The Mobility Innovation Center announced that Qing Shen, professor of Urban Design & Planning and an expert in transportation planning and policy, has received a $100,000 award to study commuting patterns and develop a model to understand the effect of telework and flexible scheduling. The project will build off the existing Commute Trip Reduction (CTR) survey for employers who are in the CTR program as required by state law in the central city portion of Seattle. In addition, a complementary…
Research Theme: Climate & Energy
Scholarship on climate change mitigation and adaptation, as well as energy efficiency
Celina Balderas Guzmán
Celina Balderas Guzmán, PhD, is Assistant Professor in the Department of Landscape Architecture. Dr. Balderas’ research spans environmental planning, design, and science and focuses on climate adaptation to sea level rise on the coast and urban stormwater inland. On the coast, her work demonstrates specific ways that the climate adaptation actions of humans and adaptation of ecosystems are interdependent. Her work explores how these interdependencies can be maladaptive by shifting vulnerabilities to other humans or non-humans, or synergistic. Using ecological modeling, she has explored these interdependencies focusing on coastal wetlands as nature-based solutions. Her work informs cross-sectoral adaptation planning at a regional scale.
Inland, Dr. Balderas studies urban stormwater through a social-ecological lens. Using data science and case studies, her work investigates the relationship between stormwater pollution and the social, urban form, and land cover characteristics of watersheds. In past research, she developed new typologies of stormwater wetlands based on lab testing in collaboration with environmental engineers. The designs closely integrated hydraulic performance, ecological potential, and recreational opportunities into one form.
Her research has been funded by major institutions such as the National Science Foundation, National Socio-Environmental Synthesis Center, UC Berkeley, and the MIT Abdul Latif Jameel Water and Food Systems Lab. She has a PhD in the Department of Landscape Architecture and Environmental Planning from the University of California, Berkeley. Previously, she obtained masters degrees in urban planning and urban design, as well as an undergraduate degree in architecture all from MIT.
Narjes Abbasabadi
Narjes Abbasabadi, Ph.D., is an Assistant Professor in the Department of Architecture at the University of Washington. Dr. Abbasabadi also leads the Sustainable Intelligence Lab. Abbasabadi’s research centers on sustainability and computation in the built environment. Much of her work focuses on advancing design research efforts through developing data-driven methods, workflows, and tools that leverage the advances in digital technologies to enable augmented intelligence in performance-based and human-centered design. With an emphasis on multi-scale exploration, her research investigates urban building energy flows, human systems, and environmental and health impacts across scales—from the scale of building to the scale of neighborhood and city.
Abbasabadi’s research has been published in premier journals, including Applied Energy, Building and Environment, Energy and Buildings, Environmental Research, and Sustainable Cities and Society. She received honors and awards, including “ARCC Dissertation Award Honorable Mention” (Architectural Research Centers Consortium (ARCC), 2020), “Best Ph.D. Program Dissertation Award” (IIT CoA, 2019), and 2nd place in the U.S. Department of Energy (DOE)’s Race to Zero Design Competition (DOE, 2018). In 2018, she organized the 3rd IIT International Symposium on Buildings, Cities, and Performance. She served as editor of the third issue of Prometheus Journal, which received the 2020 Haskell Award from AIA New York, Center for Architecture.
Prior to joining the University of Washington, she taught at the University of Texas at Arlington and the Illinois Institute of Technology. She also has practiced with several firms and institutions and led design research projects such as developing design codes and prototypes for low-carbon buildings. Most recently, she practiced as an architect with Adrian Smith + Gordon Gill Architecture (AS+GG), where she has been involved in major projects, including the 2020 World Expo. Abbasabadi holds a Ph.D. in Architecture from the Illinois Institute of Technology and Master’s and Bachelor’s degrees in Architecture from Tehran Azad University.
The Influence of Street Environments on Fuel Efficiency: Insights from Naturalistic Driving
Wang, X.; Liu, C.; Kostyniuk, L.; Shen, Q.; Bao, S. (2014). The Influence of Street Environments on Fuel Efficiency: Insights from Naturalistic Driving. International Journal Of Environmental Science And Technology, 11(8), 2291 – 2306.
Abstract
Fuel consumption and greenhouse gas emissions in the transportation sector are a result of a three-legged stool: fuel types, vehicle fuel efficiency, and vehicle miles travelled (VMT). While there is a substantial body of literature that examines the connection between the built environment and total VMT, few studies have focused on the impacts of the street environment on fuel consumption rate. Our research applied structural equation modeling to examine how driving behaviors and fuel efficiency respond to different street environments. We used a rich naturalistic driving dataset that recorded detailed driving patterns of 108 drivers randomly selected from the Southeast Michigan region. The results show that, some features of compact streets such as lower speed limit, higher intersection density, and higher employment density are associated with lower driving speed, more speed changes, and lower fuel efficiency; however, other features such as higher population density and higher density of pedestrian-scale retails improve fuel efficiency. The aim of our study is to gain further understanding of energy and environmental outcomes of the urban areas and the roadway infrastructure we plan, design, and build and to better inform policy decisions concerned with sustainable transportation.
Keywords
Travel; Consumption; Emissions; Cities; Energy; Street Environments; Fuel Efficiency; Structural Equation Modeling; Naturalistic Driving
Activity-Based Life Cycle Analysis of a Curtain Wall Supply for Reducing Its Environmental Impact
Yi, June-seong; Kim, Yong-woo; Lim, Ji Youn; Lee, Jeehee. (2017). Activity-Based Life Cycle Analysis of a Curtain Wall Supply for Reducing Its Environmental Impact. Energy And Buildings, 138, 69 – 79.
Abstract
Life-Cycle Assessment has been used extensively in the construction industry to assess the environmental impacts of building materials. Attributional LCA considers processes in a supply chain which allows users to identify a process to improve to minimize the environmental impacts. However, the level of detail adopted in traditional attributional LCA is aggregate, not appropriate for process improvement efforts in the construction project context which is characterized as a complex system. This paper proposes Activity-based LCA (ABLCA) which adopts the methodology of the activity-based costing system to carry out the assessment and analysis of environmental impacts for the life cycle. The research carried out a case study on the curtain wall supply chain. The outcome of inventory analysis for each activity and environmental impact assessment showed the curtain wall supply chain process made an impact on five environmental impact categories: global warming air, acidification air, HH criteria air; eutrophication air, and photochemical smog air. With comparison to the outcome of environmental impact assessment from existing LCA, the proposed management system to investigate environmental impacts was addressed. The proposed ABLCA enables management to develop an environmental-impacts-reduction plan focusing on critical activities. (C) 2016 Elsevier B.V. All rights reserved.
Keywords
Construction Industry & The Environment; Energy Conservation In Construction Industry; Building Materials & The Environment; Complexity (philosophy); Global Warming & The Environment; Activity-based Management; Attributional Lca (life-cycle Assessment); Curtain Wall; Environmental Impacts; Activity-based Life Cycle Analysis; Ablca; Construction Industry; Building Materials; Inventory Analysis; Life-cycle Assessment; Environmental Impact Categories; Curtain Wall Supply Chain Process; Environmental Impact Assessment; Environmental-impacts-reduction Plan; Environmental Factors; Inventory Management; Life Cycle Costing; Product Life Cycle Management; Supply Chain Management; Walls; United-states; Performance; Buildings; Energy; Trends; Lca; Environmental Impact; Supply Chains; Environmental Assessment; Construction Materials; Life Cycle Engineering; Eutrophication; Life Cycle Analysis; Construction; Climate Change; Global Warming; Smog; Life Cycle Assessment; Case Studies; Cost Analysis; Acidification; Photochemical Smog; Environmental Management; Life Cycles
Application of Prevention Through Design (PTD) to Improve the Safety of Solar Installations on Small Buildings
Ho, Chung; Lee, Hyun Woo; Gambatese, John A. (2020). Application of Prevention Through Design (PTD) to Improve the Safety of Solar Installations on Small Buildings. Safety Science, 125.
Abstract
As a viable, clean and renewable energy resource, solar energy has gained a significant interest in the US residential sector. Most solar systems are installed on rooftops to take advantage of available space and reduce land use. However, this installation environment also exposes workers to unique safety hazards related to existing roof conditions such as slippery roofing materials, irregular roof layouts, and steep roof slopes. Although Prevention through Design (ND) has been widely considered as an effective way to address safety issues during the design phase, little to no studies have applied ND to improve safety in solar energy installations. To fill this knowledge gap, this research aimed to investigate how, during the design phase, to address the safety concerns of solar workers when installing solar energy systems on residential buildings. Through a series of interviews, four case studies, and a seminar, seven solar ND attributes were identified: roofing materials, roof slopes, roof accessories, panel layouts, fall protection systems, lifting methods and electrical systems. Based on the attributes, a ND protocol was developed that can serve as guidance for implementing ND in solar installations. This paper presents the research activities and findings, and feedback gained from solar contractors through a seminar on the study. The study is expected to contribute to reducing safety hazards by implementing ND, help improve safety performance in solar installations on small residential buildings and support the promotion of safety in sustainable construction.
Keywords
Roofing Materials; Renewable Energy Sources; Sustainable Construction; Solar Energy; Clean Energy; Construction Safety; Prevention Through Design; Small Buildings; Solar Installations; Buildings (structures); Construction Industry; Hazards; Occupational Safety; Roofs; Safety; Solar Power; Sustainable Development; Steep Roof Slopes; Design Phase; Solar Energy Installations; Solar Workers; Installing Solar Energy Systems; Residential Buildings; Seven Solar Ptd Attributes; Roof Accessories; Ptd Protocol; Solar Contractors; Safety Performance; Viable Energy Resource; Clean Energy Resource; Renewable Energy Resource; Us Residential Sector; Solar Systems; Installation Environment; Unique Safety Hazards; Roof Conditions; Slippery Roofing Materials; Irregular Roof Layouts; Issues; Accident Prevention; Protocol; Energy Sources; Residential Areas; Land Use; Prevention; Design; Falls; Occupational Hazards; Contractors; Residential Energy; Protection Systems; Renewable Energy; Buildings; Roofing; Layouts
Does Polycentric Development Produce Less Transportation Carbon Emissions? Evidence from Urban Form Identified by Night-Time Lights Across US Metropolitan Areas
Jung, Meen Chel; Kang, Mingyu; Kim, Sunghwan. (2022). Does Polycentric Development Produce Less Transportation Carbon Emissions? Evidence from Urban Form Identified by Night-Time Lights Across US Metropolitan Areas. Urban Climate, 44.
Abstract
Identifying the comprehensive metropolitan urban form is important to propose effective policies to mitigate transportation carbon emissions. A publicly accessible night-time light dataset was used to identify urban centers and develop two polycentric indices to compute the composition and configuration of urban form, respectively. We used the most populous 103 U.S. metropolitan statistical areas (MSAs), with their corresponding transportation carbon emissions, polycentric indices, population sizes, gross domestic product (GDP) per capita, and road network densities. We first explored the typology of urban form and classified MSAs into six types based on two polycentric indices. We then introduced correlation analysis and statistical models to test the relationships between polycentric urban form and transportation carbon emissions. We found: (1) more urban centers lead to more emissions (compositional dimension), (2) more spatially distributed urban centers result in less emissions (configurational dimension), and (3) population and GDP per capita are positively related to carbon emissions. These findings suggest the importance of measuring two polycentric dimensions separately but using them together. Urban planners should consider mixed strategies that combine the traditional intra-center-based smart growth principles and the metropolitan-level inter-centers spatial plan to effectively counteract climate change.
Keywords
Polycentric Urban Form; Urban Centers; Carbon Emissions; Night-time Lights; Smart Growth; Climate Change; Co2 Emissions; Spatial Structure; Satellite Imagery; Cities; Patterns; Trends; Growth; Determinants; China
Eco-Evolutionary Dynamics in an Urbanizing Planet
Alberti, Marina. (2015). Eco-Evolutionary Dynamics in an Urbanizing Planet. Trends In Ecology & Evolution, 30(2), 114 – 126.
Abstract
A great challenge for ecology in the coming decades is to understand the role humans play in eco-evolutionary dynamics. If, as emerging evidence shows, rapid evolutionary change affects ecosystem functioning and stability, current rapid environmental change and its evolutionary effects might have significant implications for ecological and human wellbeing on a relatively short time scale. Humans are major selective agents with potential for unprecedented evolutionary consequences for Earth's ecosystems, especially as cities expand rapidly. In this review, I identify emerging hypotheses on how urbanization drives eco-evolutionary dynamics. Studying how human-driven micro-evolutionary changes interact with ecological processes offers us the chance to advance our understanding of eco-evolutionary feedbacks and will provide new insights for maintaining biodiversity and ecosystem function over the long term.
Keywords
Biological Evolution; Urbanization; Climate Change; Ecosystems; Well-being; Co-evolution; Eco-evolutionary Dynamics; Ecosystem Function; Urban Ecosystems; Ecological Consequences; Phenotypic Plasticity; Rapid Evolution; Regime Shifts; Elevated Co2; Biodiversity; Selection; Community; Patterns
Lighting Energy Consumption in Ultra-Low Energy Buildings: Using a Simulation and Measurement Methodology to Model Occupant Behavior and Lighting Controls
Zhu, Panyu; Gilbride, Michael; Yan, Da; Sun, Hongshan; Meek, Christopher. (2017). Lighting Energy Consumption in Ultra-Low Energy Buildings: Using a Simulation and Measurement Methodology to Model Occupant Behavior and Lighting Controls. Building Simulation, 10(6), 799 – 810.
Abstract
As building owners, designers, and operators aim to achieve significant reductions in overall energy consumption, understanding and evaluating the probable impacts of occupant behavior becomes a critical component of a holistic energy conservation strategy. This becomes significantly more pronounced in ultra-efficient buildings, where system loads such as heating, cooling, lighting, and ventilation are reduced or eliminated through high-performance building design and where occupant behavior-driven impacts reflect a large portion of end-use energy. Further, variation in behavior patterns can substantially impact the persistence of any performance gains. This paper describes a methodology of building occupant behavior modeling using simulation methods developed by the Building Energy Research Center (BERC) at Tsinghua University using measured energy consumption data collected by the University of Washington Integrated Design Lab (UW IDL). The Bullitt Center, a six-story 4831 m(2) (52,000 ft(2)) net-positive-energy urban office building in Seattle, WA, USA, is one of the most energy-efficient buildings in the world (2013 WAN Sustainable Building of the Year Winner). Its measured energy consumption in 2015 was approximately 34.8 kWh/(m(2)a (TM) yr) (11 kBtu/(ft(2)a (TM) yr)). Occupant behavior exerts an out-sized influence on the energy performance of the building. Nearly 33% of the end-use energy consumption at the Bullitt Center consists of unregulated miscellaneous electrical loads (plug-loads), which are directly attributable to occupant behavior and equipment procurement choices. Approximately 16% of end-use energy is attributable to electric lighting which is also largely determined by occupant behavior. Key to the building's energy efficiency is employment of lighting controls and daylighting strategies to minimize the lighting load. This paper uses measured energy use in a 330 m(2) (3550 ft(2)) open office space in this building to inform occupant profiles that are then modified to create four scenarios to model the impact of behavior on lighting use. By using measured energy consumption and an energy model to simulate the energy performance of this space, this paper evaluates the potential energy savings based on different occupant behavior. This paper describes occupant behavior simulation methods and evaluates them using a robust dataset of 15 minute interval sub-metered energy consumption data. Lighting control strategies are compared via simulation results, in order to achieve the best match between occupant schedules, controls, and energy savings. Using these findings, we propose a simulation methodology that incorporates measured energy use data to generate occupant schedules and control schemes with the ultimate aim of using simulation results to evaluate energy saving measures that target occupant behavior.
Keywords
Control-systems; Patterns; Offices; Lighting Control; Ultra-low Energy Building; Occupant Behavior; Building Simulation; Energy Consumption
Residential Building Lifespan and Community Turnover
Ianchenko, Alex; Simonen, Kathrina; Barnes, Clayton. (2020). Residential Building Lifespan and Community Turnover. Journal Of Architectural Engineering, 26(3).
Abstract
Environmental impact studies within the built environment rely on predicting building lifespan to describe the period of occupation and operation. Most life cycle assessments (LCAs) are based on arbitrary lifespan values, omitting the uncertainties of assessing service life. This research models the lifespan of American residential housing stock as a probabilistic survival distribution based on available data from the American Housing Survey (AHS). The log-normal, gamma, and Weibull distributions were fit to demolition data from 1985 to 2009 and these three models were compared with one another using the Bayesian information criterion. Analysis revealed that the estimated average housing lifespan in the United States is 130 years given model assumptions, although a probabilistic approach to lifespan can yield higher accuracy on a case-by-case basis. Parameters for modeling housing lifespan as log-normal, gamma, and Weibull survival functions are published with the intent of further application in LCA. The application of probabilistic housing lifespan models to community-wide turnover and integration with existing simulations of natural disaster are proposed as potential ways to achieve community sustainability and resilience goals. (c) 2020 American Society of Civil Engineers.
Keywords
Energy-consumption; Service Life; Cycle; Demolition; Emissions; Design; Impact; Model; Housing Stock Lifetime; Residential Buildings; Housing Turnover; Life Cycle Assessment; Service Life Prediction