Estimation of E-waste Generation—A Lifecycle-Based Approach

Reshma Roychoudhuri, Biswajit Debnath, Debasree De, Pavel Albores, Chandrima Banerjee, Sadhan Kumar Ghosh

Research output: Chapter in Book/Published conference outputChapter


The problem of e-waste disposal is a very well-known fact, and its generation is increasing exponentially every year. In 2015, 54 million tons of e-waste was generated, whereas it has been predicted that around 50 million tons of e-waste will be generated worldwide by 2018, by the UN report. Another source predicts that e-waste generation will be 72 million tons by 2017. This anomaly exists due to the different methodologies adopted in prediction of e-waste. The most common method used so far to calculate the amount of e-waste generated is as follows. The amount of EEE sold by manufacturers is collected first. The average lifespan of an EEE is known. Thus, applying the average lifespan of the EEE on the amount sold per year, the amount of e-waste is calculated. However, this method is not free from flaws since a sizable portion of the EEE, once the average lifespan is over, does not directly become e-waste. They land in the second-hand market and are resold, and are again used for more number of years. Hence, the process of becoming e-waste for these recycled products is delayed. Once an EEE leaves the Original Equipment Manufacturer (OEM), the lifecycle of an EEE begins. After a certain time of use, the user may discard it for several reasons, which then becomes Used EEE (UEEE). One can exchange this UEEE for a newer and upgraded models (or cash) via authorized or unauthorized resellers, in which case also the UEEE lands up in the second-hand market. The original user can also discard the product completely so that it lands up as e-waste. From the e-waste, precious metals are recovered through recycling process and the discarded parts mostly end up as landfill. In this paper, a model has been proposed based on the lifecycle of EEE. Based on this model, an attempt has been made to predict the amount of e-waste generation in India. Standard data available from the data bank of EU has been used for this purpose. The work has been carried out using Vensim software. The results have been compared with the real-life data.
Original languageEnglish
Title of host publicationWaste Management and Resource Efficiency
Subtitle of host publicationProceedings of 6th IconSWM 2016
EditorsSadhan Kumar Ghosh
ISBN (Electronic)978-981-10-7290-1
ISBN (Print)978-981-10-7289-5
Publication statusPublished - 22 Sept 2018


Dive into the research topics of 'Estimation of E-waste Generation—A Lifecycle-Based Approach'. Together they form a unique fingerprint.

Cite this