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The purpose of this study is to investigate and analyse the potential of existing buildings in the UK to contribute to the net-zero emissions target. Specifically, it aims to address the significant emissions from building fabrics which pose a threat to achieving these targets if not properly addressed.

The study, based on a literature review and ten (10) case studies, explored five investigative approaches for evaluating building fabric: thermal imaging, in situ U-value testing, airtightness testing, energy assessment and condensation risk analysis. Cross-case analysis was used to evaluate both case studies using each approach. These methodologies were pivotal in assessing buildings’ existing condition and energy consumption and contributing to the UK’s net-zero ambitions.

Findings reveal that incorporating the earlier approaches into the building fabric showed great benefits. Significant temperature regulation issues were identified, energy consumption decreased by 15% after improvements, poor insulation and artistry quality affected the U-values of buildings. Implementing retrofits such as solar panels, air vents, insulation, heat recovery and air-sourced heat pumps significantly improved thermal performance while reducing energy consumption. Pulse technology proved effective in measuring airtightness, even in extremely airtight houses, and high airflow and moisture management were essential in preserving historic building fabric.

The research stresses the need to understand investigative approaches’ strengths, limitations and synergies for cost-effective energy performance strategies. It emphasizes the urgency of eliminating carbon dioxide (CO₂) and greenhouse gas emissions to combat global warming and meet the 1.5° C threshold.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.

Reflective practice (RP) is a key skill for developing one’s professional practice. It has, however, not been unanimously prioritised in public health (PH) competency and education frameworks. Reflection activities are often unstructured in higher education. There is also a dearth of literature on the RPs of undergraduate PH students. This study aims to explore in greater depth how RP helps undergraduate PH students explore their own learning in internships.

Reflection prompts were designed using the DEAL model. 124 written reflection entries from 32 students were collected and analysed thematically using a deductive-inductive approach. The conceptual framework of internship learning goals by Ash and Clayton (2009) was used to guide the deductive analysis.

Three themes were identified: initial engagement with reflective learning; gradual integration of reflective learning, and a transformative phase involving professional development, personal growth, civic learning, growth through struggle, being confronted with differences in expectations, and skill acquisition.

This study extends the limited evidence regarding RP in undergraduate non-medical PH education, and contributes toward informing the revision of undergraduate PH programmes, for example, by integrating structured reflection earlier in the curricula, and establishing/supporting mentorship programmes between institutions. The findings call for PH educators to be more intentional in creating opportunities to nurture RP among budding PH professionals.