Quantification of Goods Purchases and Waste Generation at the Level of Individual Households. (25th February 2014)

• Record Type: Journal Article
• Authors: Harder, Robin; Kalmykova, Yuliya; Morrison, Gregory M.; Feng, Fen; Mangold, Mikael; Dahlén, Lisa
• Is Part Of: Journal of industrial ecology. Volume 18:Number 2(2014)
• Page Start: 227
• Page End: 241
• Publication Date: 2014-02-25
• Subjects: Industrial ecology -- Periodicals; Product life cycle -- Environmental aspects -- Periodicals; Industrial management -- Environmental aspects -- Periodicals; Écologie industrielle -- Périodiques; 658.56
• DOI: 10.1111/jiec.12111
• Languages: English
• ISSNs: 1088-1980

Abstract

<abstract abstract-type="main"> <title>Summary</title> <p>Quantifying differences in resource use and waste generation between individual households and exploring the reasons for the variations observed implies the need for disaggregated data on household activities and related physical flows. The collection of disaggregated data for water use, gas use, electricity use, and mobility has been reported in the literature and is normally achieved through sensors and computational algorithms. This study focuses on collecting disaggregated data for goods consumption and related waste generation at the level of individual households. To this end, two data collection approaches were devised and evaluated: (1) triangulating shopping receipt analysis and waste component analysis and (2) tracking goods consumption and waste generation using a smartphone. A case study on two households demonstrated that it is possible to collect quantitative data on goods consumption and related waste generation on a per unit basis for individual households. The study suggested that the type of data collected can be relevant in a number of different research contexts: eco‐feedback; user‐centered research; living‐lab research; and life cycle impacts of household consumption. The approaches presented in this study are most applicable in the context of user‐centered or living‐lab research. For the other contexts, alternative data sources (e.g., retailers and producers) may be better suited to data collection on larger samples, though at a lesser level of detail, compared with the two data collection approaches devised and evaluated in this study.</p> </abstract>