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Int. J. Environ. Res. Public Health 2012, 9(10), 3437-3453; doi:10.3390/ijerph9103437

Article
A Coupling Kinetics Model for Pollutant Release and Transport in the Process of Landfill Settlement
Ying Zhao , Qiang Xue * and Lei Liu
State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan, Hubei 430071, China; Email: yzhao@whrsm.ac.cn (Y.Z.); lgdliulei@163.com (L.L.)
*
Author to whom correspondence should be addressed; Email: qiangx@whrsm.ac.cn; Tel.: +86-139-8629-0178.
Received: 31 May 2012; in revised form: 12 September 2012 / Accepted: 24 September 2012 /
Published: 27 September 2012

Abstract

: A coupling kinetics model is developed to simulate the release and transport of landfill leachate pollutants in a deformable municipal solid waste landfill by taking into account of landfill settlement, seepage of leachate water, hydrolyse of insoluble and degradable organic pollutants in solid phase, biodegradation of soluble and degradable organic pollutants in solid phase and aqueous one, growth of aerobic and anaerobic microorganism, and consumption of dissolved oxygen. The release and transport of organic pollutants and microorganisms in landfills in the process of landfill settlement was simulated by considering no hydraulic effect. Simulation results demonstrated that the interaction between landfill settlement and the release, transport and biodegradation of landfill leachate pollutants was significant. Porosity and saturated hydraulic conductivity were not constants because of the landfill settlement, which affected the release, transport and biodegradation of landfill leachate pollutants, and furthermore acted on the landfill settlement. The simulation results accorded with the practical situation, which preliminarily verified the reliability of the mathematical model and the numerical program in this paper.
Keywords:
municipal solid waste; landfill leachate pollutants; aerobic and anaerobic degradation; dissolved oxygen; settlement; coupling kinetics model

1. Introduction

The release and transport of landfill leachate is a complex process, affected by landfill settlement, fluid movement, biodegradation and temperature changes, so a complete model which describes the release and transport of landfill leachate pollutants must contain mechanical, hydraulic, gas transport, temperature and biodegradation models, but it is almost impossible to realize a five-field coupling simulation, so this is often simplified to two or three field coupling model.

Many researchers have studied the multi-field coupling problems of landfill leachate transport, and new models have been developed based on more detailed mathematical descriptions of the landfill and incorporating other aspects of interest apart from hydrology, such as the biological and physical-chemical degradation and settlement. Demirekler et al. [1] developed a three-dimensional mathematical model to estimate the quality and quantity of the landfill leachate produced. The effect of overburden stress was considered. Lobo et al. [2,3] has reported the first version of MODUELO. The development of the second version and the Meruelo Landfill (Spain) simulation results were presented in Lobo et al. [4,5,6]. Chanthikul et al. [7] developed a mathematical model of BOD5 concentration without and with leachate recirculation. Durmusoglu et al. [8] developed a one-dimensional multiphase numerical model to simulate the vertical settlement involving liquid and gas flows in a deformable MSW landfill. McDougall [9] developed a hydro-bio-mechanical model for settlement and other behavior in land filled waste. Fellner and Brunner [10] established a 2-dimensional 2-domain model for simulating the leachate generation from MSW landfills. A flow field consisting of a vertical path (channel domain) surrounded by the waste mass is defined using the software HYDRUS-2D. One-dimensional advection–dispersion transport modeling was conducted as a conceptual approach for the estimation of the transport parameters of fourteen different phenolic compounds and three different inorganic contaminants migrating downward through the several liner systems in Gamze et al. [11]. Gaetano et al. [12] presents a 1D mathematical model for the simulation of the percolation fluxes throughout a landfill for MSW, which considered the landfill divided in several layers evaluating the inflow to and outflow from each layer as well as the continuous moisture distribution. But, there are still one or more defects in most models as follows: (a) The pollutants were considered as a single solute, whether it is soluble or insoluble, degradable or non-degradable was not definitely differentiated; (b) Solid-phase pollutants and its dissolution to aqueous phase weren’t taken into account; (c) The effect of oxygen on biodegradation was neglected and the transition from aerobic degradation to anaerobic one wasn’t taken into account; (d) the effect of settlement on porosity, saturated hydraulic conductivity and the transport of pollutant was neglected.

A coupling kinetic model was developed to simulate the release and transport of leachate pollutants in a deformable MSW landfill taking into account of hydrolyse and dissolution of solid-phase pollutants, oxygen consumption and transition of aqueous-phase pollutant biodegradation from anaerobic stage to aerobic one, and other behaviors such as convection and hydrodynamic dispersion, adsorption/desorption and growth of microorganism. A case study was given by considering none hydraulic action for studying the change law of water quality and quantity, which preliminarily verified the reliability of the mathematical model by comprising with the practical situation.

2. Mathematical Model

2.1. Basic Assumptions

The release and transport of organic pollutants in landfill is a complicated process which is accompanied by physical behavior and chemical and microbial reactions. It can be barely described by a completely correct model. The development of the simulation model must be based on some suitable assumptions. The assumptions of the models in this study are as follows: (a) Landfill gas is released rapidly after generation, so the landfill leachate transport is considered as a single phase flow; (b) MSW particles are incompressible, but degradable; (c) The simulated landfill was taken as a biochemical reactor. Organics transport and transform under a series of physical, chemical and biological actions, such as convection and hydrodynamic dispersion, hydrolyse, dissolution, adsorption/desorption and biodegradation; (d) Density and viscosity coefficient of landfill lecheate are constants.

2.2. Landfill Settlement Model

2.2.1. Mass-Conservation Equation

Based on the mass conservation principle the mass-conservation equation of solid phase is:

Ijerph 09 03437 i001

where Ijerph 09 03437 i002 is the space coordinates [L]; Ijerph 09 03437 i003 is the current time [T]; Ijerph 09 03437 i004 is the solid phase density [ML3]; Ijerph 09 03437 i005 is the porosity; Ijerph 09 03437 i006 is the velocity of solid phase [LT1]; Ijerph 09 03437 i007 is the source/sink term, which is caused by the degradation of solid waste, the release of inner source water etc. [ML3T1].

2.2.2. Mechanical Model

The Merchant model was used to simulate landfill settlement. It was constructed by a Hooke elastomer and a Kelvin model in series. Kelvin model was constructed by a Hooke elastomer and a Newton viscosity mode in parallel. The creep equation is:

Ijerph 09 03437 i008

where Ijerph 09 03437 i009 is the deviator strain tensor [LL1]; Ijerph 09 03437 i010 is the deviator stress tensor [ML1T2]; Ijerph 09 03437 i011 is the viscosity coefficient [ML1T2]; Ijerph 09 03437 i012 and Ijerph 09 03437 i013 are the shear modulus for Hooke elastomer and Kelvin model, respectively [ML1T2].

In addition:

Ijerph 09 03437 i014

Ijerph 09 03437 i015

So the effective stress can be written as:

Ijerph 09 03437 i016

In Equations (3)–(5), Ijerph 09 03437 i017 is the strain tensor [LL1]; Ijerph 09 03437 i018 is the mean strain [LL1]; Ijerph 09 03437 i019 is the effective stress tensor [ML1T2]; Ijerph 09 03437 i020 is the mean effective stress [ML1T2]; Ijerph 09 03437 i021 is the bulk modulus [ML1T2]; Ijerph 09 03437 i022 is the Kronecher symbol; and:

Ijerph 09 03437 i023

Furthermore, the effective stress principle can be described by:

Ijerph 09 03437 i024

where Ijerph 09 03437 i025 is the total stress [ML1T2]; Ijerph 09 03437 i026 is the liquid saturation [LL3]; Ijerph 09 03437 i027 is the liquid pressure [ML1T2].

Geometric equation and stress equilibrium equation are:

Ijerph 09 03437 i028

Ijerph 09 03437 i029

The stress equilibrium equation represented with displacement can be obtained by plugging Equation (7) and Equation (8) to Equation (9):

Ijerph 09 03437 i030

The velocity of solid phase is:

Ijerph 09 03437 i031

Equation (1) and Equation (7) (or Equation (10)), Equation (8) and Equation (11) are the basic equations of landfill settlement model. The liquid pressure Ijerph 09 03437 i032 was contained in it, so the hydraulic model must be developed for obtaining Ijerph 09 03437 i032.

2.3. Hydraulic Model

Based on the mass conservation principle the continuity equation of aqueous phase is:

Ijerph 09 03437 i033

where Ijerph 09 03437 i034 is the liquid phase density [ML3]; Ijerph 09 03437 i035 is the source/sink term [ML3T1]; Ijerph 09 03437 i036 is the absolute velocity of aqueous phase [13] [LT1]; and Ijerph 09 03437 i037 is the relative velocity of aqueous phase to the solid phase [LT1].

During settlement, the solid particles as well as the liquid move simultaneously. Hence, it is necessary to state Darcy’s law relative to solids movement. That is:

Ijerph 09 03437 i038

where Ijerph 09 03437 i039 is the volumetric moisture content [L3L3]; Ijerph 09 03437 i040 is the hydraulic pressure head [L]; Ijerph 09 03437 i041 is the saturated hydraulic conductivity tensor [LT1]; Ijerph 09 03437 i042 is the relative permeability.

VG function [14] is used to describe the water retention curve:

Ijerph 09 03437 i043

where Ijerph 09 03437 i044, Ijerph 09 03437 i045, Ijerph 09 03437 i046 are parameters; Ijerph 09 03437 i047 and Ijerph 09 03437 i048 are the residual and saturated volumetric moisture contents, respectively.

So the relative permeability can be written as:

Ijerph 09 03437 i049

where Ijerph 09 03437 i050 is the effective saturation.

Ijerph 09 03437 i051 and Ijerph 09 03437 i035 [15] are calculated by:

Ijerph 09 03437 i052

Ijerph 09 03437 i053

where Ijerph 09 03437 i054, Ijerph 09 03437 i055, Ijerph 09 03437 i056, Ijerph 09 03437 i057, Ijerph 09 03437 i058, Ijerph 09 03437 i059 and Ijerph 09 03437 i060 are parameters; Ijerph 09 03437 i061 is the particle density of MSW [ML3].

2.4. Pollutant Release and Transport Model

2.4.1. Conceptual Framework

Organic biodegradation in landfills can be divided into two stages: (1) aerobic biodegradation and (2) anaerobic biodegradation. The first one always occurs in the initial landfill stage, and it can be also divided into two stages: (1) the hydrolysis stage of insoluble macromolecular organics to soluble and small molecular ones and (2) the biodegradation of soluble organics to H2O and CO2, etc. When the oxygen is consumed, biodegradation enters the anaerobic stage. In this stage, macromolecular organics are hydrolyzed to small molecular ones, and then decomposed to CH4 and H2O by anaerobic microorganisms after the acidification process.

Based on above biodegradation process, organic pollutants in landfill can be classified as insoluble and degradable ones (IDS), soluble and degradable ones (SDS), and adsorbed ones (AS) in solid phase; and soluble and degradable ones in aqueous phase (SDA). Microorganism includes aerobic and anaerobic ones in aqueous phase (AM and ANM) and hydrolysis ones in solid phase (MS). The model which describes the pollutant release and transport in landfill can be developed by using the mass conservation principle, including hydrolysis of IDS, dissolution and biodegradation of SDS, adsorption/desorption and aerobic and anaerobic biodegradation of SDA; growth and death of AM, ANM and MS, and consumption of dissolved oxygen (DO). The biodegradation process of organics was shown in Figure 1.

Ijerph 09 03437 g001 1024
Figure 1. The biodegradation process of organics in landfills.

Click here to enlarge figure

Figure 1. The biodegradation process of organics in landfills.
Ijerph 09 03437 g001 1024

2.4.2. Hydrolysis of IDS

The hydrolysis of insoluble macromolecular organics (IDS) to soluble and small molecular ones can be described as first order reaction:

Ijerph 09 03437 i063

where Ijerph 09 03437 i064 is the hydrolysis rate of IDS [MM1T1]; Ijerph 09 03437 i065 is the concentration of IDS [MM1] and Ijerph 09 03437 i066 is the hydrolysis constant [T1].

2.4.3. Dissolution of SDS

The dissolution of SDS is closely related to the water content and the pollutant concentrations in solid and aqueous phase. It is described by [16]:

Ijerph 09 03437 i067

where Ijerph 09 03437 i068 is the dissolution rate of SDS [MM−1T−1]; Ijerph 09 03437 i069 and Ijerph 09 03437 i070 are the concentrations of SDS at time t and initial time, respectively [MM−1]; Ijerph 09 03437 i071 is the concentration of SDA [ML−3]; Ijerph 09 03437 i072 is the maximum concentration of SDA [ML−3]; Ijerph 09 03437 i073 is the dissolution rate constant [ML−3T−1]; Ijerph 09 03437 i074 is the dissolution coefficient.

2.4.4. Biodegradation

The decomposition and stabilization of MSW in landfill is essentially a microbial metabolic process. The depletion of the substrate and microorganism growth can be described by Monod kinetics [17], hence for MS accumulation:

Ijerph 09 03437 i075

where Ijerph 09 03437 i076 is the growth rate of MS [MM1T1]; Ijerph 09 03437 i077 is the concentration of MS [MM1]; Ijerph 09 03437 i078 is the maximum specific growth rates for MS [T1]; Ijerph 09 03437 i079 is the half saturation constant for SDS [MM1].

The depletion rate of the substrate is directly related to MS accumulation through a cell/substrate yield coefficient Ijerph 09 03437 i080:

Ijerph 09 03437 i081

where Ijerph 09 03437 i082 is the depletion rate of SDS [MM1T1]; the Ijerph 09 03437 i083 is the stoichiometric yield coefficient for MS (biomass produced per unit amount of electron donor utilized) [MM1].

When the dissolved oxygen (DO) exists, and its concentration is low, the cell growth rate for AM and ANM can be represented by the following double Monod models [18]:

Ijerph 09 03437 i084

Ijerph 09 03437 i085

where Ijerph 09 03437 i086 and Ijerph 09 03437 i087 are the cell growth rates for AM and ANM, respectively [ML3T1]; Ijerph 09 03437 i088 and Ijerph 09 03437 i089 are the concentrations of aerobic microorganism and anaerobic microorganism, respectively [ML3]; Ijerph 09 03437 i090 is the DO concentration [ML3]; Ijerph 09 03437 i091 and Ijerph 09 03437 i092 are the maximum specific growth rates for aerobic and anaerobic microorganism, respectively [T1]; Ijerph 09 03437 i093 and Ijerph 09 03437 i094 are the half saturation constant for aerobic and anaerobic microorganism, respectively [ML3]; Ijerph 09 03437 i095 and Ijerph 09 03437 i096 are the half saturation constants for DO [ML3].

The depletion rates of the substrate and DO in aqueous phase are directly related to AM and ANM accumulation through cell/substrate yield coefficients Ijerph 09 03437 i097, Ijerph 09 03437 i097 and Ijerph 09 03437 i098:

Ijerph 09 03437 i099

Ijerph 09 03437 i100

Ijerph 09 03437 i101

where Ijerph 09 03437 i102 and Ijerph 09 03437 i103 are the aerobic and anaerobic degradation rates of SDA, respectively [ML3T1]; Ijerph 09 03437 i104 is the consumption rate for DO [ML3T1]; Ijerph 09 03437 i105 and Ijerph 09 03437 i106 are the stoichiometric yield coefficients for aerobic microorganism and anaerobic microorganism, respectively (biomass produced per unit amount of electron donor utilized); Ijerph 09 03437 i107 is the consumption coefficient of DO (oxygen consumed per unit amount of SDA).

The MS, AM and ANM decay are given by:

Ijerph 09 03437 i108

Ijerph 09 03437 i109

Ijerph 09 03437 i110

where Ijerph 09 03437 i111, Ijerph 09 03437 i112 and Ijerph 09 03437 i113 are the endogenous cell death or decay rates of MS, AM and ANM, respectively [ML3T1]; Ijerph 09 03437 i114, Ijerph 09 03437 i115 and Ijerph 09 03437 i116 are the endogenous cell death or decay coefficients of MS, AM and ANM, respectively [T1].

2.4.5. Adsorption/Desorption of SDA

Langmuir adsorption model can describe the adsorption behavior of the pollutants in MSW well [19]. So the adsorption rate is described by:

Ijerph 09 03437 i117

where Ijerph 09 03437 i118 is the adsorption rate [MM1]; Ijerph 09 03437 i119 and Ijerph 09 03437 i120 are the adsorption concentration and maximum adsorption concentration of IDS [MM1]; Ijerph 09 03437 i121 is the equilibrium sorption constant [ML3]; Ijerph 09 03437 i122 is the first order adsorption/desorption rate constant [T−1].

2.4.6. Governing Equations

Based on the mass conservation principle and considering landfill settlement and hydrolysis of macromolecular organics, the governing equation for IDS can be described by:

Ijerph 09 03437 i123

The SDS governing equation considering landfill settlement, hydrolysis of IDS and dissolution and biodegradation can be given by:

Ijerph 09 03437 i124

The MS governing equation considering landfill settlement, growth and decay of MS is described as:

Ijerph 09 03437 i125

The AS governing equation is:

Ijerph 09 03437 i126

The SDA transport model considering convection and hydrodynamic dispersion, dissolution of SDS, aerobic and anaerobic degradation and adsorption/desorption is given by:

Ijerph 09 03437 i127

The equations for AM and ANM by considering convection and hydrodynamic dispersion, growth and decay are given by:

Ijerph 09 03437 i128

Ijerph 09 03437 i129

The governing equation for DO is:

Ijerph 09 03437 i130

2.4.7. Numerical Solution Method

The Merchant model was obtained by Lagrangian description. Hydraulic model and pollutant release and transport model were obtained by an Eulerian description. Total settlement in untreated landfilled MSW has been estimated to range between 25% and 50% of initial fill height [20]. So the upper boundaries of fluid and pollutant transport regions are obviously moving, and the small deformation assumption isn’t suitable. The coupling of these two types of model may lead to the moving boundaries of Eulerian describing models, so the Arbitrary Lagrangian-Eulerian (ALE) method was used to the model solution for solving the moving boundary problem. Due to space limitations, the solution process can be seen in the authors’ another work [15].

3. Results and Discussion

An ideal landfill should have an effective seepage control system. After closure, it is in a relative independent state and can’t be affected by the external hydraulic environment. In this study, the change law of the main physical and chemical variables and its effect on the pollutant transport was analyzed in an ideal landfill. The simulated landfill had a rectangular vertical section of 15 m in height and 20 m in width. All boundaries were impervious. The upper boundary can move freely, and the others are all fixed. The parameters are given in Table 1. Physical and mechanical parameters were determined by testing, and biological parameters were obtained by parameter inversion. The results are shown in Section 3.1, Section 3.2, Section 3.3, Section 3.4, Section 3.5, Section 3.6, Section 3.7, Section 3.8, Section 3.9 and Section 3.10. In Figure 1 and Figure 2, z is the space coordinate of a certain particle at the initial time, that is, the corresponding space coordinate z at initial time was used to represent a certain particle. In the other figures, z is the space coordinates of a certain particle when the MSW was filled for 30 years, that is, the corresponding space coordinate z at 30 years after MSW was filled was used to represent a certain particle.

Table Table 1. Model parameters.

Click here to display table

Table 1. Model parameters.
ParameterValuesParametersValuesParametersValues
Ijerph 09 03437 i1311,320 kPa Ijerph 09 03437 i1325.0 kg·m−3 Ijerph 09 03437 i1330.02 d−1
Ijerph 09 03437 i13486.2 kPa Ijerph 09 03437 i1350.01 kg·m−3 Ijerph 09 03437 i1360.0005 d−1
Ijerph 09 03437 i1372.0×105 d−1 Ijerph 09 03437 i1381.2 kg·m−3 Ijerph 09 03437 i1390.001 d−1
Ijerph 09 03437 i1400 m Ijerph 09 03437 i1410.03 kg·m−3 Ijerph 09 03437 i14235,000 kg·m−3
Ijerph 09 03437 i1430.52 Ijerph 09 03437 i1440.0001 d−1 Ijerph 09 03437 i1450 kg·kg−1
Ijerph 09 03437 i1460.21 Ijerph 09 03437 i1470.01 d−1 Ijerph 09 03437 i1480 kg·kg−1
Ijerph 09 03437 i1491.74 m−1 Ijerph 09 03437 i1500.0002 d−1 Ijerph 09 03437 i1510 kg·kg−1
Ijerph 09 03437 i1521.38 Ijerph 09 03437 i1530.5 Ijerph 09 03437 i1540 kg·kg−1
Ijerph 09 03437 i155864 kg·m−3 Ijerph 09 03437 i1560.05 Ijerph 09 03437 i1570 kg·m−3
Ijerph 09 03437 i1580.0006 d−1 Ijerph 09 03437 i1599×10−5 Ijerph 09 03437 i1601.2×10−4 kg·m−3
Ijerph 09 03437 i1615×10−9 kg·kg−1 Ijerph 09 03437 i1626×10−5 Ijerph 09 03437 i1632.5×10−6 kg·m−3
Ijerph 09 03437 i1645.0 kg·kg−1 Ijerph 09 03437 i165100 Ijerph 09 03437 i1668×10−3 kg·m−3
Ijerph 09 03437 i1645.0 kg·kg−1 Ijerph 09 03437 i165

3.1. Displacement

Figure 2 shows that the settlement occurred in almost 2 years. It’s about 85% of total settlement. The total settlement was about 2.6 m, which was about 17.3% of initial fill height. The simulation results fitted well with the observed data from a similar landfill cell in Wuhan Jinkou landfill in China which was observed from 2001 to 2010, and it accorded with the reported settlement law [21,22].

Ijerph 09 03437 g002 1024
Figure 2. Displacement change with time.

Click here to enlarge figure

Figure 2. Displacement change with time.
Ijerph 09 03437 g002 1024

3.2. Porosity

Figure 3 shows that porosity decreased at first and then increased with time due to the landfill settlement and organic biodegradation. The 85% settlement that occurred in 2 years led to the MSW compression and the decrease of porosity. After 2 years, the effect of biodegradation on porosity was more and more obvious. The organic biodegradation led to the reduction of solid mass, and the porosity presented an increasing trend. When the MSW was filled for 30 years, the porosities at top and bottom increased to 0.55 and 0.458 again, respectively. Meanwhile, the decrease of the MSW porosity at bottom due to the landfill settlement was more obvious; however the increase of the one at top due to organic biodegradation was more obvious. In addition, the porosity presented an increasing trend with the fill height increasing.

Ijerph 09 03437 g003 1024
Figure 3. Porosity change with time.

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Figure 3. Porosity change with time.
Ijerph 09 03437 g003 1024

3.3. Saturated Hydraulic Conductivity

Figure 4 shows that the change of saturated hydraulic conductivity was similar to that of porosity, and the effect of displacement was significant. It decreased at first and then increased taking two years as a turning point. Increase was the main trend of Ks of the upper MSW, and the lower ones had a decreasing trend. The Ks at z = 0.73 m decreased from 0.8 m·day−1, which was the initial value, to 0.32 m·day−1, and then tended to be stable; and the one at z = 12.4 m showed a small decrease at first, and then increased until the maximum value.

Ijerph 09 03437 g004 1024
Figure 4. Ks change with time.

Click here to enlarge figure

Figure 4. Ks change with time.
Ijerph 09 03437 g004 1024

3.4. Pressure Head

It's seen from Figure 5 the effect of settlement on pressure head wasn’t significant, although the water transport was closely related to landfill settlement, porosity and saturated hydraulic conductivity. The water mainly moved from top to bottom under gravity action and the upper pressure head decreased with time and the lower one increased by taking 5 m–6 m as separatrix.

The pressure head at the bottom reached 0.6 m when MSW was filled for 5 years, and increased gradually with time. When MSW was filled for 30 years, the MSW below 2.5 m was saturated, which was equivalent to 16.7% of the landfill height. Thus, although without the effect of groundwater and surface water invasion, the landfill leachate generated by MSW itself was large, and can’t be neglected when designing the seepage control system and leachate treatment system.

Ijerph 09 03437 g005 1024
Figure 5. Pressure head change with time.

Click here to enlarge figure

Figure 5. Pressure head change with time.
Ijerph 09 03437 g005 1024

3.5. IDS

Figure 6 shows that because it’s assumed that the hydrolysis rate of IDS was only related to its own concentration, and the whole landfill cell has the same initial IDS concentration values, the calculated IDS concentration was only the decaying exponential function of time and independent of fill height and other parameters.

Ijerph 09 03437 g006 1024
Figure 6. IDS Concentration change with time.

Click here to enlarge figure

Figure 6. IDS Concentration change with time.
Ijerph 09 03437 g006 1024

3.6. SDS

SDS concentration in this landfill increased at first and then decreased with time as seen in Figure 7. This change process was closely related to the dissolution and biodegradation of SDS and the hydrolysis of IDS. Because of the fast hydrolysis of IDS in the early period of the landfill, the SDS concentration increased rapidly. Over time, IDS concentration gradually decreased, and SDS continuously dissolved from solid phase and was biodegraded, so the SDS concentration decreased year by year. The inflexion point was about the eleventh year.

The difference of SDS concentrations between every height was small and is more obvious before the MSW was filled for 15 years. Because the pore water of lower waste was tending to be saturated gradually, and the dissolution of soluble organic pollutants was accelerated, there was a little difference between upper waste and lower one after the MSW was filled for 15 years.

Ijerph 09 03437 g007 1024
Figure 7. SDS concentration change with time.

Click here to enlarge figure

Figure 7. SDS concentration change with time.
Ijerph 09 03437 g007 1024

3.7. MS

The MS concentration increased year by year, and the difference between every height was small as seen in Figure 8.

Ijerph 09 03437 g008 1024
Figure 8. MS concentration change with time.

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Figure 8. MS concentration change with time.
Ijerph 09 03437 g008 1024

3.8. SDA

Figure 9 shows the simulation results of SDA fitted well with the observed data from the Wuhan Jinkou landfill in China, which verified the accuracy of the model and parameters. These data were observed from 2001 to 2010. The suspended particles in water samples were filtered out and the SDA content was represented by chemical oxygen demand (COD) of the sample. SDA concentration increased at first and then decreased. At the early period, because of the higher SDS concentration and its dissolution to aqueous phase, the SDA concentration increased rapidly. Meanwhile, the water content of the lower waste was relatively higher, which accelerated the dissolution of SDS, so the SDA concentration in lower waste was higher than the upper one. The rapid dissolution of SDS in the early period also led to the higher SDA concentration in upper waste than the lower one in the later period of landfill.

Ijerph 09 03437 g009 1024
Figure 9. SDA concentration change with time.

Click here to enlarge figure

Figure 9. SDA concentration change with time.
Ijerph 09 03437 g009 1024

3.9. ANM

It is seen from Figure 10 that the ANM concentration change was similar to that of MS in Figure 8, but it had a significant difference along height. The ANM concentration at z = 0.73 m was almost three times of the one at z = 12.40 m at utmost. This is mainly because the higher organic concentration in the lower waste provided sufficient nutrients for microorganisms and promoted their growth, while at later periods the SDA concentration in lower waste became lower, the ANM concentration presented a decreasing trend combining with its own decay.

Ijerph 09 03437 g010 1024
Figure 10. ANM concentration change with time.

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Figure 10. ANM concentration change with time.
Ijerph 09 03437 g010 1024

3.10. AM and DO

Figure 11 and Figure 12 show that the change of DO was consistent with AM, which concentrations presented a rapid decreasing trend with time, and reached 0 when MSW filled for 200 days. The values for the 1,001th day to 10,000th day were omitted in Figure 11 and Figure 12 because they were the same as on the 1,000th day.

Ijerph 09 03437 g011 1024
Figure 11. AM concentration change with time.

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Figure 11. AM concentration change with time.
Ijerph 09 03437 g011 1024
Ijerph 09 03437 g012 1024
Figure 12. DO concentration change with time.

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Figure 12. DO concentration change with time.
Ijerph 09 03437 g012 1024

4. Conclusions

A coupling kinetic model of landfill leachate pollutant release and transport in the process of landfill settlement was developed, which contained three sub models-landfill settlement model, hydraulic model and pollutant release and transport model. Landfill settlement, convection and hydrodynamic dispersion of leachate, hydrolysis, dissolution, adsorption/desorption, biodegradation of pollutant and other behaviors were considered. The release and transport of` pollutants and microorganisme in a landfill was simulated by considering no hydraulic action. The total settlement in this landfill cell was about 2.6 m, which was about 17.3% of initial height, and 85% almost occurred within 2 years. The simulation results fitted well with the observed data, and accorded with the reported settlement law. The changes of porosity and saturated hydraulic conductivity were closely related to settlement and biodegradation. They all presented a decreasing trend at first, and then increased with time. The leachate generated by MSW itself can saturated 16.7% of the landfill, so when designing the seepage control system and landfill leachate treatment system, this must be fully considered. The soluble and degradable organic pollutants in solid phase and aqueous phase presented an increasing trend at first and then decreased with time, respectively, due to the release of pollutants from the solid phase. The peak value of the latter could reach 30 kg·m3. The microorganisms in the solid phase and aqueous phase presented an increasing trend with time.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (11002153), the National Basic Research Program (973) of China (2012CB719802), the Key Technologies Research and Development Program of Wuhan City (201060723312), Cheng Guang Project for Youth Science and Technology of Wuhan City (201050231025).

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