Literature DB >> 30514461

Changes of waste generation in Australia: Insights from structural decomposition analysis.

He He1, Christian John Reynolds2, Zixiang Zhou3, Yuan Wang4, John Boland5.   

Abstract

Waste generation is linked to consumption both in households (Final demand) and in the supply chain. Gaining understanding into the driving forces that change of waste generation in the supply chain can contribute to solving issues of waste management. The environmentally-extend input-output model is an effective tool with which to investigate the relationship between economic activities and waste generation. In this paper structural decomposition analysis (SDA) is employed to analyse the determinants of changes of waste generation in Australian economy from 2007-2008 to 2013-2014. Empirical results indicate that the major determinant for the increase of waste generation was change in Final demand's overall level of economic activity. Changes in the production mix of Final demand (mix effect) was responsible for a decrease of waste generation in Australian economy during the period. The Manufacturing sector was found to have the highest waste generation intensity. Meaning that each million $AUD output of the Manufacturing sector resulted in the most amount of waste generation. In addition, technological change has contributed the largest waste generation effect for the Construction sector in 2011-2012. These findings suggest that Final demand, technological changes and sectoral changes are identified as the drivers of Australian waste generation historically. To reduce waste generation, policy must be targeted at altering behaviour of consumption and waste generation, and increasing innovation of new ecological technologies for Australian industry.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Keywords:  Input-output analysis; Structural decomposition analysis; Waste generation

Mesh:

Year:  2018        PMID: 30514461     DOI: 10.1016/j.wasman.2018.11.004

Source DB:  PubMed          Journal:  Waste Manag        ISSN: 0956-053X            Impact factor:   7.145


  3 in total

1.  Identifying Driving Factors of Jiangsu's Regional Sulfur Dioxide Emissions: A Generalized Divisia Index Method.

Authors:  Junliang Yang; Haiyan Shan
Journal:  Int J Environ Res Public Health       Date:  2019-10-19       Impact factor: 3.390

2.  Analysis of the drivers of CO2 emissions and ecological footprint growth in Australia.

Authors:  Hasan Rüstemoğlu
Journal:  Energy Effic       Date:  2021-12-23       Impact factor: 2.574

3.  LMDI Decomposition Analysis of E-Waste Generation in the ASEAN.

Authors:  Gobong Choi; Taeyoon Kim; Minchul Kim
Journal:  Int J Environ Res Public Health       Date:  2021-12-06       Impact factor: 3.390

  3 in total

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