Intelligent Novel Solid Waste Management System (QEJ Bricks Biocell Approach)

Intelligent “QEJ bricks” is a novel management system that manages waste, biogas, and energy in landfills. Different than conventional disposal in landfills, waste is put between bricks that are perforated containments filled up on-place or prefabricated at a factory with porous hydrophobic polymer. These bricks can be made up of recyclable material available on the dumping area. QEJ bricks are utilized to provide a porous medium for biogas collection. Since the material is hydrophobic, it does not contain water in the voids providing more space for gas transport. An intelligent system of sensors, data acquisition, and fuzzy logic are implemented to QEJ bricks. Sensors acquire data about biogas concentration gradient, pressure gradient, flow rate, and temperature as input information for a learned fuzzy system that gives incessant simulation to the biogas transport rates (diffusion and convection) in the hydrophobic polymer media. Different than classical methods, the evacuation system in the QEJ bricks management system is integrated, intelligent and dynamic. At the collection ports, the valves are connected with a sensor-data acquisition system that supplies information for a fuzzy logic control system, which in turn controls the valves for evacuation processes.

The research idea in this paper entails controlling methane and carbon dioxide in landfills by a new intelligent approach. This intelligent approach involves a new configuration of a gas collection system, a new permeable hydrophobic polymer medium for gas collection, and a fuzzy system for modeling and controlling gas movement in the system.

In voids within the porous media, gas moves by diffusion due to a concentration gradient and/or by convection due to a pressure gradient. An equation of mass conservation for gas diffusion-convection in a porous media can be written as:

Where Ci is concentration of the ith component of the gas mixture (kg/m3), Uj is convection velocity (flow Q per unit area) in the jth direction (m/day), Dij is the diffusion coefficient of gas i in the jth direction (m2/day), and Lj is jth distance (m) (1).

The convection flow of gas Q (m3/day) is described by the following formule:

Where ∇P is the pressure gradient (Pa/m), A is cross-sectional area normal to flow, ρ stands for the density of the fluid (kg/m3), g denotes the acceleration due to gravity (m/s2) (2), and Lj is the distance in j direction. The conductivity coefficient, K, is a function of the properties of both the soil and the fluid in accordance with the following equation (3):

Where k is the intrinsic permeability of the porous material (m2), and μ is the dynamic viscosity of the fluid (Pa.s). It is assumed that the intrinsic permeability is a function only of the properties of the porous material, not the permeating fluid.

Diffusion is a generic transport process encountered in fluids, by which molecules that can move randomly are redistributed until equilibrium is reached when concentration becomes uniform (4). The main diffusion equation, known as Fick’s first law, can be written as follows for the gas flux:

Where Fg is given as a mass transfer rate per unit area (kg/s•m2), C is the concentration of the diffusing substance (kg/m3), L is the spatial coordinate (m) measured perpendicularly to the unit cross sectional area, D is the diffusion coefficient (m2/s), and the negative sign indicates that flux occurs in the opposite direction to the concentration increase. When equation 5 is rewritten in terms of partial pressure gradients (e.g. refs 5, 6) one can establish a parallel between Fick’s first law and the formulas used for advection transport. Crank (ref 5) used an equation for one-dimensional flux in an isotropic non-reactive medium as described below:

This is the usual form of Fick’s second law. More general expressions can also be developed for anisotropic or heterogeneous media and for reactive materials that consume or generate a diffusive element (5,7).

The transfer of biogas through solids toward a gas collection system is a limiting factor (8). The gas collection efficiency in landfills is between 40-90% (9). Biogas is collected by means of some vertical and horizontal drain pipes and is then burned in flares or employed to produce heat and energy (10). The designs for gas abstraction systems include different types of well configurations such as vertical, horizontal, hybrid, etc (11). The landfill gas collection system consists of a vertical extraction well, a transport pipe network, a blower for passive gas collection or pumping for active collection, monitoring equipment, and a flare stack (12). There are other processes of gas collection such as gas layers. The coarse materials (grain size fraction of 16-32 mm of gravel, crushed lime stone, crushed granite, and crushed basalt) proved to be the most suitable for laying layers for gas inclusion because it showed high intrinsic permeability (13). There are other methods of gas collection such as collection covers that collect gases in wastewater treatment lagoons, sludge ponds, aeration systems, flow equalization tanks, and pretreatment tanks (e.g. Gas Collection Covers made by Geomembrane Technologies Inc. (GTI), New Brunswick, Canada).

Consequently, mass conservation for convection-diffusion of gas mixture in landfill porous media is highly prone to uncertainty. Behavior of mixture of gases in porous media is uncertain under variable environmental conditions, thus new intelligent approaches for biogas collection and control are needed.

QEJ Bricks Biocell Approach
Intelligent “QEJ bricks” is a novel management system (originated by authors: Qasaimeh, Elektorowicz, and Jasiuk) that serves as a new system for managing waste, biogas, and energy in landfills. Different than conventional disposal in landfills, waste is put between bricks that are perforated containments filled up on-place or prefabricated at a factory with porous hydrophobic polymer. These bricks might be made up of recyclable material (e.g. styrofoam) available in the dumping area. QEJ bricks are utilized to provide a permeable medium for biogas collection. Since the material is hydrophobic, it does not contain water in the voids providing less bioactivity and more space for gas transport. Consequently, the proposed medium in this research complies with the following features:

  • Negligible water content (more permeable)
  • No microbial growth inside (no clogging)
  • High porosity (more air filled voids)
  • Light and easily reformed material
  • Cheap and recyclable material

For investigation of gas transport within the polymer, diffusion and convection flow tests are to be conducted. The temperature, porosity, and water content are vital factors affecting the biogas transport in porous media. By increasing the porosity and decreasing the water content, more efficient biogas transport (convection and diffusion) could be predicted. The temperature effect could vary from one gas to another. Figure 1 shows the effect of temperature variation on coefficient of conductivity (K) and coefficient of diffusion (D) for the design of biogas transport in hydrophobic permeable polystyrene medium.

Figure 1: Effect of temperature variation on coefficients of conductivity (K) and diffusion (D) for simulation of biogas transport in design hydrophobic medium.

The hydrophobic medium could be a material such as polymers (e.g. polystyrene (PS), polyethylene (PE)) that can be frequently found in the refuse. To fulfill sustainable development principles, polymers used for hydrophobic medium can also be formed from recyclable materials available in the landfill mass. Another source of sustainable materials for brick formation is the wasted polymers obtained during erroneous polymerization processes that take place occasionally in the factory.

QEJ Bricks Fabrication
QEJ bricks can be formed either in a factory or on site. At landfills, there are many sources of plastic and hydrophobic materials available. Styrofoam is one of the hydrophobic materials that can be reused for QEJ brick production. There are two scenarios suggested. The first is that empty, perforated, and light brick-containments from plastics are produced in the factory in a way that can be easily transported, stored and joined together in the landfill (e.g. Figure 2).

Figure 2: QEJ Brick with hydrophobic styrofoam.

Once bricks are installed in trenches or in a cell, they are filled with shredded recyclable hydrophobic material (e.g. styrofoam). The second scenario is to use recyclable hydrophobic material in the factory by reforming it with a porosity of 95% (e.g. Figure 3). In this case, entire bricks are transported and stored and installed in the field.

Figure 3: QEJ brick Styrofoam reform.

Landfill Operation with QEJ Bricks
In the QEJ bricks management system, the waste is put and compacted between hydrophobic bricks installed in landfill trenches or biocells as shown in Figure 4. Starting with one brick then adding another brick as the height of waste rises up.

Figure 4: Landfill Operation with QEJ Bricks: a) initial operation for two biocells; b) finished first cell and chronological operation for subsequent cells.

The process of building the bricks is chronological as the confining bricks are built with sequential order to maintain structure stability and uniform consecutive processes during biocell construction. Figure 5 shows the waste profiles during the QEJ bricks operation. Profiles A and B are previous past operations, C is the current profile showing the chronological order of spreading waste and building bricks, D is the future profile, and E is the future geomembrane profile once cells are finished and closed.

Figure 5: Landfill Profiles while QEJ Bricks Operation: A and B are previous past profiles, C is the current profile, D is the future profile, E is the future geomembrane profile.

Waste Stabilization
In landfill cells, waste treatment is accomplished by aerobic processes and is followed by anaerobic processes for waste stabilization, waste degradation, and biogas generation. QEJ bricks can be used to introduce air during aerobic processes. In addition, the bricks are used to collect biogas generated through biological processes in aerobic/anaerobic phases. In addition, the QEJ bricks system could be adapted to include leachate recirculation system to stimulate bioactivity. In each finished cell, bricks are connected to valves and a piping system that convey biogas to a storage volume (Figure 6).

Figure 6: QEJ bricks management system with biogas collection and leachate recirculation in biocells.

Furthermore, biogas produced within the QEJ bricks system begins to move in the least resistant pathway toward the areas of less pressure and concentration. Biogas transfers fast and smoothly through the homogenous and neatly filled waste where there is no pressure build up, no inactive zone obstruction, and no heterogeneous gas transfer. Biogas tends to move toward the permeable evacuated QEJ bricks and then they are collected at ports. The behavior of gas transport within polymer media and the evacuation processes through valves, pipes and ports are all controlled by an intelligent fuzzy system.

Fuzzy Logic System

Fuzzy Logic Scheme
Fuzzy logic is a superset of conventional logic that has been extended to handle the concept of partial truth-values between “completely true” and “completely false”. Fuzzy Logic is a departure from classical two-valued sets and logic, which uses “soft” linguistic (e.g. large, hot, tall) system variables and a continuous range of truth-values in the interval [0, 1], rather than strict binary (True or False) decisions and assignments (14).

In Fuzzy logic, μs describes the membership function of S, or the degree to which X is a member of the set S. This is known as the degree of truth:

A fuzzy inference system is a system that uses a collection of fuzzy membership functions and rules, instead of Boolean logic, to reason about data. A typical fuzzy system consists of a rule base, membership functions, and an inference procedure (14). The general fuzzy process proceeds in fuzzification, inference, and defuzzification (15).

Fuzzification is the process that changes the crisp value to fuzzy value using membership function. The membership functions defined on the input variables are applied to their actual values to determine the degree of truth for each rule premise (16).

The truth-value for the premise of each rule is computed and applied to the conclusion part of each rule. This results in one fuzzy subset to be assigned to each output variable for each rule. MIN or PRODUCT is used as inference rules. In MIN inference, the output membership function is clipped off at a height corresponding to the rule premise’s computed degree of truth (fuzzy logic AND). In PRODUCT inference, the output membership function is scaled by the rule premise’s computed degree of truth (17). AND represents the intersection or MIN between two sets, expressed as:

OR represents the union or MAX between two sets, expressed as:

NOT represents the opposite of the set, expressed as:

c. Defuzzification
Defuzzification is used when it is useful to convert the fuzzy output set to a crisp number. Three of the more common techniques of defuzzification are the centroid, maximizer, and weighted average methods. In the centroid method, the crisp value of the output variable is computed by finding the value of the center of area (COA) of the membership function for the fuzzy value. In the maximizer method, one value by which the maximum output of the variable values is selected. In the weighted average method, it averages weighted possible outputs (18).

Fuzzy Logic Modeling
In this paper, Fuzzy logic simulates ambiguous methane and carbon dioxide transport in the hydrophobic medium. The fuzzy logic integrates multi inputs (temperature, concentration gradient, and pressure gradient) and multi outputs (diffusion/convection of methane and carbon dioxide) in a sub-set model. Fuzzy learning analysis showed more than 99% correlation between investigational data and fuzzy modeled data for methane and carbon dioxide transport via convection and diffusion in porous hydrophobic polymer medium (19). Fuzzy system incorporates gas transport rates according to the following sets:

Where Gi is biogas transport rate for i gas (methane, carbon dioxide), Ki is the conductivity coefficient of biogas i, ∇Pi is the pressure gradient, T is the temperature, Di is the diffusion coefficient of gas i, and ∇Ci is the concentration gradient.

Fuzzy system modeled the diffusion transport and convection transport for carbon dioxide and methane in two sub-models according to the above-defined sets (Figures 7 and 8) within variable conditions.

Figure 7: Matlab design fuzzy models (Gi1) for convection flow for carbon dioxide and methane within variable conditions (temperature of 21.4 oC, pressure gradient of 0.717 N/m2 m).

Figure 8: Matlab design fuzzy models (Gi2) for diffusion flux for carbon dioxide and methane within variable conditions (temperature of 17.5 oC, concentration gradient of 0.648 kg/m3 m).

Integrated Intelligent Fuzzy System
Biogas tends to transport toward the permeable evacuated QEJ bricks and then they are collected at ports. Gas transport processes are controlled by integrated intelligent fuzzy control system. The data acquisition system takes input data from sensors/meters at QEJ bricks about biogas pressure, concentration, flow rate, and temperature. Then it provides the input data to fuzzy models Gi1 and Gi2 to find biogas flow and flux. Finally, the input data is given to the fuzzy control system (Figure 9, 10) that automatically uses data to provide a signal to control valves at evacuation ports, consequently controlling biogas evacuation processes with efficient biogas transfer through the waste and the bricks (20).

Figure 9: Matlab design for integrated intelligent QEJ bricks management system.

Figure 9 shows the simulation run of the intelligent data acquisition-fuzzy control system described in Figure 10 for biogas collection processes with fuzzy rule viewer and control device viewer showing how the valve is opening and closing due to fuzzy control according to biogas pressure and velocity. The fuzzy modeling system is being tested after calibration is accomplished. The gas transport information obtained from the designed intelligent system responds strictly with the data available. Diffusive flux and convective flow of methane and carbon dioxide in hydrophobic polymer medium are shown in Figure 11 for experimental data (Exp), fuzzy modeled data (Fuzzy), and Fick’s law data. The experimental and fuzzy modeled data for methane and carbon dioxide transport due to convection and diffusion in porous hydrophobic polymer medium show more than 99% correlation.

Figure 10: Design of fuzzy control system for biogas evacuation.

For the intelligent fuzzy control system, Figure 12 indicates the scale up of biogas outflow rate released for collection due to fuzzy control according to biogas pressure and velocity process demonstrated in Figure 10.

Figure 11: Biogas transport rates via concentration and pressure gradient for experimental data (Exp), fuzzy modeled data (fuzzy), and Fick’s law data in hydrophobic medium at 25 °C.

Figure 12: Schedule of gas pressure and volume as a result of intelligent fuzzy controller.

Advantages of Intelligent QEJ Bricks Management System
Intelligent QEJ Bricks confines the waste with a new trend that provides a proper waste disposal, control of the generated biogas, permeable medium for conveying gas to collection storage, and integrated intelligent biogas management.

Intelligent QEJ Bricks system is also a state of the art method for reusing and recycling materials at the dump. As the bricks are hydrophobic, they contain no water, more air voids, and thus more permeable medium for biogas collection. The QEJ bricks system is flexible to apply successive aerobic – anaerobic processes and leachate recirculation which in turn increases waste degradation and stabilization.

Prospective advantages of intelligent QEJ bricks management system may include:

  • Integrated operation system that combines waste disposal, biogas evacuation, and biogas control
  • Fast decomposition and biological stabilization of the waste
  • More biogas generation
  • Smooth and fast transfer of biogas from waste to the bricks
  • Lower waste toxicity and mobility due to both aerobic and anaerobic conditions
  • Good candidate to apply for bioreactor landfill
  • Application of “reuse and recycle” solid waste management

The U.S. environmental protection agency (EPA) developed the solid waste management pyramid, which ranked the most preferable ways to address solid waste management. Source reduction, which includes reuse, was the listed as the best approach, followed by recycling. These two approaches are applied in the intelligent QEJ bricks management system in addition to enhanced gas uptake and better control of greenhouse gas emission.

This paper provides a novel municipal solid waste management system for biogas control in landfills. The MSW management system proposed in this research (Intelligent QEJ Bricks) provides new approaches on: management and operation, material medium for biogas collection, biogas transport modeling, design configuration, and automatic intelligent control system for biogas transport. The new operation of the developed system includes a series of cells with porous bricks built sequentially to form walls confining the waste. This approach employs an integrated operation system that combines waste disposal, biogas evacuation, and biogas control. The control concept in this research entails three parts: i) the control incorporated from the new configuration of the system that surrounds and captures all available biogas, ii) the control of the polymer medium that makes the gas move in the least resistant path i.e. within the polymer medium, iii) the fuzzy logic regime for transport-evacuation processes for available biogas that is being delivered for storage and utilization. The space in the system could be used in the future after waste consumption, and the bricks could be used for air distribution at early aerobic processes for newly utilized waste.

Acknowledgements: The financial support from the Natural Sciences and Engineering Research Council of Canada under grant RGPIN-18948 is gratefully acknowledged.


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