Grantee Research Project Results
Final Report: A Long Term Integrated Framework Linking Urban Development, Demographic Trends and Technology Changes to Stationary and Mobile Source Emissions
EPA Grant Number: R831841Title: A Long Term Integrated Framework Linking Urban Development, Demographic Trends and Technology Changes to Stationary and Mobile Source Emissions
Investigators: Anas, Alex , Hewings, Geoffrey
Institution: The State University of New York at Buffalo , University of Illinois Urbana-Champaign
EPA Project Officer: Chung, Serena
Project Period: November 1, 2004 through October 31, 2007 (Extended to October 31, 2010)
Project Amount: $675,000
RFA: Regional Development, Population Trend, and Technology Change Impacts on Future Air Pollution Emissions (2004) RFA Text | Recipients Lists
Research Category: Climate Change , Air
Objective:
The project focused on developing an integrated modeling package, a tool for testing trends and policies that together determine future emission levels. The precise aims of the model integration effort targeted by the project were as follows:
We sought to develop a tool capable of producing long-term (25–50 year) projections of stationary and mobile-source emissions in a metropolitan area. The way emission models are used is at best accurate for short horizons, taking as given local projections of local economic activity and population change. Instead of simply extrapolating these local trends, we sought to explain them by modeling the fundamental behavioral relationships among individuals and firms and by linking these underlying economic relationships to secular national and international trends in population, economic development and technological changes relevant to emissions. Among the specific demographic trends examined were the graying of the population, reductions in household size and international immigration. We also examined the possibility of the continued deindustrialization of U.S. manufacturing and its impact on a metropolitan area with considerable manufacturing, using the Chicago MSA. We considered new technologies likely to impact emissions, such as electric vehicles and hydrogen fuel-cell vehicles, as well as electricity/energy production with a higher renewable fuel mix under higher sustained energy prices.
The modeling framework is a dynamic computable general equilibrium model (DCGEM) for a metropolitan area based on principles of economic behavior and that can be calibrated well from existing data. The sub-models are (1) The Regional Economy and Land Use (RELU) model developed at the University at Buffalo, which treats the location, production and transportation decisions of both businesses and consumers and the land development decisions of developers under a variety of government taxes and subsidies; (2) TRAN, a model of highway-transit modal choice and congested travel conditions on highway networks developed at the University at Buffalo; (3) a model of the energy/electricity sector and its relation to demand from industrial production, residential use and vehicular transportation to be developed in this project; and (4) models of emissions from mobile and stationary sources, including those from production outside the electricity sector. We interfaced these models to establish feedbacks among them consistently with microeconomic theory so that they allow simulation of the workings of the Chicago regional economy.
The research was intended to provide a tool that is portable from one metropolitan area to another. It helped identify the policies or trends that are the most effective in reducing emissions, and specify how quickly and at what cost. It determined whether the benefits of two policies or planning actions are sub-additive or super-additive. Hence, it could help direct future research and provide guidance to future policy initiatives that are economically and politically viable. Application of the model to other regions in the future would increase understanding of whether the policy actions should vary among metropolitan regions or whether the same policies are effective everywhere.
Summary/Accomplishments (Outputs/Outcomes):
RELU-TRAN
We integrated the RELU model with the TRAN model for a representation of the Chicago MSA, consisting of 15 geographic zones spanning the city, the suburbs and the exurban area, four industries (agriculture, manufacturing, business services and retail trade), four consumer income quartiles, four building types (single-family residential, multiple family residential, commercial and industrial), undeveloped land, and an aggregated representation of the highway network. The total number of equations solved by RELU-TRAN is 656. The model is capable of predicting the effects of changes in transportation capacities, land use policies and a variety of taxes, as well as in exogenous trends of population increase, export expansion and improved industrial productivity on the regional economy, transportation, and land use changes at the metropolitan level.
Such a model as RELU-TRAN that simulates the working of the regional economy, its land use and travel is centerpiece in an effort to correctly forecast emissions in urban areas. Since emissions are a byproduct of economic activity, they cannot be forecast well unless the underlying economic activity is forecast properly. Because RELU-TRAN is a model that relies on the state-of-the-art theory in the urban economics and transportation fields, it plays a key role in the assembly of models that the project aimed to develop.
There are many examples of practical applications of the model assembly that was developed. One is the use of aggressive land development restrictions to limit urban sprawl and the expansion of low-density suburban areas. Such policies would, in the long run, result in higher density developments in the built-up areas, resulting also in lower vehicle miles traveled, more traffic congestion and more transit use. This, in turn, would alter energy/electricity consumption by residences and by vehicles (depending also on the types of vehicles being used as the vehicle fleet changes via car ownership decisions). Emissions, in turn, will be affected. The assembly of models would trace all of these effects, but it also would be able to quantify other costs and benefits of the aggressive land use policies, such as higher rents and other price distortions in the markets for labor and urban products.
We have completed the inclusion of a complete automobile sector into RELU-TRAN; that is, we have completed the RELU-TRAN2 model. RELU-TRAN2 adds the following features to RELU-TRAN1:
Consumer automobile choices and gasoline demand
Consumers chose vehicles according to various fuel economy levels. The choice is determined by vehicle acquisition and maintenance costs and by the preference for abstract vehicle features, such as comfort and safety, that are inversely proportional to fuel economy. Thus, RELU-TRAN2 can test not only how fuel costs and changes in fuel cost affect the types of vehicles owned, but it also determines the consumers’ responses to changes in various vehicle ownership costs. The entire model has been recalibrated to Chicago MSA (year 2000). The recalibrated model has a demand elasticity for gasoline that is consistent with the econometric literature on this issue. By making various runs of the RELU-TRAN2 model, we are able to generate the response to a fuel price increases over the very short, short, medium and long runs. Among other effects, the model also measures the rebound effect due to vehicle efficiency improvements, which means that improving vehicle fuel economy levels (i.e., increasing miles per gallon) can—in some ranges—increase total gasoline consumption, because consumers travel longer distances because the fuel needed per mile is reduced (i.e., because travel gets cheaper).
Local road congestion
Congestion on local roads, as well as major roads and expressways, is modeled. The recalibrated RELU-TRAN2 models how congestion occurs on local roads. This is important because congestion increases or congestion pricing in RELU-TRAN1 showed that traffic from major roads and expressways can spill over to local roads, which become congested in turn. RELU-TRAN1, however, was not designed to model such congestion increases. Therefore, we had to introduce this important feature in RELU-TRAN2, making it a more realistic model.
CO2 forecasting
We have added to RELU-TRAN2 the mobile emissions procedure so that in addition to fuel, RELU-TRAN2 forecasts CO2 emissions by automobiles. Because of this, the emissions implications of various congestion pricing, fuel taxing and land use control policies can now be tested using RELU-TRAN2.
Welfare analysis
The welfare analysis capability of RELU-TRAN2 has been greatly improved. The model now is capable of doing detailed welfare analysis of all the policies it can simulate. This analysis determines the distribution of benefits among consumers (indicating who benefits and who loses) and calculates monetary measures of welfare changes by consumer type. Also, costs and benefits to third parties reflected in the values of the Chicago real estate stock are calculated, and so are revenues generated by such pricing policies as fuel taxes or congestion tolls. Furthermore, these revenues can be redistributed among the different consumer groups or to geographically identified consumers. In this way, the model compares different redistribution schemes and can select the best one.
Policy simulations
Numerous simulations with the recalibrated RELU-TRAN2 model have been run, and the results are being discussed in the Ph.D. dissertation of the research assistant on the project. These results also will be the basis of publications to be completed in the coming months.
Conclusions:
The results to date, which are all relevant and faithful to the originally proposed project goals, can be summarized as follows:
Development and testing of RELU-TRAN1 and 2 are major accomplishments, because this is the first time in the history of urban modeling that a unified treatment of regional economy, land use and transportation has resulted in an operational model using analytical microeconomic principles of how markets operate.
Extension of RELU-TRAN2 to RELU-TRAN3 in the final year (November 1, 2009 to October 31, 2010) to incorporate residential, inter-industry energy/electricity demands and vehicle-driven energy demands by synthesizing the outputs produced at University of Illinois at Urbana-Champaign (UIUC), will further extend the model’s capabilities. Completing the emissions forecasting capability of RELU-TRAN3 model assembly will enable its application to environmental issues and the evaluation of economic tradeoffs involving emissions, going beyond just vehicle emissions to include emissions and power generation related to residential demand and industry.
Planned activity
We currently have plans to conduct the following activities:
- Integrating the electricity demand and electricity production sectors into RELU-TRAN2, which will be named RELU-TRAN3. In this part of the work, the electricity production and transmission sector model developed by REAL-UIUC will be integrated into RELU-TRAN2 together with the electricity demand generated from buildings, inter-industry demands and other sources (e.g., electric vehicles).
- Calibration of RELU-TRAN3 for Chicago so that the whole modeling assembly meets empirically known relationships in land use, transportation, production, electricity and emissions.
- Testing of the calibrated RELU-TRAN3 for convergence and stability of the algorithm.
- Simulations with the calibrated RELU-TRAN3 to test especially the relationships between urban sprawl, congestion and various pricing policies on the one hand and emissions on the other.
Journal Articles on this Report : 6 Displayed | Download in RIS Format
Other project views: | All 24 publications | 13 publications in selected types | All 8 journal articles |
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Type | Citation | ||
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Anas A, Liu Y. A regional economy, land use, and transportation model (RELU-TRAN©): formulation, algorithm design, and testing. Journal of Regional Science 2007;47(3):415-455. |
R831841 (2007) R831841 (2008) R831841 (2009) R831841 (Final) |
Exit Exit |
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Anas A. A unified theory of consumption, travel and trip chaining. Journal of Urban Economics 2007;62(2):162-186. |
R831841 (2007) R831841 (2008) R831841 (2009) R831841 (Final) |
Exit Exit |
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Anas A, Lindsey R. Reducing urban road transportation externalities: road pricing in theory and in practice. Review of Environmental Economics and Policy 2011;5(1):66-88. |
R831841 (Final) |
Exit Exit Exit |
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Anas A, Hiramatsu T. Effect of the price of gasoline on the urban economy: from route choice to general equilibrium. Transportation Research Part A: Policy and Practice 2011;46(6):855-873. |
R831841 (Final) |
Exit |
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Anas A. A summary of the applications to date of RELU-TRAN, a microeconomic urban computable general equilibrium model. Environment and Planning B--Urban Analytics and City Science 2013;40(6):959-970. |
R831841 (Final) |
Exit |
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Anas A, Hiramatsu T. The economics of cordon tolling: general equilibrium and welfare analysis. Economics of Transportation 2013;2(1):18-37. |
R831841 (Final) |
Exit |
Supplemental Keywords:
RFA, Scientific Discipline, Air, Air Quality, Environmental Chemistry, climate change, Air Pollution Effects, mobile sources, Environmental Monitoring, Ecological Risk Assessment, Ecology and Ecosystems, Urban and Regional Planning, Atmosphere, ecosystem models, infrastructure systems, traffic, engine exhaust, modeling regional scale ozone, vehicle emissions, human activities, motor vehicle emissions, Emissions Inventory Modeling System, air quality models, ozone, automotive emissions, traffic patterns, automobiles, automotive exhaust, green house gas concentrations, modeling, mobile source emissions, emissions impact, atmospheric pollutant loads, tropospheric ozone, regional emissions model, global warming, predicting ecological response, climate variability, community structure, Global Climate Change, ambient air pollutionProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.
Project Research Results
- 2009 Progress Report
- 2008 Progress Report
- 2007 Progress Report
- 2006 Progress Report
- 2005 Progress Report
- Original Abstract
8 journal articles for this project