Estimating Vehicle Emissions in Response to Urban Sprawl

October 29, 2008 By: Tim Dolney

Simulating Urban Growth

Although VERTUS was created as a stand-alone simulation engine, it was implemented within the Urban Growth Simulator (UGS) to offer urban planners a simulation tool that quantifies all environmental effects resulting from urban sprawl. UGS was developed by researchers in the Applied Geography Lab at Kent State University to serve as an impact assessment tool for urban sprawl within a 15-county region in northeast Ohio.

The UGS interface where users project the number of residential, commercial, or industrial developments. This example simulates adding 50 new houses in Parkman Township, Geauga County, Ohio. Locations of new housing developments are represented in orange.

UGS performs simulations of urban growth according to a projected amount of residential, commercial, or industrial locations entered by the user, with the average lot size in acres. Locations of these newly sprawled areas can be further defined as either along a road frontage or away from the road in clusters. Users have the option to incorporate any or all of the growth management strategies that their communities use or are considering adopting. These include open space management, avoiding development on environmentally critical areas, avoiding development of farmlands, and limiting developments in a pre-set growth boundary. With user inputs defined, the simulator first looks for developable land in current or proposed water- and sewer-service areas. If no suitable sites are found, a random number generator is used to identify developable vacant and farmland cells, which are assumed to be redeveloped.

Statistics of user inputs are provided, in addition to a summary of how simulated development affected land use in terms of the amount of agricultural land and critical nature lost.

The program repeats this process for other locations until the specified area is built out according to the user-selected growth management strategies. When simulation is complete, UGS displays results on a map showing the location of newly sprawled areas. The user can also view statistics that state how much agricultural and critical nature area was lost and the amount of nutrients loaded into the soil due to the simulated development. Also, users can export the locations of simulated sprawling developments as a polygon shapefile (a format readable by most GIS software packages) for integration with VERTUS or further analysis in a desktop GIS.

Local Emissions

The local emissions interface provides users with predefined values depending on the township chosen. The model first considers the township and the number of houses simulated in UGS; these dictate the commuting characteristics of the population traveling from new housing developments. The model then determines how many workers reside in new housing developments by multiplying the number of new houses (50) and the number of workers per household (1.38) in that particular township. The model then considers the number of non-commuters: those who work at home, walk or ride their bike, and carpool to work; forty-eight percent of workers in Parkman Township fall into this category. This translates to a total of 36 home-work journeys based on the initial input of 50 new houses. The final input partitions home-work journey vehicles into passenger cars (PCs) and light-duty vehicles (LDVs) (trucks, vans, SUVs) according to demographic and social characteristics of each township. Specifically, higher LDV usage occurs in those townships with higher income households and a larger number of persons per household.

The inputs for the local emissions interface shown here are indicative of the 50 houses added to Parkman Township. The map displays the street network of the township, locations of new housing (red), and the HAP (green). A summary of commuting characteristics is provided, showing vehicle emissions across multiple units and time periods.

Each township has its own set of variables used to calculate inputs. The user has the option to alter any of the inputs defined by the model to test alternate scenarios and examine how each affects the amount of emissions generated. Once all inputs are defined, the model then calculates local emissions by simulating the home-work journey from new housing (red dots) to the HAP (green dot). Output for each emission type is provided as the additional amount generated in tons per year.