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Can hazardous waste supply chain ‘hotspots’ be identified using an input–output framework?

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  • Court, Christa D.
  • Munday, Max
  • Roberts, Annette
  • Turner, Karen

Abstract

The paper examines a method to attribute hazardous waste streams to regional production and consumption activity, and to connect these same waste streams through to different management options. We argue that a method using an input–output framework provides useful intelligence for decision makers seeking to connect elements of the management of the hazardous waste hierarchy to production and to different patterns and types of final consumption (of which domestic household consumption is one). This paper extends application of conventional demand driven input–output attribution methods to identify hazardous waste ‘hotspots’ in the supply chains of different final consumption goods and consumption groups. Using a regional case study to exposit the framework and its use, we find that domestic government final consumption of public administration production indirectly drives hazardous waste generation that goes to landfill, particularly in the domestic construction and sanitary services sectors, but also in the manufacture of wood products.

Suggested Citation

  • Court, Christa D. & Munday, Max & Roberts, Annette & Turner, Karen, 2015. "Can hazardous waste supply chain ‘hotspots’ be identified using an input–output framework?," European Journal of Operational Research, Elsevier, vol. 241(1), pages 177-187.
    • Handle: RePEc:eee:ejores:v:241:y:2015:i:1:p:177-187
    DOI: 10.1016/j.ejor.2014.08.011
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    References listed on IDEAS

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    Cited by:

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    2. Ghalehkhondabi, Iman & Maihami, Reza & Ahmadi, Ehsan, 2020. "Optimal pricing and environmental improvement for a hazardous waste disposal supply chain with emission penalties," Utilities Policy, Elsevier, vol. 62(C).
    3. Claudia Schilkowski & Manish Shukla & Sonal Choudhary, 2020. "Quantifying the circularity of regional industrial waste across multi-channel enterprises," Annals of Operations Research, Springer, vol. 290(1), pages 385-408, July.
    4. Acquaye, Adolf & Ibn-Mohammed, Taofeeq & Genovese, Andrea & Afrifa, Godfred A & Yamoah, Fred A & Oppon, Eunice, 2018. "A quantitative model for environmentally sustainable supply chain performance measurement," European Journal of Operational Research, Elsevier, vol. 269(1), pages 188-205.
    5. Chunlin Xin & Jie Wang & Ziping Wang & Chia-Huei Wu & Muhammad Nawaz & Sang-Bing Tsai, 2022. "Reverse logistics research of municipal hazardous waste: a literature review," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 1495-1531, February.
    6. Radovan Šomplák & Jiří Kropáč & Jaroslav Pluskal & Martin Pavlas & Boris Urbánek & Petra Vítková, 2022. "A Multi-Commodity Mathematical Modelling Approach—Hazardous Waste Treatment Infrastructure Planning in the Czech Republic," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
    7. Mohammadi, Mehrdad & Jula, Payman & Tavakkoli-Moghaddam, Reza, 2017. "Design of a reliable multi-modal multi-commodity model for hazardous materials transportation under uncertainty," European Journal of Operational Research, Elsevier, vol. 257(3), pages 792-809.
    8. Glenn A. Aguilar-Hernandez & Carlos Pablo Sigüenza-Sanchez & Franco Donati & João F. D. Rodrigues & Arnold Tukker, 2018. "Assessing circularity interventions: a review of EEIOA-based studies," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 7(1), pages 1-24, December.

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