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600451-00067

SWUTC Research Project Description

The Life-cycle Costs and Benefits of Different Land Use and Transportation Patterns

University:  University of Texas at Austin

Principal Investigator:
Kara Kockelman
Department of Civil and Environmental Engineering
(512) 471-0210

Project Monitor:
Arpad Horvath, Ph.D.
Professor
Department of Civil and Environmental Engineering
University of California at Berkeley
215 McLaughlin Hall
Berkeley, CA 94720-1712

Funding Source:  USDOT and State of Texas General Revenue Funds

Total Project Cost: $79,285

Project Number:  600451-00067

Date Started: 5/1/12

Estimated Completion Date:  6/30/13

Project Summary

Project Abstract:
The work will examine the costs and benefits of different land use patterns, as these relate to transportation demands (for freight and passenger travel), travel speeds, home and business sizes, vegetative cover patterns, and associated infrastructures (including water, sewer, natural gas, and electricity provision and use levels).

Tabulations will include construction and operating materials (by type), energy and water consumption levels per capita (while controlling for climate), travel demand and other implications (including emissions and health). Such distinctions will highlight the differences in sustainability of different development settings, and the integrated nature of travel, the built environment, energy, water, health, and the environmental. Results will suggest opportunities for more sustainable policies and practices, including changes in building codes, zoning practices, transport investments, and energy policy.

Project Objectives:
This work will seek to quantify the infrastructure differences, travel differences, emissions, and energy differences of different land use settings, to accommodate the same number of persons and jobs in different built environments. For example, example cities and neighborhoods will provide examples of land use patterns and building styles, and the inputs for and outputs of these setting will be tabulated to then quantify life-cycle cost, carbon, VMT, and other differences (per capita). Tabulations will include construction and operating materials (by type), energy and water consumption levels per capita (while controlling for climate), travel demand and other implications (including emissions and health).  Such distinctions will highlight the differences in sustainability of different development settings, and the integrated nature of travel, the built environment, energy, water, health, and the environmental. Results will suggest opportunities for more sustainable policies and practices, including changes in building codes, zoning practices, transport investments, and energy policy.

Task Descriptions:
Task 1: Synthesis of Relevant Literature and Contacting of Experts in the Field
The research team will start by collecting recent and relevant literature. For example, works by A Horvath, M Chester, C Hendrickson, S Matthews, Greene, John Zhai, and M Blackhurst will be reviewed. In addition to these, the team will contact experts in this field of research for their suggestions and ideas, in terms of papers and reports to be reading and data sets to be tapping.

Task 2:  Data Collection
As part of this work, a variety of datasets related to building, travel, water use and energy use will be studied. Specifically, we will use extensive building data (characterizing public and private construction), commercial and household travel data, water use and energy use data, parcel map data, input-output matrices and techniques (for materials and energy flows), ArcGIS for data manipulation, and statistical computing for behavioral prediction under different land use settings. We will work off data that the construction industry uses for life-cycle assessment (including works by the project advisor [e.g., Arpad Horvath’s LCA of travel modes in the Bay Area, written with Mikhail Chester, who has papers on parking energy implications, transportation emissions costs, and so forth] and national energy labs [e.g., the Transportation Energy and Building Energy Data Books]. Example data sets include the American Housing and National Household Travel Surveys, Residential and Commercial Business Energy Surveys. Many other data sets need to be obtained, after consulting with those who do regular building LCA (in Task 1).

Task 3: Data Analysis
Different built environment settings and building types (e.g., single-family low-density residential vs. moderate-density vs. high-density) will be characterized and then their typical inputs tabulated (including ranges of inputs, since averages can hide great variation in building techniques). These will be in terms of input tons, dollars, kWh, volumes and areas – as appropriate — per square foot, dwelling unit, lane-mile, parking space, employee, etc. – as relevant for the development type and built environment setting. For example what is the amount of pavement, sidewalks, sewer lines, etc. per home, person and worker under each setting?

Input-output analysis will be used to capture upstream inputs (e.g., energy that accompanies 1 ton of concrete or steel, or is used to process and deliver 1 ccf of water or natural gas to a home or business or public park).

Regression models will be used as appropriate, to anticipate the total energy demands of different structures. With hundreds and typically thousands of data points on the energy requirements of various building types (from the RECS and CBECS data sets, for example) or the VMT and vehicle choices of households in various settings (from Austin or Seattle Travel Surveys, for example), we can anticipate average energy and travel demands of a wide variety of settings (and the variability and range in those values), for use in models of a variety of development settings/land use patterns. Model types include log-linear estimates of energy demand using ordinary or weighted least-squares techniques, multinomial or nested logit models for vehicle choices, and systems of equations for related responses (e.g., VMT across different vehicles owned, energy and water use per household).

Travel demand models to anticipate destination, mode, and route choices may then be applied, to anticipate speeds and emissions implications of various settings. Speeds and gasoline consumption levels are not provided in household and commercial travel surveys, so it is difficult to tie these to development patterns without some demand model runs. Kockelman et al.’s Project Evaluation Toolkit’s emissions rates, and Lemp et al.’s Austin-based travel demand model assumptions may be used for this (and applied using TransCAD software). The question here is whether to code networks to represent different the different networks (which can be time-consuming), or hope that existing networks can somehow be used. Simpler methods for anticipating accurate speed and emissions implications (than full-network applications) will be sought, as feasible.

Task 4: Model Applications
The results of this tremendous data assembly and calculations will be applied to a wide variety of development settings, with many assumptions on building types, ages, parcel sizes, vehicle ownership, travel patterns, etc. These will mimic, to the greatest extent possible, existing land use styles, from Seattle, Phoenix, Austin, NYC, LA, and/or other settings – both at the neighborhood and regional levels. Tabulations will describe energy, water, materials, and travel demands, and monetary cost, emissions, health, and other implications of such settings. There may be advantages and disadvantages to each setting (e.g., building costs vs. travel costs, materials use vs. transport emissions, travel time savings vs. energy savings). As feasible, the willingness to pay and welfare implications of different land use settings will also be quantified. (For example, many households and firms may not presently aspire to live in the most sustainable settings; what is the implicit cost to essentially ensuring such a setting?)

Task 5: Report Writing and Results Dissemination
Results from this work will be produced in the form of reports and research papers. These will include details of data assembly and analysis, and LCA estimates of energy and other impacts/outcomes of a wide variety of development settings. Key results relating to energy, emissions, health, and human welfare implications will be highlighted for planners, designers, policymakers, other stakeholders, and the public at large.


Implementation of Research Outcomes:
This work expanded knowledge of relationships between the built environment, energy consumption, and greenhouse gas emissions. While much research has considered the role of neighborhood design on energy use (by way of travel behavior and at‐home energy use), very little work has also considered the “embodied” energy and emissions of those neighborhoods and their supporting infrastructure. This research created a framework and provided numeric details for analyzing and comparing energy sinks and emission sources in a holistic manner, taking into account multiple energy sources over the lifetime of buildings and infrastructure systems (such as roads, water and wastewater pipes, sidewalks, public lighting, driveways, and parking surfaces).

This research was very interdisciplinary in its nature, since it concerns different pieces of the built environment, infrastructure, and energy analysis. While there have been many detailed life-cycle analyses from different fields (e.g., architectural engineering, materials science, industrial ecology), this study compiles many of these results together in a larger system analysis. By taking advantage of existing knowledge from disparate fields, this work extends research from a number of fields that consider energy, emissions, life‐cycle studies, urban design, transportation policy, and others.

Products developed by this research include:

Spreadsheet toolkit to guide life‐cycle energy and emissions estimates for different neighborhood styles and demographics. This open‐source tool can be used for holistic built environment energy evaluation and comparison. Currently, no such tools exist to parse energy sources (from daily energy use and embodied, life‐cycle energy sources) or identify energy impacts of policies and designs on life‐cycle energy and emissions impacts.

Paper 1 titled “Transportation Systems and the Built Environment: A Life‐Cycle Energy Case Study and Analysis,” under review for publication to Energy Policy and for presentation at the 2014 TRB.

Paper 2 titled “Life-cycle Energy Impacts of Different Neighborhood Types:  Identifying Critical Design Levers for the Short and Longer Terms” will be presented at the 60th Annual North American Meetings of the Regional Science Association International, in Atlanta, Georgia, November 13‐16, 2013, and will soon be submitted to a journal (like Energy Policy) for review.

Additionally, this project contributed to thesis research, which contains all the details of methods, analysis, and results.

Impacts/Benefits of Implementation:
This work, in part, identified relative energy consumption sources of typical neighborhoods, and provides a context for improving short‐ and long‐term energy efficiency measures. Results show that the public can reduce holistic energy consumption by living in neighborhoods that allow for more non‐motorized travel, and require shorter driving distances, but also require fewer life‐cycle resources to construct, maintain, and support with infrastructure over the long term. This research adds tangible estimates to how much the “big picture” of their neighborhood impacts energy use and illuminates the most beneficial choices (in home/apartment style, neighborhood location, and daily driving and energy consumption behavior) for reducing energy demands and associated emissions.

Web Links:
Final Technical Report