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~~7a <br />of the mix of variables that comprise these neighborhoods are the most crucial? If we can identify <br />which of the variables. is most effective, and measure their effects, then architects and developers <br />can incorporate them into smart growth, and air quality analysts can credit such design with <br />emissions reductions. <br />Our location efficiency study explores the hypothesis that the .average household's auto ownership <br />and driving decrease measurably as likely trip destinations become more convenient, especially by <br />non-automotive modes. Further, it tests the assumptions that residential density, center proximity, <br />local shopping, public transit accessibility and the pedestrian and bicycle friendliness of the <br />neighborhood are good measures of that convenience. <br />Which variables do we test? <br />• Density - a measure of the number of nearby destinations. Residential density, the number of <br />households per residential acre, seems to be the best measure, probably because it focuses on the <br />developed area and is not diluted by farmland or parks within the zone but outside the everyday <br />neighborhood. But other measures of density are also tested. <br />• Center proximity - a measure of the neighborhood's access to concentrations of jobs and <br />shopping. <br />• Local shopping - a measure of the amount of restaurants, markets, retail stores, insurance <br />agents, and of course video rental stores, nearby. ~ . <br />• Public transit -important as an alternative to driving. <br />• Pedestrian and bicycle friendliness -how attractive are areas to these alternatives to driving. <br />We would also have liked to test the impacts of parking supply, but were barred by the lack of <br />detailed zonal data on parking. Traditional dense areas have narrow streets and limited parking. In <br />addition, the land required by on-site parking itself reduces the density. In the Bay Area, a 3-story <br />apartment house's density could range from 28 units/acre to 64 due only to differences in parking <br />requirements of existing zoning laws.14 Consequently, to some extent density captures parking <br />tightness. <br />This study also sought to quantify the statistical relationship of such locational variables to auto <br />ownership and driving to facilitate the Location Efficient Mortgagec"' (LEM). The LEM allows a <br />household to buy a more expensive home in a location efficient area by committing its auto <br />savings to repaying the mortgage, interest, taxes and insurance. I reported preliminary results of <br />this study in the 1997 AWMA meetings.'s <br />THIS LOCATION EFFICIENCY STUDY <br />This study, sponsored by the Natural Resources Defense Council (NRDC), the Center for <br />Neighborhood Technology (CNT) in Chicago, and the Surface Transportation Policy Project in <br />Washington, DC, includes every neighborhood in the San Francisco, LA and Chicago areas. <br />The zones analyzed are the Chicago Area Transportation Study's 316 Dram-Empal zones <br />covering the Chicago metropolitan area, the Southern California Association of Governments' <br />1700 Travel Analysis Zones covering the Los Angeles metropolitan area and the Metropolitan <br />Transportation Commission's 1099 Travel Analysis Zones in the San Francisco metropolitan area. <br />4 <br />