PhD-BPD Dissertation Defense Presentation: Suzy Li
Title: Evaluating Smart Neighborhood Surfaces: Environmental, Social, and Infrastructural Implications for Sustainable Urban Futures
Name: Suzy Li, LEED AP, Ph.D. candidate in Building Performance and Diagnostics (PhD-BPD)
Date: Monday, December 8, 2025
Time: 10:00am-12:00pm ET
Location: Intelligent Workplace (IW) Conference Room, MM 415 & Zoom
Dissertation Committee:
Prof. Vivian Loftness, FAIA, LEED AP (Chair)
University Professor
School of Architecture
Carnegie Mellon University
Kristen Kurland
University Professor
Carnegie Mellon University
Erica Cochran Hameen, Ph.D., Assoc. AIA, NOMA, LEED AP
Associate Professor
School of Architecture
Carnegie Mellon University
Prof. Matthew M. Mehalik, Ph.D.
Executive Director, Breathe Project
Adjunct Faculty, Heinz College, Carnegie Mellon University
Abstract:
Rapid urban development has greatly intensified soil sealing by impervious surfaces, contributing to rising urban temperatures, flooding, and associated health risks. Across U.S. cities, an average of 66% of land cover is now impervious, reaching up to 85% in some areas. The environmental impact of these surfaces is closely tied to their material properties, including reflectivity and porosity. However, comprehensive and comparable data on city surface performance remain limited, and existing studies often focus on single surface types or outcomes. To address this gap, a smart surface taxonomy has been developed, encompassing 50 neighborhood-scale surface types across roofs, streets, sidewalks, and parking lots. Each type is linked to quantified environmental performance indicators such as surface temperature, rainfall retention capacity, and carbon benefits, synthesized from existing literature. Using ESRI ArcGIS Pro, raster imagery and spatial statistical analyses were applied to classify city surface characteristics and examine correlations with environmental and social equity indicators in two case study cities: Pittsburgh and Los Angeles. Results reveal that impervious surfaces cover 55% of Pittsburgh (22% roofs, 30.7% roads, 2.3% parking lots, 52% dark) and 40.2% of Los Angeles (15.7% roofs, 19.4% roads, 5% parking lots, 61% dark). Historically redlined neighborhoods were notably hotter — by 2.6°C in Pittsburgh and 1.99°C in Los Angeles — illustrating the role of surface color and composition in shaping urban heat inequities. The combined analysis of surface characteristics and the Social Vulnerability Index reveals mixed but spatially non-stationary relationships with climate, health, air quality, and housing value indicators, as demonstrated through Generalized Linear Regression and Geographically Weighted Regression. In response, the dissertation introduces a Surface Equity Score (SES) as an evidence-based decision-support tool to identify priority neighborhoods in Pittsburgh and Los Angeles for targeted smart surface interventions. Finally, an application guide on smart sidewalks has been developed to illustrate how these strategies can be implemented in practice, including in the context of emerging EV charging infrastructure along sidewalks. By situating smart surface and smart sidewalk strategies within a methodological framework that combines simulation, quantitative performance assessment, and SES-based prioritization, the dissertation demonstrates a clear pathway from environmental analysis to actionable implementation.