Urban Systems Dynamics

2011-2012

Research Activities
Society’s response to climate change, in the form of adaptation decisions, affects urban systems by making cities more or less resilient, distributing risk, and altering the trajectory of the economy. Urban system dynamics research at DCDC investigates interrelationships of climate, water, and urban form and implications for decision making under uncertainty and urban climate adaptation.

In recent work, DCDC post-doctoral scholar Ariane Middel, in collaboration with Anthony Brazel, Chris Martin, Subhrajit Guhathakurta (now with Georgia Tech), and Ph.D. student Kathrin Häb (University of Kaiserslautern, Germany) examined how microclimate varies with urban form and land cover. This research seeks to identify the most effective urban form and design strategies to reduce residential energy and water use during the summer months. Taking advantage of the North Desert Village experimental neighborhood (associated with CAP LTER) at Arizona State University’s Polytechnic campus as a test bed, they simulated microclimatic conditions for four residential landscape designs (native, xeric, oasis, mesic) using the ENVI-met model. In addition, they developed six urban form scenarios representing a cross-section of typical residential neighborhoods in Phoenix in terms of building density and characteristics. Combined ENVI-met model runs of urban form and landscaping scenarios will give insight into potential mitigation and adaptation strategies against UHI effects at a micro-scale. Finally, the team will run eQuest for the combined scenarios using ENVI-met model outputs as boundary conditions to assess the effect of urban form and design on building energy use. Preliminary results will be presented at the 8th International Conference on Urban Climate (ICUC8) to be held in Dublin in August 2012.

In their ongoing NOAA-funded collaboration with Portland State University, Patricia Gober, Ariane Middel, Anthony Brazel, and Soe Myint explored the tradeoff between outdoor water use and temperature amelioration in Portland and Phoenix (Gober et al. in press, Urban Geography). This case study is an extension of last year’s effort (Middel et al. in press, International Journal of Climatology) that investigated how land cover alterations change the surface energy balance and create distinct urban climates. Again, the team used the Local-Scale Urban Meteorological Parameterization Scheme (LUMPS) to quantify the relationship between the amount of vegetation, resulting outdoor water use, daytime heating and nighttime cooling, and subsequent cooling efficiency of water during hot, dry summer months (June in Phoenix, July in Portland). Furthermore, they analyzed tradeoffs in both cities under three land use scenarios (green city, xeriscaping, and densification) and three climate change scenarios.

In another recently completed study involving the LUMPS model, Ariane Middel and colleagues investigated the daytime cooling efficiency of various land cover in Phoenix (Middel et al. in press, Climate Research). The team simulated the hourly urban energy balance for two hot summer days for 11,025 90 x 90m grid cells in the urban core. They evaluated the modeling results using surface temperatures from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery and reference evapotranspiration values from a meteorological station in the study area. To examine the cooling-water use tradeoff of different land cover configurations, the team adopted a cooling efficiency measure based on sensible and latent heat flux differences. They also determined the time of sensible heat flux transition (time when the sensible heat flux turns negative) for each grid cell to investigate the sensible heat reversal at night.

Research Findings
Tradeoffs between Water Use, Land Cover, and Urban Heat
Patricia Gober, Ariane Middel, Anthony Brazel, and Soe Myint and colleagues from Portland State University investigated a pressing urban sustainability question: how do land cover characteristics and climate affect urban heating and outdoor water use? The team developed three land-cover and climate scenarios each for Phoenix and Portland, and used the LUMPS model to simulate the urban energy balance. Gober et al. (in press, Urban Geography) report model outcomes showing that reduced vegetation cover decreases outdoor water use, but increases urban heating at night in both cities. Both water use and nighttime urban cooling seem to be less sensitive to climate than to land-use. Study results further indicate that a densification of the study areas, i.e. substituting impervious surfaces with buildings, is the most efficient cooling strategy.

DCDC post-doctoral scholar Ariane Middel, Anthony Brazel, Shai Kaplan, and Soe Myint used the LUMPS model to systematically analyze the daytime trade-off between water demand of various landscapes in Phoenix and the amount of cooling achieved (Middel et al. in press, Climate Research). Results of this tradeoff study indicate that the high heat storage capacity of impervious surfaces delays the sensible heat flux reversal at night up to three hours. Areas in Phoenix with high impervious cover and little vegetation (e.g., industrial sites) have negative cooling efficiencies. Overall, the urban core in Phoenix is slightly more cooling efficient than the Sonoran desert, but efficiencies do not improve much with vegetation fractions above 20%. Simulation results suggest that heterogeneous neighborhoods with drier landscaping are the best landscapes to balance cooling and water use in Phoenix. However, this tradeoff needs to be further investigated considering other factors, such as human vulnerability and energy use, particularly in the face of a changing climate.

2010-2011

Research Activities
Urban planner Subhrajit Guhathakurta led a team that included engineer Eric Williams, DCDC II postdoc Ariane Middel, and several graduate students, to develop a dynamic network model to examine trends in energy use and carbon emissions associated with urban form, land-use patterns, buildings, and travel behavior. Their networked infrastructure model integrates energy use in separate categories (vehicles, travel infrastructure, buildings) into a dynamic network where each activity node depends upon other nodes of both similar and different activities. Their analysis addresses questions about human-climate interactions in the city such as: how do different urban forms and land-use patterns contribute to energy use and GHG emissions; how do urban energy use and GHG emissions evolve as a community changes over time; and how do socioeconomic characteristics of the population influence patterns of land use and travel behavior and their implications for energy and emissions?

In another recently completed study, Guhathakurta and colleagues advanced three aspects of life cycle assessment (LCA) of residences: functional unit, technological progress, and scaling properties. They explored these issues through a case study of energy use of detached homes in Phoenix. This research relates residential energy use to unit size, characteristics, and neighborhood urban form. The objective is to inform planning of energy-efficient and low-carbon residential communities in the US. Additionally, this team developed a parametric LCA model that can estimate the embedded energy and GHG emission in the material manufacturing and construction processes for most types of single-family homes in Phoenix.

Geographers Patricia Gober, Anthony Brazel, Soe Myint, and postdoc Ariane Middel continued their NOAA-funded collaboration with Portland State University. Recent work examines how changes in land use/cover alter the local surface energy balance and contribute to distinct urban climates. The objective is to identify the extent to which current land cover and regional climate controls the surface energy balance. The researchers are using a Local Scale Urban Meteorological Parameterization Scheme (LUMPS) to analyze the relative attributions of local weather extremes and land-cover variations on the urban energy balance. Several articles from this effort are under review, and one published article (Myint et al. 2011) describes the remote sensing that underpinned the land-cover classification.

DCDC Researchers: