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WASTE CHARACTERIZATION STUDIES IN WASTE MANAGEMENT MUNICIPALITY UNIONS IN TURKEY – METHODOLOGY AND RESULTS
In the framework of the IPA project "Technical Assistance to Prepare Integrated Solid Waste Management Projects in Turkey- Lot 1” (EuropeAid/128133/D/SER/TR) Solid Waste Characterization Studies (SWCS) were implemented in the Aegean, Marmara and Thracian Region of Turkey. SWCS provides municipality service unions with waste data required for the formulation and implementation of waste management planning and with information on technical concepts and designs for waste treatment plants. To investigate Municipal Solid Waste (MSW) an advanced methodology was developed. The methodology is based on the experience of international waste analysis knowledge [1;2;3;4] and is compared to the Turkish guidance on waste characterization. It considers the waste services in small and medium municipalities (population between 2.000 and 200.000 inhabitants and selected villages). Municipalities of these size has not been surveyed much in Turkey yet. Basic element of this methodology is, that the samples are taken at source before they are loaded to the refuse collection vehicle and compressed. This ensures, that the components can be identified clearly and that moisture transmission from organic to other components is minimised. First results show, that organic is the predominant category (50 to 60 %). Organic is main source for water in MSW. Recyclables are varying according to different strata and separate collection arrangements implemented.
Keywords: Municipal solid waste, waste characterization, sampling, sorting analysis, waste composition
In the framework of the IPA project "Technical Assistance to Prepare Integrated Solid Waste Management Projects in Turkey- Lot 1” (EuropeAid/128133/D/SER/TR) Solid Waste Characterization Studies (SWCS) were implemented in several waste management municipal service unions in the Aegean, Marmara and Thracian Region of Turkey in Summer 2012 and winter 2012/13. At least two analysis campaigns in summer and winter time are necessary to represent the variation of waste composition in the course of the year. Most of the municipalities surveyed have a population of less than 120.000 inhabitants. For municipalities of this size currently few data are available in Turkey. SWCS provides municipality unions with waste data required for the formulation and implementation of waste management strategies and planning and with information on technical concepts and designs for waste treatment plants. The main purposes of Solid Waste Characterization Studies are:
Data and information from Solid Waste Characterization Studies (SWCS) are the indispensable basis for the planning, decision, construction and improvement processes within municipal and operational waste management. SWCS results describe the amount and composition of each waste type at source and/or disposal site and particle size distribution. In addition future waste amounts and composition can be forecasted (waste prognosis). Based on the targets for waste prevention and waste recovery on the one hand and the present waste amounts and composition on the other hand, measures for waste reduction, waste recovery and waste treatment can be developed.
2. METHODOLOGY FOR WASTE CHARACTERIZATION
Basic element of the methodology applied is, that the samples (defined units of waste) are taken before they are loaded to the refuse collection vehicle and compressed. This ensures, that the components can be identified clearly, that moisture transmission from organic fractions to other components is minimised and that as much information as possible can be assigned to the sample (such as number of households, social status, ratio of business using the same waste bin etc.). Furthermore the variance between samples collected at households is lower as it is between samples of refuse vehicles. This is because waste amounts and composition can be assumed simular between households. After mixing the waste from households in the collection vehicle it is nearly impossible to take samples with compareable low variance as from samples taken at households. Sampling at source will reduce the amount of waste to be analysed tremendously and therefore also the costs of the analysis.
2.1. Sampling methodology
The samples were taken according to the methodology of multistage stratified random selection. The multistage approach reduces the expenditure of planning the survey and taking samples. The survey area will be subdivided on the first stage into statistical areas (e. g. rural districts into municipalities or cities into town districts) and on the second stage into living areas (e. g. town districts into streets or residential blocks). Relevant information about the waste generator is needed on the lowest stage only (reduction of planning effort). The samples can be taken from the selected areas on the lowest stage (reduction of sampling effort).
Stratification of the parent population has also been proven essential. Dependencies of waste amount and composition from criteria such as social structure, residential structure, seasons, bin size, fee system, different collection systems etc. can be considered and will reduce the variance and therefore the costs of the analysis. In order to gain an insight on the total waste in the surveyed area and to get a significant validity of the obtained data according to the parent population (residual waste amount from households in survey area) a stratification is applied according to criteria as elaborated on further. A stratification is the statistical subdivision of the heterogeneous value of parent population into homogeneous part entirety (i.e. areas of similar residential structure). As such the planned surveys of wastes from households are viewed upon according to influences by features like container volume, container systems and community structure. Hence, a stratification permits partial cognition of important details of waste management aspects. It allows also to reduce the extent of random sampling by a given degree of the desired result exactness. On account of this technique the expense may be considerably reduced without jeopardising the safety of data.
Furthermore it is important to select sampling units which have the same probability to be selected (random selection). This means, that sampling units have to be defined with equal volume. We propose sampling units to be analysed separately with a volume of 1 m³. Smaller units can be summarized (e. g. 2 x 500 l or 4 x 240 l). In the case of a waste collection system without waste bins appropriate waste bags or buckets has to be provided as sample units.
To achieve representative results with sufficient accuracy it is important to calculate the total sample size (number of samples multiplied with the size of a single sample unit) as precisely as possible. Due to our experience it is sufficient to collect 40 to 50 single sample units (each with a volume of 1 m³) to predict the composition for the main fractions with an accuracy (deviation from the mean value) of less than 10 %. The exact number of sample units depends on the heterogeneity of the sample units, which has to be determined by a pre-test or estimated by previous results of results from similar analyses. The sampling process for the multistage stratified random selection is schematically given in figure 1.
Figure 1: multistage stratified random selection
2.2. Sorting methodology
Each single sample unit with a volume of 1 m3 has to be analysed according to a standardised sorting procedure. Depending on the requirements, the samples will be classified into fractions and each fraction will be sorted manually into defined categories according to a standardised sorting catalogue. The mentioned screen sizes are often used in European Solid Waste Analysis but can vary according to the project objectives. In any case it is recommended to use a screen size of 10 mm because components with smaller size should be summarised to one fraction (Fine fraction). For the definition of sorting categories we propose a standardized sorting catalogue used in European countries. This ensures comparable data on international level and allows international waste management companies a first good assessment of the waste quality to be processed. Figure 2 illustrates the sorting procedure.
Figure 2: Sorting schemata
3. Implementation of solid waste characterization
STILL IN PROCESS
STILL IN PROCESS
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