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Copyright © ISWA 2002

Waste Manage Res 2002: 20: 514–528 Printed in UK – all rights reserved

Waste Management & Research

ISSN 0734–242X

Modelling for environmental assessment of municipal solid waste landfills (Part II: Biodegradation)

The biodegradation module of a simulation program for municipal solid waste landfills (MODUELO) was developed. The biodegradation module carries out the balance of organic material starting with the results of the hydrologic simulation and the waste composition. It simulates the biologic reactions of hydrolysis of solids and the gasification of the dissolved biodegradable material. The results of this module are: organic matter (COD, BOD and elemental components such as carbon, hydrogen, nitrogen, oxygen, sulfur and ash), ammonium nitrogen generated with the gas and transported by the leachates and the potential rates of methane and carbon dioxide generation. The model was calibrated by using the general tendency curves of the pollutants recorded in municipal solid waste landfills, fitting the first part of them to available landfill data. Although the results show some agreement, further work is being done to make MODUELO a useful tool for real landfill simulation.

Introduction Landfill simulation

In the recent past, the use of simulation programs as tools for the design and monitoring of different environmental installations (sewerage networks, water treatment plants, etc.) has become widespread. However, a series of programs has not yet been accepted as a general reference for the simulation of landfills and their effects on the environment, as has happened in other fields (such as SWMM (Huber et al. 1988) or MOUSE (Danish Hydraulic Institute 1998) for sewerage networks, for example). A

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Amaya Lobo García de Cortázar Javier Herrero Lantarón Oscar Montero Fernández Iñaki Tejero Monzón Grupo de Ingeniería Ambiental. Universidad de Cantabria (Spain).

Maria Fantelli Lamia Empresa de Residuos de Cantabria (Spain).

Keywords: Landfill, biodegradation, organic pollution, leachate, mathematical modelling, dynamic simulation, municipal solid waste, landfill history, wmr 438–7. Corresponding author: Amaya Lobo García de Cortázar, Grupo de Ingeniería Ambiental. Dpto. Ciencias y Técnicas del Agua y Medio Ambient, Universidad de Cantabria, EU Ingeniería Técnicas de Minas, 39316 Tanos, 254 Bulevar Ronda Rufino Peón, Torrelavega (Cantabria), Spain.

Received 2 August 2000, accepted in revised form 11 September 2002.

model, validated with real data from various facilities, which considers the several aspects that must be taken into account for the design and control of the environment protection systems in landfills does not exist. One of the most important environmental effects of a municipal solid waste landfill is the pollution of underground water due to the migration of contaminated leachate. For this reason, great efforts have been made in modelling to predict the amount of leachate and its movement within the waste and through drainage elements and liners. Widely accepted hydrologic models such as HELP (Schroeder et al. 1994) are used for this. However, this has

Modeling for environmental assessment of municipal solid waste landfills (part II: Biodegradation)

not been the case of the models representing the waste degradation processes and their results (i.e. gas generation, water pollution, etc). In the last thirteen years, many mathematical models have been used in landfills with several objectives, mainly to quantify the potential pollutant emissions and to evaluate the options of landfill gas harnessing. Few reports describe models for the assessment of the effects on the environment of different design or operation strategies. Although some previous attempts have been reported (Vincent et al. (1991), PITTLEACH-2 (AlYousfi 1992, Pohland et al. 1994, Al-Yousfi et al. 1998), HEAT-GAS (El-Fadel et al. 1996a, 1996b, 1996c & 1997), …), only recently has work been started on the development of these kinds of models (Butler et al. 1999, Hanel et al. 2001, Haarstrick et al. 2001a & 2001b, Lee et al. 2001, McDougall et al. 2001, Shelley et al. 2001, White et al. 2001, Zacharof et al. 1999 & 2001). As the definition of the processes and the detail required for the simulation become greater, a more accurate approach to hydrology is required to simulate the biochemical degradation of waste. It is necessary to consider the three spatial dimensions of the landfill, gas generation and transport and water movement and pollution are interrelated, heat generation and transport have to be coupled and settlement must also be modelled. Many of the simplest models, whatever their final objectives are, gave acceptable fits to specific field data for the facilities from which the expressions were developed, but none has been adopted and generally used in the same way HELP has. There are two main reasons for this situation: on the one hand, the great complexity of the processes that take place in the heterogeneous mass of wastes made it impossible to handle all the variables required and, on the other, there is a scarcity of available historical data to assist with the calibration, validation and development of the models being proposed. Landfill biodegradation modelling

Two kinds of formulations can be distinguished among those that try to represent the degradation of waste in the landfill: “global” and “biokinetic” ones. The “global” formulations group all the processes in simple expressions, generally of the exponential type, that quantify the amount of gas generated as a function of time and include a few empirical calibration parameters (Palos Verdes, Sheldon Arleta, etc, many of them described in detail by El-Fadel et al. 1997). As opposed to the former, the “bio-

kinetic” models study the landfill as a bioreactor and establish more complicated formulations, based on anaerobic digestion modelling, where not only the final products take part but also the substrates and the biomass (Halvadakis 1983, Haarstrick et al. 2001a & 2001b, Lee et al. 1983, McDougall et al. 2001, Shelley et al. 2001, Straub et al. 1982a & 1982b, Swarbrick et al. 1995 & 2001, Young 1989 & 1995). By simulating the proper degradation process, even in a simplified way, its applicability can be expected to be transferable to any landfills. Among the simplest “global” expressions and the multistage “biokinetic” ones, other models arise that consider several consecutive steps. but which try to avoid the intensive use of empirical parameters by developing simplified formulae. The calibration of these latter models can be based only on the fit of the observed gas production curves, as Zacharof et al. (2001) or also depend on biokinetic fundamentals (Manna et al. 1999), as is the case of MODUELO, the model described here. The biodegradation model that is presented in this paper has also been developed based on kinetic theories, in an attempt to simplify the formulation. Its objective is to simulate accurately enough the processes in large volumes of waste such as those found in landfills. The required calculating effort and the precision obtainable in the light of the usually poor data available have to be balanced.

The MODUELO general algorithm MODUELO is a dynamic simulation program for landfills that is being developed as a general tool for municipal solid waste, landfill design, operation and monitoring. This program, whose first part was presented in a previous paper (Lobo et al. 2002) estimates leachate flow, its organic pollution and the gas produced over time. Lobo et al.(2002) developed the mathematical scheme and the models adopted in two of the program’s three main modules: the “present landfill layout” and the “hydrologic module”. The landfill in MODUELO is modelled as a three-dimensional grid constituted by parallelepipedic cells that form layers whose vertical dimension can vary along its height. Six types of cells can be defined in the landfill: the “land” (natural terrain) and “empty” cells that do not interact with the others; the “landfill cell”, that is meant to be the typical operating cell of any landfill, including any drainage system and the daily cover; the “cover cell”, a landfill cell with the characteristics of the final closure; Waste Management & Research

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Amaya Lobo García de Cortázar, Javier Herrero Lantarón, Oscar Montero Fernández, Iñaki Tejero Monzón, Maria Fantelli Lamia

and the “soil” and “drain” cells, that represent fillings of waste with different permeabilities. The “present landfill layout” module reproduces the fill order and the characterisation of the grid representing the landfill, as well as its layout and the active cells for each time step (each hour). Later, with climatic data and based on Darcy’s law, the “hydrologic module” calculates the water flow between cells, giving the leachate flow in the drainage collection system and the moisture in each cell over time. The data resulting from both modules constitute part of the input for the degradation calculations that the “biodegradation module” carries out, which is treated in this paper.

Biodegradation Module General layout

The hydraulic, physio-chemical and biological processes which take place in a medium as complex as a landfill, give rise to a great variety of organic and inorganic substances that are transported by the infiltrated liquid or emitted as gas. The MODUELO degradation module estimates the organic pollution present in the leachate and the volume of gas generated by the biologic decomposition of the waste, distinguishing between the volumes of CH4 (methane) and CO2 (carbon dioxide). The leachate pollution is expressed as the weight of carbon (C), hydrogen (H), nitrogen (N), oxygen (O) and sulfur (S) in both biodegradable and non-biodegradable forms, ammonia (NH3) originating in the gas generation process and the parameters of BOD (biochemical oxygen demand) and COD (chemical oxygen demand). This first version does not include other pollutants such as heavy metals, salts, etc. The processes that induce organic waste degradation over time in landfills are usually simplified into five main stages: one aerobic and four anaerobic (hydrolysis, acidogenesis, acetogenesis and methanogenesis). This model does not take into account the effect of the aerobic stage, which is usually so short that oxygen is rapidly consumed if artificial ventilation systems do not exist. The anaerobic phenomena are simplified in two main steps: the dissolving of hydrolysable particulated organic material and the subsequent biological anaerobic degradation of the “gasifiable” (Ehrig et al. 2001), i.e. “convertible to gas” fraction

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of this dissolved material. The simplified model considers the observed phenomena that two main steps can limit the rate of the break down of organic matter in landfills. These steps being the hydrolysis of the solids and the formation of methane from acetic acid and carbon dioxide. The authors believe that simulating the global process by means of two stages can accurately reproduce the rates of pollutant release into the water and gas generation processes. Avoiding the rest of the biochemical steps leads to significant calculation simplification and time savings, which is very important in a program like MODUELO, which must repeat the degradation calculations for each landfill cell and for each time step. A summary of the degradation algorithm is presented in the following paragraphs, as well as a description of the model chosen for the waste, which conditions the data required, the mathematical expressions of the breakdown processes and the calculation of the resulting parameters. The two stages of the degradation model presented below consider each landfill cell as a closed bioreactor and are applied to each one for each time step. Their interactions are controlled by the pollutant transport. Required data

To define the materials constituting each waste cell, the present quantities and future development rates for the different types of waste have to be introduced in the “production module” (Lobo et al. 2002). It is possible to input waste characteristics on two levels of classification, according to how detailed the available data are. For example, the cardboard present in the waste may be expressed as a general quantity or be divided into amounts of cardboard, carton and dirty cardboard. The primary classification establishes nine groups of organic waste (paper, cardboard, food waste, yard waste, wood, cellulose, textiles, rubber and leather, and plastics) and four groups of inorganic wastes (glass, metals, ceramics and other non combustible wastes). In order to represent their biodegradability, the organic waste materials have been divided in three classes considering their hydrolysis rates: readily, slowly and non hydrolysable or inert. For each primary waste component, it is necessary to define its proportion with respect to the total annual volume of waste; its “chemical formula” (content in C, H, N, O, S and ashes); the nature of its “degradability” (whether it is slowly or readily hydrolysable or whether it is non hydrolysable); the percentage of its mass


Table 1: Values of the moisture influence factor for hydrolysis (FM). (Arias et al. 1995, Fantelli 1990). Moisture (% in dry weight) 0 < M < = 15 15 < M < = 35 35 < M < = 65 65 < M < = 90 90 < M

FM Coefficient 0 (M -15)/80 0.25 + (M - 35)/60 0.75 + (M - 65)/100 1

that is hydrolysable (hydro) and the fraction of the hydrolysable part that is “biodegradable” (fbio). Here “biodegradable” does not strictly mean “substances that can be converted by microorganisms” (in which case all the matter would be “biodegradable”), but those that are “gasifiable”, that have the potential to be degraded to methane and carbon dioxide. In order to facilitate the wastes’ characterisation data input the program will assign fixed chemical formulae (Tchobanoglous et al. 1996) and degradable fractions to each of the primary classification groups. The user would not need to specify the flux of each kind of organic material (“readily hydrolysable biodegradable”, “readily hydrolysable non biodegradable”, “slowly hydrolysable biodegradable”, etc) but the amount of each component (paper, food wastes, etc) arriving in the landfill. Of course it is desirable to have a complete characterisation of the specific waste degradability but this assumption would be a valuable help if data are not available. It is not to be forgotten that specific data available in this type of facility are always limited. Hydrolysis

All of the phenomena that give way to dissolving the particulate material that initially makes up the solid waste fall under the name of “hydrolysis”. These phenomena, which are primarily attributed to the enzymatic activity of fermentative microorganisms, are assumed to follow firstorder kinetics. A first-order model is applied to each class of degradable matter in a cell. The mass of solid material of type “j” (SMij; “i” = “readily”, “slowly hydrolisable”; “j” = “biodegradable”, “non biodegradable”) that is broken down to dissolved matter of type “j” (DMj) during a time step (Dt) in the cell number “k” will depend on the total amount of solid matter of type “j” remaining in it (1). DMjHYD(k;t)=iSMij(k;t)= i khi’. SMij(k;t). t (1) SMij(k;t+t) = SMij(k;t) – SMij(k;t) (2)

khj’ is the effective hydrolysis rate corresponding to the hydrolysis characteristics “j”. The dissolution rate of a component will vary depending on the conditions of the interaction between enzymes and waste. Some models include factors reducing a maximum hydrolysis rate taking into account its inhibition by the presence of hydrolysis products (Lee et al. 1993; Straub et al. 1982b; McDougall et al. 2001; the accessibility to the waste structure and its crystallinity (Lee et al. 1993; McDougall et al. 2001), its moisture content (McDougall et al. 2001; Williams et al. 1987), ... Here khj’ = khj.FM.FT, where khj = maximum hydrolysis constant rate, “khrea” for readily hydrolysable matter and “khslo” for slowly hydrolysable matter; FM = influence factor of the moisture that determines the solid/liquid interface (table 1) and FT = temperature influence factor on hydrolysis. The hydrolysis rates are very sensitive parameters in most landfill gas generation models, usually used as calibration constants (El Fadel et al. 1997). They depend on waste characteristics but can also be influenced by sitespecific conditions not taken into account in the model. Maximum reference values can be taken from those obtained under controlled conditions (Pfeffer (1974) reports values from 0.007 to 0.99 d–1 in bioreactors and Williams et al. (1987), from lysimeter experiments, an interval from 0.0008 to 0.1 d–1) or from the more easily soluble components of the mixture, as cellulose. On all accounts reported values vary depending on the global degradation model and the landfill considered, from hydrolysis constants in the order of 10–6 d–1 (El-Fadel 1996) to the range of 10–1 d–1 (Haarstrick et al. 2001a). Another parameter, the “activation time” (tact) has been included to describe the lag in the degradation processes in the landfill, where the waste forms isolated clusters, enclosed in bags, etc, with respect to an ideal situation where the solid is completely surrounded by water, which permits an immediate enzymatic attack. This initial lag is incremented by an acclimatisation period, a time which the respective microorganisms need to “get used to” the new substrate, that will vary depending on the degradability of the waste. The sum of these two periods for the readily and slowly hydrolysable substances, respectively, results in each activation time parameter (“tact,rea” and “tact,slo”). Finally, part of the hydrolysable fraction (“fhydro”) of each material could remain undissolved in the landfill for reasons such as being enclosed in isolated-from-water Waste Management & Research

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areas. This effect is described by a new parameter, “fah”, “actually hydrolysed fraction” that, applied to the ideally hydrolysable mass of each material, expresses the part that is really hydrolysed in the specific conditions of the landfill. “fah” can be viewed as a parameter taking into account the “accessibility” of the matter to the microorganisms. It has to be considered as a site specific calibration parameter that can vary from 0 (microorganisms cannot access any fraction of the waste and the landfill remains “mummified”) to 1 (the ideal situation in which all the degradable matter can be broken down). For simplifying the calculations, it has been accepted that the dissolution affects each considered element of matter j (C, H, O, N, S and ashes) proportionally. Its chemical formula (i.e. the fraction of the total mass that each element represents) remains constant. That means that there is no need to assume any compound as representative of the substances that stay dissolved in the leachate before their breakdown to gas. The mass of dissolved matter, biodegradable or non biodegradable, will be the sum of the masses of the elements (C, H, O, N, S and ashes) of each type (Fig. 1). So, each expression developing the transformation (hydrolysis and gasification) and transport of the waste (1, 2, 3, 4, 5 and 6) is applied to each of the chosen elements. Transport of pollutants

The transport of the substances that have been dissolved in a cell is assumed to occur by advection (diffusion and dispersion phenomena have been neglected). Therefore, pollutants move from cell to cell and to the leachate collection system carried by the water flow. Moreover, an instantaneous mixing of the moisture that flows to a cell and its previous water content is assumed. So, if we consider a cell “k”, once the volumes of water flowing from the six adjacent “i” cells are known, in time t, “Qik(t)”, the mass quantity of each dissolved pollutant transported (twelve substances are considered (C, H, O, N, S and ash, each of them “biodegradable” and “non biodegradable”) will be “DMTT(k;t)” (3). DMTT(k;t) = i Qik(t) t . DM(i;t) / h(i;t)

(3)

Where t is the time step; h(i;t) : moisture content of cell i in the instant t, calculated as by Lobo et al. 2002. The total change in the dissolved pollutant mass content in cell i will result from the sum of this transport term,

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DMTT(k;t), and the transformation terms due to hydrolysis (DMjHYD(k;t)) and gasification (DMbGAS(k;t)). Biodegradation

The breaking down of dissolved biodegradable matter (DMb) to gas (BM) is simulated according to first-order kinetics (4) with rate, kbio, constant and equal for all of the biodegradable elements. DbGAS (k;t) = –kbio. DMb (k;t). t

(4)

BM (t) = DMbGAS (k;t)

(5)

DD_MbGAS(k;t) : increment of the biodegradable elements’ mass content in cell k due to their conversion to gas. It is assumed that the degradation is carried out completely, as if all the hydrolysed biodegradable matter (CCbHHbOObNNb) were converted to carbon dioxide, methane and ammonia, according to expression (6). CCbHHbOObNNb + [(4Cb – Hb – 2Ob + 3Nb) / 4] H2O

[(4Cb +

Hb – 2Ob – 3Nb) / 8] CH4 + [(4Cb–Hb–2Ob+3Nb) / 8] CO2 + Nb NH3

(6)

As can be concluded from (6) the biodegradation kinetics (4 and 5) apply only to the biodegradable carbon, hydrogen, oxygen and nitrogen. The organic material that has been hydrolysed but not degraded appears polluting the filtrated liquid. Methane gas and carbon dioxide are gasified immediately and “extracted” directly while the NH3 remains dissolved in the leachate. Gas movement and interaction with water flow is not simulated in this first version, nor is the carbonic and ammonia equilibrium. By using the simplifications presented, the overall quantities of gas and pollutants that will be emitted by the landfill can be estimated with a less-than-daily temporal precision (in longer periods) because phenomena, such as those retarding the release of gas to the outside, are not included. Thus, for example, an acceptable approximation to the monthly quantity of gas emitted could be made (supposing that all the generated gas is eventually released), but not that which emanates from the landfill on a day-to-day basis. Organic pollution parameters

In order to quantify the great variety of organic constituents that leachate can transport, chemical oxygen


Fig. 1: Schematic of the components of matter considered and their interrelationships.


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demand (COD) is one of the most important parameters, as it is, in general, for wastewaters. The COD quantifies the overall organic material (biodegradable and nonbiodegradable) present in the liquid without the need to identify each compound. Its use simplifies the quantification or comparison of the pollution in different leachates. Furthermore, in municipal solid waste landfills, the characteristics of many of the organic substances polluting the leachate allow their elimination in wastewater treatment plants with biological processes. The estimation of the biochemical oxygen demand (BOD) allows the quantification of the biodegradability of these compounds. The quantities of the non-biodegradable hydrolysed organic material and the remaining biodegradable material (not yet converted to gas) are the direct result of the model. To express these organic pollution values, according to the most widely-used parameters, the program calculates the oxygen consumed in reactions (7), BOD, and (8), COD. Expressions (7) and (8) try to reproduce the stoichiometry of the reactions that take place during the BOD (the aerobic consumption of the biochemically degradable matter) and COD (chemical oxidation of the organic matter by potassium dichromate) tests. CCbHHbOObNNb + [(4Cb+Hb–2Ob-3Nb)/4] O2

Cb CO2 + [(Hb-

3Nb)/2] H2O + Nb NH3

(7)

layers with a thickness of 50 cm with low-permeability daily cover 20 cm thick. The final slope was interrupted by three berms of about 20 m wide to ensure stability, which caused a change of the “hydrologically active” area throughout the landfill’s life, as is common for these depression-type landfills. The final area of the surface extended in plan to 39,600 m2, with a total volume of 429,200 m3. Discretisation of Meruelo I occupies a total of 876 cells (14x14m2), the landfill-type cells being 2.5 m high (1.9 m of waste and 0.6 m of intermediate cover). The landfill’s development was simulated from its origin in December 1988 to December 1997. Its final covering was simulated to take place on December 1990 (when the operation of Meruelo II started). The model was executed several times, varying the percentage of overall “accessed” material (fah), the rapid and slow hydrolysis constants (khrea and khslo) and the biodegradation constant (kbio), maintaining the rest of the parameters (activation time for each kind of substance and the different characteristics of degradability of each waste) with the values shown in table 3. Table 2 shows the composition of the waste stream. In all cases food, paper and cardboard were considered readily hydrolysable, while rubber, leather, textiles and wood were considered slowly hydrolysable. The remaining waste components were considered inert.

C(Cn+Cb)H(Hn+Hb)O(On+Ob)N(Nn+Nb) + [(4(Cn+Cb)+(Hn+Hb)–2(On+Ob))/4] O2

(Cn+Cb) CO2 + (Hn+Hb)/2 H2O + (Nn+Nb)/2 N2

(8)

Where Cb, Hb, Ob and Nb are the masses of biodegradable carbon, hydrogen, oxygen and nitrogen present in the leachate respectively, and Cn, Hn, On and Nn are the non biodegradable masses.

Preliminary calibration Application to Meruelo I landfill

A preliminary calibration of the degradation model was made from the Meruelo landfill (Spain) based on data for its first stage (Meruelo I) that was operative from December 1988 to December 1990. During this period, the municipal solid waste generated in the central and eastern areas of the region of Cantabria were buried in the lowest part of a valley, from elevation 186.6 m to elevation 221.6 m. The 202,100 tons of waste were accumulated behind small berms with a height of 2.5 meters, forming

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Available data

Meruelo I had been the subject of several studies for the characterisation of the waste (Arias et al. 1995, Szantó et al. 1992), of the leachate (Fantelli 1990, Tejero et al. 1993) and its geotechnical behaviour (Sánchez Alciturri et al. 1993a & 1993b). With respect to the landfill emissions characterisation, it was extracted from available reports which included a large amount of valuable data. This, along with their knowledge of the landfill, was the reason why the authors chose Meruelo I for initial testing of MODUELO. With respect to the generated pollutants, measurements were made from March 1990 to October 1990 for the leachate characterisation. Samples were taken every three days and the following parameters were evaluated: instantaneous water flow, pH, conductivity, suspended solids, volatile suspended solids, COD, alkalinity, chloride, sulfate, ammonium, nitrite, nitrate and orthophosphate content. The problem this landfill creates is that no further data on the releasing of pollutants from


the analysed area could be obtained, as the leachate collection system for stage 1 was connected to that of stage 2. As a result this study can only be presented as “preliminary” and not as a “complete” calibration, as it is based on limited data. In a previous paper (Lobo et al. 2002) the calibration of the hydrologic module and its results reproducing the leachate volume data points from the measurements were presented. During this period 29,200 m3 of rainfall on the landfill surface produced 8,371 m3 of leachate, having set the initial and minimum field capacity of the waste at 47% and 30% and the saturation moisture of the waste at 70%. A detailed description of the parameter values resulting from the calibration is presented by Lobo et al. The calibrated hydrologic section generates the moisture content and water flow – time data for each cell which is essential for the simulation of the organic material’s breakdown. The degradation module parameters were then calibrated to fit the results of the measured data. As the available data series were too short to obtain, reliable long-term parameters, this preliminary calibration was carried out taking into account not only the data series available for the first part of the simulated period, but also the general tendencies of the pollutant emissions observed in other landfills during their after-care period (Stegmann et al. 1989, Ehrig et al. 2001). On the other hand the available data have been processed in order to characterise the total measuring period from the measured point values. For each pollutant it was assumed that the average of the measured point concentrations in the leachate made in the same month represent the corresponding daily average of that substance concentration. Multiplying these daily concentration values by the corresponding water flow, the average daily loads for each month were obtained. During the calibration this monthly data have also been fitted, to the COD and NH4–N series.

With respect to NH4–N, an estimation was needed, as organic nitrogen was not measured and the output of the model specifies only NH3–N coming from the gas generation process and hydrolysed biodegradable N and non biodegradable N, without distinction between the organic and the ammonia forms. In order to compare the simulated results with the measured values, it was assumed that all the NH4–N content of the leachate comes from the NH3 generated together with the methane (6), being all the hydrolysed matter’s nitrogen in the organic form. It thus assumes that all the organic N resulting from the hydrolysis process is converted to ammonium in one step, together with the methanogenesis, instead of considering the amount released in each step of the anaerobic degradation.

Results Calibration results

Table 2 shows the degradation-model parameter values resulting from the calibration described above. Fig. 2 preTable 2: Composition of the waste in Meruelo I. Main components

Proportion of the total mass of waste (%)

READILY HYDROLYSABLE MATTER Paper Cardboard Food waste SLOWLY HYDROLYSABLE MATTER Wood Textiles Rubber and leather INERT MATTER Cellulous materials Plastics Glass Metals Other inorganic/ non combustible wastes

15.7 6.2 52.1 2.4 3.7 1.0 2.0 8.3 4.0 3.2 1.4

Table 3: “Biodegradation” parameters’ values adopted for Meruelo I (“calibration”) and for the sensitivity analysis. Parameter fah

Description Fraction of the hydrolysable part of the waste that is actually accessible for

Calibration value

Sensitivity values

tact,rea

microorganisms in the landfill conditions Hydrolysis’ activation time period for the readily hydrolysable matter (year)

0.65 1

0.65, 0.8 1

tact,slo

Hydrolysis’ activation time period for the slowly hydrolysable matter (year)

0

0

khrea

Maximun hydrolysis rate for the readily hydrolysable matter

(d-1)

0.0004

0.0004, 0.0012

khslo

Maximum hydrolysis rate for the slowly hydrolysable matter (d-1)

0.002

0.002, 0.0006

kbio

Rate of conversion to gas of the biodegradable fraction of the hydrolysed waste (d-1)

0.005

0.005, 0.0015


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sents the relationship between the observed and the simulated daily average values corresponding to each month of the measuring campaign for the water flow, COD and NH4–N loads in the leachate collection system. A model’s tendency to overestimate the pollutant fluxes in this case can be observed. In fact the relative differences between the simulated total mass of COD and NH4–N transported by the leachate during the considered period and the values estimated from the measures are around 30% (289,020 kg versus 220,340 kg “measured”) for the COD and 38% for the ammonium nitrogen (5,020 kg versus 3,630 kg). Considering the mean values of the concentrations the deviation reduces significantly in the case of COD, with an average relative overestimation of 3% (daily average simulated concentration of 35,800 mg/L versus 34,800 mg/L measured). These values agree well with the conclusions obtained from the hydrologic calibration (Lobo et al. 2002). The accumulated volumes of leachate “recorded” and simulated during these 7 and a half months (6,233 m3 and 8,371 m3 respectively) deviate by 30%, which could be attributed to a possible leakage through the landfill barrier. In that case a similar fraction of the total dissolved pollutants would migrate, being not registered in the leachate characterisation. Results seem to reveal this problem, as

30% of the global mass is missing, although the simulated concentrations of COD fit closely. For the NH4–N concentrations the relative error is much greater (about –16%, being the measured daily average value of 790 mg/L versus 660 mg/L for the simulation). This deviation could be attributed to the fact that more NH3 is being dissolved during fermentation processes not considered by the model so that it is included in the organic N fraction (as total nitrogen concentration average in the simulated leachate is 1170 mg/L, the simulated organic N would be 512 mg/L). Although the way the measured data have been estimated, averaging point observations, can have an influence, this result indicates that the model should be improved upon in this respect. It might be improved by incorporating a NH3–N generation factor in the hydrolysis step, so that the ammonia generation before methane production phases would be taken into account. The proposed approach, giving the N that is finally converted to gas and the total nitrogen content of the leachate, could be useful in obtaining an order of magnitude for the presence of NH3, but the big range of the total Khjeldal nitrogen/ammonium nitrogen), but has to be taken into account. Ratios TKN/NH4–N reported for different landfills vary from 30% to 150%. It should not be forgotten that the ammonium load is one of the most difficult leachate parameters to predict (Ehrig et al. 2001, Stegmann et al. 1989). Fig. 3 shows the graphs of long-term behaviour of COD, BOD, TKN, estimated NH4–N concentrations and CO2 and CH4 resulting from the calibrated simulation. In order to analyse these results adequately, it is important to consider the distinction between the point values, influenced by the rainfall events, and these representing general tendencies. The pollutant concentration values and the generated gas volumes seem to sensibly follow the reported general tendencies in other municipal landfills (Bagchi 1984, Crawford et al. 1985, Ehrig et al. 2001, Lu et al. 1984, Qasim et al. 1994, Stegmann et al. 1989, Tchobanoglous et al. 1996). Fig. 2: Comparison of the daily averages COD and NH4–N loads and leachate flow Around the date of its closure (day corresponding to each month of the measuring programme for MERUELO I and the simulated 730 in the graphs), a maximum in the values.

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Fig. 3: Results of simulation for MERUELO I (in all cases the X-axis represents days since landfills’ opening.


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Fig. 4: Effect of the ‘actually hydrolysed fraction’ fah, on emission trends of MERUELO I.

Fig. 5: Effect of hydrolysis constants, khrea and khslo, on emission trends of MERUELO I (‘khc’ = calibration value).

Fig. 6: Effect of biodegradation rate, kbio, on emission trends of MUERUELO I.

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organic pollution of Meruelo I leachate was reached (38,000 mgCOD/L and 29,000 mgBOD/L), which is in the upper range of the reported intervals (boundary of 60,000 mgCOD/L and 30,000 mgBOD/L have been published (Tchobanoglous et al. 1996)). They coincide with the observed values which could be due to the topography of Meruelo, being high but of relatively small superficial area. This form of waste deposition decreases the rainfall that penetrates per unit of waste volume, and therefore, the pollution washed-out by leachate leads to greater concentrations, although the mass remains the same. It has also been reported (Ehrig et al. 2001) that leachate from landfills with more waste dumped in shorter operation periods usually results in higher COD concentrations. After closure, the organic pollution started to decrease steeply, while the methanogenic stage developed(as indicated by the gas components graph). BOD/COD ratios decreased throughout the landfill’s life (as biodegradable matter was converted to gas) from a starting value of 0,9 that exceeds usual values (reported to be greater than 0,4) to 0,3 at the end of the studied period. The nitrogen compounds simulated curves also fall within the expected tendency, being the absolute values in the high range (ammonium maximum concentrations around 1,500 mgN/L (Stegmann et al. 1989) and 2,000 mgN/L (Ehrig et al. 2001) have been reported). A significant increase of the total organic nitrogen concentrations was produced after closure (the maximum concentrations around 2,800 mgTKN/L were reached three and a half years after closure), mainly composed of NH4 from the gas formation process. As in other landfills (Stegmann et al. 1989, Ehrig et al. 2001), there was a plateau of high values for several years before a gentle decrease. A delay can be observed between the simulated gas generation and NH4–N appearance in the leachate that corresponds to the need of the leachate to reach the leachate collection system before being analysed, while the gas was assumed to be collected instantaneously. With respect to the gases, the maximum generation rate for both CO2 and CH4 was expected to occur before Meruelo I’s closure. After this, the curves show a steep decrease corresponding to the gradual exhaustion of the “biodegradable” matter, which can last a very long time. The CH4/CO2 ratio stayed approximately constant with CH4 constituting 53% of the mixture. This was due to the simplification, that assumes that all of the sequential phenomena that produce gas occur at a single time, without

intermediate generation of gas (CO2, H2). As a result the simulated gas composition (6) is only sensitive to changes in the “biodegradable” matter’s composition with time. With this assumption variations of gas composition as a consequence of different stages or rates in the production of CO2 (acetogenic and acidogenic phases, for example) and CH4 cannot be simulated. On the other hand having neglected the solution of CO2 in the leachate can have a significant effect too. The resulting gas volumes only serve as a guide to the methane generation potential. Actually, part of the mass that generates methane will have been lost in the form of other gases but, as these losses become negligible as the methane phase progresses, the long-term curves can give an acceptable estimation. Model sensitivity

In order to test MODUELO and assess the influence of several parameters on the results obtained simulating a real case, the sensitivity of the model’s application to the Meruelo I landfill was analysed. Here is a brief summary of the principal conclusions obtained. The base case used for comparisons is that resulting from the calibration. Table 3 shows the parameter values employed in the different simulations, that were chosen trying not to deviate from what a real case could be (i.e., keeping them on the range of the calibrated results). Figs. 4, 5 and 6 present the results. The only parameter that changes the amount of landfill emissions is fah, which controls the quantity of the potentially degradable solid waste that can be accessed by the microorganisms in the specific landfill site. As Fig. 4 shows, the change in the fah values causes a vertical displacement of the curves: if the fah value reduces, the emitted substances reduce (pollutant concentrations and gas volumes at a determined time decrease), although it retains the general tendency with time. Nonetheless, the influence of fah in degradation kinetics can be appreciated from the slopes of the increasing and decreasing parts of the curves, that are steeper the higher fah is (more solid matter is dissolved). The effect on liquid and gaseous emissions is similar. MODUELO is very sensitive to hydrolysis constants, as are other models. By increasing khrea and khslo, the “activity” period of the landfill is reduced, as can be seen in Fig. 5. If kbio does not change and khj are increased, a greater amount of “biodegradable” compounds is transported and appears in the leachate and the amount of gas generated Waste Management & Research

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falls. Finally, Fig. 6 shows the great sensitivity that the model shows to the gasification rate, kbio. The increase of the degradation rate decreases the leachate pollution while increasing the gas generated (greater biodegradable matter decomposed before reaching the leachate collection system); so that kbio can be calibrated by fitting the pollutant fractions being emitted with the leachate and the gaseous form.

Conclusions This paper treats the biodegradation module of the simulation program for MSW landfills that were initially presented by Lobo et al.(2002). With this module, based on hydrologic simulation data and reproducing the landfill operation history, the program reproduces the tendency of the pollution-time curves: COD, BOD and total organic nitrogen present in the leachate and the potential methane and carbon dioxide generation rates. The scarcity and nature of the data available for the specific fitting to Meruelo I do not allow the extrapolation of conclusions concerning its capability of reproducing the long-term behaviour of site-specific cases. Simplified models have been chosen, in an attempt to look for time and memory calculation savings: thus, making the program able to manage 3-D discretisation, which is essential in many sites, as in depression-type landfills. Data input has also been especially considered, making it possible to characterise the waste by specifying the principal component streams, which is usually the only information available to the operators. In this aspect, an important

effort remains to be made in order to properly define the degradability of each component (in the fhydro model). In each specific site, the model parameters (fah, khrea, khslo, tact,rea, tact,slo and kbio) should be calibrated to fit the observed emissions’ behaviour in a similar way as in the case of Meruelo I, which was presented by Lobo et al. 2002 and here. Thus, the module presented in this paper is meant to be the base for the development of a useful tool for the design and management of municipal solid waste landfills. At this developing stage, MODUELO can be helpful for approximating the capacity necessary for leachate treatment facilities (in flow and pollutant load), whether harnessing the generated gas is profitable or not, the effects of different alternatives to the landfill space filling and cover material, etc. It can also be used to estimate the environmental impact due to the emissions generated over time, during its operation phase as well as in the after-care period, and as a result, can facilitate the planning of adequate measures to attenuate them. MODUELO aims to constitute a direct help for the design of new facilities, for the analysis of leachate recycling and other remediation strategies, for the detection of the protection system’s failures (leakage through the barrier, etc) or to evaluate the stability of old dumping sites. But there are still many aspects in which MODUELO has to be and is being improved. The model will be extended to simulate other pollutants, incorporating the effect of temperature on waste decomposition, the generation of gases in intermediate breakdown phases, the movement of gas in the waste, and improving the hydrologic model with a model of flow in non-saturated areas, etc.

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Appendix: Greek letters and symbols Symbol

fhydro Fraction of the waste component that is hydrolysable fbio Fraction of the hydrolysable fraction of the waste component that can be biodegraded to gas SMij Solid material of type ij (“i”= readily hydr., slowly hydr.; “j” = “biodegradable” or “non biodegradable”) DMj Dissolved matter of type j –_ Increment of _ during the time step t Time step

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kh’ FM FT kh tact fah Qik h

Effective hydrolysis rate. Moisture influence factor on the hydrolysis. Temperature influence factor on the hydrolysis Maximum hydrolysis rate Activation time for the degradation process Fraction of the solid waste that can actually be accessed by microorganisms Water volume flowing from cell I to cell k Moisture content