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Urban Scale Modeling & Climate Change

On this Project:

On this Project:

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Rahaf Hasan

PhD Student

Funds:

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This work is funded by the National Science Foundation: 

Collaborative Research: Climate Impacts on the Urban Built Environment (Grant No. 2035150)

Advancing Life Cycle Assessment Methodologies for Building Stocks

Cities worldwide are increasingly vulnerable to climate change, presenting significant challenges to the resilience of the built environment. As buildings must adapt to immediate climate impacts—such as heat waves and intense storms—they also need to mitigate their long-term contributions to climate change. The complexities of energy use patterns, which vary over time due to changing climate conditions and by climate zone, make it essential to assess the sustainability of both adaptation and mitigation strategies. Acknowledging these dynamics is crucial for evaluating the effectiveness of approaches that enhance climate resilience while reducing energy consumption and greenhouse gas emissions.

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Traditional Life Cycle Assessment (LCA) methodologies have been instrumental in evaluating the environmental impacts of buildings. However, many of these approaches adopt a static view, overlooking the dynamic nature of systems over time. This project seeks to address these limitations by developing a dynamic LCA model that integrates climate change scenarios and system dynamics. By doing so, we aim to provide more accurate and actionable insights into sustainable development and policymaking, enabling a comprehensive understanding of how building stocks can adapt to and mitigate the impacts of climate change.

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To achieve this, we are developing an urban-scale dynamic Life Cycle Assessment (LCA) model that incorporates materials, climate change scenarios, and energy source scenarios. Unlike conventional LCA methodologies, which often assume static conditions, our innovative approach integrates dynamic systems thinking to provide more accurate insights into the environmental impacts of buildings over time. This model will facilitate scenario analyses that identify effective pathways for reducing energy consumption and emissions, thereby enhancing climate resilience in urban settings.

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Our approach combines both archetype and building-by-building data aggregation to feed into dynamic energy models and the LCA framework. By analyzing energy usage under varying climate scenarios and energy grid mixes, we can pinpoint sustainability hotspots and assess the effectiveness of different strategies iteratively. Ultimately, this research aims to advance knowledge of sustainable urban resilience strategies and inform policymakers and urban planners, aligning with broader urban climate goals.

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