CHARACTERISATION OF MUNICIPAL SOLID WASTE COMPOSITION INTO MODEL INPUTS J. LAMBORN Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Australia Email: [email protected] SUMMARY: Landfill gas generation models require the conversion of waste composition data into model inputs. Waste composition data is usually collected in the form of waste fractions: green waste, food, plastics, metals, paper, inert etc. These waste fractions need to be characterised into cellulose, hemicellulose, lignin and inert; for inputs into models. This paper analyses the work that has been done on this characterisation and identifies where future work could be undertaken to help with the conversion of waste composition data into model inputs. 1. INTRODUCTION A landfill gas generation model is a tool that provides an estimation of generated methane or total landfill gas volume over time from a particular volume of waste. The purpose of a model is to describe (in simple terms) the complex changes during decomposition of waste in a landfill. For a model to accurately reflect the processes within a landfill, it must take into account the complex nature of the microbiological decomposition of waste within a landfill, the nature of the landfill itself, the chemical reactions and the ability of gases and liquids to move through the landfill. These types of models are known as component models and are the next generation of landfill models. The leading component models are LDAT (University of Southampton, UK), POSE (Technical University Braunshweig, Germany), HBM (Napier University, UK) and MODUELO (University of Cantabria, Spain). These models were all compared as part of the Hydro-Physico-Mechanics 2 (HPM2) Challenge to landfill modellers in 2007 (Ivanova, Richards et al. 2007b). One of the main inputs required for any landfill gas generation model is the waste composition data. For this data to be of use for a landfill model, it must be converted into input values that the particular model requires. Depending on the complexity of the model being used, the waste compositions are normally converted into the categories of fast, medium and slow degradation rates. Simple models tend to combine all these rates together to create a combined decay rate that is normally used within a first order decay model. Better developed models use a combination of degradation rates. Component models vary in their approach to dealing with the conversion of the waste composition into model inputs. Majority of models require two - three degradation rates. From the results of HPM2 (Beaven, Ivanova et al. 2007) it was noted that the conversion of the experimental data into input data was challenging for most of the models. Third International Workshop “Hydro-Physico-Mechanics of Landfills” Braunschweig, Germany; 10 - 13 March 2009 Third International Workshop “Hydro-Physico-Mechanics of Landfills”, 2009 2. WASTE COMPOSITION DATA Waste composition data is usually collected in the form of waste fractions such as: green waste, food, plastics, metals, paper, textiles, glass, inert etc. Many Environment Protection Agencies around the world undertake regular analysis of their municipal solid waste (US-EPA 2008) (Sustainability-Victoria 2007). Waste composition and quantities vary from country to country and within regions within the one country. Therefore local data is required to predict landfill degradation rates and methane quantities. Some landfills and large scale test cells have a good record of the waste composition, quantities and length of filling; however most full–scale landfills are lacking this high quality input data. The waste surveys undertaken at regional, state and/or national level can help provide guidance when individual site data in missing. A good comparison of waste composition data from around the world was undertaken by Barlaz in 2006, as shown in Table 1. Table 1. Selected global waste composition data (Barlaz 2006) Waste component US Singapore UK Germany Spain Australia 2001 2000 2004 2001 1999 Total paper 28.0 20.6 19 10.3 21 9.9 Newsprint 3.0 Office paper 2.1 Magazines 0.9 Boxes 5.4 Other paper 16.6 Total metals 7.4 3.2 8 5.4 4 7.1 Aluminium cans 0.5 Steel cans 0.6 Other metals 6.3 Total plastics 14.9 5.8 7 7.9 11 7.3 PET 0.3 Milk and water 0.3 bottles (HDPE) Other plastic 14.3 Total glass 6.3 1.1 4 4 7 6.8 Glass containers 5.3 Other glass 1.0 Food waste 15.8 38.8 38.1 Yard waste 7.5 2.7 17.8 Compostables 41 26.0 44 Textiles, rubber and 8.5 0.9 2 3.5 5 leather Wood 7.4 8.9 6 3.3 6.4 Other 2.0 15.3 13 34.5 8 6.6 Miscellaneous 2.2 2.7 5.1 inorganics Once the waste composition data for a particular site is known (or estimated), this information needs to be converted into terms that predictive landfill models can use. The number and type of parameters required will depend on the model. However, the component models tend to require multiple degradation rates, rather than a single decay rate such as the more simple models use Third International Workshop “Hydro-Physico-Mechanics of Landfills”, 2009 i.e. the US-EPA first order decay model, LANDGEM (US-EPA 2005). 3. WASTE CHARACTERISATION STUDIES A number of studies have been undertaken over the last decade examining the characterisation of waste composition into cellulose, hemicellulose, and in some cases lignin. ● (Ham, Norman et al. 1993) ● (Stinson and Ham 1995) ● (Eleazer, Odle Iii et al. 1997)/(Barlaz, Eleazer et al. 1997b), (Barlaz, Eleazer et al. 1997a) ● (Wang, Odle et al. 1997) ● (Baldwin, Stinson et al. 1998) ● (Komilis and Ham 2000) ● (Environment_Agency 2004) ● (Rodriguez, Hiligsmann et al. 2005) ● (Barlaz 2006) ● (Ivanova, Richards et al. 2007a) ● (Barlaz 2008) These studies have examined different waste streams and some of these studies are significantly more comprehensive than others. 3.1 Municipal Solid Waste Studies These studies show a large variety in values of all the MSW composition studies examined. This is due to the issues, as discussed above, in the composition and quantities of municipal solid waste between regions, states and countries. Therefore, these values should only be used a guide for modelling purposes due to the range of results, as shown in Table 2. Table 2. Comparison of Municipal Solid Waste studies Hemi- Volatile Source Secondary sourceCellulose Lignin Protein (C+H)/L cellulose solids % % % % (Ham, Norman 17.28 5.14 12.67 2.77 1.77 38.85 et al. 1993) (Eleazer, Odle Iii et al. 1997) (Barlaz, Eleazer 28.8 9 23.1 1.64 75.2 et al. 1997b) (Barlaz, Eleazer et al. 1997a) Ham and (Barlaz 2006) 42.4 6.6 10.9 3.89 Bookter (1982) Third International Workshop “Hydro-Physico-Mechanics of Landfills”, 2009 Hemi- Volatile Source Secondary sourceCellulose Lignin Protein (C+H)/L cellulose solids % % % % Jones and Grainger 25.6 11.9 7.2 4.5 59.6 (1983a,b) Bookter and 63.4 9 15.7 4.04 Ham (1982) Barlaz et al. 51.2 8.7 15.2 4.15 78.6 (1989) Eleazer et al. 28.8 10.6 23.1 1.64 75.2 (1997) Rhew and Barlaz 38.5 6.7 28 1.68 (1995) Ress et al. (1998) 48.2 10 14.5 4.06 71.4 Barlaz 36.7 10.8 13.6 3.19 (unpublished) Price et al. 43.9 5.8 25.1 2.15 (2003) Barlaz 54.3 12.1 5.38 86 (unpublished) Barlaz 22.4 11 2.57 (unpublished) (Ivanova, Richards et al. 24.8 6.7 9.7 3.2 2007a) Average 37.59 8.41 15.85 2.77 3.13 69.26 SD 13.62 2.19 6.39 1.24 15.60 3.2 Various Waste Composition Studies The results from a number of studies have been grouped by waste type as shown in tables 3 – 6. Table 3. Comparison of Paper Product Studies Secondary Hemi- (C+H)/ Volatile Category Source Cellulose Lignin Protein source cellulose L solids % % % % Newspaper (Stinson and 51 25.1 Ham 1995) (Eleazer, Odle 48.5 9 23.9 2.41 98.5 Iii et al. 1997) (Environment _Agency 18.5 9 2004) Wu et al. 48.3 18.1 22.1 3.00 98 (Barlaz 2006) (2001) Third International Workshop “Hydro-Physico-Mechanics of Landfills”, 2009 Secondary Hemi- (C+H)/ Volatile Category Source Cellulose Lignin Protein source cellulose L solids % % % % Eleazer et 48.5 9 23.9 2.41 98.5 al. (1997) (Barlaz 2008) 48.5 9 23.9 2.41 98.5 Average 43.88 10.82 23.78 2.56 98.38 SD 12.48 4.07 1.07 0.30 0.25 Office (Eleazer, Odle 87.4 8.4 2.3 41.65 98.6 Paper Iii et al. 1997) Wu et al. 64.7 13 0.93 83.55 88.4 (Barlaz 2006) (2001) Eleazer et 87.4 8.4 2.3 98.6 al. (1997) (Barlaz 2008) 87.4 8.4 2.3 98.6 Average 81.73 9.55 1.96 62.60 96.05 SD 11.35 2.30 0.69 29.63 5.10 Magazines (Environment _Agency 42.3 9.4 2004) Other (Stinson and 100 0 paper Ham 1995) (Eleazer, Odle 42.3 9.4 15 3.45 74.3 Iii et al. 1997) (Environment _Agency 87.4 8.4 2004) Eleazer et 42.3 9.4 15 3.45 74.3 (Barlaz 2006) al. (1997) (Barlaz 2008) 42.3 9.4 15 3.45 74.3 Average 62.86 9.15 11.25 3.45 74.30 SD 28.50 0.50 7.50 0.00 0.00 Corrugated (Eleazer, Odle 57.3 9.9 20.8 3.23 98.2 containers Iii et al.