Josias Zietsman

Environmentally Conscious Highway Design for Crest Vertical Curves

The primary objective of this study was to provide guidelines and tools for quantifying the environmental impacts in terms of fuel consumption and emissions of various highway geometric design conditions related to crest vertical curves. Second-by-second speed profiles were generated with speed prediction and polynomial models, and fuel consumption and emission rates based on vehicle-specific power and speed were extracted with the recently developed motor vehicle emission simulator (MOVES) modeling software. The generated speed profiles were matched with the extracted rates and aggregated during a trip on the curves. A benefit–cost analysis was also carried out with existing data from Washington State. The results demonstrated that the design vehicle respectively consumed and produced 10% less fuel and carbon dioxide on the crest vertical curve designed with a rate 1.5 times greater than the minimum rate of the vertical curvature documented in the AASHTO Green Book. For other emissions—carbon monoxide, oxides of nitrogen, hydrocarbons, and particulate matter of 2.5 μm or less—there were also reductions by up to 31% on the curve. The results also showed that the environmental economic benefits from flattening the curve design exceeded additional construction costs for a 30-year design period. Vertical curve design providing a flattened curvature can be environmentally and economically beneficial throughout the life of the highway. This study shows the efficacy of environmentally friendly design for sustainable transportation.

Sustainable transportation – alternative perspectives and enduring challenges

ABSTRACT This paper provides a discussion centred on the notion of ‘sustainable transportation’ as a concept for transportation academics and practitioners. Sustainable transportation broadly reflects the principles of sustainable development in the transportation sector. As with the broader notion of sustainability, there are several alternative perspectives on the definition, application, and value of the concept. The paper discusses key topics pertaining to the notion of sustainable transportation and how it is currently understood and applied. These include (1) concepts related to sustainability/sustainable development as a whole, including conflicts between approaches and definitions of sustainability, (2) an exploration of sustainable transportation and how it is addressed by the transportation sector, and (3) the use of indicators to apply sustainability concepts. We then identify several challenges that complicate the progress towards sustainable transportation – including issues with clearly defining the term, cross-cutting nature of the problem, inherent conflicts in sustainability, the multitudes of frameworks and metrics available, the politics of sustainability, and alternative discourses that exist in transportation practice. Based on our own research in this area, we conclude with recommendations for an overarching framework to address these issues. We propose an approach that is context-specific, outcome-focused, and holistic to tackle the enduring challenges of sustainable transportation.

Development of fuel and emission models for high speed heavy duty trucks, light duty trucks, and light duty vehicles

The current state-of-practice emission modeling tools, namely: MOBILE, EMFAC, the Comprehensive Modal Emission Model (CMEM), and VT-Micro model do not provide reliable emission estimates for high speeds greater than 80 mph since the models do not have supporting data at these high speeds. Consequently, the research presented in this paper gathers field data and develops models for the estimation of fuel consumption, carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOX), hydrocarbon (HC), and particulate matter (PM) emissions at high speeds. A total of nine vehicles including three semi-trucks, three pick-up trucks, and three passenger cars are tested on a nine-mile test track in Pecos, Texas. The fuel consumption and emission rates are measured using two portable emission measurement systems. Models are developed using these data, producing minimum errors for fuel consumption, CO2, NO2, HC, and PM emissions. Alternatively, the NO and NOX emission models produce the highest errors with the least degree of correlation. The study demonstrates that the newly constructed models overcome the shortcomings of the state-of-practice models and can be utilized to evaluate the environmental impacts of high speed vehicles.

Field Evaluation of Carbon Dioxide Emissions at High Speeds

This study has two main objectives. First, the impact of vehicle cruise speed on its carbon dioxide (CO2) emission rates at speeds up to 95 mph is evaluated with field data gathered under real-world driving conditions. Second, the cycle-based CO2 emission rates for a broad range of average cycle speeds are investigated. A portable emission measurement system unit was used to measure tailpipe emissions of three light-duty gasoline vehicles and three Class 2b diesel vehicles. The vehicles were tested on a speed track 9 mi high in Pecos, Texas, while the driver followed predeveloped drive patterns. The drive patterns were used to ensure good coverage of various steady-state and transitional operational modes of the vehicles. The results show that the CO2 emissions of gasoline vehicles follow a sharply increasing pattern between 40 mph and 70 mph. At speeds higher than 70 mph, the vehicles fuel economy tends to decrease at a small rate or to stay flat. The Class 2b diesel vehicles, in contrast, show a monotonically increasing trend for speeds higher than 40 mph. The second-by-second emission data were used to develop a series of instantaneous emission models capable of providing accurate emissions at each speed and acceleration rate. The models were applied to a series of representative drive cycles to provide distance-based average CO2 emission rates. The results indicate that the gasoline vehicles have a minimal CO2 emission interval between 55 and 65 mph. Diesel vehicles, however, seem to reach their minimum CO2 production at 55 mph and the trend increases on both sides of this optimal speed.

Corridor-Level Air Quality Analysis of Freight Movement: North American Case Study

The main objective of this research is to investigate the issues and opportunities for improving climate change and air quality implications of freight movement along a North American corridor. The paper presents a case study to determine the impact of truck and rail freight movement on air quality along the corridor from Mexico City, Mexico, to Montreal, Quebec, Canada. Network and freight activity data were assembled for the corridor for a base case (corresponding to the year 2010) and a future case (corresponding to the year 2035). Emission rates for the case study were obtained from the U.S. Environmental Protection Agencys MOBILE6.2 emission model. Parameters such as vehicle age distribution from vehicle registration data were used to refine the emission rates. Rail emissions calculations are based on U.S. average emission and fuel consumption rates. These rates were revised to reflect the ongoing improvements in locomotive engine standards. The results show that freight movement will continue to cause substantial amounts of carbon dioxide emissions. Current levels of rail emissions are not significant compared with those of trucks; however, the share of rail emissions for some pollutants will increase over time. Because of the vast differences between truck and rail operations in terms of routing and operational practices, it is recommended that rail and truck analyses be performed separately to gauge environmental and air quality impacts. It was also determined that the emerging sources of data such as Global Positioning Systems and engine loggers can lead to improved monitoring accuracy; however, making use of these potential resources requires cooperation between the freight industry and transportation and environmental agencies.

Addressing Sustainability and Strategic Planning Goals Through Performance Measures: Study of Bus Rapid Transit Systems in El Paso, Texas

Increasing emphasis is being placed on sustainability in the transportation sector. The City of El Paso, Texas, has been proactive in its approach and commitment to sustainability. The citys 2011 strategic plan lists various transportation- and community-oriented goals that provide direction for sustainable transportation initiatives. The new bus rapid transit system projects in the city are an important part of these and are the focus of the project described in this paper. This paper summarizes a recent exercise conducted to conceptualize the relevance of sustainability to transit corridors in El Paso and to identify performance measures that El Paso can implement. A set of 25 potential sustainability performance measures for rapid transit system corridors was identified. Selected performance measures from this set can be used to support specific corridor-level applications and to develop initiatives that can support the city at a strategic level to identify, track, and implement performance measures for sustainability and measure and communicate the value of investment in transit systems. The findings from this research will allow the city to communicate the value and benefit of bus rapid transit systems and provide tracking and decision-making tools that may be used to evaluate sustainability by the use of appropriate performance measures. The performance measures developed as part of this work will also have broader applicability to other cities, planning organizations, and transit agencies and can function as a performance measurement toolkit for practitioners looking to study sustainability in the context of transit systems.

Characterization of On-Road Emissions of Compressed Natural Gas and Diesel Refuse Trucks

Portable emission measurement systems were used to perform on-road emissions testing of compressed natural gas (CNG) and diesel refuse trucks to determine whether replacing diesel-fueled refuse trucks with CNG-fueled trucks would reduce emissions and fuel consumption. Two types of on-road testing were conducted: one while performing actual garbage collection in a service area (in-service testing) and the other following predeveloped duty cycles (duty cycle testing). Carbon dioxide (CO2), gaseous pollutants [oxides of nitrogen (NOx), carbon monoxide (CO), and hydrocarbons (HC)], and particulate matter (PM) emissions as well as carbon-based fuel consumption from refuse trucks during both types of testing were measured and analyzed. The analyzed results showed that CNG refuse trucks generally produced about 20% lower CO2 emissions and significantly lower NOx emissions compared with diesel trucks. However, CNG trucks emitted more CO and HC than diesel trucks. Almost all measured HC and PM emissions from diesel trucks were negligible. Measured PM emissions from CNG trucks were also negligible. Detailed tests and analyzed results are presented in this paper.

The Impact of Different Validation Datasets on Air Quality Modeling Performance

Many studies rely on air pollution modeling such as land use regression (LUR) or atmospheric dispersion (AD) modeling in epidemiological and health impact assessments. Generally, these models are only validated using one validation dataset and their estimates at select receptor points are generalized to larger areas. The primary objective of this paper was to explore the effect of different validation datasets on the validation of air quality models. The secondary objective was to explore the effect of the model estimates’ spatial resolution on the models’ validity at different locations. Annual NOx and NO2 were generated using a LUR and an AD model. These estimates were validated against four measurement datasets, once when estimates were made at the exact locations of the validation points and once when estimates were made at the centroid of the 100m×100m grid in which the validation point fell. The validation results varied substantially based on the model and validation dataset used. The LUR models’ R2 ranged between 21% and 58%, based on the validation dataset. The AD models’ R2 ranged between 13% and 56% based on the validation dataset and the use of constant or varying background NOx. The validation results based on model estimates at the exact validation site locations were much better than those based on a 100m×100m grid. This paper demonstrated the value of validating modeled air quality against various datasets and suggested that the spatial resolution of the models’ estimates has a significant influence on the validity at the application point.

Advancing Health Considerations Within a Sustainable Transportation Agenda: Using Indicators and Decision-Making

Urban transportation planning and decision making broadly centers on the provision of transportation infrastructure and services in a manner consistent with established procedures and priorities. Decision-making in this context goes hand-in-hand with the use of indicators to represent and measure progress towards the goals and objectives being pursued. Sustainable transportation principles provide a desirable framework for the development of an urban transportation planning agenda that addresses environmental, economic and societal goals. Several transportation planning activities around the world use some form of a sustainable transportation definition in the framing of their higher-level goals and priorities, with indicators to reflect the same. This chapter discusses how health considerations can potentially be addressed within a sustainable transportation agenda, specifically through the use of indicators. Similar to sustainable transportation, the area of health and transportation is broad, cross-cutting and holistic. There are several synergies between the areas of health and sustainability. Appropriate consideration of these overlaps and the use of compatible indicators can promote the advancement of health considerations in transportation planning and decision-making. However, it is important to keep in mind the bigger picture with regard to sustainable transportation, which often goes beyond health considerations.

Effectiveness of Idle Reduction Technologies in Reducing Driver Exposure to Diesel Emissions

The purpose of this study was to investigate the effectiveness of idle reduction technologies (IRTs) in reducing driver exposure to diesel exhaust, and to study the cost effectiveness of these technologies. IRTs are devices that provide heating and cooling to the cabin of a truck without idling the truck engine. The focus was on diesel-powered IRTs (auxiliary power units and fuel-operated heaters), and their impact on particulate matter (PM2.5) exposure of drivers sleeping or resting in the truck’s cabin. The focus was on diesel-powered IRTs as these devices generate their own emissions, potentially exacerbating in-cab exposure levels. The project involved initial field data collection at truck stops in the states of Georgia, Texas and California. This was followed by laboratory testing in an environmentally controlled test chamber on a sample of trucks, with and without the use of IRTs. The study findings showed that the use of IRTs resulted in a significant reduction of PM2.5 levels in the truck cabin when compared with the baseline scenario of a truck parked with the engine off and the doors and windows closed. Idling the truck engine and running the air conditioning system was also found to reduce in-cabin PM2.5 levels relative to the baseline. The study supports the premise that IRTs reduce driver exposure to diesel exhaust. Additionally, it was found that these devices are cost effective in that they all have payback periods of less than five years, making them viable alternatives to idling the truck engine during long-duration rest periods.