Mass timber construction has recently gained popularity due to its outstanding environmental benefits and building performance, which hold revolutionary potential for the construction industry. However, its impacts from the perspective of occupants have not been thoroughly explored. This study introduces an innovative empirical approach that explores the potential benefits of mass timber construction for individuals and organizations, with an emphasis on the workplace. We review the conceptual framework regarding how visual and physical exposure to timber construction materials and finishes have a positive effect on individuals and organizations at a broad level. We propose a more holistic mixed-method behavioral approach to studying occupant behavior and well-being by integrating self-reported questionnaires, objective biomarkers (heart rate variability and hair cortisol), and indoor environmental quality (IEQ) measures. Our study offers a novel research primer on the exploration of mass timber construction impacts and benefits for both office workers and construction workers. Participants from different office settings completed pre- and post-occupancy evaluation surveys to assess their experiences, including IEQ satisfaction, productivity, and health. Office workers were located in three different offices: a controlled laboratory environment, an open-plan office, and an open-plan space with a timber interior. The construction workers worked in a timber space for three months and then moved to work in a building with a concrete structure. The analysis included descriptive statistics, t-tests, ANOVA, and linear regression to compare differences between office settings and assess the relationship between environmental variables and overall satisfaction in IEQ, comfort, productivity, and health. In office workers, in terms of building image, thermal comfort, and artificial lighting, the data analysis revealed significant differences in occupants’ satisfaction levels between office settings. However, the low number of participants affected the results, and some factors were not found significant in relation to the office setting. Among tradespeople, there was no relationship between the building environment and productivity, health, or comfort. However, the results of hair cortisol testing indicated that working in a timber space can decrease the level of cortisol (stress) and have an impact on the productivity of workers. Such occupant’s perspective research is pivotal to informing policy makers, developers, business owners, construction professionals, timber industry stakeholders, environmentalists, and researchers in their decision-making processes. Fostering the future widespread adoption and advancement of mass timber construction.

Urban building energy models (UBEMs) are key tools for quantifying citywide building energy demand and on-site renewable supply, yet most studies focus on a single city and rely on locally available data under heterogeneous modelling standards, leaving no consistent basis for cross-climate comparison. This study proposes an integrated UBEM framework built on globally accessible open data. A nested pipeline couples microclimate correction with building energy demand and rooftop photovoltaic (PV) potential simulation at the block scale, and is applied to Melbourne, New York, Hong Kong, Helsinki and Dubai to generate a comparable dataset of 1,358 blocks. Across the five cities, the block-level Spearman correlation between energy use intensity (EUI) and PV generation per unit roof area is consistently strong and positive, while the Jaccard overlap between the top 10% hotspots of EUI and PV ranges from 0.23 to 0.65, indicating that local supply and demand can be spatially mismatched at the block level. Three tree-based surrogate models are benchmarked, with XGBoost reaching an R2 of 0.897 for EUI and 0.871 for PV. A global sensitivity analysis based on the Hilbert-Schmidt independence criterion (HSIC) shows that urban morphology dominates both targets in all five cities, while cluster-level rankings reveal within-city heterogeneity. Shapley additive explanations (SHAP) provide directional and per-block attribution; their partial disagreement with HSIC on the EUI ranking highlights a caveat of surrogate-based interpretation. The framework offers a consistent parameter system and an interpretable surrogate for cross-climate UBEM analysis, supporting early screening of demand-supply matching in urban energy planning.

Urban building energy models (UBEMs) are key tools for quantifying citywide building energy demand and on-site renewable supply, yet most studies focus on a single city and rely on locally available data under heterogeneous modelling standards, leaving no consistent basis for cross-climate comparison. This study proposes an integrated UBEM framework built on globally accessible open data. A nested pipeline couples microclimate correction with building energy demand and rooftop photovoltaic (PV) potential simulation at the block scale, and is applied to Melbourne, New York, Hong Kong, Helsinki and Dubai to generate a comparable dataset of 1,358 blocks. Across the five cities, the block-level Spearman correlation between energy use intensity (EUI) and PV generation per unit roof area is consistently strong and positive, while the Jaccard overlap between the top 10% hotspots of EUI and PV ranges from 0.23 to 0.65, indicating that local supply and demand can be spatially mismatched at the block level. Three tree-based surrogate models are benchmarked, with XGBoost reaching an R2 of 0.897 for EUI and 0.871 for PV. A global sensitivity analysis based on the Hilbert-Schmidt independence criterion (HSIC) shows that urban morphology dominates both targets in all five cities, while cluster-level rankings reveal within-city heterogeneity. Shapley additive explanations (SHAP) provide directional and per-block attribution; their partial disagreement with HSIC on the EUI ranking highlights a caveat of surrogate-based interpretation. The framework offers a consistent parameter system and an interpretable surrogate for cross-climate UBEM analysis, supporting early screening of demand-supply matching in urban energy planning.