The infrastructure space is very large with an annual global budget worth trillions of dollars. Sustainable infrastructure is the main underpinning to achieve the United Nations Sustainable Development Goals (SDGs). Thus, infrastructure is the nexus for the successful implementation of the respective SDGs. Sustainability assessment and reporting is a major global paradigm shift in engineering practice, education, research, and development. There are challenges in assessing and reporting infrastructure delivery at local, regional, national, continental, and global levels. These include different methods, frameworks, standards, and tools that compete with each other resulting in current silos-based solutions to the problem. In early October 2023, Members of the European Parliament (MEP) deepened their commitment to align Corporate Social Responsibility Directives (CSRD) and European Sustainability Reporting Standards (ESRD), which is widely seen as a game-changer. Some of the issues and challenges to address in sustainability assessment and reporting include; alignment of processes, moving from generalizations to industry and sector-specific indicators/metrics, understanding the materiality and relevance of items under discourse to employees, end-users, stakeholders and shareholders, risk management including climate change vulnerabilities induced by operations in complex supply chains, integrating disparate systems for use in decision-making, and technological innovations that ensure interoperability at appropriate interfaces. As a baseline, assessment, and reporting should holistically balance Brundtland's foundational triple-bottom-line (i.e. economy, society, and environment), governance, health, and safety amongst others.
The themes of interest in the research topic include:
- Sustainable development - Sustainability engineering - Key performance indicators (KPIs) - Frameworks, methods, models, and tools for sustainability assessment and reporting - Risks and risk management - 3D Concrete printing - Energy efficiency - Resource management - Ontologies - Interoperability - Artificial Intelligence (AI) - Machine Learning (ML) - Natural Language Processing (NLP) - Generative Artificial Intelligence (GenAI)
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