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This study will outline progress of an ongoing Teaching and Learning Engineering Innovation project in the Department of Building and Civil Engineering at the Galway-Mayo Institute of Technology, which has employed incremental diffusion approaches to embed sustainability as a core threshold concept across all degree programmes. Phase 1 involved undertaking a curriculum review of all programmes in the Department to identify opportunities to embed sustainability in programme and curriculum design, particularly focusing on constructively aligning learning outcomes, graduate attributes and competences to pedagogy and assessment strategies. This was followed by the design and piloting of a questionnaire survey, which was disseminated to all students within the department to identify pro-environmental attitudes, self-reported behaviours, social and moral norms etc. A reciprocal learning framework encompassing curriculum and pedagogical experimentation, ongoing collaborative industry research on resource efficiency and the circular economy, the ‘living lab’ campus and other initiatives associated with the Green Campus programme is under development in phase 2. This paper will present findings from a selection of experimental interventions tested in phase 1 with students on the B.Sc. in Construction Management and the B.Sc. in Quantity Surveying and Construction Economics where complexity, ‘wickedness’, reflexivity, personal and professional identities and possible futures were debated and discussed. This is informing the development of an educational framework to facilitate a transition within the Department to move from learning ABOUT sustainability (accommodative) using narrow ‘bolt-on’ discipline-specific approaches to learning FOR sustainability (reformative) where the campus operations, curriculum and institute policy begin to be reconceptualised to capacity-building learning AS sustainability (transformative) (Sterling et al., 2013) through experiential learning communities of practice that aim to bring about whole institutional change. no

Aiming towards recommendation of updates to the standards that concern distributed wind systems, this report addresses ‘small’ wind turbines and associated technology, as well as larger turbines not covered by either the small wind or ‘large’ industrial standards. Via previous and ongoing discussions within the International Energy Agency’s Wind Technical Collaboration Program (IEA Wind TCP) and the current task (IEA Task 41), the need for such updates have been identified. Areas of research to support such updates are outlined, based on the joint experiences and interactions between Task 41 members and industry in IEA workshops. Beyond understanding issues with the existing standard, research is needed to document problems and concerns, and justify potential revisions. In the past, targeted research under the IEA Wind TCP produced results for experts to consider when (re-)writing standards, such as the previous (second) revision of the IEC 61400-2 on small wind turbines; here Task 41 also aims to do so. Finally, potential updates are given, as planned for deliverable 1.1 in the (EUDP funded part of the) IEA Task 41 project.

This report describes a simple method for categorizing uncertainties of two key siting parameters,the 50-year wind and the turbulence intensity. The assessment closely follows the methodologiesand data that are used for calculating the two siting parameters. The methodologies are describedin Larsén et al. (2021). This is a simple method in a sense that uncertainty categories are esti-mated, rather than probabilities of targeted parameters. This is seen as a necessary and an efficientapproach for the GASP project, as there are many sources of input data and the quality assess-ment is in general absent or only qualitatively available. In addition, the GASP calculations aredone over the entire globe using one consistent methodology. This methodology, including manylayers of sub-methods, is challenged to different degrees in different areas, due to different flownatures and complexities for modeling. At the same time, the available measurements are toofew to guide us toward a typical uncertainty assessment global-wise. These, altogether, makes itdifficult to quantify the overall effects from the many uncertainty contributors in terms of proba-bilities.The methods for the uncertainty assessment are introduced in Sect. 2 and a presentation of thefinal uncertainty class layer is provided in Sect. 3.