ESTIMATING THE PROBABILITY OF EXCEEDING GROUNDWATER QUALITY STANDARDS1

ABSTRACT: A model for estimating the probability of exceeding groundwater quality standards at environmental receptors based on a simple contaminant transport model is described. The model is intended for locations where knowledge about site-specific hydrogeologic conditions is limited. An efficient implementation methodology using numerical Monte Carlo simulation is presented. The uncertainty in the contaminant transport system due to uncertainty in the hydraulic conductivity is directly calculated in the Monte Carlo simulations. Numerous variations of the deterministic parameters of the model provide an indication of the change in exceedance probability with change in parameter value. The results of these variations for a generic example are presented in a concise graphical form which provides insight into the topology of the exceedance probability surface. This surface can be used to assess the impact of the various parameters on exceedance probability.     

A short review on hydrothermal liquefaction of livestock manure and a chance for Korea to advance swine manure to bio-oil technology

Due to the abundant supply and suitable physicochemical characteristics of livestock manure, it may be a useful biomass to produce biofuels, such as “bio-oil.” Hydrothermal liquefaction is a promising method for converting such wet biomasses into a liquid fuels and has attracted attention worldwide. In this review, the current state of research on the hydrothermal liquefaction of livestock manure biomasses is summarized. The effect of operating parameters on the yield of bio-oil is also reviewed. The fundamental characteristics of raw manure biomasses and converted oils are outlined and discussed in the paper. To reduce the use of fossil fuel and nuclear energy, the South Korean government has pledged to increase renewable energy. Based on findings from a literature review, it can be concluded that there is a chance for Korea to advance bio-oil production from the abundant and tremendous energy potential of swine manure by a hydrothermal liquefaction process.     

Movement towards a low carbon emitted environment: a test of some factors in Malaysia

There exists a high global concern in different nations on environmental sustainability especially at the focal stage of increased economic growth and development process due to high level of environmental degradation and pollution. The major aim of this study was to empirically examine how to minimise carbon emissions (CO₂) in Malaysia which are mainly caused by energy production, fossil fuel consumption, population density and economic growth. The study adopted the method of autoregressive distributed lag bound testing approach to analyse the data for the period 1971–2011. The study found that economic growth in Malaysia has a direct relationship with CO₂ emissions in both the short run and the long run. Similarly, there is a positive relationship between fossil fuel consumption and CO₂ emissions over the same period. Population density was found to have positive impacts on CO₂ emissions. Contrarily, the relationship between the activities of energy production and pollution is negative in the long run. The study recommends that a targeted GDP growth rate should be set with the consideration to avoid more environmental pollution. In addition, the positive impact of fossil fuel consumption on the environmental pollution implies that there is a need to make and implement policies that will encourage the use of public transportation system more than private transportations. That is, the unnecessary use of private vehicles should be discouraged in order to reduce the extent of fossil fuel consumption.     

Non-linear autoregressive neural network approach for inside air temperature prediction of a pillar cooler

The volcanic plate made pillar cooler system is designed for outdoor spaces as a heat exchanging medium and reduces the outcoming air temperature which flows through the exhaust port. This paper proposes the use of artificial neural networks (ANNs) to predict inside air temperature of a pillar cooler. For this purpose, at first, three statistically significant factors (outside temperature, airing and watering) influencing the inside air temperature of the pillar cooler are identified as input parameters for predicting the output (inside air temperature) and then an ANN was employed to predict the output. In addition, 70%, 15% and 15% data was chosen from a previously obtained data set during the field trial of the pillar cooler for training, testing and validation, respectively, and then an ANN was employed to predict inside air temperature. The training (0.99918), testing (0.99799) and validation errors (0.99432) obtained from the model indicate that the artificial neural network model (NARX) may be used to predict inside air temperature of pillar cooler. This study reveals that, an ANN approach can be used successfully for predicting the performance of pillar cooler.     

Impact of landfill liner time–temperature history on the service life of HDPE geomembranes

The observed temperatures in different landfills are used to establish a number of idealized time–temperature histories for geomembrane liners in municipal solid waste (MSW) landfills. These are then used for estimating the service life of different HDPE geomembranes. The predicted antioxidant depletion times (Stage I) are between 7 and 750 years with the large variation depending on the specific HDPE geomembrane product, exposure conditions, and most importantly, the magnitude and duration of the peak liner temperature. The higher end of the range corresponds to data from geomembranes aged in simulated landfill liner tests and a maximum liner temperature of 37 °C. The lower end of the range corresponds to a testing condition where geomembranes were immersed in a synthetic leachate and a maximum liner temperature of 60 °C. The total service life of the geomembranes was estimated to be between 20 and 3300 years depending on the time–temperature history examined. The range illustrates the important role that time–temperature history could play in terms of geomembrane service life. The need for long-term monitoring of landfill liner temperature and for geomembrane ageing studies that will provide improved data for assessing the likely long-term performance of geomembranes in MSW landfills are highlighted.     

Pyrolysis kinetics behavior of solid tire wastes available in Bangladesh

Pyrolysis kinetics of available bicycle/rickshaw, motorcycle and truck tire wastes in Bangladesh have been investigated thermogravimetrically in a nitrogen atmosphere at heating rates of 10 and 60 degrees C/min over a temperature range of 30-800 degrees C. The three tire wastes exhibited similar behaviors in that, when heating rate was increased, the initial reaction temperature decreased but the reaction range and reaction rate increased. The percentage of total weight loss was higher for truck tire waste and lower for bicycle/rickshaw tire waste. The pyrolysis of truck tire waste was found to be easier than that of bicycle/rickshaw and motorcycle tire wastes while it was comparatively more difficult for motorcycle tire waste. The overall rate equation for the three tire wastes has been modeled satisfactorily by one simplified equation from which the kinetic parameters of unreacted materials based on the Arrhenius form can be determined. The predicted rate equation compares fairly well with the measured TG and DTG data. DTA curves for all of the samples show that the degradation reactions are three main exotherms and one endotherm.     

Deterioration of water quality of Surma river

Surma River is polluted day by day by human activities, poor structured sewerage and drainage system, discharging industrial and household wastes. The charas (natural channels) are responsible for surface runoff conveyance from its urban catchments to the receiving Surma River. Water samples have been collected from a part of Surma River along different points and analyzed for various water quality parameters during dry and monsoon periods. Effects of industrial wastes, municipal sewage, and agricultural runoff on river water quality have been investigated. The study was conducted within the Chattak to Sunamganj portion of Surma River, which is significant due to the presence of two major industries – a paper mill and a cement factory. The other significant feature is the conveyors that travel from India to Chattak. The river was found to be highly turbid in the monsoon season. But BOD and fecal coliform concentration was found higher in the dry season. The water was found slightly acidic. The mean values of parameters were Conductivity 84–805 μs; DO: dry-5.52 mg/l, monsoon-5.72 mg/l; BOD: dry-1mg/l, monsoon-0.878 mg/l; Total Solid: dry-149.4 mg/l, monsoon-145.7 mg/l. In this study, an effort has been taken to investigate the status of concentration of phosphate (PO⁻⁴) and ammonia–nitrogen (NH₄–N) at four entrance points of Malnichara to the city, Guali chara, Gaviar khal and Bolramer khal. Data has been collected from March–April and September–October of 2004. Concentrations have been measured using UV Spectrophotometer. Although the phosphate concentration has been found within the limit set by DOE for fishing, irrigation and recreational purposes, however ammonia–nitrogen has been found to exceed the limit.     

Climate change in Asia: issues and policy options

This article provides a brief review of some of the policy issues facing the Asian region with respect to climate change and its economic consequences. The environmental consequences of Asia's economic rise threaten the future growth of the region. Despite recent economic expansion, Asia will be one of the areas of the world most vulnerable to climate change. While Asia currently contributes moderately to greenhouse gas emissions, the potential for increases in emissions is significant. National and regional policy options, including abatement and adaptation, are examined as strategies for tackling the likely effects of climate change. This study recommends that national initiatives that have no 'regrets' properties be a priority area for further research so that they can be implemented as soon as possible. It is envisaged that in the short to medium term, identifiable no regrets policies can be a useful tool for reducing emissions and vulnerability to climate change in developing regions such as Asia.     

Construction and evaluation of simulated pilot scale landfill lysimeter in Bangladesh

This research concentrates the design, construction and evaluation of simulated pilot scale landfill lysimeter at KUET campus, Khulna, Bangladesh. Both the aerobic and anaerobic conditions having a base liner and two different types of cap liner were simulated. After the design of a reference cell, the construction of landfill lysimeter was started in January 2008 and completed in July 2008. In all construction process locally available civil construction materials were used. The municipal solid waste (MSW) of 2800–2985 kg having the total volume of 2.80 m³ (height 1.6 m) and moisture content of 65% was deposited in each lysimeter by applying required compaction energy. In contrast, both the composition in terms of methane (CH₄), carbon dioxide (CO₂) and oxygen (O₂) as well as the flow rate of landfill gas (LFG) generated from MSW in landfill lysimeter were measured and varied significantly in relation to the variation of lysimeter operational condition. Moreover, anaerobic lysimeter-C shows the highest composition of LFG in compare to the anaerobic lysimeter-B due to the providing of lower compaction of cap liner in anaerobic lysimeter-C. Here, it is interesting to note that in absence of compacted clay liner (CCL) and hence percolation of rainwater that facilitates rapid degradation of MSW in aerobic lysimeter-A has resulted in the highest settlement than that of anaerobic landfill lysimeter-B and C. Moreover, in case of anaerobic lysimeter-B and C, the leachate generation was lower than that of aerobic lysimeter-A due to the providing of cap liner in anaerobic lysimeter-B and C, played an important role to reduce the percolation of rainwater. The study also reveals that the leachate pollution index (LPI) has decreased in relation to the increasing of elapsed period as well as the LPI for collection system of aerobic lysimeter-A was higher than that of the collection system of anaerobic lysimeter-B and C. Finally, it can be depicted that LPI for lysimeter was significantly high and proper treatment will be necessary before discharging the lysimeter leachate into the water bodies.     

Solid waste bin detection and classification using Dynamic Time Warping and MLP classifier

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.