Franklin Gbologah

Demonstrating a Bottom-Up Framework for Evaluating Energy and Emissions Performance of Electric Rail Transit Options

Current frameworks for analyzing emissions performance of public transportation systems use top-down approaches that can often provide useful information at the network level but can be uninformative at the project level at which the influence of route and vehicle characteristics can significantly impact emission profiles of candidate transit options. This paper describes an alternative bottom-up framework that uses second-by-second travel activity data to estimate total power consumption and related emissions for propulsion purposes with application to electric rail transit systems. The model was developed and calibrated with data from Portland, Oregon, and was supplemented with activity data from Chicago, Illinois. The results showed a predicted 1% to 8% difference in expected power consumption relative to estimates derived from the national transit database. In addition, the results highlighted how the speed profile, configuration of the train in number of cars, and mix of power generation sources could significantly vary emissions performance across different service routes. The developed framework can serve as an important tool for a transit planner or policy maker to evaluate the emissions performance of electric rail transit options. This framework has the advantage of relevance at both the network and project levels. At the project level, users can easily perform detailed sensitivity analysis on aspects of transit services such as vehicle and fuel technologies, passenger loading profiles, train size, and track profile. This framework gives transportation planners a flexible and efficient tool for emissions performance analysis.

Load-Based Life Cycle Greenhouse Gas Emissions Calculator for Transit Buses: An Atlanta, GA, Case Study

Using the Public Transit Greenhouse Gas (GHG) Emissions Management Calculator (hereafter the Calculator), this paper presents a case study of transit bus GHG emissions using Atlanta, Georgia, data. The Calculator, developed by Georgia Tech researchers, is the first load-based life cycle emissions model for transit buses. The modal modeling approach of the Calculator estimates emissions as an indirect function of engine load, which in turn is a function of transit service parameters such as driving cycle (idling and speed-acceleration profile), road grade, and passenger loading. Direct emissions are calculated based on the scaled tractive power (STP) operating mode bins employed in the Motor Vehicle Emissions Simulator (MOVES) model, and life cycle emissions are calculated using the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model. The case study compares life cycle greenhouse gas emissions of five vehicle technologies, conventional compression ignition, parallel hybrid electric, series hybrid electric, battery electric, and fuel-cell electric, in combination with three fuel types, conventional diesel, compressed natural gas (CNG), and 20% biodiesel. The comparisons are carried out for two public transit route types, e.g. an urban transit route vs. an express bus route. The Atlanta case study showcases the practice-ready capabilities of the GHG emissions calculator in assessing the differences in technology and fuel performances under different operating conditions. The results illustrate that the decision as to which bus technology-fuel combination produces the least greenhouse gas emissions is a function of location and route characteristics. The Calculator will support transit agencies in evaluating bus technologies for GHG emissions within the context of local conditions.

Comparison of Fuel-Cycle Emissions per Passenger Mile from Multiple Bus and Rail Technologies

This paper examines the fuel-cycle passenger-mile emissions from multiple bus and rail technologies using a travel-activity-based bottom-up approach. There is abundant literature on transits emissions savings, but most prior studies rely on the top-down fuel consumption approach. While the top-down approach paints a broad picture of transit emissions on a national or regional level, it cannot reflect changes in emissions as a function of operational characteristics such as passenger loading. It is also difficult to estimate passenger-mile emissions of new vehicle/fuel technologies for which fuel economy data are hard to obtain using the top-down approach. This paper develops a unified load-based methodology framework that compares fuel-cycle passenger-mile emissions across transit technologies, including alternative fuels and advanced technologies. The methodology reflects the intricate trade-offs between the increased total emissions and decreased passenger-mile emissions as passenger load increases under specific local meteorological and route settings. Using the load-based methodology, the paper demonstrates the varying levels of emissions savings of transit fuels and technologies giving different passenger loadings scenarios. The methodology presented in this paper serves as the foundation of a transit emissions calculator currently under development. The calculator will prove instrumental for local transit agencies to compare fuel/technology alternatives in terms of emissions savings.

Calibration of a Digital Camera for Rapid Auditing of In Situ Intersection Illumination

The regular auditing of installed roadway lighting performance is essential in ensuring that in situ light levels are within design specifications despite the effects of lamp deterioration or changes in roadway functional class. However, existing guidelines for measuring roadway lighting performance are tedious and often impractical for transportation agencies and municipalities, which are already faced with time and resource constraints. A method for calibrating a digital single lens reflex camera for rapid assessment of illumination levels at roadway intersections is developed in this paper. The method uses an image analysis approach to extract pixel information in a digital image and link it to the scene luminance. It uses high-precision light meters to perform an initial calibration of the digital camera that has proved to be stable over long periods. The method was tested with field data, and the results indicate that average scene luminance derived from this method differs by less than 4% from the average observed scene luminance captured by high-precision luminance meters involving a rigorous field measurement methodology. The methodology developed in this study offers transportation agencies and municipalities a rapid, inexpensive, and efficient method for auditing the adequacy of roadway illumination.

Load-Based Life-Cycle Greenhouse Gas Emissions Calculator: Running Emissions Sensitivity Analysis

This paper describes a running emissions sensitivity analysis of the U.S. Environmental Protection Agencys (EPAs) MOVES2010b model at the project level through the implementation of the Public Transit Greenhouse Gas (GHG) Emissions Management Calculator. MOVES model running emissions for diesel transit buses were estimated for 17 heavy-duty transit bus driving cycles across 12 different locations and meteorological conditions. The preliminary results examine the estimated annual diesel transit bus NOX and CO2 emissions. With an understanding of the scaled tractive power operating mode bin distribution of a driving cycle and the MOVES model emission rates, the annual emissions can be analyzed and compared. The results obtained from this sensitivity analysis indicate the potential usefulness of the Public Transit GHG Emissions Management Calculator for use in evaluating emissions across driving cycles and environmental operating conditions in a comparative mode.