Estimation Of Waste Generation Research Articles

Solid waste characterization and reducing potential at Faculty of Engineering, University of Surabaya

Reducing solid waste generation is one of the green campus achievement programs at the University of Surabaya (Ubaya). It is essential to determine the quantity and composition of all faculty’s solid waste generation. The Faculty of Engineering significantly contributes to the amount of waste generation in Ubaya. Research related to the Faculty of Engineering solid waste characteristics needs to be conducted. The purposes of the study were estimating the quantity of solid waste generation and observing the composition of solid waste at the Faculty of Engineering. The method of this research was a survey of waste generation. The estimation of waste generation was taken for 12 (twelve) days during April 2018. The study results showed that the average solid waste generation faculty of engineering was to be 19.26 kg/day, and the percentage of solid waste was found to be food waste 27%, plastic 25.8%, food packaging 17.6%, Paper 9.8%, and Residue 19.8%.

An overview of factors affecting the rate of generation and Physical Composition of Municipal Solid Waste

An efficient waste management strategy requires a detailed waste characterization, quantification and prediction of the rate of generation and physical components of waste, which is also an index of the recoverable energy. A comprehensive data of waste generation and composition creates awareness for the concerned policy makers and organization responsible for waste management. The objective of studies on estimation of waste generation and physical content is to provide baseline data for effective waste management planning. Several factors account for the variation in the rate of generation and the physical content of waste generated at different places. This study aims at identifying and analyzing some of these factors. The review reveals that waste generation and composition follows different patterns in different places at different locations at different times and season. A major factor that influences the rate of generated waste per year and the percentage composition of each physical waste stream is the socio-economic level. Moreover, the organic stream of the waste depends largely on the income level. High content of organic waste is identified in the low-income region, this paper, therefore, recommends the setting up of treatment facilities for organic waste at the organic-rich region.

Study of household solid waste generation and composition in Medan City, Indonesia; a case study in Medan Labuhan and Medan Tuntungan

This study aims to estimate solid waste generation and its composition of households in Medan City. Medan Labuhan and Medan Tuntungan sub-districts were selected as study area. Data of this study was collected in 2017. The estimation of waste generation was conducted based on Indonesian standard SNI 19-3964-1994. The study found that the household solid waste generation in Medan Labuhan generated 0.233 kg/person/day of solid waste and 0.254 kg/person/day in Medan Tuntungan. The result in composition revealed three main fractions they are 45.2- 52.3% of organic waste, followed by 19.5-23.7% of plastic, 12.513.1% of paper and other fraction such as wood, glass, textile, and metal. This study showed a potential of recyclable materials in the composition of household waste. It is necessary to initiate minimizing of waste generation, reusing, separating, and recycling waste.

Estimation of Waste Generation from Tidal Flood in North Semarang Sub-District

Tidal floods often occur in North Semarang Sub-District due to rising sea levels. One of the impacts is waste generation. Waste management is needed to prevent environmental degradation. An important factor is quantity of waste for the management plan. The purpose of this study to estimate waste generation from tidal floods. Scenario models are needed to find out the area affected because there is no existing data. Scenario data uses DEMNAS, land subsidence data, tidal data, and Sea Level Rise data. The Admiralty method is used to determine the Highest High Water Level (HHWL) value, the quantitative spatial method for the tidal flood scenario and the estimated quantity of waste. Calculation of the HHWL value of 1.16 m is added to the SLR data. The result of tidal flood height is 1.27 m. There are three affected villages (Panggung Lor, Bandarharjo, and Tanjungmas) and affected area is 55.95 Ha. The accuracy rate is 82.86% which is tested using Confusion Matrix. The results of the scenario model are arranged in a grid and then sampled. The estimated waste yield is 70,095.26 kg. The benefits of this data are to facilitate cleaning agent in waste management including cost and technical planning.

A charge model for household waste management services: a case study of Tehran municipality

In practice, it is difficult to implement Pay-As-You-Throw charge systems based on accurate estimates of waste generation. In many cities, this is made impossible, due to lack of technical and administrative infrastructure and cultural considerations, especially in developing countries. This paper presents an alternative two-component charge model that is the combination of cost-accounting technique of Waste Management Services (WMSs) and econometric functions of waste generation. Practical and computation steps considered by the model are presented as a proposal to reform the current system of waste charge in Tehran municipality. The presented model is simple to implement and resolves some of the disadvantages of the traditional methods of waste charge systems, including insufficient revenue to cover the cost of waste management and unfairness related to social inequality.

Modeling Indigenous Footpath and Proximity Cut-off Values for Municipal Solid Waste Management: A Case Study of Ilorin, Nigeria

Indigenous footpaths have been the major means of passage from origin to destination before the advent of cars and town planning. Over the years, these traditional areas have retained their original attributes with additional walking links to the motorable roads. In this study, footpaths to municipal solid waste bins were modelled in order to locate waste bins within an area in Ilorin, north central Nigeria. A network dataset was built in a standard GIS application (ArcMap 10) from the downloaded satellite image of the study area. The Location-Allocation tool in the Network Analyst window was then used to determine the optimal location of facilities based on cut-off walking distance which defines command area of a waste bin. The result of this analysis could act as a decision support tool for the determination of type, size and removal frequency of each waste bin based on estimates of waste generation from each command area.

Estimation of Waste Generation and Recycling Potential from Traditional Market: A Case Study in Hue City, Vietnam

This study was conducted to provide a detailed description of waste generation and characteristics from a traditional market in Hue city, located in central Vietnam. The authors conducted a waste generation survey and a waste composition survey for 309 stalls/vendors in five markets by 17 business categories for 10 consecutive days. The waste generation rates by stall/vendor and by floor area were assessed in three waste categories: general waste, recyclable, and food residues. The general waste that would be sent to a landfill site was classified into 10 physical categories and 77 sub-categories. For general waste, food waste accounted for the largest part, followed by plastic and grass. By multiplying the waste generation rate by stall/vendor by the total number of stall/vendors in 23 markets, the authors estimated the total amounts of general waste, recyclable, food residue and total waste by business category. The total waste generated from market was 17.0 tons/day, of which 4.6 tons (27.1%) were collected by pig farmers for feeding livestock and 0.6 tons (3.6%) were sold to the recycling market. The composting potential accounted for 55.2% of total waste generation from the traditional market in Hue. The recycling potential accounted for 5.1%. The total disposal amount sent to the landfill site would be reduced from 69.2% to 8.8% of the total. The 95% confidence interval (CI) of total waste amount from 23 markets was also estimated using Monte Carlo simulation based on the mean and standard error of the waste generation rate. The range of 95% CI was 14.9 - 18.9 tons/day.

Estimation of waste generation from floods

A framework of correlation for estimating the amount of waste generation from floods is developed. Flood waste data were collected from four recent typhoons in Taiwan. Parameters affecting the flood waste are analyzed. Population density, flooded area and amount of total rainfall are chosen as the correlating parameters for the model development, and regression diagnostics are performed to check the validity of the collected data. The simple linear model is shown to be incapable of correlating the flood waste data. An exponential model is proposed and shown to give acceptable correlation with the flood waste data spanning five orders of magnitude. The model can be useful in the planning of waste cleanup after floods.