A Method for Assessing the Risks to Sustainability Posed by Process Operations
Bibliographic Data
| ID | 12307175 |
|---|---|
| Authors | Richard C Darton (0000-0003-1381-6693, Department of Engineering Science University of Oxford Oxford UK), Colin J Axon (0000-0002-9429-8316, Department of Engineering Brunel University of London London UK, corresponding author) |
| Year | 2025 |
| Volume | 34 |
| Issue | 2 |
| Pages | 1719-1733 |
| Publication date | 2025-11-12 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sustainable Development (JOURNAL) |
| Journal identifiers | ISSN: 0968-0802 • E-ISSN: 1099-1719 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/sd.70423 |
| OpenAlex | W4416205511 |
| Language | EN |
| References cited | 43 |
We present a framework for assessing the risks to sustainability posed by any given set of processes. The objective is to improve sustainability by enabling better decision‐making in policy and business contexts. The framework can be applied to any system of processes where available information supports discovery and quantification of sustainability‐risk, defined as risk to the ability of future generations to meet their needs. Processes are screened to identify sustainability‐risks, which are scored on a common scale to avoid arbitrary weighting factors. The method yields an overall risk score for the system, and an analysis of where and how sustainability‐risk arises. We demonstrate the method by applying it to the system that provides for the UK's production and use of liquid biofuels. A set of 18 distinct causes of risk is discovered, and impacts are assessed by triple‐bottom line accounting. The innovation risk optimism bias is the highest‐scoring cause of risk, followed by price volatility associated with competition between markets for bio‐feedstocks. In this case, the wide variety of risk types and severity, and scale of action, suggests that promoting sustainability requires a tailored response to address specific risks
Process (computing · Risk management · Scale (ratio · Set (abstract data type · Sustainability · Variety (cybernetics · Weighting · Agriculture Sustainability and Environmental Impact · Bioeconomy and Sustainability Development · Food Waste Reduction and Sustainability
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| Highly cited | No |
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