A Framework for Sustainable Passive Architectural Adaptation in Urban Housing

Thesis Abstract

Urban housing globally faces intensifying energy costs and climate-related thermal discomfort, highlighting the need for scalable, low-energy, climate-responsive design approaches that can adapt to diverse social, economic, and urban contexts. This study develops a framework for sustainable passive architectural adaptation (SPAA) in urban housing by integrating passive design strategies with context-sensitive decision-making to optimize energy performance, occupant comfort, and retrofit feasibility. The aim is to create a theoretically grounded yet practically deployable framework that guides designers, policymakers, and developers toward passive strategies that are robust to climate variability and urban constraints. Specific objectives are (i) to conceptualize a framework that links climate-responsive passive design strategies with urban housing typologies and retrofit pathways; (ii) to identify contextual determinants—climatic, material, socio-economic, and regulatory—that influence the adoption and effectiveness of passive adaptation measures; (iii) to develop decision-support tools that quantify trade-offs between embodied energy, operating energy, and occupant comfort across different urban housing sectors; (iv) to validate the framework through empirical assessment of existing urban housing projects in three metropolitan contexts; and (v) to formulate implementation guidelines and policy recommendations for scaling passive adaptation in dense urban neighborhoods. The methodology adopts a mixed-methods, multi-scalar design anchored in theoretical constructs from Passive House principles, bioclimatic design, and the socio-technical transition theory. The research comprises three sequential phases. Phase I is a theory-driven synthesis combining a systematic literature review and a comparative analysis of 60 urban housing case studies to identify effective passive strategies and contextual drivers, employing thematic synthesis and GIS-based spatial analysis. Phase II operationalizes SPAA into a computable decision-support model, integrating thermal simulations (EnergyPlus), daylighting analysis ( Radiance), and multi-criteria decision analysis (MCDA) to evaluate 120 hypothetical retrofit scenarios across representative urban housing typologies. Phase III provides empirical validation through field surveys and instrumented monitoring of 30 residential units across three cities, using calibrated data loggers for interior temperature and humidity, occupant surveys (n=360), and interviews with architects, developers, and local authorities (n=40). The population includes urban apartment blocks and terraced houses constructed from conventional materials within temperate to hot-humid climates. Sampling combines stratified random sampling for occupant surveys and purposive sampling for stakeholder interviews. Instrument validity and reliability are established through pilot testing, Cronbach’s alpha for survey scales, and triangulation with archival records and design documents. Data analysis employs descriptive statistics and inferential techniques including multiple regression to identify predictors of thermal comfort and energy performance, ANOVA to compare performance across typologies and climates, and structural equation modeling to test the proposed conceptual links within SPAA. The modelling component leverages a life-cycle assessment (LCA) to evaluate embodied versus operational energy across retrofit options, and a sensitivity analysis to examine uncertainty in material choices and climate projections. The study grounds the framework in the theoretical underpinnings of bioclimatic architecture, the Passive House standard, and the socio-technical transition framework to elucidate adoption dynamics and governance implications. Expected findings indicate that SPAA can substantially reduce operational energy consumption by 20–40% in retrofit scenarios without compromising occupant comfort, with greater gains in dense urban forms where shading, ventilation, and thermal mass are optimized in concert with building envelope improvements. The research anticipates identifying a core set of context-adaptive passive strategies (e.g., enhanced natural ventilation with airtight enclosure, solar shading optimization, thermal mass integration, and daylighting discipline) and a decision-support toolkit that enables stakeholders to tailor interventions to climate, occupancy patterns, and municipal regulations. Contributions to knowledge include (i) a transferable, theory-informed framework for sustainable passive adaptation in urban housing, (ii) an integrated methodological approach combining simulation, empirical validation, and MCDA for retrofit decision-making, and (iii) policy-oriented guidelines for scaling passive approaches within urban fabric and regulatory systems. The study concludes that sustainable passive adaptation is feasible at scale when design decisions are embedded within a robust framework that accounts for climate, urban form, occupancy, and governance, and recommends advancing performance verification protocols, standardizing retrofit data sharing, and adopting SPAA-guided criteria in zoning and building codes to accelerate adoption.