Noor Ezlin Ahmad Basri

Regional landfills methane emission inventory in Malaysia

The decomposition of municipal solid waste (MSW) in landfills under anaerobic conditions produces landfill gas (LFG) containing approximately 50—60% methane (CH4) and 30—40% carbon dioxide (CO2) by volume. CH4 has a global warming potential 21 times greater than CO2; thus, it poses a serious environmental problem. As landfills are the main method for waste disposal in Malaysia, the major aim of this study was to estimate the total CH4 emissions from landfills in all Malaysian regions and states for the year 2009 using the IPCC, 1996 first-order decay (FOD) model focusing on clean development mechanism (CDM) project applications to initiate emission reductions. Furthermore, the authors attempted to assess, in quantitative terms, the amount of CH4 that would be emitted from landfills in the period from 1981—2024 using the IPCC 2006 FOD model. The total CH4 emission using the IPCC 1996 model was estimated to be 318.8 Gg in 2009. The Northern region had the highest CH4 emission inventory, with 128.8 Gg, whereas the Borneo region had the lowest, with 24.2 Gg. It was estimated that Pulau Penang state produced the highest CH4 emission, 77.6 Gg, followed by the remaining states with emission values ranging from 38.5 to 1.5 Gg. Based on the IPCC 1996 FOD model, the total Malaysian CH 4 emission was forecast to be 397.7 Gg by 2020. The IPCC 2006 FOD model estimated a 201 Gg CH4 emission in 2009, and estimates ranged from 98 Gg in 1981 to 263 Gg in 2024.

RP3CA: An expert system applied in stormwater management plan for construction sites in Malaysia

Abstract The stormwater management in construction site is an important, complicate and time-consuming task that relates to huge amount of information, data, domain law, and expert knowledge and experience in terms of environmental protection, soil erosion, and receiving water protection. This paper presents an expert system “RP 3 CA” that is used to mitigate stormwater pollution during construction activities. A most important function of the RP 3 CA is its user interface, which utilizes Geographic Information System functions as a supportive component to display spatial maps. Decision tables and trees are used to acquire expert knowledge and experience. Certainty Factor is used for measuring the expert belief or disbelief of the system rules. Opinion integration of multiple experts is obtained by application of Expert Choice software where various alternatives are available. Assessment suggestions and results are derived utilizing a forward chaining inference mechanism. Unit testing, integrated testing, system testing, two test cases, comparison of system results, internal experts, and external experts, reviewers feedback by system application, and validation of system reasoning are used to demonstrate the proposed RP 3 CA.

Modeling of methane oxidation in landfill cover soil using an artificial neural network

Knowing the fraction of methane (CH4) oxidized in landfill cover soils is an important step in estimating the total CH4 emissions from any landfill. Predicting CH4 oxidation in landfill cover soils is a difficult task because it is controlled by a number of biological and environmental factors. This study proposes an artificial neural network (ANN) approach using feedforward backpropagation to predict CH4 oxidation in landfill cover soil in relation to air temperature, soil moisture content, oxygen (O2) concentration at a depth of 10 cm in cover soil, and CH4 concentration at the bottom of cover soil. The optimum ANN model giving the lowest mean square error (MSE) was configured from three layers, with 12 and 9 neurons at the first and the second hidden layers, respectively, log-sigmoid (logsig) transfer function at the hidden and output layers, and the Levenberg-Marquardt training algorithm. This study revealed that the ANN oxidation model can predict CH4 oxidation with a MSE of 0.0082, a coefficient of determination (R 2) between the measured and predicted outputs of up to 0.937, and a model efficiency (E) of 0.8978. To conclude, further developments of the proposed ANN model are required to generalize and apply the model to other landfills with different cover soil properties. Implications: To date, no attempts have been made to predict the percent of CH4 oxidation within landfill cover soils using an ANN. This paper presents modeling of CH4 oxidation in landfill cover soil using ANN based on field measurements data under tropical climate conditions in Malaysia. The proposed ANN oxidation model can be used to predict the percentage of CH4 oxidation from other landfills with similar climate conditions, cover soil texture, and other properties. The predicted value of CH4 oxidation can be used in conjunction with the Intergovernmental Panel on Climate Change (IPCC) First Order Decay (FOD) model by landfill operators to accurately estimate total CH4 emission and how much it contributes to global warming.

Biomethanation of kitchen waste and sewage sludge in anaerobic baffled reactor

Biomethanation is a promising method for transformation of organic fraction of municipal solid waste (OFMSW) to valuable energy. In addition, as OFMSW has considerable portion in any community generated solid waste, biomethanation reduces the total waste to be collected, transported and disposed to the landfill. In this study application of laboratory-scale anaerobic baffled reactor (ABR) for production of methane gas through co-digestion of kitchen waste and sewage sludge was investigated. Performance of four ABRs with identical volume of 75 l under hydraulic retention time (HRT) of 3 days and with kitchen waste and sewage sludge mixed at ratio of 100:0, 75:25, 50:50 and 25:75 was compared in terms of methane yield and microorganisms growth. Results indicate that, the ABR containing 75% kitchen waste and 25% sewage sludge had highest volumetric percentage of methane (>;80%). This amount was relatively reasonable for other samples except sample with 100 % kitchen waste (<; 20%). pH investigation shows sample containing 100% kitchen waste is slow compared to the others in term of higher-molecular-mass compounds breakdown as well as development of both acid formers and methane formers. This signifies that not only the suitable substrate but also proper development of different species of microorganisms is vital in any biomethanation system.

Production of renewable energy by transformation of kitchen waste to biogas, case study of Malaysia

Municipal Solid Waste (MSW) management has been highlighted by the Malaysian government as an important agenda in ensuring successful development of the country. Due to the fast growing urbanization and industrialization of the country, a tremendous increment of solid waste generation is an unavoidable occurrence. With increased levels of waste production, limited area for landfilling, and increased awareness of environmental impact, alternative methods for treatment of solid and agricultural wastes are being sought. Currently these wastes load to the dumping sites and release undesired methane into the atmosphere. A typical composition of MSW in Malaysia comprises as high as 70 to 80% of organic waste with high moisture content (80 to 85%), which is suitable for biological transformation to biogas. Therefore, in this study, application of an anaerobic digester for transformation of kitchen waste was investigated. The best organic loading rate (OLR) and slurry concentration for highest biogas production rate were examined. Results show COD reduction of 80, 97, 85, 80 and 70 % for OLR of 2, 4, 8, 15 and 20 kg/m3, respectively. The best biogas production rate (0.6 m3/kgVS) was achieved at slurry concentration of 40 g/L.

Floc behavior and removal mechanisms of cross-linked Durio zibethinus seed starch as a natural flocculant for landfill leachate coagulation-flocculation treatment

This study investigated the behavior and mechanisms of cross-linked Durio zibethinus seed starch (CDSS) flocculants for landfill leachate treatment. A physical-chemical treatment method of coagulation-flocculation process and starch modification were implemented in treating stabilized leachate from Matang Landfill, Perak, Malaysia. In practical, the removal performance of color, COD, suspended solid and turbidity for CDSS flocculants were evaluated by combining with primary coagulant of polyaluminium chloride (PAC). In this study, the application of crosslinking modification for Durio zibethinus seed waste starch flocculants showed good improvement. The impurities removal for colour, COD, suspended solid and turbidity were increased by the addition of CDSS flocculants. Furthermore, the average size of the floc was also increased from 60.24 µm to 89.5 µm. Despite, the addition of CDSS flocculants produced a reduction of PAC coagulant from 2700 mg/L to 2200 mg/L, with 500 mg/L reduction on the PAC dosage dependency. Therefore, these results affirmed the potentials of crosslinked modification for Durio zibethinus seed waste starch flocculants in landfill leachate treatment.

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

An Expert System for Construction Sites Best Management Practices

The construction industry has the potential to significantly impact our environment. Using Best Management Practices (BMPs) at construction sites is the most effective way to protect our environment and prevent pollution. In recent years, intelligent systems have been used extensively in different applications areas including environmental studies. As an aid to reduce environmental pollution originating from construction activities, expert system software -CSBMP- developed by using Microsoft Visual Basic. CSBMP to be used for BMPs at construction sites was designed based on the legal process. CSBMP primarily aims to provide educational and support system for environmental engineers and decision-makers during construction activities. It displays system recommendations in report form.When the use of CSBMP in construction sites BMPs becomes widespread, it is highly possible that it will be benefited in terms of having more accurate and objective decisions on construction projects which are mainly focused on reducing the environmental pollution.

Study on Performance and Characteristic of Microorganisms in a Waste-to-Energy System

Performance and characterization of microorganisms in a laboratory-scale anaerobic baffled reactor (ABR) was studied. The ABR was fed continuously at organic loading rate (OLR) of 15.2 g COD/l.d with a substrate containing pre-tested combination of kitchen waste and activated sludge. The HRT (hydraulic retention time), C/N (carbon/nitrogen) and F/M (food/microorganisms) ratios were maintained at 3 d, 31.4 and 0.35 gCOD/gVSS.d, respectively. The amounts of fat, protein, cellulose, hemi-cellulose and lignin which are significant polymers for anaerobic digestion start-up were found to be in appropriate ranges. Results show reduction of pH in front compartments and its boost in successive compartments. This indicates proper placement of acidogens and methanogens in the ABR. Also, significant growth in height of ABR granule bed was observed in the system based on formation and retention of granules. Microorganism characterization reveals large population of Methanosarcina in front part of the reactor although toward the end the amount for Methanosaeta increased. While Methanobacterium, Methanosprilium, Methanococcus and Methanobrevibacter were observed in the ABR, higher percentage of Methanosarcina and Methanotrix indicates production of methane from acetate conversion.