ABSTRACT
Using low-cost feedstocks such as rendered animal fats in biodiesel production willreducebiodieselexpenditures. One of the low-cost feedstocksfor biodiesel production could be the fat extracted from poultry feathers producedin slaughterhouses abundantly. This paper describes a new and environmentally friendly process for developing biodiesel production technology from feather waste produced in poultry industry. In this research the crude oil of poultry feather fat was extracted by soxhlet method using hexane as a solvent. The data resulted from gas chromatography [GC] revealed these percentages for fatty acid compositions: myristic acid [3%], palmitic acid [30%], stearic acid [22%], oleic acid [8.1%], linoleic acid [3%] and arachidonic acid [7%].In this experimental research, the effects of some parameters such as alcohol to oil molar ratio [4:1,6:1, 8:1], catalyst concentration [0.75,1 and 1.25% w/w] and the transesterification reaction time[40,60 andSOmin] on the percentage offatty acids conversioninto methyl ester[biodiesel] are studied. The results show increasing catalyst concentration up to 1% causes the oil to biodiesel conversion percentage having an upward trend and then adownward trend byincreasing catalyst concentration up to 1.25%. With increasing molar ratio from 4:1 to 6:1 and then 8:1, oil to biodiesel conversion percentage increased 16% and2%, respectively. Ultimatelythe optimum point defined by response surface method [RSM] forproducing biodiesel from feather fat is calculated catalyst concentration of 1 wt%, 7.24:1 molar ratio and in 75 minutes resulting in conversion percentage of 97.62
ABSTRACT
Tehran has a population of over 12 million and produces more than 7500 tons of waste every day. Tehran's municipal solid waste is processed and landfilled at Kahrizak disposal center. Due to inappropriate waste management, a lake with a leachate volume of 180,000m3 has been formed. To solve this problem a leachate treatment plant is currently under construction. A byproduct of leachate treatment is biogas. In this study, the feasibility of electricity generation using biogas has been investigated. Considering that 68.81% of the waste is degradable, the produced leachate has a high organic load [COD = 53900 mg/L and BOD = 34400mg/L]. The results showed that a power plant with a capacity of 1.8 MW could be constructed in the site. This electricity can be utilized in Kahrizak Disposal Site and also sold to the network [10 US cents/ kilowatt]. Financial analysis using ProForm software shows 1.3 years of payback period and emission reduction of carbon dioxide equal to 5752 tones/year in comparison with the natural gas power plant. Therefore this project is financially feasible for private investors with internal rate of return equal to 77% or more
ABSTRACT
In this paper different a,lternatives for hospital waste disposal in Karaj are compared with respect to practicability. The objective of this study is to conduct a survey of present practices [e.g. available procedures, techniques, and methods of handling and disposing of hospital waste], and determine the generation rate of hospital wastes. The study was performed in city of Karaj. Karaj is one of the largest cities in the country. There are 11 hospitals in Karaj [8 governmental hospitals and 3 private hospitals] with a total of 1443 active beds. All the hospitals selected for surveying. Several methods were used to collect data. Survey questionnaires were distributed by the author in each hospital. These questionnaires were based on Likert style. The questionnaires contained information regarding the generation of waste and the core aspects of segregation, collection, internal and external storage, transport, treatment, and ultimate disposal. On-site inspections and interviews were conducted by the author after being authorized by hospital management. To support and supplement information collected in the survey, interviews were conducted with the managers responsible for environmental healthcare in each hospital, as well as with all levels of employees who work in collection, handling and disposal of waste within the hospital. SPSS Software program was used to analyze the collected data. One of the first and most important steps in the development of risk or cost analyses in the field of medical waste management involves understanding the generation rates and quantity of the waste that needs to be managed and treated. Waste is produced from the various activities performed in the hospitals. Domestic waste is generated from food preparation, administrative departments, housekeeping and so on. These wastes have the same composition as municipal solid waste and should be segregated correctly and dealt with by the municipal waste disposal system. Infectious waste is a byproduct of diagnostic and experimental activities and therapeutic methods such as surgery, dialysis, biopsies, injections and chemotherapy. The results of the survey indicate that in these hospitals 4505 kg solid waste is produced each day that 46.67% of them were Domestic like waste, 52% was infectious waste and 1.37% was sharp cutting materials. The mean of daily waste generation was 3.12 Kg per active bed. The Domestic like and infectious wastes were not segregated properly
Subject(s)
Waste Management , Medical Waste Disposal , HospitalsABSTRACT
Municipal solid waste [MSW] is the natural result of human activities. MSW generation modeling is of prime importance in designing and programming municipal solid waste management system. This study tests the short-term prediction of waste generation by artificial neural network [ANN] and principal component-regression analysis. Two forecasting techniques are presented in this paper for prediction of waste generation [WG]. One of them, multivariate linear regression [MLR], is based on principal component analysis [PCA]. The other technique is ANN model. For ANN, a feed-forward multi-layer perceptron was considered the best choice for this study. However, in this research after removing the problem of multicolinearity of independent variables by PCA, an appropriate model [PCA-MLR] was developed for predicting WG. Correlation coefficient [R] and average absolute relative error [AARE] in ANN model obtained as equal to 0.837 and 4.4% respectively. In comparison whit PCA-MLR model [R= 0.445, MARE= 6.6%], ANN model has a better results. However, threshold statistic error is done for the both models in the testing stage that the maximum absolute relative error [ARE] for 50% of prediction is 3.7% in ANN model but it is 6.2% for PCA-MLR model. Also we can say that the maximum ARE for 90% of prediction in testing step of ANN model is about 8.6% but it is 10.5% for PCA-MLR model. The ANN model has better results in comparison with the PCA-MLR model therefore this model is selected for prediction of WG in Tehran