie


Transport and collection16 Resources (ENV) Emissions (Env.)

20 03 01 mixed municipal waste 0.00Total 0.00

T -14Zabrze


652.35

98.36 T-15Jaworzno


Transport and collection Resources (ENV) Emissions (Env.)

1820 03 01 mixed municipal waste 286.28

Total 286.28 0.01T-16

Dabrowa GórniczaResources (ENV) Emissions (Env.)

66.46T-23

Physical persons


160.07 18367T-22 97 24876

53.16 WtórmeX Siemnowice 3655 201.736509 43.45

245.184980

53896Resources (ENV) Emissions (Env.)

60405 604055024 5023

T-17EKOFOL Bytom


T-18Osetnica


286.28 T-19Puławy

Composting Plant


T-20SARIA Małopolska


T- 21SATER Kamie�ski


T-22

ZOM Mysłowice

MPGKM Siemianowice �l.

MPO -Jaworzno

MULTIGRAT Katowice

PUK Ruda �l�ska

Total

ALBA PGK Czelad�

ALBA PTS, Chorzów

AUTO ŁAD, Chorzów

BUSDYGON, Katowice

ESTA Ruda �l�ska

KEDAT D�browa Górnicza

Lobbe Recykling Sosnowiec

LOBBE-�l�sk Sosnowiec

Total

MPGK Katowice

ALBA �l�sk

ALBA MPGK D�browa Górnicza

TCHORZ Katowice

Figure 18: Katowice flowrate data


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4.1.2. Data treatment

After collection, the major steps of data treatment consisted in:

� Identification of inconsistencies (definition of streams, definition of waste, dates…),

� Identification of incoherence (in - out ≠ 0); Data that were not coherent were reconciliated.

A major step in the treatment of data consists in the synthesis of flows circulations and grouping (aggregation) of operations according to available data. It leads to the definition of a simplified and operational flowsheet (Figure 19). In the case of Katowice, most of the collection operators have been lumped together as not particular data concerning the km driven, the number of vehicles/workers, etc. was supplied. All collection operations use default values. For landfills, the Landeco represents the major part of the waste deposited and is intended to become the only sanitary landfill of the city. All other landfills are also lumped together.

Figure 19: Flowsheet of Katowice case study


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4.2. Waste management system of Katowice

The waste is generated by 323.400 inhabitants living in 22 districts.

Separate collection is provided for 20 districts, about 98% of population and 317.300 inhabitants. Zarzecze and Podlesie are the districts where separate collection in not carried out.

The facilities used for the waste treatment are the following:

� Sorting plants

1 sorting plant for mixed secondary materials (6 km from Katowice city)

� Mechanical and biological treatment plant

Two mechanical and biological treatment plant are used for mixed waste:

• Katowice mechanical and biological treatment plant (6km)

• Pulawy mechanical and biological treatment plant (291 km)

� Incineration plant (Dabrowa Gornicza - 25km)

� Landfilling

15 landfills are available around Katowice city.

LANDECO Landfill received only waste from Katowice (54 % waste landfilled in 2003).

The 14 other landfills (from 7km to 246 km far from Katowice city) received 46% of the waste disposed in landfill in 2003. The mean distance driven to bring waste to other landfill is 34 km.

4.3. Waste generated

Amount Tons per year Nb inhabitants concerned Kg / Inhab. year

Mixed waste 113 730 323 400 351.7 Paper 1342 317 300 4.2 Glass 711 317 300 2.2 Mixed secondary materials (Plastics & metal) 257 317 300 0.8

Batteries 3 323 400 Manually collected road waste 3 430 Garden and park waste 157 Market waste 594

Sum 120 224 323 400

Table 22: waste flows collected in Katowice


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Composition (%)

Woo

d

Pap

er

Gla

ss

Fe M

etal

s

NFe

Met

als

Pla

stic

s

Text

iles

Bio

was

te

Oth

ers

Mixed waste 2.3 25.6 10.1 1.8 0.6 15.3 4.9 32.4 6.9 Paper 0.0 95.0 0.0 0.0 0.0 2.0 0.0 1.0 2.0 Glass 0.0 0.1 98.0 0.2 0.1 0.2 0.0 0.1 1.5 Mixed secondary materials (Plastics & metal) 0.0 1.1 1.5 19.2 3.4 59.8 0.0 0.7 14.4

Manually collected road waste 0.5 35.0 2.5 1.0 1.0 8.0 0.5 32.0 19.5

Batteries 100 Garden and park waste 26.0 1.0 0.5 0.5 0.5 1.0 0.0 45.0 25.5 Market waste 5.0 2.0 1.0 0.5 0.5 1.0 0.0 80.0 10.0

Table 23: Waste composition in Katowice using AWAST default composition per flow

4.4. Waste treatment details

4.4.1. Collection

MPGK is competing with 10 other companies for the collection of waste.

� Mixed waste

The frequency of collection depends on agreement with client and can be: from 3/week, 2/week, 1/week, 1/2weeks and 1/month. Without specific information, we assumed once a week.

Mixed waste are sent to mechanical biological treatment (MBT) plant (37% of mixed waste generated) or landfill (63%) with or without passing trough a transfer station: 16 % (8 132 tons) of the mixed waste received in Katowice mechanical biological treatment plant (49 476 tons) are transferred to landfill.

� Separate collection of paper, glass and mix(plastics and metal)

Two systems are available:

• Container system

• Bag system

Collection system (details) Frequency of collection

Amount of waste

collected (tons per year)

Waste collector

Container system

Bring collection : 370 collection points for 400 to 500 inhabitants each

Once a week MPGK and

other collectors

Bag system Kerbside collection: 2500 private houses involved in this collection

Twice a month 250.61 MPGK collector


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� Other waste collected

• Batteries are sent to France or Sweden to be recycled

• Manually collected road waste are transported to Katowice MBT

• Garden and park waste mainly to landfill

• Market waste to landfill


The Katowice sorting plant (Capacity: 2000 tons/year) receives paper, glass, mixed plastics and metals from separate collection. The mass flows data were supplied in the questionnaire.

Waste sorted Tons per year

Outputs of the sorting plant

Tons per year % input

Sorting products 1452.10 62.9% Paper 1341.86 Paper 1117.93 Glass 711.41 Glass 185.33

Metals 3.04 Mixed secondary materials (Metals and plastics)

256.65 Plastics 145.80

Sum 2309.92 Sorting refuses 857.82 37.1%

Table 24: Katowice sorting plant

4.4.3. Mechanical biological treatment plant (MBT)

The mechanical biological treatment plant of Katowice (nominal capacity of 50 000 tons/year) is based on 2 biostabilisator (DANO). The mass flows data were supplied in the questionnaire.

Input Tons per year Output Tons per year

Mixed waste 41343.5 Biologically pre-treated waste

27 983 Landfill (27 717)

Incineration (266) Manually collected road waste 3430.3 Scrap (metal) 451 Garden and park waste 1.4 Compost 8562

Table 25: Katowice mechanical biological treatment plant

The compost is used for reclamation of landfill, construction of roads. The refuse (biologically pre-treated waste) are disposed in landfill (99% of refuse) or incinerated (1%).

4.4.4. Incineration

No information is available on this plant located at 25 km from Katowice. It is supposed to treat 150 000 t/year among which the waste from Katowice represent only 266 t/year All outputs are obtained by calculation using default AWAST parameters and the allocation to Katowice is made using the mass ratio 266/150000.


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Input Output

Description Amount (tons per year) Description Amount

(tons per year) %Input

Bottom ashes 46,42 17% Scrap (metal) 4,10 2% Filter cake 0,04 0.015%

Biologically pre-treated waste from Katowice MBT

266

Fly ashes 4,13 2%

Table 26: Incineration plant used to treat waste from Katowice

4.4.5. Results

Matter balance

� 120 224 tons of waste are collected.

� 45 061 tons are sent to mechanical and biological treatment (37.5%).

� 266 tons are incinerated (0.2%)

� 2 310 tons are sorted (1.9%).

� In fine:

• 8 576 tons of compost are produced (7.1%).

• 1 910 tons are sent to recycling industry (1.6%).

• 101 750 tons are disposed of (84.6%).

Figure 20: Matter balance (Katowice case study)


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Emissions to air

The values presented in Table 27 are issued from default AWAST values. They account essentially from admitted measures for Collection & transport and MBT, and emissions limits set by regulation for incineration and landfill. Landfill emissions are the result of three contributions: biogas not collected, biogas flared and biogas combustion for energy recovery. In Katowice status quo, this later option is not practiced.

Status quo

Kg/year Collection & transport

Incineration plant

Mechanical biological treatment

plant (MBT)

Sorting plant Landfill SUM

Tons treated 167 951 266 45 061 2 310 101 750

CO2 fossil 2 409 309 113 298 128 306 29 484 135 773 2 816 170

CO2 org 0 120 983 6 647 754 13 276 599 20 045 336

CH4 10 0 63 321 0 1 649 085 1 712 415 Particles 3 407 16 62 14 159 3 659 NOx 31 276 317 13 056 304 11 066 56 018

SO2 1 087 79 24 6 1 121 2 317 Ni 0.000 0.080 0.003 0.001 0.003 0.086 Zn 0.000 3.790 0.040 0.009 0.043 3.882 Cd 0.000 0.080 0.000 0.000 0.010 0.091 Hg 0.000 0.080 0.000 0.000 0.010 0.090 Pb 0.000 0.260 0.000 0.000 0.000 0.260 Dioxin(mg/year) 0.000 0.160 0.000 0.000 0.000 0.160

Table 27: Gaseous emissions (kg/year) calculated for Katowice waste management system for the year 2003

Emissions to water

The emissions to water concern the incineration plant, the MBT plant and the landfill operation.

The questionnaire for MBT provides the global quantity of liquid emissions (including leachate) of 841 m3/year. This corresponds to a specific emission of 18.7 l/t of raw matter. The default value used in composting is 1.5 l/t. So far, the default composition of leachate is not used. The global flow of water + leachate is supposed to be released in the environment respecting the regulatory limits.

The default value is used for incineration (500 l/t of dry matter). The composition is set according to regulation limits.

The quantity of leachate generated in landfills is calculated as follows:

• Rainfall in Katowice: around 700 l/m2

• Surface area of cells in exploitation stage: 13300 m2 (corresponding to the land use – see next paragraph)

• Leachate generated corresponding to 20% of the total rainfall: 1 862 000 l/year.

Here also, no composition data is available.


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Status Quo MBT/compost Incineration Landfill Sum Waste treated t/year 45 061 266 101 750 Liquid emission l/year 841 200 93 100 1 862 000 2 796 300 Component unit COD kg/year 105.2 11.6 232.8 349.5 Hydrocarbons kg/year 8.4 0.9 18.6 28.0 Phenols kg/year 0.1 0.01 0.2 0.3 Halogenated organics kg/year 0.8 0.1 1.9 2.8 F- kg/year 42.1 4.7 93.1 139.8 As kg/year 0.1 0.01 0.2 0.3 Cd kg/year 0.2 0.02 0.4 0.6 Pb kg/year 0.4 0.05 0.9 1.4 Cr (VI) kg/year 0.1 0.01 0.2 0.3 Hg kg/year 0.04 0.005 0.1 0.1 CN kg/year 0.1 0.01 0.2 0.3 Heavy metals kg/year 12.6 1.4 27.9 41.9 Suspended solids kg/year 25.2 2.8 55.9 83.9

Table 28: Emissions to water for Katowice treatment plants

Land use

The following land use assessment is based on the amount of waste generated in Katowice treated in those plants. The column “Land use (amount prorate)” represents the area effectively took up to treat the yearly amount of waste generated in Katowice whereas the column “Land use (Plant)” represents the total area took up by the plant according to its capacity.

Land use (ha) (amount prorate)

Waste input (tons per year)

Land use (ha) (Plant)

Sorting plant 0.07 2 310 1.0 Incineration plant 0.00 266 2.0 MBT 0.07 45 061 2.8 Landfill 1.33 101 750 26.7

Sum 1.47 32.5

Table 29: Land use for Katowice treatment plants and disposal for the year 2003

Energy balance

This energy balance is based on the amount of waste generated in Katowice treated in those plants. Figures for MBT and sorting plant are derived from questionnaires. Other figures are results of models.

Status quo

Transport &

Collection MBT Sorting plant

Incineration plant Landfill Total

Waste treated (t/year) 167 951 45 061 2 310 266 101 750 Fuel consumption (GJ/year) 22 526 1 700 391 2 1 798 26 417 Electricity consumption (MWh/year) 932 210 14 142 1 298 Electricity production (MWh/year) 62 62 Steam production (GWh/year) 0.3 0.3

Table 30: Calculated energy consumption and production for waste management system of Katowice for the year 2003


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Cost balance (VAT not included)

As a general guideline in the Holiwast case studies, priority is given to real field data. AWAST production costs models were adjusted to fit data supplied by the Holiwast partner GIG, reported in the following table.

Cost data Source of cost data

Transport

0.11 euros / ton.km for mixed waste 0.13 euros / ton.km for secondary materials 0.09 euros / ton.km for biowaste

Mean value from National Plan of Waste Management

Collection 20 euros/ton for mixed waste 36 euros/ton for secondary material Real data from MPGK Waste collector

MBT Detailed questionnaire

Incineration 64.5 euros/ton Mean value from National Plan of Waste Management

Landfill 9.7 euros/ton Mean value from National Plan of Waste Management

Sorting Detailed questionnaire

Table 31: Cost data supplied for Katowice case study

On the basis of these available data, the AWAST production costs models were adjusted as follows:

� Sorting and mechanical biological treatment: the detailed questionnaires were used to perform a precise adjustment of the AWAST cost models. All cost factors were adjusted: capital cost, payroll, maintenance cost, revenues…

� For the incineration plant and landfill: only mean values were available.

To fit these mean values, the following adjustments were performed:

• Incineration:

The lifespan was reduced and factors describing capital costs, fixed cost (other than wage bill), relative cost (maintenance bill), repairs and renewal cost were increased by a global ratio.

• Landfill:

Land purchase, environmental fees and closure and post-closure costs were not taken into account. Moreover, all cost factors (the cost for land excavation, for the laying of a geotextile and a geomenbrane, for leachate and gas collection, for employees salaries, equipments, environmental monitoring…) were reduced to fit the mean value of disposal in Poland.

� Transport:

The mean values in term of euros per ton and kilometre driven were used to assess the costs linked to the waste transport applying these data to the tons and kilometres driven estimated by AWAST simulator.

� Collection:

For the costs of waste collection, mean value in euros per ton of waste collected were used directly in the simulator. The waste collection model cannot be adjusted to reproduce the real data from MPGK waste collector.


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The results of costs calculation for the year 2003 are given in the following table:

Details of costs (K€)

Amount of waste treated

(Tons per year)

Euros per ton treated

Total costs (K€)

Production costs (K€)

Receipts (K€)

Transport 51 911 1.3 66.273 66.273 Collection 116 040 20.3 2 357.757 2 357.757 Sorting 2 310 162.0 374.272 425.868 - 51.596 MBT 45 061 20.7 932.141 1 013.931 - 81.790 Landfill 101 747 12.9 1 311.678 1 311.678 For the treatment of residues Incineration 266 59.6 15.849 17.647 - 1.797 Hazardous landfill 3 200 0.834 0.834

SUM 317 339 132.3 5 058.804 5 193.897 - 135.184

Table 32: Cost assessment of Katowice waste management system for the year 2003

The incomes from waste treatment are based on the following data supplied by GIG:

Euros per ton Selling price of the recovered materials

paper and cardboard 25 plastic packaging 130

glass packaging (white) 32.5 glass packaging (colour) 17.5

metals packaging 20 Selling price of the compost 9.50

Table 33: Incomes of Katowice waste management system for the year 2003

NB: the cost linked to the recycling of batteries was not taken into account.

Details of costs (K€)

Amount of waste treated (Tons

per year)


Total costs (K€) Production

costs (K€)

Receipts (K€)

Costs linked to treatment

of residues (K€)

Source of receipts

Details of the

treatment of residues

Transport 51 911 1.3 66.273 66.273

Collection 116 040 20.3 2 357.757 2 357.757

Sorting 2 310 166.9 385.595 425.868 - 51.596 11.323 Products to recycling

Residues in landfill

MBT 45 061 29.3 1 318.925 1 013.931 - 81.790 386.784 Sell of compost

Residues in landfill or incinerated

Landfill 72 897 12.8 930.254 930.254

132.3 5 058.804 4 794.083 - 133.386 398.107


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The final net cost of the collection/treatment system in Katowice in 2003 is equal to 5 059 k€ (15.6 € per inhabitant or 42€ per ton of waste generated).


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5. TURIN CASE STUDY

5.1. Methodology


Most of the data necessary for the Turin case study comes from the AMIAT (Azienda Multiservizi Igiene Ambientale Torino) company which is in charge of the refuse treatment, disposal and recovery cycle since 1969. Data for the year 2004 were thus collected. AMIAT deals with about 500,000 tonnes of waste per year coming from 900,000 citizens of the Town of Turin. From the late 70’s Amiat introduced in Turin the separate collection of paper, glass, tins, wood, food and hazardous waste.




� Identification of incoherence (in - out ≠ 0); Data that were not coherent were reconciliated,

� Collection of missing data, taking into account data regarding material balances, energy consumption and production, environmental emissions and costs.

All the data collected were used to build the simulator of the waste management in Turin for the year 2004 (see Figure 21) taking into account all waste fluxes from the input (waste collection) to output (secondary material, recycling, disposal, etc.). The simulator combines a flowsheet that describes the system in terms of material streams and treatment operations, a phase model that describes all the characteristics of all materials involved in the flowsheet (raw waste, products, reagents …) and mathematical models for each unit operation (collection, transport, biotreatment, thermal treatment) that summarize current knowledge with respect to efficiencies, environmental emissions, energy fluxes. The calibration procedure consists in comparing the results of the calculations with the data that has been collected. This calibration step concerns as well the matter balance as the energy or costs analysis.


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Separate collection of mixed waste - detail (CMD)

Separate collection of biowaste (SC)

Transport of mixed waste (TRS)

Transport of recyclables

Scrap TRS-RECD

Compost TRS-RECD

Off-gas TRSSupplies

Transport of recyclabes (TRS)

Scrap TRS-RECD

Compost TRS-RECD

Off-gas TRSSup plies

Off-gas TRS

Mixed waste TRS-LM

Sup plies

Sorted mixed secondary materials TRS-RECD

Transport of sorted materials (TRS)

Residues TRS-LM

Supplies Off-gas TRS

Sorted mixed secondary material SMS-TRS

Sorting residues SMS-LMMixed packaging waste

Sorting plant for mixed secondary materials (SMS)

Off-gas SPSup plies

Separate collection of secondary material (SCS)

Greenwaste SC-OBT

Supplies

Scrap C-RECD

Composting plant 'Italconcimi - Tor ino"

Scrap C-TRS

Composting plant "Borgotaro Torinese - Torino"

Off-gas TRS

Residues TRS-LM

Transport of residues (TRS)Sup plies

Residues TRS-LM

Off-gas TRSTransport of residues (TRS)

Sup plies

Off-gas TO

Paper & Carboard TIBS

Paper & Carboard PHH


Paper & Carboard SC-RECD


Plastics


Paper & Cardboard

Plastics SCS-RECD

Plastics SCS-RECD

Plastics SCS-RECD

Separate collection of secondary materials (SCS)

Plastics TIBS

Plastics PHH

Plastics PHH

Glass SCS-RECDGlass SCS-RECD

Separate collection of secondary materials (SCS)

Glass PHH

Glass PHHGlass PHH

GlassGlass SCS-RECD

Collecting point for other waste (CPO)

Sup pliesBiowaste TIBS

Biowaste PHHBiowaste SC-OBT

Separate collection of biowaste (SC)

Biowaste SC-OBT

Wood waste

Green waste

Biowaste SC-OBTBiowaste PHH

Food waste

Mixed waste

Landfill for municipal solid waste "Basse di S tura - Torino"

Mixed waste CMD-LM

Mixed waste CMD-TSMixed waste CMD-LM

Mixed waste CMD-LM

Mixed wasteCMD-TS

Transfer station "gerbido"

Mixed waste PHH

Hazrdous waste TO-RECD

Metals TO-RECD

WEEE TO-RECD

Transport of other waste (TO)

Sup plies

Recycling detail (RECD) "Serv iz i Industriali - Torino, Oli Metal - Tor ino"

Off-gas C Residues C-TRS

Compost C-RECD

Residues C-TRSOff-gas C

Compost C-TRS

Recycling - detail (RECD) "Eurometalli - Torino"

Recycling - detail (RECD) "AMIAT TBD - Volpiano"

Recycling - detail (RECD) "Cassetta - Lombriasco"

Recycling - detail (RECD) "Demap - Benasco"

Hazardous waste CPO-TO

Metals CPO-TO

WEEE CPO-TO

Off-gas CPO

Glass SCS-RECD

Plastics SCS-RECD

Separate collection of secondary material (SCS)

Mixed Secondary material SC-SMS


Recycling - detail (RECD) "Publirec - Colegno"

Recycling - detail (RECD) "CMT - La Loggia, Cartamacero di Bertolino - Leini, Italmaceri - Torino"

Wood waste SC-RECD

Recycling - detail (RECD) "Piattaforma Ecolegno AMIAT - Torino"Separate collection of wood (SC)

Greenwaste SC-OBT

Transport of road waste (TRS)

Biowaste SC-OBT

Road waste TRS-LM

Mixed waste TS-TRS

Leachate LM

Off-gas LM

Off-gas TS

Sup plies

Mixed waste PHH

Sup plies

Hazardous waste PHH

Metals PHH

WEEE PHH

Off-gas SCSSup plies

Glass TIBS

Sup plies

Off-gas SCS

Plastics PHH


Mixed secondary material PHH


Off-gas SCSup plies


Wood waste PHH

Off-gas SC

Sup plies

Green waste PHH

Off-gas SCSup plies

Biowaste PHH

Off-gas TRSSup plies

Road waste ENV

Off-gas CMDSup plies

Mixed waste PHH

Torino Case Study

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Figure 21: Flowsheet of the Turin Case study


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5.2. Waste management system of Turin

5.2.1. General information

Turin is located in northwest Italy, near the Alps. The Turin case study takes into account the waste generated by 900,000 inhabitants (living in 10 districts). The amount of waste yearly collected is about 500,000 tones. Municipal Solid Waste is managed by a public company (AMIAT) owned by the municipality of Torino. AMIAT is responsible for all the tasks regarding collection, transport, disposal and delivery at recycling plants. AMIAT covers all management cost and is funded by the incomes of Turin’s waste–tax and the revenues for recyclable materials. The evolution of the total amount waste collected between the years 1999 is depicted on Figure 22.

0

100000

200000

300000

400000

500000

600000

700000

800000

1999 2000 2001 2002 2003 2004

Mixed packaging waste

Used clothes

Brown & White goods

Hazardous

Wood

Metals

Plastics

Glass & Cans

Paper & Cardboard

Garden/Green waste

Food waste

Total sep. Collection

Residual waste

Figure 22: Evolution of the total amount of waste collected in Turin

Collection schemes have been set up in 4 collection zones of Turin corresponding to about 125,000 inhabitants. Collection is performed door-to-door, for the main waste streams which are:

� Residual waste,

� Foodwaste,

� Paper and cardboard,

� Glass,

� Plastics,

� Metals.

To represent the collection scheme used in Turin, it could have been possible to look precisely to the organization in each of the ten districts. However, this approach would have required huge amounts of precise data which are very difficult to obtain. Moreover, the additional precision would not have been of much use. Fortunately, AMIAT supplied us with figures of collection schemes (amounts of waste collected, number of vehicles used, hours for collection per year and per area) on three areas (A, B, C, see Figure 23).


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Area A gathers districts 6 and 7, area B is equal to district 8 strictly, area C north gathers districts 1, 3, 4 and 5 and area C south gathers districts 2, 9 and 10.

Figure 23: Splitting of Turin for collection scheme representation

Here are the main figures concerning streams for these three areas and for the year 2004 (cf. Table 34).

AREA A

AREA B

AREA C north

AREA C south

C.so Mortara ang. C.so Svizzera

P.za Bottesini

V. Sacchi ang. V. Pastrengo

V. S. Marini ang. C.so Orbassano

V. Germagnano

V. Gorini 8 V. Zini ang. C.so Bramante

C.so Brescia ang. C.so Regio Parco

Center of collection zones

Garage for AMIAT vehicles


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t/y Inhabitants MSW Plastics Glass Foodwaste P&C

Area A 139,359 69,386 631 2,741 2,330 11,910

Area B 193,324 76,971 1,051 2,223 3,854 9,534

Area C 570,227 202,117 3,591 7,940 15,311 28,305

TOTAL 902,910 348,475 5,274 12,906 21,494 49,749

Table 34: Main separately collected streams in Turin for the year 2004


� Landfill site of “Basse di Stura”

Residual MSW collected in the town of Turin and materials collected during street-cleaning and sweeping activities are disposed onto the sanitary landfill. Waste disposed for the year 2004:

• MSW 523,495 t/y

• Industrial waste 63,666 t/y

• Sewage sludge 82,745 t/y

The total area of the “new” landfill is equal to 660,000 m2 for a capacity of 19,200,000 m3. The opening year of the “new landfill” was 1983 and the closing year is forecasted for December 2009. The flowrate of the extracted biogas is equal to 10,500 Nm3/h. 11 landfill gas powered engines have a total power of 14 MW. The total amount of landfill gas extracted in 2004 was 90,000,000 Nm3 and the total electricity produced equal to 73,680,000 kWh. 4 flares are used to burn the residual biogas. Leachate is collected by 14 sinks, for about 252,000 m3.

� Composting plant of Borgaro Torinese

The plant started to operate in 1999 to compost garden and food waste separately collected. The total area of the plant is equal to 70,000 m2 (35,000 m2 are roofed). Most of the critical actions (waste unloading, sieving, shredding, mixing of bulky agents, composting) are performed in closed halls, kept depressurised).

� Recycling plant for packaging and dry-recyclables

In Italy, the National Packaging Association (CONAI) is responsible for realising recycling platforms that represent the destination of the materials collected at municipalities. The packaging-producer associations are:

• Comieco for paper and cardboard,

• Rilegno for wood,

• Corepla, Conip for plastics,

• Coreve for glass,

• CAN, Cial for cans

Mixed waste packaging is collected and delivered to a sorting plant (Publirec).


The total amount of waste generated in the town of Turin for the year 2004 is given in Table 35.


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Amount Tons

Mixed waste 331,051 Paper 79,191 Glass 12,920

Mixed secondary materials (Plastics & metal) 10,070

Road waste 17,423 Biowaste 54,481 Plastics 7,066 WEEE 2,122 Metals 2,183

Hazardous 352 SUM 516 859

Table 35: Amounts of waste generated in Turin for the year 2004

The composition of each type of waste generated is given in Table 36.

Composition (%)

Woo

d

Pap

er

Gla

ss

Fe M

etal

s

NFe

Met

als

Pla

stic

s

Bio

was

te

Text

iles

Oth

ers

Mixed waste 0.4 21.1 10.3 1.8 0.6 12.6 34.9 3.0 15.3 Paper 0.0 95.0 0.0 0.0 0.0 2.0 2.0 1.0 0.0 Glass 0.0 0.1 98.0 0.1 0.0 0.1 0.0 0.0 1.5

Mixed secondary materials (Plastics & metal) 0.0 2.0 3.0 3.0 1.0 73.0 1.0 0.0 17.0

Road waste 0.5 35.0 2.5 1.0 1.0 8.0 32.0 0.5 19.5 Biowaste 15.0 4.8 0.3 0.7 0.3 1.6 60.8 0.0 16.6 Plastics 0.0 2.0 3.0 3.0 1.0 73.0 1.0 0.0 17.0 WEEE 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 Metals 0.0 1.0 1.0 60.0 10.0 1.0 1.0 0.0 26.0

Hazardous 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0

Table 36: Compositions of waste generated (mass %), Turin case study

The amount of waste generated in Turin per capita is given in Table 37.


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Amount Tons per year Kg / Inhab. Year (902.910 inhab.)

Mixed waste 331,051 366.6 Paper 79,191 87.7 Glass 12,920 14.3

Mixed secondary materials (Plastics & metal) 10,070 11.2

Road waste 17,423 19.3 Biowaste 54,481 60.3 Plastics 7,066 7.8 WEEE 2,122 2.3 Metals 2,183 2.4

Hazardous 352 0.38

Table 37: Amount of waste generated in Turin per capita for the year 2004


5.4.1. Collection

The separate collection of waste in Turin is carried out by AMIAT. For the specific collection of paper and cardboard, the company Cartesio brings in its technical means. We were provided for each waste stream and for each area with the type and the number of vehicles used and the number of working hours for collection. For lacking information we have assessed model parameters with default values and some other information have been averaged in case we had too much detail. All separately collected streams have been split to take into account the specificities of the collection in the three areas of Turin.

Here are for all the fluxes, the main parameters used in the models:

1. Mixed waste

The frequency of collection depends on the area, on the type of vehicle and the type of container used. We assume a collection frequency of twice a week. As well, according to the hours of working written out on the AMIAT report, the collection efficiency (tons of waste collected per hour) differs from one area to one another. For area A, this parameter is equal to 0.85, 1.3 for area B and 1.4 for area C. The vehicle transport capacity is taken at 15 m3 and we assumed that there were two operators (1 driver + 1 collector) to do the collecting round. Mixed wastes as well as road wastes are disposed of at the sanitary Landfill “Basse di Stura”.

2. Separate collection of food waste

We assume a collection frequency of twice a week. Efficiencies are equal to 0.4, 0.4 and 0.45 for area A, B and C respectively. The vehicle transport capacity is taken at 12 m3 and two crews are working per day of collection. The driver operates alone without any collector. Food waste feeds the composting plant “Borgaro – Torinese”. The compost and scrap recovered after the composting process are recycled; residues are disposed of in the Landfill.


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3. Separate collection of green waste and wood

Garden and park waste as well as wood waste are separately collected. Part of the green wastes ( � 21%) is brought in the composting unit together with food waste in order to enhance the composting process (aeration of windrows). The left part feeds the composting plant “Italconcimi” located in Torino. We assumed that, as for food waste composting plant, the scrap and compost recovered after the sorting-composting process are recycled and the refuse is disposed of in the Landfill. Without any information upon the collection of these two streams, we assessed the models parameter with European default values: a collection efficiency of 2 tons of waste collected per hour, a frequency equal to once a week, one crew per day of collection and per vehicle, a crew composed of a driver plus a collector, a volume of vehicle equal to 15 m3 for green waste and 20 m3 for wood waste.

4. Separate collection of mixed secondary materials

As well as for green waste, we did not have any information on the separate collection of mixed secondary materials except that the collection is performed at public market places (200 producers). We took an efficiency of 1.2 tons of waste collected per hour and a frequency equal to once a week. The volume of used vehicles is equal to 20 m3.

5. Separate collection of paper

For separate collection of paper and cardboard, AMIAT subcontracts the company Cartesio, the technical means of which are given in Table 38.

Typology n°3-wheel vehicle, gasoline 1Skip with bin-lift (small) 18Skip with bin - lift (Gasolone) 36Truck for container movement and transport (small) 1Compactor (<3,5 tons) 24Compactor (> 3,5 tons) 6Truck with crane (> 7 tons) 2Truck for container movement and transport 3Cars and small vans 3Total 94

Collection vehicle

n°Collection operators 96Personal for maintenance (assistnace) and cleaning 6Administration staff 14Total 116

Staff


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Typology n°50 lt baskets 83 000240 lt wheelbins 5 000330 lt wheelbins 960360 lt wheelbins 200660 lt wheelbins 2 200Roadcontainer 1100 lt. 400Roadcontainer 1300 lt. 0Big-baskets and Rolls 350Container 20 cm 19Container 25 cm 2Press container 4Roadcontainer 1100 lt. For scools -property of AMIAT 61Roadcontainer 1300 lt. For scools -property of AMIAT 35Wheelbins 240 lt. Property of Amiat for schools and areas n° 90Wheelbins 330 lt. Property of Amiat for schools and areas n° 150Wheelbins 240 lt. Property of Amiat for URBAN project 2002 300TOTALE 92 771

Collection tools and equipment

n°Collection at households and residential areas 262Collection at business activities 111TOTALE 373

Weekly collection rounds

Table 38: Technical means of the Cartesio Company in charge of Paper & Cardboard collection in Turin

To calibrate the model for the collection of paper we assumed an efficiency of 1 tons of waste collected per hour, a collection frequency equals to once a week with one crew (assuming one driver working also as collector) per day of collection and per vehicle.

6. Separate collection of plastics

The collection efficiency is considered to be the same in all the areas and is taken equal to 0.9 tons of waste collected per hour. The frequency is equal to once a week with one crew per day of collection and per vehicle. There are no collectors added to the drivers in the vehicle.

7. Separate collection of glass

The collection efficiency is equal to 0.32, 0.42 and 0.42 tons per hour in area A, B and C respectively. The collection of glass is performed once a week with one crew per day of collection and per vehicle. The useful volume of vehicle is equal to 15 m3 and there are no collectors added to the drivers in the vehicles.


Separately collected mixed wastes packaging, mostly plastics, are sorted in the Publirec sorting plant in the town of Collegno which is about 12 km far from Turin. Without any information on the outputs of the plant, we assume a global sorting performance of 75% of the plastics category in the mixed waste packaging stream. The left material compose the stream of the residues which is disposed of in the landfill.


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5.4.3. Results

Matter balance

� 516,859 tons of wastes are collected.

� 130,043 (= 132795 – 2752) tons are sent to recycling industry (25.16%).

� 15,223 (= 33898 – 18561-114) tons concerned organic recycling (2.95%).

� 2,752 tons of compost are produced (0.5%).

� 371.591 tons are disposed of (71.89%).

Plastics 5,513

Compost 2,752

Scrap 114

Landfill371,591

Green waste 10,754

Manually collectedRoad waste 17,423

CO

LLE

CTI

ON

516

,859

tons

/yea

r

WEEE 2,122Batteries 352

Residues 4,557

SortingPlants10,070

Paper 79,191Glass 12,920Metals 2,183

Composting33,898

Residues 18,561

Mixed waste331,051

Market waste 10,070

Food waste 23,144

Wood 20,583

Plastics 7,066

132795

Plastics 5,513

Compost 2,752

Scrap 114

Landfill371,591

Green waste 10,754

Manually collectedRoad waste 17,423

CO

LLE

CTI

ON

516

,859

tons

/yea

r

WEEE 2,122Batteries 352

Residues 4,557

SortingPlants10,070

Paper 79,191Glass 12,920Metals 2,183

Composting33,898

Residues 18,561

Mixed waste331,051

Market waste 10,070

Food waste 23,144

Wood 20,583

Plastics 7,066

132795

Figure 24: Synthetic view of calculated waste flows (Turin case study)


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Emissions to air

For HOLIWAST, the following list of “pressures” was proposed: CO2, CH4, particles, land area, NOx, SO2, Ni, Zn, Cd, Hg, Pb, dioxin. The values presented in Table 39 are issued from default AWAST values. They account from measures for Collection & transport and composting. Landfill emissions are the result of three contributions: biogas not collected, biogas flared and biogas combustion for energy recovery. Flares and combustion emissions are taken at regulation limits.

Status quo Kg/year

Collection & transport

Transfer station

Sorting plant Composting Landfill SUM

Tons treated 516859 120000 10070 38898 371591

CO2 fossil 5 795 000 160 125 45 686 361 884 497 799 6 860 495

CO2 org 0 0 0 9 366 000 76 607 000 85 973 000

CH4 24 1 0 89 213 7 269 002 7 358 240 Particles 8 100 77 22 175 23 240 31 614 NOx 75 000 1 651 471 20 261 71 131 168 514

SO2 2 617 30 9 68 5 094 7 818 Ni 0.000 0.004 0.001 0.008 0.011 0.02 Zn 0.000 0.050 0.014 0.114 0.156 0.33 Cd 0.000 0.001 0.000 0.001 0.382 0.38 Hg 0.000 0.000 0.000 0.000 0.380 0.38 Pb 0.000 0.000 0.000 0.000 0.000 0.00 Dioxin (mg/year) 0.000 0.000 0.000 0.000 1.080 1.08

Table 39: Gaseous emissions (kg/year) calculated for Turin waste management system for the year 2004

Emissions to water

The emissions to water concern the composting plant and the landfill operation.

The default value used in composting is 1.5 l/t. The leachate is supposed to be released in the environment respecting the regulatory limits.


• Rainfall in Turin: 632 l/m2


• Leachate generated corresponding to 20% of the total rainfall.


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Status Quo Composting Landfill Sum Waste treated t/year 38898 371591 Liquid emission l/year 58 347 2 148 800 2 207 147 Component unit COD kg/year 7.3 268.6 275.9 Hydrocarbons kg/year 0.6 21.5 22.1 Phenols kg/year 0.0 0.2 0.2 Halogenated organics kg/year 0.1 2.1 2.2 F- kg/year 2.9 107.4 110.4 As kg/year 0.0 0.2 0.2 Cd kg/year 0.0 0.4 0.4 Pb kg/year 0.0 1.1 1.1 Cr (VI) kg/year 0.0 0.2 0.2 Hg kg/year 0.0 0.1 0.1 CN kg/year 0.0 0.2 0.2 Heavy metals kg/year 0.9 32.2 33.1 Suspended solids kg/year 1.8 64.5 66.2

Table 40: Emissions to water from Turin waste management system

Land use

The land use assessment is based on the amount of waste treated. The column “Land use (amount prorate)” represents the area effectively took up to treat the amount of waste generated in Turin whereas the column “Land use (Plant)” represents the total area took up by the plant thus taking into account the land use for imported streams treatment or disposal.

Land use20 (amount prorate)

Land use (plant)

Land use (ha/year)

Waste input

(tons per year)

Total waste

treated21 (tons per

year)

Land use (ha)

Comments (duration of plant operation)

Sorting plant 0.13 10 070 10 070 2.0 15 years

Transfer station 0.1 120 000 120 000 1.5 15 years

Composting 0.075 33 900 33 900 1.5 20 years Landfill 1.7 373 057 700 000 90 28 years

Sum 2 537 027 95

Table 41: Land use calculated for Turin treatment plants and disposal for the year 2004

20 Land use (ha) directly linked to the treatment of waste from Turin 21 with waste imported


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Energy balance

Energy balance is given in terms of mega joules consumed per year and per each type of treatment/disposal (see Table 42). Figures are assessed in line with the waste quantities effectively generated in Torino. For instance, the total electricity production of the Landfill “Basse di Stura” is 75 475.3 MWh/year for the year 2004. However, wastes generated in Torino and disposed in the Landfill do not represent more than 51.7% of the total waste disposed of. Thus, the effective electricity production for waste coming specifically from Turin is equal to 39 066 MWh/year.

Status quo

Transport &

Collection Transfer station

Sorting plant

Composting plant Landfill TOTAL

Tons treated 690 435 120 000 10 070 33 900 373 057 Fuel consumption (GJ/year) 53 746 2 121 605 4 793 6 594 67 859 Electricity consumption (MWh/year) 108 242 441 448 1 238 Electricity production (MWh/year) 39 066 39 066 Steam production (GWh/year)

Table 42: Calculated energy consumption and production for waste management system of Turin for the year 2004


AWAST production costs models were adjusted to fit data from AMIAT. We knew from AMIAT that the average disposal cost in Turin for the year 2004 was 65 €/t. This figure has been used to calculate the cost for the disposal of residues coming from the composting and the sorting plants. The official gate fee for disposing MSW for the town of Turin was equal to 105 €/t, VAT excluded, in the year 2004. Finally, AMIAT got in 2004 the total amount of 115,260 k€ for all the collection services in Turin.

The adjustment was done for the landfill and the collection cost models. For the landfill cost model, it only concerned the parameters used for operating costs assessment. That means parameters used to take into account the cost for land excavation, for the laying of a geotextile and a geomenbrane, for leachate and gas collection, for salaries of employees, equipments, environmental monitoring, administrative costs and taxes. For the collection cost model as for the landfill cost model, the adjustment was done on factors describing the repair and the maintenance of containers, factors linked to taxes, bonus, clothes allowances, vehicles insurance, vehicles consumables consumption (tires, oil, batteries …) and maintenance.

The results of costs calculation are given in Table 43.


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Amount of waste treated (Tons in 2004)

Euros per ton

treated

Total costs (k€)

Receipt (k€) Details

Transport 173,576 32,7 - Collection 516,859 265 114,940 -

Sorting 10,070 120 1,206 -940 With of sorting products (170.5 euros/t), with disposal cost of

residues (105 euros/t)

Composting 33,898 58 1,969 - Without the sale of compost, with disposal cost of residues

(105 euros/t) Transfer 120,000 7 843 -

Recycling -4,550

Prices of recycling products (Paper : 78.8 euros/t, Glass : 15.5 euros/t, Plastics : 170.5 euros/t, Wood : 6.5 euros/t)

Landfill 371,591 94.5

(105 for MSW)

37,275 -2,166 With funds for the final closure of landfill

Civic amenity 4,657 100 468 -

TOTAL 156,735 -7,656

Table 43: Cost assessment of Turin waste management system for the year 2004

Finally, the final net cost stated by AMIAT of the collection/treatment system in Turin is equal to 149,079 k€ in 2004, that is to say a mean cost equal to 288 €/ton of waste collected. This cost is very high. It is justified by an expensive collection detailed for each waste type in Table 44 where even the collection of MSW is out of commonly encountered values. No precise justification was given for such figures.

Collected waste Tons of waste

treated

Capital cost (vehicles & containers)

(k€)

Operating cost (labour, taxes,

insurances, maintenance)

(k€)

Other costs (administrative

and management

expenses, financial costs)

(k€)

Sum (k€)

Sum (€/ton)

Biowaste 23,144 2,025 5,199 429 7,654 331 Glass 12,920 659 3,929 286 4,875 377

Plastics 7,066 184 1,080 143 1,407 199 Green waste 10,754 74 1,169 143 1,387 129

MSW 331,051 5,812 64,371 5,290 75,473 228 Wood 20,583 3,624 3,735 286 7,645 371

Paper & Cardboard 79,191 1,168 11,892 1,353 14,413 182

Mixed waste packaging 10,070 116 1,828 143 2,087 207

TOTAL 114 941

Table 44: Cost assessment of separately collected waste in Turin for the year 2004

NB: the costs linked to the recycling of batteries and WEEE were not taken into account.


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6. TØLLØSE CASE STUDY

6.1. Methodology


Most of the basic experimental data necessary for the case study comes from NOVEREN, the company in charge of collection and different sites for the treatment of the waste for Tølløse

• NOVEREN I/S, Affaldsplan 2005-2016, Vedtaget af NOVERENs bestyrelse, 15.10.2004

• Årsrapport 2005, NOVEREN I/S

• Årsrapport 2004, NOVEREN I/S

• GRØ NT REGNSKAB 2004, NOVEREN I/S

The rest comes from Danish averages (Waste statistics 2003 from the Danish Ministry of Environment –EPA) and from an interview of our partner 2.0 LCA with Anne Sofie Olsen, waste coordinator of Tølløse Municipality. Data for the year 2004 were thus collected and complemented with the waste statistics 2003 concerning the waste composition.




� Identification of incoherence (in - out ≠ 0); Data that were not coherent were reconciliated,

� Collection of missing data, taking into account.

All the data collected were used to build the simulator of the waste management in Tølløse for the year 2004 (see Figure 25)


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Figure 25: Flowsheet of Tølløse case study


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6.2. Waste management system of Tølløse

The population of Tølløse is 10.000 inhabitants. In Tølløse, they use 260 liter waste bin with two rooms - one for the green plastic bag with biowaste (40% of the volume) and on for the red plastic bag for other waste (60% of the volume) for the domestic waste. The household brings the bin to kerbside - or pay to have it rolled out by the waste collector. The private household is collected every 14 days, both biowaste and other at the same time. All bins are weighted and payment is by weight since 1993. Inspiration for the scheme came from Tinglev, who were the first to introduce weight based schemes in Denmark. Paper and glass containers are placed in the neighbourhood and other types of household waste (bulky waste) can be delivered to the container station. Domestic waste is collected by a contracted waste hauler and delivered to NOVEREN where the biowaste is composted (indoor facility). NOVEREN is owned by 9 municipalities in North Sealand (Bjergsted, Nykøbing-Rørvig, Tornved, Dragsholm, Kalundborg, Trundholm, Holbæk, Svinninge and Tølløse).


� Civic amenity site

� Transfer station

Three transfer stations are used, Holbaek, Kalundborg and Audebo.

� Biological treatment plant

Two biological treatment plants are used:

• Audebo indoor facility for biowaste in Holbæk (30km)

• biological treatment plant for garden waste in Vig (40 km)

� Landfill

Mixed waste and incombustible waste coming from the Tølløse civic amenity site are sent to the Audebo landfill gas plant in Holbæk. The landfill of Audebo covered an area of approximately 5.8 ha in 2001 and more than 150.000 tonnes of waste have been deposited. When totally extended the landfill will cover an area of approx. 17.5ha with a total waste volume of 1.4 mill tonnes of waste. In 2000, a biogas utilisation plant was constructed with production of electricity and heat.

� Incineration plant (Funen - 150km)

All mixed waste collected in Tølløse are sent to that plant.


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Amounts (tons of waste generated in 2004)

Mixed waste 2 541 Paper 524 Glass 181 Batteries 30 Garden waste 905 Biowaste 449 Metals 394 WEEE 60 Total 5 083

Composition

Woo

d(%

)

Pap

er (%

)

Gla

ss (%

)

Fe m

etal

s (%

)

Nfe

met

als(

%)

Pla

stic

s (%

)

Text

iles

(%)

Bio

was

te (%

)

Oth

ers

(%)

Mixed waste 32.7 9.7 1.9 1.6 0.5 16.3 3.9 4.8 28.5 Paper 0 95 0 0 0 2 0 1 2 Glass 0 0.1 98 0.2 0.1 0.2 0.0 0.1 1.5 Batteries 0 0 0 0 0 0 0 0 100 Garden waste 26 1 0.5 0.5 0.5 1 0 45 25.5 Biowaste 1 2 0 1.0 0 2 0 90 4 Metals 0 1 1 60 10 1 0 1 26 WEEE 0 0 0 0 0 0 0 0 100

Table 45: Waste generated in Tølløse


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6.4.1. Collection

NOVEREN services 9 municipalities of which Tølløse is one. Private household is collected every 14 days, both green (biowaste) and red (other) plastic bags at the same time. The truck includes a divider separating the waste in the emptying process.

The waste hauler is obliged to check the sorting and if faults are made, to give the household a warning (paper slip) the first time and not to take the waste the second time; failure rate is very low.

Bulky waste can be delivered to the container site where entrance is controlled by your social security card.

Battery waste is collected in small containers in schools, institutions, city hall, shops, etc. who all deliver to the container site where the batteries are sorted in hazardous and "non-hazardous" by the personnel at the container site. New containers will be introduced at the container site in spring 2006 for packaging waste (metal and plastic) as part of new requirements (EU packaging directive targets are not fulfilled by transport waste recycling).

Other waste is in transit for incineration and NOVEREN makes contracts for incineration depending on price etc.; presently waste is incinerated at Funen according to ASO. Non-combustible waste (fractions of the bulky waste) are landfilled.

WEEE will be collected at the container site.

6.4.2. Biological treatment

Two biological treatment plants are used:

• Audebo indoor facility for biowaste in Holbæk (30km) established by February 1st 2003

• biological treatment plant for garden waste in Vig (40 km)

The “Audebo” biological treatment plant is based on a two phase technology: anaerobic digestion and composting (the AIKAN System). The fully complete plants comprise a ventilated waste reception hall, separate process modules, stores for gas and percolate as well as a hall for storing the fully treated compost.

��

�

�

The solid waste is not moved between the modules during the process. The biogas process makes optimal use of the energy in biodegradable waste. Composting the solid residua ensures a compost product of high quality. Plastic and other impurities that have been sorted out and removed can be used in the incineration plant. The step by step process is the following:


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� Waste bags are opened and impurities are sorted out and removed using moveable and equipment: A mixer operated by a tractor is used to break up the waste. The slowly rotating blades open the bags and break up organic compounds into smaller particles, simultaneously ensuring that incorrectly sorted waste such as metal, glass, nappies and plastic do not affect the process.

� The sorted waste is broken up into smaller particles, and structural material that allows for the aeration and drainage of the waste mass is added. The waste mass (raw material) is then mixed thoroughly in the mixer and is then transferred to a process module via a conveyor belt mounted on the back of the mixer.

� The mixed waste is loaded into a process module. When the process module is full it is closed with an air-tight door. Liquid anaerobically digested material from the existing biogas plant is added through a system of pipes. To achieve the fastest possible process time the liquid, which is formed during the process, is collected, reheated and re-circulated in the process module. Biogas is continuously produced in a separate reactor tank. Biogas is combusted in a gas turbine, which produces electricity and heat. �

� After the satisfactory conversion of the waste, the waste mass is drained of percolate and the composting process begins. After the composting process (3 weeks) the compost is transferred to a storage hall where it is further stabilised and refined.�

In 2004, 3 068 tons of compost were produced for 13 584 tons treated (448.6 tons coming from Tølløse).

In Vig composting plant, in 2004, 690 tons of compost were produced for 5 742 tons treated (905.1 tons coming from Tølløse).

Residues from those two plants are landfilled.

6.4.3. Audebo landfill

From waste landfilled, 100 to 120 Nm3 of biogas per ton are produced. The biogas is burned to produce electricity and heat during 8 hours per day. The nominal capacity of the biogas burning facilities is 100 Nm3/h.

In 2004, 14 375 tons of waste were disposed of (coming from Tølløse and others cities); 191 MWh of electricity and 225 MWh of heat were produced from biogas for 133 MWh consumed.

Source: www.noveren.dk


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6.4.4. Results

Matter balance

� 5 083 tons of waste are collected.

� 2 216 tons are incinerated (43.6%).

� 1 354 tons are sent to organic recycling (26.6%).

� In fine, compared to the tons of waste collected :

• 1 305 tons are sent to recycling industry (25.7%) and 493 tons of bottom ashes are reused (9.7%).

• 285 tons of compost are produced (5.6%).

• 1 172 tons are disposed of (23.1%).

Figure 26: Tølløse Matter balance in 2004 (tons)


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Off-gas (pressure to environment)

For HOLIWAST, the following list of “pressures” was proposed: CO2, CH4, particles, land area, NOx, SO2, Ni, Zn, Cd, Hg, Pb, dioxin. The calculations include the combustion of biogas (biological treatment and landfill), the combustion of fuel by vehicles (all operations), the combustion of waste (incineration).

Status quo

Kg/year

Collection &

transport Transfer station

Biological treatment

plant Incineration

plant Landfill SUM Tons treated 9 554 2 729 1 354 2 216 1 172

CO2 fossil 83 745 3 642 14 454 1 008 674 1 564 1 112 078

CO2 org 126 712 771 345 133 850 1 031 907

CH4 0.3 0.02 0 0.005 41 832 41 832 Particles 119 2 51 138 14 323 NOx 1 094 38 303 2 760 61 4 256

SO2 37 1 13 687 3 741 Ni 0.002 0.000 0.000 0.710 0.000 0.71 Zn 0.023 0.001 0.005 32.970 0.000 33.00 Cd 0.000 0.000 0.078 0.690 0.000 0.77 Hg 0.000 0.000 0.078 0.690 0.000 0.77 Pb 0.000 0.000 0.000 2.270 0.000 2.27 Dioxin (mg/year) 0.000 0.000 0.000 1.400 0.100 1.50

Table 46: Gaseous emissions (kg) calculated for Tølløse waste management system for the year 2004

Emissions to water

The emissions to water concern the incineration plant, the MBT plant and the landfill operation.

The default value used in biological treatment is 1.5 l/t. The global emission is supposed to be released in the environment respecting the regulatory limits.

The default value is used for incineration (500 l/t of dry matter). The composition is set according to regulation limits.


• Rainfall in Tølløse: 571 l/m2


• Leachate generated corresponding to 20% of the total rain flow.

No composition data is available.


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Status Quo Biological treatment Incineration Landfill Sum

Waste treated t/year 1 354 2 216 1 172 Liquid emission l/year 2 031 775 600 26 266 803 897 Component unit COD kg/year 0.3 97.0 3.3 100.5 Hydrocarbons kg/year 0.0 7.8 0.3 8.0 Phenols kg/year 0.0 0.1 0.0 0.1 Halogenated organics kg/year 0.0 0.8 0.0 0.8 F- kg/year 0.1 38.8 1.3 40.2 As kg/year 0.0 0.1 0.0 0.1 Cd kg/year 0.0 0.2 0.0 0.2 Pb kg/year 0.0 0.4 0.0 0.4 Cr (VI) kg/year 0.0 0.1 0.0 0.1 Hg kg/year 0.0 0.0 0.0 0.0 CN kg/year 0.0 0.1 0.0 0.1 Heavy metals kg/year 0.0 11.6 0.4 12.1 Suspended solids kg/year 0.1 23.3 0.8 24.1

Table 47: Emissions to water from the Tølløse waste management system.

Land use

The column “Land use (amount prorate)” represents the area effectively took up to treat the amount of waste generated in Tølløse whereas the column “Land use (Plant)” represents the total area took up by the plant thus taking into account the land use for imported streams treatment or disposal.

Land use (ha)

(amount prorate) Waste input

(tons per year) Land use (ha)

(Plant)

Transfer station 0.002 2 729 0.4 (3 plants)

Incineration plant 0.004 2 216 6.3

Biological treatment plant 0.002 1 354 1.6

(2 plants)

Landfill 0.023

1172 5.6

(1 landfill for non hazardous waste)

Sum 0.031

Table 48: Land use calculated for Tølløse treatment plants and disposal for the year 2004

Energy balance

This energy balance is based on the amount of waste treated in those plants generated in Tølløse.


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Status quo

Transport &

Collection Transfer station

Biological treatment Incineration Landfill TOTAL

Tons treated 9 554 2729 1 354 2 216 1 172 Fuel consumption (GJ/year) 949.7 48.2 191.5 15.7 20.7 1 226 Electricity consumption (MWh/year) 6.8 11.4 209.3 10.0 237 Electricity production (MWh/year) 66.8 457.8 14.3 539 Steam production (GWh/year) 2.3 0.02 2.4

Table 49: Calculated energy consumption and production for waste management system of Tølløse for the year 2004


AWAST production costs models were adjusted to fit data supplied for the case study by 2.-0 LCA consultants Holiwast partner reported in the following table:

Cost data

Transport No specific data

Collection

Global ratio of 60 euros per ton for mixed waste without the costs linked to containers Others examples of collection costs: Bergen 159 euros/ton, Copenhagen 118 euros/ton, Helsinki 74 euros/ton

Recycling Revenues linked to the collected products directly sent to recycling industries. No specific data

Civic amenity site No specific data Biological treatment plant of Audebo Global ratio of 101 euros/ton

Transfer station No specific data Incineration Global ratio of 37 euros/ton and details in “Regnskab Og rapport 2005”

Landfill Global ratio of 54 euros/ton Electricity selling and purchase price

Table 50: Cost data supplied for Tølløse case study

The adjustments performed are the following:

� Transport of waste, recycling, civic amenity site, transfer stations and the composting plant of Vig:

No specific data were supplied to adjust the AWAST collection model to the local context of the case study. So, default values from AWAST project were used to assess these costs.

� Audebo landfill:

The local specific prices of electricity selling and purchase were used. Without taking into account land purchase, environmental fee estimated by AWAST but with closure and post-closure costs, the model estimates a landfill cost of 52 euros per ton compared to the 54 euros per ton. No further adjustment was performed because a detailed description of the landfill cost was not available and the difference between the two costs in euros per ton does not oblige to implement a further global adjustment.

� Audebo biological treatment plant:


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The AIKAN process is not a usual one. So, no cost model is available in the AWAST simulator to assess the cost of such process. The global ratio of 101 euros per ton treated was used directly within the simulator.

� Incineration plant:

Operating costs were adjusted based on data extracted from “Regnskab Og rapport 2005”. Investment costs were then adjusted to fit the global ratio of 37 euros per ton.

� Collection:

The purchase cost of vehicle and the vehicle lifespan was given by 2.-0 LCA consultants Holiwast partner. The AWAST cost assessment after adjustment of the operating conditions of the waste collection evaluates the collection cost of mixed waste to 56 euros per ton without container cost.

A cost of 60 euros per ton for the collection of mixed waste (apart from the container cost) was supplied for Tølløse city. The cost model was then not further adjusted considering that the model fits well the real data at least for mixed waste collection. No data were available for other waste collection (paper, glass).

In fine, the following waste collection costs were estimated:

Euros per ton

Glass (bring collection) 64

Paper (bring collection) 73

Biowaste and mixed waste collection Waste collected within the same divided bin (kerbside) 128

Table 51: Costs of waste collection in Tølløse

The results of costs calculation are given in the following table.


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Details of costs (k€)

Amount of waste treated (tons in 2004)

Euros per ton

treated

Total net costs (k€) Production

cost (k€) Receipt

(k€)

Details

Transport 7 568 6.8 51.784 51.784 Collection 1 986 110.1 218.651 218.651 Civic amenity site 3 097 50.4 156.000 156.000

Transfer station 2 729 24.5 66.890 66.890

AD / Composting plant

449 65.4 29.323 29.323


905 28.9 26.192 26.192

Incineration 2 216 70.0 67.450 155.049 -87.599

Without the cost linked to treatment of residues

Landfill 1124 54.1 58.407 60.832 -2.425 Treatment of residues from incineration Hazardous landfill 48 9.608 9.608 Disposal of fly ashes

and filter cake

Bottom ashes treatment 493 4.720 4.720 Treatment of bottom

ashes before re-use

Recycling -70.470 -70.470 Collected products directly to recycling

SUM 618.555 779.048 -160.494

Details of costs (k€) Details

Amount of waste treated (tons in 2004)


Total costs (k€) Production

cost (k€)

Receipt (k€)

Cost linked to the

treatment of residues

(k€)

Transport 7 568 6.8 51.784 51.784 Collection 1 986 110.1 218.651 218.651

Civic amenity site 3 097 50.4 156.000 156.000

Transfer station 2 729 24.5 66.890 66.890

AD / Composting plant

449 100.5 45.099 29.323 15.777 Residues in landfill


905 57.4 51.965 26.192 25.773 Residues in landfill

Incineration 2 216 36.9 81.778 155.049 -87.599 14.328 Landfill 325 51.9 16.857 17.557 -0.700 Recycling -70.470 -70.470 SUM 618.555 721.446 -158.769 55.877

Table 52: Cost assessment of the waste management system in Tølløse for the year 2004

NB: the costs linked to the recycling of batteries and WEEE were not taken into account.


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The final net cost of the collection/treatment system in Tølløse is equal to 619 k€. This cost can be evaluated as follows:

� 62 € per inhabitant (10 000 inhabitants)

� 122 € per ton generated (5 083 tons generated in 2004)


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7. CONCLUSION

The following table synthesizes the waste management system implemented within the case studies:

Turin Katowice Tølløse

Inhabitants 902 910 323 400 10 000 Mixed waste Mixed waste Mixed waste

Paper / Glass / Plastics / Metal / Mixed secondary

materials

Paper / Glass / Mixed secondary materials

(Plastics & metal)

Paper / Glass Metals

Biowaste Biowaste Manually collected

road waste Garden and park

waste

Manually collected road waste

Garden and park waste + Market waste

Garden and park waste

Waste considered within case studies

WEEE Batteries

Batteries

WEEE Batteries

Tons of waste generated 516 859 120 224 5 083

Year of reference (data) 2004 2003 2004

Waste generated in Kg per inhabitant 572 372 508

Mixed waste to landfill Mixed waste to incineration

Main waste treatment Biowaste and garden and park waste to

composting

Mixed waste to mechanical and

biological treatment plant and landfill

Biowaste to composting

Table 53: Synthesis of the waste management in the three case studies

The list of waste flows to be included in HOLIWAST case studies was defined during the project. The waste flows considered within these three case studies are the ones from this predefined list that could be identified within the waste management systems. Not all the streams are present in the three case studies. Thus, the comparison of the waste management systems of the three case studies must be performed with caution.


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Turin Katowice Tølløse

% Recycling (tons of products sent to recycling industries divided by the waste generated in tons)

25% 2% 26%

(+10% reuse of bottom ashes)

% Compost (tons of compost produced divided by the waste generated in tons)

1% 7% 6%

Waste treatment cost in euros per tons 288 €/ton 42 €/ton 122 €/ton

Waste treatment cost in euro per inhabitant 165 €/hab 16 €/hab 62 €/hab

Table 54: Synthesis of the matter and cost balance of the three case studies

In the same way, the comparison between waste management costs should be performed with caution because a lot of factors are influencing this evaluation:

� the waste considered within the three case studies are those for which data have been reported by the persons contacted (municipalities and companies operating waste management);

� the amount of real data on costs differs significantly between the three cases: missing data have been replaced by default values from AWAST database and costs models;

� the exact content of costs included in supplied data is not known precisely. These data are extracted from specific accounting systems which are not harmonised at European level. Even if some costs (collection costs in Turin) appear extremely high, the real data have always been favoured compared to costs calculated by the models.


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Annex 1

Questionnaire - composting

Katowice

Identification

Type of process (cf. typology below) M-U-T DANO

Nominal capacity (t/year) 50 000 Mg (200 Mg/day)

Working periods (hours/day, days/year) 24, 250

Process synoptic

Description of equipments (type SILODA reactor, type BRS tube, densimetric table, screen, �rammel, press, grinder, crusher, overband,…)

Tube Biostabilisator, drum screen,

Livell screen, magnetic separator – conveyor belt, separator for hard materials– conveyor belt

Matter balance Data source (annual report…) Annual Report 2003 - Data

concerning categories and quantity of waste, methods of management and installations and facilities used for recovery

and disposal of waste

Date of the data January 1 – December 31,2003

Type of waste coming in the installation 20 03 01 – mixed waste

Capacity (t/year) 50 000


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Composition of waste[%]– data from investigations –Dec. 2000

- Organic waste (plant food) - Organic waste (animal food) - Paper and cardboard - Plastics - Textiles - Glass - Metals - Other organic waste - Mineral fraction – below 10 mm - Other mineral fraction

29.06

0.97

25.64

15.28

4.89

10.14

2.43

4.65

4.63

2.31

Additives, composition and flowrate (t/year)

- 20 03 01 – mixed waste - 20 03 03 – waste from cleaning roads - 20 02 01 – biodegradable waste - 03 01 05 – sawdust - 19 12 12 – others from mechanical treatment

of wastes

42 975.53

3 579.55

279.16

7.18

960.40

Water consumption (m3/year) 1382.4

Total discharge of water (with leachate) (m3/year) 841.2

Discharge of leachate (m3/year)

Composition of leachate Meets requirement for waste water as a feed to sewage

treatment, directly connection to sewage treatment plant

Mean residence time in the reactor or in the tube (days) 24 to 36 hours

Mean residence time on the maturing platform (days) 180 days

Annual production of compost (t/year) 7 733


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Composition of the compost [kg/1 mg dry matter]

- Organic matter - Nitrogen (N) - Phosphorus (P205) - Potassium (K2O) - Calcium (CaO) - Magnesium (MgO)

244.00

9.10

5.60

2.50

80.70

6.60

Annual amount of refuse (t/year) 29 797.25

Refuse composition [%]

- Moisture - Combustible matter - Non-combustible matter - Heat of combustion [kJ/kg] - Heating value [kJ/kg]

36.7

42.0

21.3

19 730

10 320

Annual amount of scrap (t/year) 306.54

Other information concerning materials flow rates Waste come only from Katowice City site

Cost assessment (VAT not included)

Process Investment cost (€)

(value on 01.01.1995)

3 394 328,74

Operating costs (€/year) 1 377 715.22


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Split of operating costs (payroll, maintenance and repair, renewal of equipments, removal of by-products…)

- Pay-roll - Maintenance and repairing - Renewal of equipment - Removal of by-products

267 248.63

193 801.73

139 726.54

481 211.86

Land purchase cost (€)

Tax (€)

No data

60 347.66

Treatment cost for the treatment of one ton of waste (€)

28.82

Selling price of the compost (€) 9.50

Energy assessment

Electricity consumption (kWh/year) 931 811.00

Fuel consumption (type and quantity) (L/year) Fuel oil, 48 077.0

Transport of compost : localisation of final destination and kilometers (km per trip - one way), type of vehicle used (truck, boat, train) and capacity of storage (m3)

- Destination - Type of vehicle - Capacity of storage [m3]

15 km

Truck (with containers)

36

Transport of refuse : destination (incineration, landfill …) and kilometers (km par trip – one way)

- Landfill - Incinerator

2.5 km

28 km

Social assessment


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Number of employees (administration, manager and technician)

- Head - Manager - Administration staff - Laboratory staff - Process operation staff - Security staff

1/3

1

1

1

16

4

Typology of composting processes :

Critical data Nice-to-have


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Questionnaire – sorting plant

Katowice

Identification Type of waste to be sorted

- 20 01 01 paper and cardboard - 15 01 06 mixed packaging - 20 01 06 glass

Jan. 1 – Dec. 31, 2003

265.8 Mg/year

487.8 Mg/year

480.0 Mg/year

Characteristics (composition et density) No data

General characteristics of the plant Type (Manual, semi-mechanised, mechanised, automated) manual

Nominal capacity per flow (t/year) 1 650

Working period per month (days/month) 21

Lifespan of the plant (years) 9

Number of sorting line(s)

- line (called soft) for manual sorting of paper, cardboard, plastics and textiles

- line (called hard) for manual sorting of glass and metal cans

1

1

Number of conveyor belt(s) 4

Capacity (t/h) and characteristics (width, positive or negative sorting) of the conveyor belt(s)

- Capacity by positive sorting - Width of conveyor belts - Sorting positive

1

1000 mm

Matter balance Date of the data Jan. 1 – Dec. 31, 2003


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Amount of waste annually treated per type of waste (t/year)

- 20 01 01 – paper and cardboard - 15 01 06 – mixed packaging - 20 01 06 - glass

265.8

487.8

480.0

Amount of waste annually sorted per product (t/year)

- 20 01 01 – paper and cardboard - 15 01 02 – plastic packaging - 15 01 07 – glass packaging - 15 01 04 – metals packging

128.9

57.3

75.8

11.3

Amount of sorting refuse (t/year) 960.4

Annual variation of the stocks (sorted and not sorted products)


265.8

487.8

480.0

Flows compositions


265.8

487.8

480.0

Synoptic and/or flowsheet of the sorting process No monitoring/no data

Equipments (give the annual electric consumption kWh/year)

Weighbridge no monitoring – no data (nd)

Overband nd

Eddy current equipment nd

Heavy/light materials separator nd

Screen/rotary screen nd

Baling press nd


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Ferrous materials press nd

Weighing belt nd

Transport

Transport of the refuse: destination (incineration, landfill) and distance (km/one way trip)

Refuse from sorting are directed to treatment in composting plant

0 km

Transport of sorted products: take-over society, destination and distance (km/one way trip)

Sorted products are taken by different users (recyclers)

Distance to destination

Max 30 km

Selling price of the recovered materials (euros/t)

- 20 01 01 – paper and cardboard - 15 01 02 – plastic packaging - 15 01 07 – glass packaging (white) - 15 01 07 – glass packaging (colour) - 15 01 04 – metals packaging

25.00

130.00

32.50

17.50

20.00

Consumption

Electricity (kWh/year) 209 657

Fuel consumption (L/year)

- fuel oil - gas

11 048

3 688

Lubricants (kg/year) 40

Water (m3/year) 460.1


Investment cost (€)

Value of equipment at the beginning

711 653,55

Operating costs (€/year) 208 153.06


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- payroll - operation/maintenance - removal of by-products

137 347.71

36 984.33

27 678.78

Land purchase (€)

Social assessment

Number of employees (administration, direction and technicians)

- Head - Manager - Administration staff - Process operation staff - Security staff

1/3

1

1

10

3



93/96

Questionnaire - transfer station

Katowice

Identification

Type of waste 20 03 01 - mixed municipal waste

Nominal capacity (t/year) 10 000

Transfer station associated with a sorting plant, incineration plant, composting plant or landfill?

Yes, transfer point is directly associated with composting plant

Principle :

Transfer without refilling (waste transferred directly to vehicles or containers)

Transfer with refilling (waste unloaded within a pit)

Transfer with refilling (waste unloaded on a flagstone)

Yes

Yes

Yes

Compaction before loading for transport (Yes/No?) No

Equipments

Pit (Yes/No?) Yes

Bridge crane (Yes/No?) Yes

Hydraulic Grab (Yes/No?) Yes

Flagstone (Yes/No?) Yes

Loader with rocker arm shovels (Yes/No?) Yes

Grab (Yes/No?) No

Sorting line (Yes/No?) No

Compactor (Yes/No?) No

Mill (Yes/No?) No

Matter balance Data source (annual report…) Annual Report 2003

Date of the data Jan.1 – Dec. 31, 2003

Tons received per type of waste (t/year) 8456.34

Tons transferred per type of waste (t/year) (if difference between waste received and waste transferred)

8456.34


Investment costs(€) Included in costs of composting plant

Operating costs (€/year) Included in costs of composting plant


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Included in costs of composting plant

Land purchase cost (€) Included in costs of composting plant

Downstream transport

Downstream transport of waste : localisation of final destination and �ilometres (km per trip – one way), type of vehicle used (truck, boat, train) and capacity of storage (m3) per type of waste

- Landfill LANDECO, Siemianowice - Landfill, Sosnowiec - Type of vehicles - Capacity (m3)

20 km

41 km

truck (with containers)

36

Consumptions

Electricity (kWh/year) Included in costs of composting plant

Fuel consumed (L/year) Included in costs of composting plant

Lubricants (L/year) Included in costs of composting plant

Water (L/year) Included in costs of composting plant

Social assessment

Number of employees (administration, manager and technician)

Included in costs of composting plant



Centre scientifique et technique Service Environnement & Procédés

3, avenue Claude-Guillemin BP 6009 – 45060 Orléans Cedex 2 – France – Tél. : 02 38 64 34 34

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