Mehdi Ghobadi

In this study, the extent to which selected economic, carbon, and future-climate assumptions influence the performance and composition of Pareto-optimal building retrofit strategies is investigated. A calibrated multi-unit residential building in Winnipeg, Canada, was evaluated using an integrated Honeybee/EnergyPlus–Grasshopper–Wallacei framework. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) was used to simultaneously minimize annual energy use, 30-year Total Cost of Building Ownership (TCBO), and life-cycle carbon emissions. Sensitivity scenarios examined discount rates, material and labor costs, electricity price, grid emission factor, future climate, carbon pricing, and the Social Cost of Carbon. Both Pareto-front displacement and changes in retrofit-variable distributions were quantified to distinguish objective-space from decision-space sensitivity. Results show that the grid emission factor produced the greatest objective-space impact, with normalized Pareto-centroid displacements of 0.207 and 0.201 for the low- and high-emission scenarios, respectively, followed closely by the Social Cost of Carbon (0.202). Future climate produced the largest decision-space response, with a mean retrofit-variable distribution shift of 19.4%, while reducing median energy use, life-cycle carbon, and TCBO by 5.4%, 7.2%, and 8.8%, respectively. Roof insulation was the most assumption-sensitive retrofit variable, exhibiting an average distributional shift of 39.4% and a maximum of 73.3%. In contrast, the lowest infiltration rate was consistently selected across all scenarios, indicating that improved airtightness is a robust and consistently optimal retrofit measure at the building scale. The findings demonstrate that stability of Pareto-objective values does not necessarily imply stability of the underlying retrofit strategy, highlighting the importance of evaluating robustness in both objective and decision spaces.

Computationally efficient building energy models are widely used in retrofit decision making, particularly during early analysis stages where rapid scenario evaluation is required. While previous studies have examined the accuracy trade-offs associated with model simplification, limited attention has been given to how simplified models perform across geographically diverse climate conditions. This study extends earlier work by investigating simplified building energy models across multiple Canadian locations. The selected cities represent a range of climatic conditions, including Ottawa, Toronto, Vancouver, St. John’s, and Edmonton. A dormitory building is used as a consistent case study. Several levels of model abstraction are applied, including thermal zoning aggregation, HVAC system simplification, and material property consolidation. Simplified models are evaluated against a detailed baseline under identical operational assumptions, with climate variation introduced solely through location-specific weather data. The analysis framework is designed to assess how spatial climate differences influence the relative accuracy, robustness, and limitations of simplified model representations under heating-dominated and mixed climate conditions. The study aims to identify patterns in model sensitivity related to climate severity and seasonal variability. It also examines the implications for energy demand estimation and retrofit screening reliability. The outcomes help clarify the appropriate use of simplified models in multi-location retrofit assessments. They also support the development of climate-aware modeling strategies that balance computational efficiency with decision-making reliability.

High-solar-reflectivity cladding materials are widely promoted to reduce cooling demand and mitigate urban heat island effects. However, in cold and mixed climates, their overall energy and carbon performance remains uncertain due to potential winter heating penalties and embodied carbon trade-offs. This study presents a comparative evaluation of energy use, annual operational carbon emissions, and material-level embodied carbon for high-reflectivity cladding applied to commercial buildings across representative Canadian climate zones. Dynamic simulations were conducted in EnergyPlus using a standardized warehouse archetype in Montreal, Toronto, and Vancouver, representing cold continental, mixed continental, and marine climates. Roof and wall solar reflectivity (albedo) was varied from 0.2 (baseline) to 0.8 (high reflectivity), while other envelope properties remained constant. Increasing reflectivity reduced annual cooling demand by approximately 15% in Montreal and Toronto and 20% in Vancouver, with the largest reductions during peak summer periods. However, reduced winter solar heat gains produced heating penalties, increasing total annual energy use by 1% in Montreal, 0.5% in Toronto, and less than 0.5% in Vancouver. Operational greenhouse gas emissions were calculated by converting simulated annual electricity and natural gas use into CO₂-equivalent emissions using provincial grid emission factors and combustion factors consistent with Environment and Climate Change Canada reporting. The results demonstrate the strong influence of regional energy supply on operational carbon outcomes. A cradle-to-gate (A1–A3) life cycle assessment quantified embodied carbon of representative cladding materials using Environmental Product Declarations and North American databases. Embodied carbon varied considerably: product-specific steel cladding manufactured in low-carbon electricity regions showed global warming potential as low as 1.76 kg CO₂e/kg, compared with industry averages exceeding 2.4 kg CO₂e/kg. Rather than performing a complete whole-life carbon assessment, this study comparatively evaluates annual operational carbon emissions and material-level embodied carbon to improve understanding of the energy and carbon implications of high-solar-reflectivity cladding materials in representative Canadian climates. The results demonstrate that climate conditions, envelope thermal performance, regional energy supply, and manufacturing pathways influence the environmental performance of cool envelope strategies.

BIM (building information modeling) is widely recognized for enhancing the efficiency and precision of building energy modeling (BEM), primarily by reducing model development time and improving model accuracy. This paper presents a novel framework leveraging “openBIM” to standardize and harmonize BIM-driven solutions for energy simulations, facilitating comprehensive operational carbon impact assessments. Unlike existing approaches, our framework uniquely integrates information delivery specifications (IDS) with openBIM standards to define the minimum data requirements within the IFC schema, tailored to various levels of development (LOD). This innovation ensures consistent data exchange and interoperability across diverse energy modeling and simulation tools, addressing common challenges of data fragmentation and inaccuracy in operational carbon assessments. By advancing the current state of the art, the proposed framework empowers energy modelers, LCA analysts, and asset managers to streamline IDS implementation, fostering more efficient and reliable construction industry practices. This research thus marks a significant step towards achieving more sustainable building projects through enhanced data-driven insights.

The building sector is crucial in keeping the environment healthy, mainly because of its energy and material usage. Roofs are one of the most important components to consider, as they not only shield the building from the elements but also have a big impact on the environment. The paper provides a state-of-the-art review of the life cycle assessment (LCA) application in the roofing industry. The review examines three main focus areas: (1) LCA of different roofing materials, (2) LCA of roofing systems, and (3) whole-building LCA. Key takeaways from the literature review demonstrate that there is significant variability in LCA methods and impact categories assessed across roofing studies. Only a few studies have explored the complete urban scale in LCA assessments of roofing components. Future research can include utilizing the potential of LCA at urban scales, which can offer a full understanding of the environmental impacts associated with roofing materials in urban settings.