The integration of communication technologies such as radio frequency identification (RFID), global positioning system (GPS), general packet radio system (GPRS), and geographic information system (GIS) with a camera are constructed for solid waste monitoring system. The aim is to improve the way of responding to customer's inquiry and emergency cases and estimate the solid waste amount without any involvement of the truck driver. The proposed system consists of RFID tag mounted on the bin, RFID reader as in truck, GPRS/GSM as web server, and GIS as map server, database server, and control server. The tracking devices mounted in the trucks collect location information in real time via the GPS. This information is transferred continuously through GPRS to a central database. The users are able to view the current location of each truck in the collection stage via a web-based application and thereby manage the fleet. The trucks positions and trash bin information are displayed on a digital map, which is made available by a map server. Thus, the solid waste of the bin and the truck are being monitored using the developed system.
In this paper, an image-based waste collection scheduling involving a node with three waste bins is considered. First, the system locates the three bins and determines the waste level of each bin using four Laws Masks and a set of Support Vector Machine (SVM) classifiers. Next, a Hidden Markov Model (HMM) is used to decide on the number of days remaining before waste is collected from the node. This decision is based on the HMM's previous state and current observations. The HMM waste collection scheduling seeks to maximize the number of days between collection visits while preventing waste contamination due to late collection. The proposed system was trained using 100 training images and then tested on 100 test images. Each test image contains three bins that might be shifted, rotated, occluded or toppled over. The upright bins could be empty, partially full or full of garbage of various shapes and sizes. The method achieves bin detection, waste level classification and collection day scheduling rates of 100%, 99.8% and 100% respectively.
The performance of a carbon-mineral composite adsorbent used in a fixed bed column for the removal of ammoniacal nitrogen and aggregate organic pollutant (COD), which are commonly found in landfill leachate, was evaluated. The breakthrough capacities for ammoniacal nitrogen and COD adsorption were 4.46 and 3.23 mg/g, respectively. Additionally, the optimum empty bed contact time (EBCT) was 75 min. The column efficiency for ammoniacal nitrogen and COD adsorption using fresh adsorbent was 86.4% and 92.6%, respectively, and these values increased to 90.0% and 93.7%, respectively, after the regeneration process.
In the present study, Electrochemical Oxidation was used to remove COD and color from semi-aerobic landfill leachate collected from Pulau Burung Landfill Site (PBLS), Penang, Malaysia. Experiments were conducted in a batch laboratory-scale system in the presence of NaCl as electrolyte and aluminum electrodes. Central composite design (CCD) under Response surface methodology (RSM) was applied to optimize the electrochemical oxidation process conditions using chemical oxygen demand (COD) and color removals as responses, and the electrolyte concentrations, current density and reaction time as control factors. Analysis of variance (ANOVA) showed good coefficient of determination (R(2)) values of >0.98, thus ensuring satisfactory fitting of the second-order regression model with the experimental data. In un-optimized condition, maximum removals for COD (48.77%) and color (58.21%) were achieved at current density 80 mA/cm(2), electrolyte concentration 3,000 mg/L and reaction time 240 min. While after optimization at current density 75 mA/cm(2), electrolyte concentration 2,000 mg/L and reaction time 218 min a maximum of 49.33 and 59.24% removals were observed for COD and color respectively.
In Malaysia, landfills are being filled up rapidly due to the current daily generation of approximately 30,000 tonnes of municipal solid waste. This situation creates the crucial need for improved landfilling practices, as sustainable landfilling technology is yet to be achieved here. The objective of this paper is to identify and evaluate the development and trends in landfilling practices in Malaysia. In 1970, the disposal sites in Malaysia were small and prevailing waste disposal practices was mere open-dumping. This network of relatively small dumps, typically located close to population centres, was considered acceptable for a relatively low population of 10 million in Malaysia. In the 1980s, a national programme was developed to manage municipal and industrial wastes more systematically and to reduce adverse environmental impacts. The early 1990s saw the privatization of waste management in many parts of Malaysia, and the establishment of the first sanitary landfills for MSW and an engineered landfill (called 'secure landfill' in Malaysia) for hazardous waste. A public uproar in 2007 due to contamination of a drinking water source from improper landfilling practices led to some significant changes in the government's policy regarding the country's waste management strategy. Parliament passed the Solid Waste and Public Cleansing Management (SWPCM) Act 2007 in August 2007. Even though the Act is yet to be implemented, the government has taken big steps to improve waste management system further. The future of the waste management in Malaysia seems somewhat brighter with a clear waste management policy in place. There is now a foundation upon which to build a sound and sustainble waste management and disposal system in Malaysia.
In this research, the capability of lateritic soil used as coagulant for the treatment of stabilized leachate from the Penang-Malaysia Landfill Site was investigated. The evaluation of lateritic soil coagulant in comparison with commercialized chemical coagulants, such as alum, was performed using conventional jar test experiments. The optimum pH and coagulant dosage were identified for the lateritic soil coagulant and the comparative alum coagulant. It was found that the application of lateritic soil coagulant was quite efficient in the removal of COD, color and ammoniacal-nitrogen content from the landfill leachate. The optimal pH value was 2.0, while 14 g/L of lateritic soil coagulant was sufficient in removing 65.7% COD, 81.8% color and 41.2% ammoniacal-nitrogen. Conversely, the optimal pH and coagulant dosage for the alum were pH 4.8 and 10 g/L respectively, where 85.4% COD, 96.4% color and 47.6% ammoniacal-nitrogen were removed from the same leachate sample. Additionally, the Sludge Volume Index (SVI) ratio of alum and lateritic soil coagulant was 53:1, which indicated that less sludge was produced and was an environmentally friendly product. Therefore, lateritic soil coagulant can be considered a viable alternative in the treatment of landfill leachate.
The presence of ammoniacal nitrogen (N-NH3) in leachate is one of the problems normally faced by landfill operators. Slow leaching of wastes producing nitrogen and no significant mechanism for transformation of N-NH3 in the landfills causes a high concentration of ammoniacal nitrogen in leachate over a long period of time. A literature review showed that the removal of ammoniacal nitrogen from leachate was not well documented and to date, there were limited studies in Malaysia on this aspect, especially in adsorption treatment. The main objective of the present study was to investigate the suitability of activated carbon, limestone and a mixture of both materials as a filtering medium, in combination with other treatments capable of attenuating ammoniacal nitrogen which is present in significant quantity (between 429 and 1909 mg L(-1)) in one of the landfill sites in Malaysia. The results of the study show that about 40% of ammoniacal nitrogen with concentration of more than 1000 mg L(-1) could be removed either by activated carbon or a mixture of carbon with limestone at mixture ratio of 5:35. This result shows that limestone is potentially useful as a cost-effective medium to replace activated carbon for ammoniacal nitrogen removal at a considerably lower cost.
Limestone has been proven effective in removing metals from water and wastewater. A literature review indicated that limestone is capable of removing heavy metals such as Cu, Zn, Cd, Pb, Ni, Cr, Fe and Mn are through a batch process or by filtration technique. The removal capability is reported at up to 90%. However, to date most of the studies have been focused on synthetic wastewater. The present study attempts to investigate the suitability of limestone to attenuate total iron (Fe) from semi aerobic leachate at Pulau Burung Landfill Site in Penang, Malaysia. Iron was found in significant quantities at the landfill site. The study also aims to establish the Fe isotherm and breakthrough time of the proposed limestone filter for post-treatment to the migrating landfill leachate before its release to the environment. The Fe isotherms were established using a batch equilibrium test, while the breakthrough characteristics were determined using continuous flow permeating through a limestone column. The latter was used in order to simulate the continuous flow of leachate that would occur in the proposed limestone filter. The limestone media used in the experiment contain more than 90% CaCO3 with particle sizes ranging from 2 to 4 mm. Four filter columns (each 150 mm in diameter and 1000 mm depth) were installed at the landfill site. Metal loadings were kept below 0.5 kg /m3 day and the experiment was run continuously for 30 days. Initial results indicated that 90% of Fe can be removed from the leachate based on retention time of 57.8 min and surface loading of 12.2 m3/m2 day. For the batch study on the Fe isotherm, the results indicated that limestone is potentially useful as an alternative leachate treatment system at a relatively low cost.
Field and laboratory studies were conducted to estimate concentration of potential contaminants from landfill in the underlying groundwater, leachate, and surface water. Samples collected in the vicinity of the landfill were analyzed for physiochemical parameters, organic contaminants, and toxic heavy metals. Water quality results obtained were compared from published data and reports. The results indicate serious groundwater and surface water contamination in and around the waste disposal site. Analysis of the organic samples revealed that the site contains polychlorinated biphenyls and other organo-chlorine chemicals, principally chloro-benzenes. Although the amount of PCB concentration discovered was not extreme, their presence indicates a potentially serious environmental threat. Elevated concentrations of lead, copper, nickel, manganese, cadmium, and cobalt at the downgradient indicate that the contamination plume migrated further from the site, and the distribution of metals and metals containing wastes in the site is nonhomogeneous. These results clearly indicate that materials are poorly contained and are at risk of entering the environment. Therefore, full characterization of the dump contents and the integrity of the site are necessary to evaluate the scope of the problem and to identify suitable remediation options.
Currently, generation of solid waste per capita in Malaysia is about 1.1 kg/day. Over 26,500 t of solid waste is disposed almost solely through 166 operating landfills in the country every day. Despite the availability of other disposal methods, landfill is the most widely accepted and prevalent method for municipal solid waste (MSW) disposal in developing countries, including Malaysia. This is mainly ascribed to its inherent forte in terms cost saving and simpler operational mechanism. However, there is a downside. Environmental pollution caused by the landfill leachate has been one of the typical dilemmas of landfilling method. Leachate is the liquid produced when water percolates through solid waste and contains dissolved or suspended materials from various disposed materials and biodecomposition processes. It is often a high-strength wastewater with extreme pH, chemical oxygen demand (COD), biochemical oxygen demand (BOD), inorganic salts and toxicity. Its composition differs over the time and space within a particular landfill, influenced by a broad spectrum of factors, namely waste composition, landfilling practice (solid waste contouring and compacting), local climatic conditions, landfill's physico-chemical conditions, biogeochemistry and landfill age. This paper summarises an overview of landfill operation and leachate treatment availability reported in literature: a broad spectrum of landfill management opportunity, leachate parameter discussions and the way forward of landfill leachate treatment applicability.
In this study, solid oil palm shell (OPS) waste biomass was subjected to microwave pyrolysis conditions with uniformly distributed coconut activated carbon (CAC) microwave absorber. The effects of CAC loading (wt%), microwave power (W) and N2 flow rate (LPM) were investigated on heating profile, bio-oil yield and its composition. Response surface methodology based on central composite design was used to study the significance of process parameters on bio-oil yield. The coefficient of determination (R(2)) for the bio-oil yield is 0.89017 indicating 89.017% of data variability is accounted to the model. The largest effect on bio-oil yield is from linear and quadratic terms of N2 flow rate. The phenol content in bio-oil is 32.24-58.09% GC-MS area. The bio-oil also contain 1,1-dimethyl hydrazine of 10.54-21.20% GC-MS area. The presence of phenol and 1,1-dimethyl hydrazine implies that the microwave pyrolysis of OPS with carbon absorber has the potential to produce valuable fuel products.
High temperature thermal plasma has a major drawback which consumes high energy. Therefore, non-thermal plasma which uses comparatively lower energy, for instance, microwave plasma is more attractive to be applied in gasification process. Microwave-induced plasma gasification also carries the advantages in terms of simplicity, compactness, lightweight, uniform heating and the ability to operate under atmospheric pressure that gains attention from researchers. The present paper synthesizes the current knowledge available for microwave plasma gasification on solid fuels and waste, specifically on affecting parameters and their performance. The review starts with a brief outline on microwave plasma setup in general, and followed by the effect of various operating parameters on resulting output. Operating parameters including fuel characteristics, fuel injection position, microwave power, addition of steam, oxygen/fuel ratio and plasma working gas flow rate are discussed along with several performance criteria such as resulting syngas composition, efficiency, carbon conversion, and hydrogen production rate. Based on the present review, fuel retention time is found to be the key parameter that influences the gasification performance. Therefore, emphasis on retention time is necessary in order to improve the performance of microwave plasma gasification of solid fuels and wastes.
The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensor intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.
The kitchen waste fraction in municipal solid waste contains high organic matter particularly carbohydrate that can contribute to fermentable sugar production for subsequent conversion to bioethanol. This study was carried out to evaluate the influence of single and combination pretreatments of kitchen waste by liquid hot water, mild acid pretreatment of hydrochloric acid (HCl) and sulphuric acid (H2SO4) and enzymatic hydrolysis (glucoamylase). The maximum total fermentable sugar produced after combination pretreatment by 1.5% HCl and glucoamylase consisted of 93.25 g/L glucose, 0.542 g/L sucrose, 0.348 g/L maltose, and 0.321 g/L fructose. The glucose released by the combination pretreatment method was 0.79 g glucose/g KW equivalent to 79% of glucose conversion. The effects of the pre-treatment on kitchen waste indicated that the highest solubilization was 40% by the combination method of 1.5% HCl and glucoamylase. The best combination pre-treatment gave concentrations of lactic acid, acetic acid, and propionic acid of 11.74 g/L, 6.77 g/L, and 1.02 g/L, respectively. The decrease of aliphatic absorbance bands of polysaccharides at 2851 and 2923 cm(-1) and the increase on structures of carbonyl absorbance bands at 1600 cm(-1) reflects the progress of the kitchen waste hydrolysis to fermentable sugars. Overall, 1.5% HCl and glucoamylase treatment was the most profitable process as the minimum selling price of glucose was USD 0.101/g kitchen waste. Therefore, the combination pretreatment method was proposed to enhance the production of fermentable sugar, particularly glucose from kitchen waste as the feedstock for bioethanol production.
This paper deals with the solid waste image detection and classification to detect and classify the solid waste bin level. To do so, Hough transform techniques is used for feature extraction to identify the line detection based on image's gradient field. The feedforward neural network (FFNN) model is used to classify the level content of solid waste based on learning concept. Numbers of training have been performed using FFNN to learn and match the targets of the testing images to compute the sum squared error with the performance goal met. The images for each class are used as input samples for classification. Result from the neural network and the rules decision are used to build the receiver operating characteristic (ROC) graph. Decision graph shows the performance of the system waste system based on area under curve (AUC), WS-class reached 0.9875 for excellent result and WS-grade reached 0.8293 for good result. The system has been successfully designated with the motivation of solid waste bin monitoring system that can applied to a wide variety of local municipal authorities system.
An advanced image processing approach integrated with communication technologies and a camera for waste bin level detection has been presented. The proposed system is developed to address environmental concerns associated with waste bins and the variety of waste being disposed in them. A gray level aura matrix (GLAM) approach is proposed to extract the bin image texture. GLAM parameters, such as neighboring systems, are investigated to determine their optimal values. To evaluate the performance of the system, the extracted image is trained and tested using multi-layer perceptions (MLPs) and K-nearest neighbor (KNN) classifiers. The results have shown that the accuracy of bin level classification reach acceptable performance levels for class and grade classification with rates of 98.98% and 90.19% using the MLP classifier and 96.91% and 89.14% using the KNN classifier, respectively. The results demonstrated that the system performance is robust and can be applied to a variety of waste and waste bin level detection under various conditions.
This paper presents solid waste bin level detection and classification using gray level co-occurrence matrix (GLCM) feature extraction methods. GLCM parameters, such as displacement, d, quantization, G, and the number of textural features, are investigated to determine the best parameter values of the bin images. The parameter values and number of texture features are used to form the GLCM database. The most appropriate features collected from the GLCM are then used as inputs to the multi-layer perceptron (MLP) and the K-nearest neighbor (KNN) classifiers for bin image classification and grading. The classification and grading performance for DB1, DB2 and DB3 features were selected with both MLP and KNN classifiers. The results demonstrated that the KNN classifier, at KNN = 3, d = 1 and maximum G values, performs better than using the MLP classifier with the same database. Based on the results, this method has the potential to be used in solid waste bin level classification and grading to provide a robust solution for solid waste bin level detection, monitoring and management.
This paper deals with a system of integration of Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system. RFID, GPS, GPRS and GIS along with camera technologies have been integrated and developed the bin and truck intelligent monitoring system. A new kind of integrated theoretical framework, hardware architecture and interface algorithm has been introduced between the technologies for the successful implementation of the proposed system. In this system, bin and truck database have been developed such a way that the information of bin and truck ID, date and time of waste collection, bin status, amount of waste and bin and truck GPS coordinates etc. are complied and stored for monitoring and management activities. The results showed that the real-time image processing, histogram analysis, waste estimation and other bin information have been displayed in the GUI of the monitoring system. The real-time test and experimental results showed that the performance of the developed system was stable and satisfied the monitoring system with high practicability and validity.
In the backdrop of prompt advancement, information and communication technology (ICT) has become an inevitable part to plan and design of modern solid waste management (SWM) systems. This study presents a critical review of the existing ICTs and their usage in SWM systems to unfold the issues and challenges towards using integrated technologies based system. To plan, monitor, collect and manage solid waste, the ICTs are divided into four categories such as spatial technologies, identification technologies, data acquisition technologies and data communication technologies. The ICT based SWM systems classified in this paper are based on the first three technologies while the forth one is employed by almost every systems. This review may guide the reader about the basics of available ICTs and their application in SWM to facilitate the search for planning and design of a sustainable new system.
Composting is a good recycling method to fully utilise all the organic wastes present in kitchen waste due to its high nutritious matter within the waste. In this present study, the optimised mixture proportions of kitchen waste containing vegetable scraps (V), fish processing waste (F) and newspaper (N) or onion peels (O) were determined by applying the simplex-centroid mixture design method to achieve the desired initial moisture content and carbon-to-nitrogen (CN) ratio for effective composting process. The best mixture was at 48.5% V, 17.7% F and 33.7% N for blends with newspaper while for blends with onion peels, the mixture proportion was 44.0% V, 19.7% F and 36.2% O. The predicted responses from these mixture proportions fall in the acceptable limits of moisture content of 50% to 65% and CN ratio of 20-40 and were also validated experimentally.