Our research evaluates and assesses 1) how changes in transportation behaviors and patterns affect public health, environmental outcome, and energy consumption; and 2) policies, planning, and mitigation strategies to reduce adverse environmental, health and energy outcomes caused by or pertinent to transportation and land use.
Away from Home and Out of School: Adolescent PA and BMI Changes That Occur with Driving and Eating Out
Forthcoming
Advanced Modeling System for Assessing Long-Term Regional Development Patterns, Travel Behavior, Emissions, and Air Quality
Daniel Rodriguez & Yan Song, Co-PIs. The fundamental goal of our research is to rigorously test the hypothesis that development patterns, implemented regionally over a planning horizon of 50 years, can significantly influence the spatial characteristics and quantity of emissions from on-road mobile sources and rail transit vehicles, and hence reduce levels of tropospheric ozone and fine particulate matter. The development patterns of interest include the type of development and its location: e.g., transit oriented development, dense mixed use development, development supportive of nonmotorized transportation modes for nonwork trips, neotraditional suburbs, new urban core development, and redevelopment. We will test our hypothesis with a case study of the Charlotte (NC) metropolitan area. Our research will inform efforts to bring the area into attainment with the 8-hour ozone National Ambient Air Quality Standards. It will augment the region’s Sustainable Environment for Quality of Life (SEQL) program. This EPA-funded initiative engages multiple stakeholders in strategic efforts to improve air quality and water quality and to achieve sustainable growth.
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Planning and Physical Activity: Testing associations between physical activity and the urban built environment
The aims of the study are to: a) replicate and test the statistical and practical significance of the relationship between objectively-measured physical activity and an expanded range of measures of the built and natural environments; b) examine potential substitution effects among the locations where physical activity can take place by collecting original data on how people allocate time to physical activity and details on where such activity occurs; and c) incorporate individual preferences and attitudes to examine issues of self-selection related to location and physical activity levels. This study takes place in Montgomery County, Maryland. The county contains a variety of built environments. From exurban areas to highly urbanized, transit-oriented areas, Montgomery County provides opportunities to test the relevant associations described herein. Across Montgomery County, there are differences in factors such as urban density, the age and racial mix of the population, employment level, income, and automobile ownership. We use a quasi-experimental research design based on a microeconomic behavioral model to examine the simultaneous influence of factors related to the physical environment on time allocated to physical activity at various locations (at home, in one's local neighborhood, for travel, or at other locations). We rely on a socio-ecologic model to identify individual factors, social factors, social-environmental factors, attitudinal/habitual factors, and physical environmental factors at the individual level that can influence the relationship modeled.
Transportation Planning: Reducing energy use in the transport sector through innovative community designs
This suite of projects is designed to understand the ecology of energy consumption at the individual level, with an emphasis on transport. Behavior is influenced by individual-centered characteristics like personal and inter-personal attributes, and by higher-level characteristics like neighborhood, community, regional, national and international factors that promote or hinder behaviors related to energy consumption. A cornerstone project in this regard is the development of the Advanced Modeling System for Assessing Long-Term Regional Development Patterns, Travel Behavior, Emissions, and Air Quality. The project is testing whether development patterns, implemented regionally over a planning horizon of 50 years, can significantly influence the spatial characteristics and quantity of emissions from on-road mobile sources and rail transit vehicles, and hence reduce levels of tropospheric ozone and fine particulate matter. Key distinguishing features of the approach are: * Development and estimation of a cross-sectional equilibrium model to simulate the land market in Charlotte, NT; * Implementation of a multimodal behavioral travel forecasting model, including non-motorized travel modes and incorporating attributes of the built environment; and * Use of an emissions model based upon the conceptual underpinnings of EPA's Multi-Scale Motor Vehicle and Equipment Emissions Estimation System (MOVES). The cross-sectional land market model allows communities to impose real-world land-market constraints and incentives (e.g., density bonuses, parking ceilings) on particular neighborhoods as the means for achieving development scenarios and measuring emissions outcomes. Also included in this suite of projects is study of the role of technological change, economic and social changes, and public policy on future energy demand, air emissions, and environmental outcomes. Much of this work involves applying risk analysis, decision analysis, and uncertainty analysis to policy issues that intersect with energy, transportation, environment, and public health. A national energy-economic modeling framework has been developed to assess future technologies, patterns of technology adoption, and the effects of technological and social changes on criteria pollutants and greenhouse gas emissions; potentials pathways of hydrogen economy in the U.S., and the impacts on energy, transportation, and greenhouse gas emissions; international comparison of the diffusion patterns of alternative fueled vehicles; and learning by doing.
Daniel Rodriguez & Yan Song, Co-PIs. The fundamental goal of our research is to rigorously test the hypothesis that development patterns, implemented regionally over a planning horizon of 50 years, can significantly influence the spatial characteristics and quantity of emissions from on-road mobile sources and rail transit vehicles, and hence reduce levels of tropospheric ozone and fine particulate matter. The development patterns of interest include the type of development and its location: e.g., transit oriented development, dense mixed use development, development supportive of nonmotorized transportation modes for nonwork trips, neotraditional suburbs, new urban core development, and redevelopment. We will test our hypothesis with a case study of the Charlotte (NC) metropolitan area. Our research will inform efforts to bring the area into attainment with the 8-hour ozone National Ambient Air Quality Standards. It will augment the region’s Sustainable Environment for Quality of Life (SEQL) program. This EPA-funded initiative engages multiple stakeholders in strategic efforts to improve air quality and water quality and to achieve sustainable growth. 
The aims of the study are to: a) replicate and test the statistical and practical significance of the relationship between objectively-measured physical activity and an expanded range of measures of the built and natural environments; b) examine potential substitution effects among the locations where physical activity can take place by collecting original data on how people allocate time to physical activity and details on where such activity occurs; and c) incorporate individual preferences and attitudes to examine issues of self-selection related to location and physical activity levels. This study takes place in Montgomery County, Maryland. The county contains a variety of built environments. From exurban areas to highly urbanized, transit-oriented areas, Montgomery County provides opportunities to test the relevant associations described herein. Across Montgomery County, there are differences in factors such as urban density, the age and racial mix of the population, employment level, income, and automobile ownership. We use a quasi-experimental research design based on a microeconomic behavioral model to examine the simultaneous influence of factors related to the physical environment on time allocated to physical activity at various locations (at home, in one's local neighborhood, for travel, or at other locations). We rely on a socio-ecologic model to identify individual factors, social factors, social-environmental factors, attitudinal/habitual factors, and physical environmental factors at the individual level that can influence the relationship modeled. 
