Premium
A new method to estimate the lifetime of long‐life product categories
Author(s) -
Dunant Cyrille F.,
Shah Trishla,
Drewniok Michał P.,
Craglia Matteo,
Cullen Jonathan M.
Publication year - 2021
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1111/jiec.13093
Subject(s) - scrap , identification (biology) , reuse , product (mathematics) , industrial ecology , material flow analysis , computer science , work (physics) , quality (philosophy) , range (aeronautics) , circular economy , risk analysis (engineering) , operations research , environmental economics , business , environmental science , economics , sustainability , engineering , mathematics , ecology , mechanical engineering , philosophy , geometry , epistemology , biology , aerospace engineering , waste management
Increased recycling and reuse rates are a central part of the objectives laid out by the COP21. Nonetheless, the practical implementation of what has been called the circular economy, as well as its true potential, are not easily established. This is because the impact and implementation time scales of any intervention depend on knowing the lifetime of products, which is frequently unknown. This is particularly true in construction, responsible for 39% of worldwide emissions, 11% of which are embodied. Most material flow analysis (MFA) models will simply assume a range of plausible life expectancies when bottom‐up data are lacking. In this work, we propose a novel method of identification using the high quality but highly aggregated trade data available and use it to establish a “mortality curve” for buildings and other long‐lasting products. This identification method is intended to provide more reliable inputs to existing MFA models. It is widely applicable because of the general availability of the underlying data. Using it on United Kingdom trade data, we identify product classes at 1 year for packaging/home scrap, 1 to around 10 years for vehicles/equipment, and around 50 years for construction. The identification approach was then validated by using classical approaches using bottom‐up data for vehicles.