Transportation Land Use, Planning, and Air Quality

The sprawling patterns of land development common to metropolitan areas of the US have been blamed for high levels of automobile travel, and thus for air quality problems. In response, smart growth programs — designed to counter sprawl — have gained popularity in the US. Studies show that residents of neighborhoods with higher levels of density, land-use mix, transit accessibility, and pedestrian friendliness drive less than residents of neighborhoods with lower levels of these characteristics. However, these studies have shed little light on the underlying direction of causality — whether neighborhood design influences travel behavior or whether travel preferences influence the choice of neighborhood. The available evidence thus leaves a key question largely unanswered: if cities use land use policies to bring residents closer to destinations and provide viable alternatives to driving, will people change their behavior in ways that reduce emissions? This study examines evidence from a study of residents of eight neighborhoods in Northern California on the link between neighborhood design and two behaviors that affect emissions: driving and choice of vehicle type. The study used multivariate modeling techniques to control for socio-demographic characteristics as well as attitudes and preferences. The results support the premise that land use policies have at least some potential to reduce driving and ownership of light duty trucks, thereby reducing emissions.

With the increasing realization that transportation facilities can no longer be designed as "reactionary" measures to land use decisions, many communities are turning to a more integrated land use and transportation planning process adhering to Smart Growth principles. Unfortunately, many local and state design standards often require roadway design parameters that are completely out of context with the surrounding environment; implementation of these "standards" within a Smart Growth framework often results in roadways that encourage higher vehicular speeds at the expense of other modes, creating a pedestrian-hostile environment in an area that should be better balanced for all modes and sensitive to the context in which it exists. This paper examines the issues facing designers wishing to create context-sensitive roadways and the flexibility afforded by nationally-accepted design practices and guidelines. It also presents some examples where this flexibility has allowed for facilities to be constructed that blend into and enhance the surrounding environment. Finally, it answers the question of "what's next?" in terms of mainstreaming the practice of context-sensitive design and solutions.

Future growth due to urban development results in changes to land use and land cover and, consequently, to biogenic and anthropogenic emissions, meteorological processes, and processes such as dry deposition. This on-going project examines the role of urban development, demographic, and technology trends on emissions and air quality using Austin, Texas as a case study. The results contrast the impacts of four different urban growth scenarios on land use/land cover and anthropogenic and biogenic emissions. A community "visioning" project, called Envision Central Texas, has resulted in four pre-determined metropolitan development scenarios based on a projected doubling of the population. The scenarios include: 1) low-density, segregated-use development based on extensive highway provision; 2) concentrated, contiguous regional growth within 1-mile of transportation corridors; 3) concentrated growth in existing and new communities with distinct boundaries; 4) high-density development and balanced-use zoning. Results from these scenarios will be contrasted with those from an integrated transportation-land use model currently under development. A photochemical grid model, the Comprehensive Air Quality Model with extensions, is being used to compare the air quality impacts of urban development from the various scenarios.

Researchers widely recognize habitat loss as the most significant cause of species imperilment in the United States. In recent years, researchers, government agencies, and land use planners have become increasingly concerned about the impacts of urbanization and residential and commercial development on habitats and biodiversity. Development has both direct impacts on wildlife through habitat loss and fragmentation and indirect impacts including spreading invasive species, increasing road density, increasing recreation activity, altering hydrologic regimes, increasing pollution, wildfire suppression, noise pollution, and increasing urban and edge predators such as raccoons and cats. Numerous studies document changes in species composition across the urban-rural land use gradient. As humans convert more land from rural and undeveloped uses to residential and commercial developments, so called urban-adaptive species thrive while urban sensitive species, which tend to be of greater conservation concern, decline. As a result, numerous authors have called for increased coordination between land use planners and ecologists in an effort to steer development away from important wildlife habitat. The most significant potential avenue for reducing development impacts is to integrate conservation and land use planning. As part of the federal State Wildlife Grants Program, every state wildlife agency, in conjunction with numerous partners, recently completed a State Wildlife Action Plan (Action Plans or Plans). The purpose of the Plans is to provide a comprehensive view of wildlife needs in each state and so help focus conservation action on priority issues. All Plans were required to identify declining species, key habitats, conservation threats and actions to prevent further species decline. As such, the Plans have the potential to inform land use planners about wildlife, habitat, and conservation priorities in each state. We reviewed the Plans from all 50 states and the District of Columbia to see how they discussed development impacts and what strategies the Plans offer to protect wildlife in rapidly urbanizing landscapes. To do this we searched each plan for references to development, urban/suburban growth, sprawl, and land use planning/planners. We then coded each reference into a series of threat and action categories and identified the resulting themes across all Plans.

An explosion of multi-lane roundabout projects has recently occurred in Central Ohio. This paper discusses four transportation improvement studies for which multiple multi-lane roundabouts were chosen as the preferred solution. The projects include: 1) a high volume partial cloverleaf interchange design that will include high-capacity roundabouts at the ramp terminal intersections and other intersections within the corridor; 2) a six-mile extension of a suburban/rural four-lane principal arterial that will include six roundabouts along it's length; 3) two closely spaced, high capacity, roundabouts in a densely developed area, near two schools, 4) roundabouts utilized for access improvements in a future office/commercial growth corridor. This paper includes a description of these projects and a discussion of how the choice of multi-lane roundabouts in Transportation planning decisions at these locations will reduce delay and vehicle emissions and air pollution while also improving safety, aesthetics, and access management. The analysis presented in this paper is highly abbreviated. Please contact the author for additional information or greater detail of the analysis.

Increasing congestion and travel delays on urban roads has lead practitioners to look at means to encourage and make alternate modes of transportation more attractive. Allocation of resources to build facilities amicable to such modes of travel is governed by activity at the location of interest. Collecting real world data for several locations is an expensive and time consuming process. On the other hand, unlike trip generation models to estimate vehicle trips, literature documents limited research to model and measure activity pertaining to alternate modes of transportation. This paper focuses on the development of models to measure pedestrian activity at intersections.

The growth of urban mobility and use of private car leads to congestion, parking and sustainability problems in most cities. Cities around the world face unacceptably high levels of air pollution, noise, congestion, parking problems and accident rates. Urban transport is also one of the main responsible factors for the emission of green house gases, but improvements are being studied and tested all around the world. The present paper describes innovative mobility systems applied to a city near Lisbon - Évora, with special focus on the interaction between parking policies, traffic management, transit operation and soft modes strategies. The solutions adopted include a new bus network, an improvement in the train shuttle service, a Park & Ride bus line named Blue Line, and an innovative pedagogical parking enforcement strategy adopted in Évora.

Activity and purpose based trip making studies are gaining popularity in current transportation research industry. The purpose is determined by activity one is to engage in at the destination of the trip. The trip purpose can be influenced by several factors, in which mainly are social economic. Transportation planners need to know the effect foresee the future origin and destination of certain community based on the household and surrounding social economic data. Based on the importance of determining the effect of trip purpose, this study applies multinomial modeling approach to evaluate various factors which determine purpose based trip. The findings from this study can be used during preliminary feasibility or planning study in determining the expected number of trips. The study utilizes trip data from the 2001 National Household Travel Survey (NHTS). Home base and non-home based work, school, shopping, family, social and religious driven trips are modeled by using different social economic variables. Multinomial logit (MNL) and multinomial probit (MNP) models are used in this study in determining the effect of the variables, due to their capability of modeling multivariate discrete response variables and flexibility of studying effect of the variables for each trip purpose model developed. The modeling result showed the presence of more number of workers in the house to influence each trip purpose mentioned. Lifecycle which classifies each household member as adult or child and retirement status appeared to influence school, family and social related trips. The families with small children were found to make fewer trips compared to those with grown up children and retired people. Individual income in the household affect much trips related to shopping, work, and social. Weekdays and rush hours have positive relation with work and school trips but negatively related to shopping, family and social trip purposes. The MNL and MNP models yield the similar results in terms of the sign and magnitude of the coefficients. However the standard errors in MNP are seen to be tighter than those in MNL. Moreover, many variables appeared to be non-significant in MNP compared to MNL.

Rapid growth in travel demand during the last decade has led to increased delays and recurring congestion costs on urban roads in many areas. In addition, crashes, construction and rehabilitation activities, weather, and special events contribute to significant levels of non-recurring congestion cost. Travelers' perception of reliability of road network is based on factors contributing to both types of congestion. However, literature documents little to no research to combine and measure congestion using both the disparate factors. Thus, there is a need to research, define and measure congestion based on factors contributing to both recurring and non-recurring congestion. Travel time is a measure which is simple and easy to understand. Reliability can be measured either in terms of travel time or in terms of variation in travel time. Using measures such as travel time reliability helps address questions such as "how reliable are our roads?" and "which path is more reliable to reach a destination from an origin within an "on-time window" during a certain time of the day?" The focus of this paper is to develop and illustrate the working of a Geographic Information Systems (GIS) based methodology to estimate travel time reliability for each link on major roads. The methodology involves 1) estimating travel time using Bureau of Public Roads equation for each link, 2) identifying the number of crashes by severity type on each link, 3) estimating travel delays due to crashes for each link, 4) estimating total travel time based on 1 and 3 for each link, and, 5) estimating travel time reliability for each link using results from Step 4. Factors such as link volume, link capacity, the travel speed, crashes and their types, and time to restore normal conditions after a crash are collected and used in the computations. As travel demand and crash occurrence depend on the time of the day, temporal variations in travel time for each link are also addressed. Data collected for the Charlotte metropolitan area in North Carolina are used to demonstrate the working of the methodology. The outcomes will help practitioners and researchers identify congested segments and suitable mitigation strategies.

There is an increasing reliance on mobile source emissions analyses as part of the transportation planning process, including regional and hot-spot analyses to fulfill the requirements of the transportation conformity rule and project-level highway air quality assessments in response to the requirements of the National Environmental Policy Act. The general procedure of an emissions analysis is to employ the U.S. Environmental Protection Agency's MOBILE6.2 model to obtain on-road mobile source emission factors, and multiply by the vehicle miles of travel to construct emission inventories. Critical to the outcome of such studies are future predictions of vehicle activity. This is especially true in evaluating transportation alternatives to assess how well a proposed project may or may not mitigate vehicle congestion and reduce emissions. This paper investigates one aspect of vehicle congestion and emissions forecasting by applying different vehicle speed estimating methodologies used for sketch planning purposes and shows the variability of MOBILE6.2 emission factors as a function of travel demand and the associated capacity (i.e., volume-to-capacity ratio).

Traffic growth forecasting plays a pivotal role in the air quality analyses conducted in nonattainment and maintenance areas throughout the country. However, traffic forecasting is a difficult and often inaccurate process. For planning purposes, many agencies have begun producing estimates of future development and traffic with ranges. This approach demonstrates the disparity of forecasts based on different sources of data and assumptions. There are opportunities for using alternative forecasts of vehicle miles of travel (VMT) within the air quality planning process. Within the transportation conformity process, alternative VMT forecasts can be used to evaluate conformity assumptions or to adjust travel demand model forecasts. Within the statewide implementation plan (SIP) process, alternative VMT forecasts can play an even greater role. They may be used to develop consistent statewide forecasting methodologies for emission inventories or may be used to develop and assess risks when preparing conformity emission budgets.

The Metrorail (Metro) in Washington, DC commenced operation in 1979. The red line extension to the Shady Grove Metro Station in Montgomery County, Maryland opened in 1984. Seven years prior to the opening of the Shady Grove transit station, the Maryland National Capital Parks and Planning Commission (MNCPPC) adopted and approved a Shady Grove Sector Plan to provide guidance for development around the transit station and to reduce the potential negative effects of a Metro station complex. In 1990, the MNCPPC adopted and approved another sector plan that recognized that transit should form the basis for land use and zoning recommendations. In the twenty-two years the station has been in operation, there have been significant land use changes within a one-mile radius of the station. The land use has transformed from predominately agriculture and forest to a mixture of low and medium-density residential, institutional, and industrial, with small pockets of commercial and open space.

Intelligent Transportation Systems (ITS) are gaining popularity in developing countries like India. Two major components of ITS are Advanced Traveler Information System (ATIS) and Advanced Public Transportation Systems (APTS). A combined application of these two components is the estimation of bus arrival times. Accurate bus arrival time information will enhance the credibility of the transit system, thereby leading to higher patronage. Significant research has already been conducted using Automatic Vehicle Location (AVL) system for predicting bus arrival times. However, there is limited literature available on the application of probe vehicle speed data and passenger data for predicting bus transit travel time. It is believed that passenger data influences bus travel time in cities of developing countries such as India. Thus, this paper focuses on the application of probe vehicle speed data and passenger data for predicting bus transit travel time. The improvement brought about by the probe vehicle speed data and passenger data in prediction of travel time over the use of only GPS data is also studied. Along with passenger data, GPS data was collected using probe buses on one of the busiest bus routes on weekday evening peak hours in Chennai city, India. Preliminary data analysis revealed that similar traffic conditions prevail over the route during the evening peak hours on all weekdays. Thus, Multiple Linear Regression (MLR) models which do well in such recurrent traffic conditions were developed. Results conclude that: use of passenger data and speed data from probe buses helped improve the performance of the model.

Public transit accessibility and ridership are affected by neighboring environment along the transit lines. This paper investigates the relations between neighborhood features and bus ridership and emissions of the Chicago Transit Authority (CTA) bus lines. A mixed regression model of bus emissions/ridership model is created to quantify the direct relations with both internal bus operation indicators such as route length and number of stops and external factors including neighborhood land use and population socio-demographics. In Chicago, there are a large number of serviced urban Black neighborhoods with low population in vicinity of bus routes, poor connectivity to transit, and low transit users to work in general, resulting in high per unit ridership bus emissions (grams/ridership) for routes servicing those areas. As the city and the transit agency have been making great effort to increasing bus ridership in those neighborhoods, more collaborative work must be done by the city, the local planning agencies and the transit agency to improve accessibility to bus service.

Urban sustainable mobility solutions are being discussed throughout the world to deal with problems of high use of land, congestion situations, energy consumption and emissions derived from road transportation. Part of these solutions concerns the promotion of public transportation as an alternative to individual transportation. Public transport only becomes an attractive option if, for the mobility provided (passenger x km), emits less pollutants and consume less energy. This paper focuses on comparing the fuel consumption and tailpipe emissions (CO₂, HC, CO, NO_x, PM) between urban Diesel buses (10 litres and 2.7 litres turbocharged Diesel) and typical gasoline and diesel European light duty vehicles (1.2 litres gasoline, 1.9 litres turbocharged Diesel). Results are analyzed as a function of transported passengers. For the proposed analysis, typical low traffic and congested traffic driving cycles were selected as an input to the EcoGest model, combined with driver behaviour characteristics and vehicle characteristics. Main results are easy-to-use charts highlighting where each mode is more attractive as a function of the number of passengers inside the bus and the number of people inside the vehicle. Results were obtained using EcoGest, a numerical model developed in our research institute. This model allows simulating the energetical and environmental performance of a road vehicle in a predefined route, accounting for the driving behaviour, vehicle specifications, powertrain specifications, occupation rate and road grade. The model has been used to simulate light duty and heavy duty vehicles, including gasoline, natural gas and hydrogen cars, and diesel and natural gas buses. Predicted results have been compared with measured fuel consumption and tail-pipe emissions in real-traffic situations, standard cycles (FTP75, NEDC), and predicted results of similar models (e.g. ADVISOR). Predictions of EcoGest are, usually, very good.

The use of hydrogen as an alternative fuel has been suggested as a key element in promoting the improvement of urban air quality and to reduce GHG emissions, while diversifying and guaranteeing the security of energy sources supply. Several projects have been undertaken to develop a strategy towards a European hydrogen-based transport system. The present paper describes the part of two of those projects: CUTE and HYFLEET:CUTE, sponsored by European Commission's 6^th Framework Research Programme, involving several partners, mainly from industry, governments, academic and transport operators. The CUTE project was officially closed on March 2006, while HyFLEET:CUTE is an ongoing project. Both projects have the objective of developing and demonstrating a hydrogen based public transport system. This paper will look at the main conclusions of CUTE project and at the life-cycle analysis of the hydrogen used in the filling station and the fuel cell buses that ran in the city of Porto. The life-cycle analysis covers al phases from production, transport, and storage of hydrogen, up to the operation in the municipal fleet. This included the study of the energy efficiencies and environmental impact (the so called well-to-tank and tank-to-wheel studies) of different hydrogen production pathways. Regarding the bus operation, the energy and environmental vehicle performance is assessed and compared with current technologies. Furthermore, in the framework of the Hyfleet:CUTE project, a new filling station was built by the French oil company Total in Berlin that uses on-site hydrogen production with a LPG reforming system, combined with liquid hydrogen trucked from a Linde factory. The municipal fleet vehicles used are built by MAN and use an internal combustion engine and compressed hydrogen storage.

During 2004–2005, the Federal Highway Administration (FHWA) contracted with a private consulting firm to conduct a review of the state of the current practice of estimating the changes in mobile source emissions from land use changes. The study systematically reviewed over 50 independent research items; conducted numerous interviews with various public and private agencies including US EPA and FHWA Division Offices; and formulated a taxonomy of the existing methodologies available to metropolitan planning organizations and other agencies to address this issue. The study concluded with a description of the obstacles in the areas of travel demand modeling, emissions modeling, research deficits, and organizational barriers that would need to be breached in order to substantially improve the state of the practice. Simple elasticity-based models are the near-universal form of estimating change at this point, but the various context-related issues of the environment make these models very difficult to calibrate with any degree of surety. This paper reviews the state of the practice discovered during this exercise and highlights some of the methodological barriers and recommendations to overcoming these obstacles. An additional review of the literature produced since the study was completed at the beginning of 2005 will also be conducted. The paper intends to provide the audience with a better grasp of the current methodological issues, applied research, and the general approach to estimating mobile source emissions from land use change.

Increasingly, planners and policy analysts are paying significant attention to the interactions connecting transportation, land use and air quality in a metropolitan setting. These efforts are driven largely by transportation conformity, a Clean Air Act provision requiring both total emission budgets and mobile-source emission sub-budgets in nonattainment areas. All transportation plans in these areas must pass a conformity review to ensure that plan implementation over a 20-year planning horizon will not violate any emission budget in any year. Many nonattainment areas have adopted or have under consideration a set of transportation demand management (TDM) tools that can be adopted to earn emission "credits" toward meeting the transportation emission budget. These measures may include smart growth policies, which are aimed primarily at the supposedly inefficient use of land in suburban development and which are believed by many observers to reduce VMT and emissions as well. They may also include a variety of transportation policies designed to reduce if not completely internalize the congestion externality. In this paper we focus on the latter type of policies. We compare the emission-reducing properties of a number of transportation policies designed primarily to address congestion. The modeling platform we use is LUSTRE, a spatially detailed and behaviorally complex simulation of transportation, land use and economic activity in the Washington, DC region. LUSTRE also calculates an overall welfare measure that is consistent with utility theory, and we add that measure to the comparison.

Urban and regional air pollution is an increasingly critical problem in areas where rapid growths occurring and future development is expected. Within the typical planning horizon, many modeling tools (e.g., land use, travel demand, and emissions models) are used to evaluate the impact of regional development, population trends, and infrastructure improvements on air quality. However, these models were not designed, nor are they generally used as a cohesive system with feedbacks between them. Consequently, there is a gap in our understanding of how different models interact and combine to influence emissions inventories associated with future policy scenarios. In this study, funded by the Environmental Protection Agency, an emissions modeling framework was developed using the UPlan, TP+/Viper, and UCDrive emission models for the San Joaquin Valley (SJV) in central California. Specifically, future land use and subsequent travel patterns and emissions inventories were examined based on four policy scenarios for the year 2030: baseline (following general plans, with no roadway expansion), controlled growth (compact urban boundary, higher residential densities, no roadway expansion), uncontrolled growth (low residential densities, roadway expansion), and as-planned (following general plans, with roadway expansion). The integrated modeling framework links emissions to levels of travel pattern variations under different land use policy and development strategies. For example, compared to a scenario with highly controlled urban growth strategies, less restraint on urban growth results in more than a 20% increase in vehicle miles traveled and about 18% higher emissions of primary pollutants at the regional scale in year 2030. By means of comparing and connecting land use, travel patterns and emissions, the sensitivity of SJV mobile emission inventories to different possible growth scenarios can be assessed.

Integrated land use-transportation-emissions models are necessary to rigorously assess the potential of land use and transportation policies to reduce the vehicular emissions contributing to tropospheric ozone and to fine particulate matter. A theoretically- and empirically-grounded model contains these major components: data on economic sectors, population sectors, and intersectoral flows of commodities and labor; a transportation network; sectoral demands for land, predicting both the quantity and location demanded; elastic trip generation; transportation mode choice including non-motorized modes as a function of built-environment characteristics; a traffic assignment algorithm; and a MOVES-like module that estimates emission factors. That technical approach is incorporated in a TRANUS-based model that is being used to assess long-term development scenarios that could be implemented in Charlotte and Mecklenburg County, North Carolina's largest metropolitan area and part of an ozone nonattainment area. A unique feature of the Mecklenburg County model is use of random-utility theory and a typology of the built environment in the estimation of key parameters describing residential and enterprise locational choices and transportation mode choice.

The degradation of the urban air quality is today object of concern since a great part of the world population lives in urban areas. While the environmental implications of industrial and transport activities are recognized for decades, the influence of the urban patterns in air quality is still poorly understood. Currently, urban areas are expanding towards rural ones which, together with the segregation of land uses related to daily activities (home, school, work, leisure), lead to an increase of motorized trips and trip distances, resulting in an increase of air pollutants emissions. This paper carries out the state of the art concerning the link between urban structure and air quality. This link is neither simple nor direct; currently there is a debate on which is the most sustainable urban form: the compact city or the disperse city. Several empirical and modeling studies integrating land use, transport and air quality issues and its main conclusions are presented. Results indicate that compact cities promote a better air quality when compared to the dispersed cities; on the other hand, when the subject is human exposure to pollutants, compact cities present worst results. These studies allow concluding about the influence of the city structure in air pollutants levels, highlighting the importance of air quality as a relevant urban planning indicator.

As the air quality modeling needs of transportation planning professionals become more complex, the models must follow suit to provide more sophisticated and advanced capabilities. The current CALINE and CAL3QHC-series roadway models promulgated by the Environmental Protection Agency (EPA) provide static environments with time-averaged, aggregate variables that are unsuitable tor micro-scale assessments. Therefore, the successor (next generation) models should be based on a simulation approach and leverage new computing technology to provide more realistic and robust modeling environments. The TRaffic Air Quality Simulation Model (TRAQSIM) developed by Wyle Laboratories meets each of these qualities. TRAQSIM's 4-dimensional (4D) environment with virtually no temporal and spatial constraints provides the model with significant growth potential including the possibility of modeling the effects of road grade and facilitating the emissions and dispersion modeling of both particulate matter (PM) and chemically reactive pollutants. As an example of the robustness of a simulation environment, the ability to directly assess input and output uncertainties is presented in this paper. The assessment is conducted for a queue reduction example where Monte Carlo simulations are used to determine whether or not the air quality related to different scenario cases are statistically different from a baseline case. These methods and results provide additional quantitative information to help transportation land use and in planning professionals make informed decisions.

Congestion is a growing concern among those professionals tasked with managing traffic flows and air quality. Congestion is also a growing concern for the trucking industry, which is tasked with delivering goods to retailers, manufacturers and service providers across the country. Congestion is costly for both the public and private sectors due to traffic delays, fuel consumption, pavement and bridge damage, and environmental concerns such as air and noise pollution. Policymakers, planners and motor carriers must make decisions on how to best manage limited capacity to optimize the performance of goods movement on the road system. However, it can be difficult to predict the impact of different decisions on the actual performance of the network. To aid decision makers in this process, the American Transportation Research Institute has developed a freight capacity model which is able to estimate the likely financial, environmental and performance-related impacts of different planning decisions for both motor carriers and public sector planners.

This report presents an analysis of the air quality impacts from the construction of the proposed Masonville Dredged Material Containment Facility (DMCF). The project entails the construction of a disposal site for dredged material in the Middle Branch of the Patapsco River, at Masonville, Baltimore City, Maryland. The Masonville DMCF project on completion will provide a disposal site to accommodate dredged material generated by various dredging projects that will occur over the next 20 years in the Baltimore Harbor area. The goal of this study was to develop air emission estimates for the different types of equipment that will be utilized in the construction phase of the Masonville DMCF project. Criteria air pollutant emissions that will result from both direct and indirect sources relative to the project were calculated to address the requirements of General Conformity of the Clean Air Act. Under the General Conformity regulations, an emissions analysis is required to determine the total direct and indirect emissions for each criteria pollutant within the project limits. Emissions over certain prescribed threshold must be mitigated.

The Clean Air Act Amendments of 1990 designated 188 air toxic pollutants as Hazardous Air Pollutants (HAPs). Certain of these HAPs are characteristic of motor vehicles and have become known as mobile source air toxics (MSAT). Public concern about evaluating MSATs in the National Environmental Policy Act (NEPA) process has prompted transportation agencies to begin addressing air toxic emissions as part of their environmental review procedures. This study developed best-practices guidance for MSAT assessments under NEPA. Current approaches used by transportation agencies to assess and communicate MSAT emissions and health impacts were compiled and reviewed. A tiered methodology was developed which guides the analyst in identifying the appropriate level of analysis for a transportation project, using typically available information and potential level of exposure based on project characteristics. Five potential levels of analysis are suggested based on both technical and policy considerations. Details are presented on how to conduct the MSAT assessment as well as on the amount of information that should be included at each level of analysis. Recommendations are provided on how best to communicate the findings of the MSAT assessment as part of environmental documents and in public review.

A growing number of epidemiological studies conducted throughout the world have identified an increase in occurrence of adverse health effects for populations living near major roads. In addition, several air quality studies have identified increased concentration levels of certain pollutants near high volume roadways. However, questions remain on the spatial extent of elevated concentrations near the road, and the factors affecting concentration variability, including traffic activity (volume, fleet mix, speed, etc.), environmental conditions, and land development. In the U.S., federal agencies have been under increasing pressure to evaluate potential air quality and health impacts related to transportation systems. This presentation provides a summary of health effect and air quality studies that have been conducted near large roadways. The presentation also describes research plans being proposed by the Federal Highway Administration (FHWA) and the U.S. Environmental Protection Agency (EPA) to address future research projects related to the FHWA's US95 settlement agreement. These studies will measure criteria and air toxic pollutant concentrations near highways, including benzene, 1,3-butadiene, acetaldehyde, acrolein, formaldehyde, and particulate matter. In addition, meteorological and highway vehicle data will be collected to identify the relationship of these factors to the ambient air concentrations. The study will be conducted at three different geographic sites in the United States to investigate regional (climate, fuel, vehicle fleet differences), seasonal, and land use effects on near road pollutant impacts. Preliminary results from a pilot study conducted in Raleigh, North Carolina during the summer of 2006 will also be presented. This information will be presented to provide information on the impacts of vehicle emissions on near road air quality, as well as the development of control strategies to mitigate the influence of vehicle emissions on the near road microenvironment.

Section 812 of the Clean Air Act Amendments of 1990 (CAAA) requires the U.S. Environmental Protection Agency (EPA) to perform periodic, comprehensive analyses of the total costs and total benefits of programs implemented pursuant to the Clean Air Act (CAA). The first analysis required was a retrospective analysis, addressing the original CAA and covering the period 1970 to 1990. The retrospective was completed in 1997. Section 812 also requires performance of prospective cost-benefit analyses, the first of which was completed in 1999. The prospective analyses address the incremental costs and benefits of the CAAA. The first prospective covered implementation of the CAAA over the period 1990 to 2010. EPA's Office of Air and Radiation (OAR) is now working on a second prospective study, looking at the period from 1990 to 2020. The analytical plan was reviewed by a statutorily-mandated outside peer review group, the EPA Science Advisory Board Advisory Council for Clean Air Compliance Analysis (SAB Council), and the SAB Council provided comments, which have been incorporated into the technical analysis planning. The purpose of this paper is to describe the development of a benzene emissions inventory in the Houston, Texas, area as part of a case study for the second prospective study. After the first prospective 812 study, the SAB Council encouraged EPA to include a hazardous air pollutant (HAP) benefits case study in future efforts to help address limitations in our ability to estimate benefits associated with HAP controls under the CAA.

The City of Hickory and Western Piedmont Council of Governments are located in the foothills of North Carolina's Appalachian Mountain range. Hickory is home to one of the State's largest remaining concentrations of furniture and textile industries. Like much of the State and Southeast Region of the U.S., the Hickory Metro area has struggled to find a new economic identity after losing 25,000 jobs since January, 2001. Hickory and the whole of Catawba County were designated as a non-attainment area for PM_2.5 (fine particulate matter) by the USEPA in December, 2004. Previously, Hickory had also been designated as non-attainment for ozone, which led to the development of an Early Action Compact (EAC) that adopted 14 local control measures to address ozone formation. This paper and presentation relates the concerns that the Unifour has expressed about the relationships between PM_2.5 monitoring methodologies, localized land uses, and the non-attainment area designation process. Land use and transportation issues have played a large role during the history of the PM_2.5 assessment process. The issue is compounded because the only PM_2.5 monitoring site is affected by out-of-state transport; is located in a low-income / minority community; and is in the heart of the remaining manufacturing sector of the City served by an active diesel rail line. The paper presents the concepts that Hickory and the Unifour Area have devised and implemented that may help other small- and medium-sized communities understand, assess, and mitigate for fine particulates.

A recently published Environmental Protection Agency (EPA) final rulemaking (40 CFR 93.116) established transportation conformity criteria and procedures for identifying transportation projects that must be analyzed for local air quality impacts in PM_2.5 and PM₁₀ nonattainment and maintenance areas. A qualitative hot-spot analysis is required for "projects of air quality concern" as defined in EPA's final rule. PM hot-spot analyses assess projects found to be of "air quality concern" through the interagency consultation screening process, in combination with changes in background air quality concentrations, to determine if new or worsened future violations will result from their implementation. This paper presents suggestions for the development and utilization of various tools based on existing studies, computations and data, which can be compiled to form an evidence toolbox for use in qualitative PM hot-spot analyses. The evidence toolbox is designed for use by transportation officials and interagency consultation groups (ICG) in order to demonstrate whether a transportation project may or may not have any adverse affect on future PM emissions.

The Metropolitan Transportation Authority, Capital Construction Company in New York is managing the construction of two projects in Lower Manhattan, funded via federal government post-9/11 recovery allocations. Lower Manhattan is one of the largest business districts in the nation, and the two projects — the South Ferry Terminal Station and the Fulton Street Transit Center — will improve transit access to, and help to revitalize downtown Manhattan. With dozens of large-scale projects in the planning and construction stages in Lower Manhattan, many having lengthy and overlapping construction periods, MTA CC has aggressively implemented Environmental Performance Commitments (EPCs), developed in conjunction with other agencies building in Lower Manhattan. Heightened community awareness of air quality issues in Lower Manhattan has made the clean diesel emissions program one of the most important of the EPCs to implement. The U.S. EPA is using MTA CC's clean diesel emissions program as a model of success to induce its implementation in other areas of the country. The clean diesel emissions program includes use of Ultra Low Sulfur Diesel (ULSD) fuel, use of Tier 2 engines and diesel particulate filters (DPF) on all off-road construction engines of 50 horsepower (hp) or greater. MTA CC worked closely with retrofit vendors, equipment/engine dealers, rental agencies, and contractors to implement and manage this program. Between the two projects almost 150 pieces of equipment have been eligible for the retrofit technology and an approximate 86 percent compliance rate has been maintained. Given that these measures reduce particulate matter emissions by more than 90 percent, and that construction diesel equipment is a significant contributor to poor air quality, the program provides significant air quality benefits to Lower Manhattan.

As an efficient traffic control strategy to ameliorate freeway traffic congestion, ramp-metering has been successfully applied in the US. However, the applicability and effectiveness of a ramp-metering strategy are required to be investigated during the pre-implementation phase in order to ensure the success of the implementation. Traffic simulation models can provide a quick and cost-effective way to test and evaluate a ramp-metering algorithm prior to implementation on a freeway network. In this report, one ramp-metering algorithm (Fixed-time ramp metering) has been evaluated over a part of Highway 85 in Waterloo, Ontario. Simulation results show that fixed time algorithm can not improve the condition of Highway 85; in some cases, the algorithm may even delay traffic and increased pollution.

There has been an increasing trend in converting some of the under-utilized high-occupancy vehicle lanes to mixed-flow lanes. This paper presents a methodology to model and evaluate the air quality impacts of such conversion using an integrated modeling tool that uniquely combine a microscopic traffic simulation tool with a modal emissions model. A freeway stretch in Southern California was used as a case study to demonstrate the deployment of the integrated tool. The results for this particular cast study show that the lane conversion will not benefit air quality if the induced demand is more than 5% of the current demand.

This paper presents the findings of a study of motorized two-wheeler emissions under lane restricted and lane-less flow conditions in heterogeneous traffic. Lane restriction is defined as the movement of particular categories of vehicles on specified lanes (dedicated lanes), whereas lane-less flow movements are conditions when vehicles are free to change lanes. This study was conducted on selected mid-block road sections of different lengths in Chennai city, India. In the process of test runs, tailpipe emissions (CO, HC and NO) were measured using a portable gas analyzer at short intervals of time. These data were then synthesized to evaluate the total emissions from the vehicles for each test run. Instantaneous speeds of the vehicles were measured using an optical sensor fixed to the wheel. Consumption of fuel by the test vehicles were also measured using a petrol reading apparatus. Based on the analysis of field data collected specifically for this study, it is concluded that lane restricted flow generally produced reduced levels of tailpipe emissions compared to lane-less conditions. The impact of various factors such as, number of lane changes, average speed and fuel consumed on emissions were also studied. In order to understand the relationships between emissions and various traffic factors, regression models were tested and built using SPSS software. Highly heterogeneous traffic conditions and the lane changing behavior of drivers in traffic conditions prevailing in urban areas in India offered unique research opportunities in this study.

Transportation Control Measures (TCMs) are often a vital component of the overall plan adopted by transportation agencies to achieve their air quality goals. However, in an environment of limited funding only the most effective projects can be implemented, and agencies require metrics to help determine which TCMs to pursue. The comparison of different TCMs is complicated by the fact that projects which address one pollutant may not impact another, and while Ozone is analyzed on a daily basis, PM_2.5 and its precursors are evaluated using an annual comparison. There is a need to simplify the analysis and selection of projects by providing a metric or composite measure that summarizes total emissions benefits in a clear and concise way. This paper focuses on a metric developed for the New Jersey Department of Transportation in support of their recent analysis of Reasonably Available Control Measures (RACMs.) The Emissions Score was developed as a way to collapse both annual and daily estimates of emission benefits for multiple pollutants into a single, consistent value. This metric considers the annual and daily emissions targets for each pollutant, the estimated current inventory for each pollutant and a series of weighting factors that emphasize the pollutants of most concern to the region. The Emissions Score was used to rank the proposed projects in terms of overall impact. Ultimately this rating, combined with other factors such as cost effectiveness and political feasibility, was used to articulate the effectiveness of the TCM projects proposed in the study.

A growing number of epidemiological studies conducted throughout the world have identified an increase in occurrence of adverse health effects for populations residing, working, or attending school near major roadways. In addition, several air quality studies have identified increased concentration levels of certain pollutants near high traffic volume roads. The U.S. Environmental Protection Agency (EPA) has begun a research program investigating the relationship of traffic activity, environmental conditions, and near road air quality. As part of this program, the EPA is investigating the influence of noise barriers, vegetation, and other roadside structures on air pollutant concentrations near the road. This presentation integrates results from an air quality modeling assessment and air quality monitoring measurements to identify how noise barriers and vegetation near roads may impact local air quality. Air quality measurements were collected at sites with and without noise barriers and vegetation along a stretch of limited access highway in Raleigh, North Carolina, USA during the summer of 2006. This study allowed an assessment of the potential influence of these structures on near-road air quality. These structures influence pollutant transport and dispersion in the near-field (<300 m). Preliminary results suggest that, under some meteorological conditions, noise barriers and vegetation may reduce air pollutant concentration levels downwind of the barrier. These results may provide useful information in assessing the role of roadside structures on near road air quality for future land use decisions.

This paper is about fostering and accommodating the use of NEVs in the City of Lincoln. NEVs are small, electric-powered personal vehicles, and are an ideal transportation alternative for local trips. The NEV Transportation Plan (Plan) was developed in response to requests from a group of citizens, and assembled to implement the community's vision to offer residents safe NEV access to downtown Lincoln and other commercial areas. The City shared this vision with owners of developable land and existing and proposed business owners in Lincoln. The Plan was approved by the City Council on August 8, 2006. This paper will summarize legal constraints and opportunities, energy and cost considerations, air quality benefits, design considerations, and NEV Transportation Planning in the City of Lincoln. Extraordinary benefits have been found in planning for the use of NEVs throughout the City and beyond.

This study investigated the impact of biodiesel (B20: 20 percent biodiesel, 80 percent conventional diesel) on oxides of nitrogen (NOx), hydrocarbons (HC), carbon monoxide (CO), and carbon dioxide (CO₂) emissions from diesel school buses. Two drive cycles were developed based on the rural and urban drive cycle data collected using global positioning system (GPS) technology. Five buses were selected according to the current model year mix in Texas and were driven following the developed drive cycles for three different fuels (TxLED, B20 market blend, and B20 all soy). A state-of-the-art portable emission measurement system (PEMS) unit was used to measure the pollutant emissions along with ambient weather condition, GPS readings, and vehicle engine data. The data were aggregated to represent the current Texas school bus fleet mix and rural versus urban miles driven. The results of statistical analysis showed that using B20 had no significant effect on the level of NOx and CO₂ emissions by the school buses. In contrary, it was found that the biodiesel resulted in a significant decrease of HC and increase of CO emissions.

Emerging vehicle technologies such as hybrids, flex-fuel, electric, and fuel cells are projected to exceed 25% of total light-duty vehicle sales by 2030. Because of their higher energy efficiency, hybrid electric vehicles (HEVs) produce lower emissions of greenhouse gases such as CO₂ than comparable gasoline vehicles. Measurements of selected advanced gasoline and diesel direct injection vehicles and gasoline-electric hybrid vehicles indicate that the HEV had the lowest emissions and highest fuel economy. One study concluded that replacing all conventional vehicles with HEV's could cut total CO and NO_x emissions in half. Flex-fuel vehicles that can use either gasoline or ethanol 85 (E85), a blend of 85% ethanol and 15% gasoline by volume have sensors that can analyze the fuel-air mixture and adjust the fuel injection and timing. Since ethanol is an oxygenated fuel, the use of ethanol may reduce emissions of products of incomplete combustion including CO and HC. However, the oxygenate may tend to increase NO_x emissions because of lean combustion. The use of blends with a high percentage of ethanol in the mix was found to produce increased emissions of NO_x and aldehydes as the ethanol content increased. However, measurements of flex-fuel Chevrolet Lumina vehicles indicated that the use of E85 may decrease vehicle CO, HC and NO_x emissions, but increase aldehydes emissions when compared to gasoline vehicles showed that NO_x emissions increased with increasing ethanol content for some fuels, but were unaffected by ethanol content for other fuels, depending on fuel volatility. Hochhauser found that use of ethanol fuel may increase vehicle permeation emissions of VOC. Therefore, flex-fuel vehicles do not assure lower emissions for at least some pollutants compared to dedicated gasoline vehicles. The objective of this study is to develop an advanced modeling system to quantify influences of land use and vehicle technologies on on-road vehicle emissions such as CO₂, CO, and NO_x. The main focus here is to demonstrate a methodology for assessing how differences in driving cycles affect link-based average emission rates for selected vehicle technologies. The methodology requires second-by-second data, with a preference for real-world in-use data where possible. The methodology is illustrated here based on data from one flex-fuel vehicle that was measured during actual driving using a portable emission measurement system (PEMS) on both gasoline and E85 and for one HEV that was tested on a chassis dynamometer. Testing for the flex-fueled vehicle was conducted by Instituto Superior Técnico (IST) in Lisbon, Portugal. The flex-fuel vehicle is a European 2006 flex-fuel Ford Focus wagon with a 1.8 liter engine (92 kW/6000rpm, 165 Nm/4000rpm). By comparison, the U.S. version of the Focus has a 2.0 liter engine (97 kW/6000rpm, 175 Nm/4000rpm). The HEV is a 2001 Toyota Prius with a 1.5 liter gasoline engine.

The transportation sector is responsible for roughly one third of national carbon dioxide emissions, making it a prime candidate for emission reductions. While no national policy to control greenhouse gases has yet been developed, many state and local governments have taken actions to reduce emissions. Twenty-eight states have adopted climate action plans, and 128 city and county governments are participating in an initiative to reduce emissions. While California has regulated tailpipe emissions of greenhouse gases, New York has enacted requirements on the transportation planning side. The 2002 New York State Energy Plan required metropolitan planning organizations (MPOs) in the state to conduct a greenhouse gas energy analysis as part of the transportation planning process for regionally significant projects. This paper provides an overview of the transportation/climate change connection and its importance to New York, summarizes the requirements of the Energy Plan and examines the analyses conducted by three of the thirteen MPOs in New York. It synthesizes their findings, and assesses what effects the greenhouse gas analyses have had on the transportation planning decision-making process and the potential for achieving greenhouse gas reductions from such exercises. Further, this paper will compare the methods used by the MPOs to quantify greenhouse gas emissions and to conduct the analysis, and recommend areas where further methodological development is needed or available for future planning documents. With political and scientific attention increasing, the transportation sector may face some form of emission reduction targets in the future—whether mandatory or voluntary. Ultimately, this paper provides a case study on the potential for New York State's Energy Plan requirements to serve as model for gaining emission reductions through the transportation planning process.

The U.S. Department of Transportation and the U.S. Geological Survey are performing a collaborative investigation of the potential impacts of climate change and variability on the transportation systems and infrastructure of that portion of the Gulf Coast extending from Mobile, Alabama to Galveston, Texas. The purpose is to understand the risks to transportation and to identify the range and timing of potential adaptation strategies that may be desirable. Changes in both average and extreme temperatures and precipitation are examined along with changes in sea level, land subsidence, and the frequency and intensity of hurricanes. Implications for long-range transportation planning and investment build on an assessment of potential impacts on individual modes of transportation. Adapting to climate change and variability can be accomplished within the framework of the existing transportation planning process, although changes in both the range of impacts considered and current institutional arrangements and partnerships may be desirable.