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<p>Operational life cycle assessments (LCAs) of campus buildings often use static electricity backgrounds, under-specified scenarios, and limited uncertainty treatment, reducing their usefulness for routine decarbonisation decisions. This study presents a prospective, attributional, location-based workflow for annual building operations. The case study is the Advanced Engineering Building at the University of Queensland, and the functional unit is one building-year. A 2 × 2 scenario design compares two factors: the electricity background (current Queensland mix versus Queensland-2050) and municipal solid-waste diversion (approximately 64% versus 77%). Operational greenhouse gas impacts are quantified in openLCA as 100-year global warming potential (GWP100; hereafter GWP) using the Australian Life Cycle Inventory database (AusLCI) and the Intergovernmental Panel on Climate Change (IPCC) 2013 method. A lightweight Brightway2 metamodel supports paired contrasts using common random numbers (CRNs) and sensitivity screening. The workflow can be understood as an auditable lifecycle-scenario layer linking a fixed foreground to versioned backgrounds rather than as a cyber-physical twin. Electricity dominates annual operational GWP, and replacing the current electricity background with Queensland-2050 reduces it by about 47%. By contrast, increasing diversion reduces annual operational GWP by only about 5.3 t CO<sub>2</sub>-eq&#xa0;yr⁻<sup>1</sup>. Sensitivity analysis identifies energy use intensity (EUI) as the dominant driver of variance, whereas waste-related inputs remain minor within the stated scope. The workflow supports repeatable building-level reporting for operators, campus sustainability managers, energy procurement teams, and policy stakeholders. It is reusable across comparable institutional buildings and reporting years.</p>

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Prospective operational life cycle assessment of energy and waste systems in a university building: an auditable workflow using openLCA and Brightway2

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月20日

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  • Siyou Wang,
  • Anthony Halog

摘要

Operational life cycle assessments (LCAs) of campus buildings often use static electricity backgrounds, under-specified scenarios, and limited uncertainty treatment, reducing their usefulness for routine decarbonisation decisions. This study presents a prospective, attributional, location-based workflow for annual building operations. The case study is the Advanced Engineering Building at the University of Queensland, and the functional unit is one building-year. A 2 × 2 scenario design compares two factors: the electricity background (current Queensland mix versus Queensland-2050) and municipal solid-waste diversion (approximately 64% versus 77%). Operational greenhouse gas impacts are quantified in openLCA as 100-year global warming potential (GWP100; hereafter GWP) using the Australian Life Cycle Inventory database (AusLCI) and the Intergovernmental Panel on Climate Change (IPCC) 2013 method. A lightweight Brightway2 metamodel supports paired contrasts using common random numbers (CRNs) and sensitivity screening. The workflow can be understood as an auditable lifecycle-scenario layer linking a fixed foreground to versioned backgrounds rather than as a cyber-physical twin. Electricity dominates annual operational GWP, and replacing the current electricity background with Queensland-2050 reduces it by about 47%. By contrast, increasing diversion reduces annual operational GWP by only about 5.3 t CO2-eq yr⁻1. Sensitivity analysis identifies energy use intensity (EUI) as the dominant driver of variance, whereas waste-related inputs remain minor within the stated scope. The workflow supports repeatable building-level reporting for operators, campus sustainability managers, energy procurement teams, and policy stakeholders. It is reusable across comparable institutional buildings and reporting years.