This study involves the production of short-chain organic acids from kitchen wastes as intermediates for the production of biodegradable plastics. Flasks, without mixing were used for the anaerobic conversion of the organic fraction of kitchen wastes into short-chain organic acids. The influence of pH, temperature and addition of sludge cake on the rate of organic acids production and yield were evaluated. Fermentations were carried out in an incubator at different temperatures controlled at 30 degrees C. 40 degrees C, 50 degrees C, 60 degrees C and uncontrolled at room temperature. The pH was also varied at pH 5, 6, 7, and uncontrolled pH. 1.0 M phosphate buffer was used for pH control, and 1.0 M HCl and 1.0 M NaOH were added when necessary. Sludge cake addition enhanced the rate of maximum acids production from 4 days to 1 day. The organic acids produced were maximum at pH 7 and 50 degrees C i.e., 39.84 g/l on the fourth day of fermentation with a yield of 0.87 g/g soluble COD consumed, and 0.84 g/g TVS. The main organic acid produced was lactic acid (65-85%), with small amounts of acetic (10-30%), propionic (5-10%), and butyric (5-20%) acids. The results of this study showed that kitchen wastes could be fermented to high concentration of organic acids, which could be used as substrates for the production of biodegradable plastics.
Iron(III)-poly(hydroxamic acid) resin complex has been studied for its sorption abilities with respect to arsenate and arsenite anions from an aqueous solution. The complex was found effective in removing the arsenate anion in the pH range of 2.0 to 5.5. The maximum sorption capacity was found to be 1.15 mmol/g. The sorption selectivity showed that arsenate sorption was not affected by chloride, nitrate and sulphate. The resin was tested and found effective for removal of arsenic ions from industrial wastewater samples.
Composting can potentially remove organic pollutants in sewage sludge. When estimating pollutant removal efficiency, knowledge of estimate uncertainty is important for understanding estimate reliability. In this study the uncertainty (coefficient of variation, CV) in pollutant degradation rate (K1) and relative concentration at 35days of composting (C35/C0) was evaluated. This was done based on recently presented pollutant concentration data, measured under full-scale composting conditions using two different sampling methods for a range of organic pollutants commonly found in sewage sludge. Non-parametric statistical procedures were used to estimate CV values for K1 and C35/C0 for individual pollutants. These were then used to compare the two sampling methods with respect to CV and to determine confidence intervals for average CV. Results showed that sampling method is crucial for reducing uncertainty. The results further indicated that it is possible to achieve CV values for both K1 and C35/C0 of about 15%.
Construction and demolition waste continues to sharply increase in step with the economic growth of less developed countries. Though the construction industry is large, it is composed of small firms with individual waste management practices, often leading to the deleterious environmental outcomes. Quantifying construction and demolition waste generation allows policy makers and stakeholders to understand the true internal and external costs of construction, providing a necessary foundation for waste management planning that may overcome deleterious environmental outcomes and may be both economically and environmentally optimal. This study offers a theoretical method for estimating the construction and demolition project waste generation rate by utilising available data, including waste disposal truck size and number, and waste volume and composition. This method is proposed as a less burdensome and more broadly applicable alternative, in contrast to waste estimation by on-site hand sorting and weighing. The developed method is applied to 11 projects across Malaysia as the case study. This study quantifies waste generation rate and illustrates the construction method in influencing the waste generation rate, estimating that the conventional construction method has a waste generation rate of 9.88 t 100 m(-2), the mixed-construction method has a waste generation rate of 3.29 t 100 m(-2), and demolition projects have a waste generation rate of 104.28 t 100 m(-2).
Malaysia is facing an increasing trend in industrial solid waste generation due to industrial development. Thus, there is a paramount need in taking practical actions and measurements to move toward sustainable industrial waste management. The main aim of this study is to assess practicing solid waste minimization by manufacturing firms. Analysis showed that majority of firms (92%) dispose of their wastes rather than utilize other sustainable waste management options. Also, waste minimization methods such as segregation of wastes, on-site recycle and reuse, improved housekeeping, and equipment modification were found to have significant contribution to waste reduction (p
The present study was undertaken to determine the bacterial agents present in various clinical solid wastes, general waste and clinical sharp waste. The waste was collected from different wards/units in a healthcare facility in Penang Island, Malaysia. The presence of bacterial agents in clinical and general waste was determined using the conventional bacteria identification methods. Several pathogenic bacteria including opportunistic bacterial agent such as Pseudomonas aeruginosa, Salmonella spp., Klebsiella pneumoniae, Serratia marcescens, Acinetobacter baumannii, Staphylococcus aureus, Staphylococcus epidermidis, Enterococcus faecalis, Streptococcus pyogenes were detected in clinical solid wastes. The presence of specific pathogenic bacterial strains in clinical sharp waste was determined using 16s rDNA analysis. In this study, several nosocomial pathogenic bacteria strains of Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, Lysinibacillus sphaericus, Serratia marcescens, and Staphylococcus aureus were detected in clinical sharp waste. The present study suggests that waste generated from healthcare facilities should be sterilized at the point of generation in order to eliminate nosocomial infections from the general waste or either of the clinical wastes.
Presence of fat, oil, and grease (FOG) in wastewater is an ever-growing concern to municipalities and solid-waste facility operators. FOG enters the sewer system from restaurants, residences, and industrial food facilities. Its release into the sewer system results in a continuous build-up that causes eventual blockage of sewer pipes. Several researchers have investigated FOG deposition based on the local conditions of sewers and lifestyle. This paper attempts to review the physical and chemical characteristics of FOG, sources of FOG, and potential chemical and biological reactions of FOG. The effect of the aforementioned factors on the FOG-deposition mechanism is also discussed. Moreover, insight into the current control and treatment methods and potential reuse of FOG is highlighted. It is expected that this review would provide scientists and the concerned authorities a holistic view of the recent researches on FOG control, treatment, and reuse.
Dairy cattle treated wastewaters are potential resources for production of microalgae biofuels. A study was conducted to evaluate the capability of Arthrospira platensis cultivated in dairy farm wastewater for biodiesel production. The biomass of Arthrospira platensis was found to be 4.98 g L-1 and produced 30.23 wt% lipids to dry biomass cultivated in wastewater which was found nitrogen stressed in photo bioreactor. The extracted lipid displayed a suitable fatty acid profile for biodiesel, although the content of linolenic acid was found a little higher than the standard EN14214. It was found that nitrogen stressed medium increase the total lipid content but temperature and intensities of light were the most important factors to control the quantity of linolenic acid and hence the quality of biodiesel, while the optimum CO2 helped to achieve maximum biomass and triacylglycerols. The Arthrospira platensis offer a good option for the treatment of wastewater before final discharge.
Leachate is one of the main surface water pollution sources in Selangor State (SS), Malaysia. The prediction of leachate amounts is elementary in sustainable waste management and leachate treatment processes, before discharging to surrounding environment. In developing countries, the accurate evaluation of leachate generation rates has often considered a challenge due to the lack of reliable data and high measurement costs. Leachate generation is related to several factors, including meteorological data, waste generation rates, and landfill design conditions. The high variations in these factors lead to complicating leachate modeling processes. This study aims at identifying the key elements contributing to leachate production and developing various AI-based models to predict leachate generation rates. These models included Artificial Neural Network (ANN)-Multi-linear perceptron (MLP) with single and double hidden layers, and support vector machine (SVM) regression time series algorithms. Various performance measures were applied to evaluate the developed model's accuracy. In this study, input optimization process showed that three inputs were acceptable for modeling the leachate generation rates, namely dumped waste quantity, rainfall level, and emanated gases. The initial performance analysis showed that ANN-MLP2 model-which applies two hidden layers-achieved the best performance, then followed by ANN-MLP1 model-which applies one hidden layer and three inputs-while SVM model gave the lowest performance. Ranges and frequency of relative error (RE%) also demonstrate that ANN-MLP models outperformed SVM models. Furthermore, low and peak flow criterion (LFC and PFC) assessment of leachate inflow values in ANN-MLP model with two hidden layers made more accurate values than other models. Since minimizing data collection and processing efforts as well as minimizing modeling complexity are critical in the hydrological modeling process, the applied input optimization process and the developed models in this study were able to provide a good performance in the modeling of leachate generation efficiently.
This study was carried out to investigate the physicochemical properties of compost from oil palm empty fruit bunches (EFB) inoculated with effective microorganisms (EM∙1™). The duration of microbial-assisted composting was shorter (∼7 days) than control samples (2 months) in a laboratory scale (2 kg) experiment. The temperature profile of EFB compost fluctuated between 26 and 52 °C without the presence of consistent thermophilic phase. The pH of compost changed from weak acidic (pH ∼5) to mild alkaline (pH ∼8) because of the formation of nitrogenous ions such as ammonium (NH4 (+)), nitrite (NO2 (-)), and nitrate (NO3 (-)) from organic substances during mineralization. The pH of the microbial-treated compost was less than 8.5 which is important to prevent the loss of nitrogen as ammonia gas in a strong alkaline condition. Similarly, carbon mineralization could be determined by measuring CO2 emission. The microbial-treated compost could maintain longer period (∼13 days) of high CO2 emission resulted from high microbial activity and reached the threshold value (120 mg CO2-C kg(-1) day(-1)) for compost maturity earlier (7 days). Microbial-treated compost slightly improved the content of minerals such as Mg, K, Ca, and B, as well as key metabolite, 5-aminolevulinic acid for plant growth at the maturity stage of compost. Graphical Abstract Microbial-assisted composting on empty fruit bunches.