Key beliefs and attitudes for sea-level rise policy

This article reviews key measures of public opinion on sea-level rise (SLR): beliefs, attitudes, issue prioritization, and policy support. To do so, we first assess the influence of SLR beliefs and attitudes on issue prioritization and policy support using state-level data. Then, we compare the state findings to other surveys conducted in a hot spot of rising coastal waters, the U.S. Mid-Atlantic, to better understand the landscape of public opinion. Our findings indicate that, as in studies of climate change public opinion, belief certainty that SLR is happening and attitudes about its consequences significantly influence issue prioritization and policy support. Compared to climate change, SLR demonstrates less salience, but is similarly a low public priority. Nevertheless, the public supports governmental policies that address the issue, preferring strategies that discourage new construction in high risk areas and employ “soft” protection through natural barriers. Among the least popular approaches are those that implement hard barriers to defend against encroaching seas. Communication programs and public consultation by governments can benefit from the use of survey data to support evidence-based decision-making.     

Analysis of cost estimation disclosure in environmental impact statements for surface transportation projects

Reliability in cost estimates in publicly funded projects is more important today than ever with increased governmental funding to infrastructure projects and associated accountability requirements, but surface transportation projects, large and small, in the United States have a legacy of cost overruns. The problems with these overruns start with the cost estimation process before projects begin. Studies have shown that early cost estimations reflect best-case scenarios rather than realistic expectations, and have attributed technical, economic, psychological, and political reasons for underestimation. The primary objectives of this research were to determine how costs have been presented and updated in environmental impact statements, to identify endemic technical problems with cost estimation during the environmental review of surface transportation projects, and to develop recommendations for improving cost estimation and disclosure. Cost estimation methods were analyzed from the documents of 100 projects, including draft environmental impact statements, final environmental impact statements, and records of decision. The study concluded that the lack of guidance on how to include cost estimation in environmental review revealed itself in the level of detail and attention given to estimating costs. Agencies omitted or included various aspects of cost estimation randomly. Professional organizations should fill the gap of the need for specific guidance to cost estimation for environmental review so it can evolve as a state of the practice.     

Vulnerability of Coastal Resort Cities to Mean Sea Level Rise in the Mexican Caribbean

We evaluated the potential economic impacts of increasing sea level rise (SLR) along the Mexican Caribbean where there are major gaps in our understanding of the mechanisms controlling flooding duration and frequency associated to future ecological and economic impacts. We determined the negative economic impact of SLR on infrastructure in the largest urban centers (Cancun, Isla Mujeres, Playa del Carmen, Puerto Morelos and Cozumel) in the state of Quintana Roo (Mexico) that are considered the largest tourism “hot spots” (resort cities) in the country. The tourism industry in this coastal area injects >8 billion dollars year^?1 to the Mexican economy. Our conservative economic assessment regarding the impact of SLR, under a 1?m scenario for all coastal cities is $330 million USD. Further projections for worst scenarios (SLR >2 m) show a non-linear trend where the cost of inaction can reach up to $1.4 billion USD (2?m SLR scenario) and $2.3 billion USD (3?m SLR scenario). This potential loss of infrastructure, as construction cost, is staggering and represents a robust baseline to start evaluating with more detail future impacts of climate variability and change on the Mexican Caribbean coastline.     

Community Severance: Where Is It Found and at What Cost?

Community severance occurs when transport infrastructure or motorised traffic divides space and people. Despite the growing awareness of its effects on the wellbeing of local communities, the problem is not usually assessed quantitatively or assigned a monetary value. This paper reviews existing practice and research on quantitative methods dealing with community severance. The problem is first decomposed into a series of questions, which are then used as a base to review the methods found in governmental guidance documents, technical reports, and academic studies. The paper ends with recommendations for the integration of severance issues into transport planning.     

Intelligent transportation systems: an impact analysis for Michigan

Are Intelligent Transportation Systems (ITS) affecting transportation industry only? ITS are currently perceived as a contribution to transportation industry only; however, by quantitatively analyzing the economic impact of ITS on the state of Michigan, this work attempts to answer the posed question. The quantitative economic analysis is carried out through the well‐established Leontief's Input–Output (I‐O) model. This model is employed to establish ITS effects on each industry by detailing RIMS II I‐O tables for Michigan constructed from the national I‐O tables. Major savings by ITS identified as reduced time delays and fuel cost savings are quantitatively simulated thereby generating an overall cost reduction factor which is incorporated in Michigan I‐O tables to modify their characteristics. ITS impact on each industry in I‐O tables is achieved by maximizing effects on certain selected industries. Impact multipliers that are customary macro‐economic measures for I‐O analysis are then calculated for all the aggregated industries. Multipliers comparison for the three cases namely before ITS implementation, conventional improvement methods, and after ITS implementation is evaluated. These values suggest greater economic benefits that may be achieved by statewide implementation of the ITS. Copyright © 2010 John Wiley & Sons, Ltd.     

Where do cyclists ride? A route choice model developed with revealed preference GPS data

To better understand bicyclists’ preferences for facility types, GPS units were used to observe the behavior of 164 cyclists in Portland, Oregon, USA for several days each. Trip purpose and several other trip-level variables recorded by the cyclists, and the resulting trips were coded to a highly detailed bicycle network. The authors used the 1449 non-exercise, utilitarian trips to estimate a bicycle route choice model. The model used a choice set generation algorithm based on multiple permutations of path attributes and was formulated to account for overlapping route alternatives. The findings suggest that cyclists are sensitive to the effects of distance, turn frequency, slope, intersection control (e.g. presence or absence of traffic signals), and traffic volumes. In addition, cyclists appear to place relatively high value on off-street bike paths, enhanced neighborhood bikeways with traffic calming features (aka “bicycle boulevards”), and bridge facilities. Bike lanes more or less exactly offset the negative effects of adjacent traffic, but were no more or less attractive than a basic low traffic volume street. Finally, route preferences differ between commute and other utilitarian trips; cyclists were more sensitive to distance and less sensitive to other infrastructure characteristics for commute trips.     

The objective versus the perceived environment: what matters for bicycling?

This paper examines the relationship between the objectively measured and perceived built environment, and the relative strength of their association with bicycling behavior. By drawing on socio-cognitive theory, a conceptual model was proposed to explain the relationships between the objective environment, perceived environment, and bicycling behavior. Objective and perceived bike environments were measured using two latent constructs and structural equation modeling was employed to estimate the models based on data from three neighborhoods in Portland, Oregon. Results of this study showed that the perception of the environment had a direct and significant effect on bicycling behavior, while the direct effect of the objective environment on bicycling behavior became insignificant when controlling for perception. We therefore concluded that the objective environment may only indirectly affect bicycling behavior by influencing perceptions. An objectively good environment for bicycling was necessary but not sufficient for bicycling. Intervention programs to improve people’s perceptions of the environment may be necessary to reap the full potential of planning and design policies.     

Green transportation taxes and fees: A survey of public preferences in California

This paper presents the results of a survey testing whether California residents would support the concept of “green” transportation taxes and fees. Green taxes and fees would be set at variable rates, with higher rates for more polluting vehicles and lower rates for those that pollute less. The results show that the concept of green transportation taxes and fees strongly appeals to Californians. The survey data were also analyzed to identify if sub-groups within the state were particularly likely to support or oppose green transportation taxes and fees. Support for the green taxes and fees held at 50% or higher across most population sub-groups. Bivariate analysis showed that demographic factors were generally poor predictors of support, but that some attitudinal and knowledge variables did correlate with increased support for the green taxes and fees. Multivariate analysis confirmed that pro-environment and pro-government attitudes are significant and strong predictors of support for increasing transportation revenues.     

Development of a sensor system for traffic data collection

Although many types of traffic sensors are currently in use, all have some drawbacks, and widespread deployment of such sensor systems has been difficult due to high costs. Due to these deficiencies, there is a need to design and evaluate a low cost sensor system that measures both vehicle speed and counts. Fulfilling this need is the primary objective of this research. Compared to the many existing infrared-based concepts that have been developed for traffic data collection, the proposed method uses a transmission-based type of optical sensor rather than a reflection-based type. Vehicles passing between sensors block transmission of the infrared signal, thus indicating the presence of a vehicle. Vehicle speeds are then determined using the known distance between multiple pairs of sensors. A prototype of the sensor system, which uses laser diode and photo detector pairs with the laser directly projected onto the photo detector, was first developed and tested in the laboratory. Subsequently this experimental prototype was implemented for field testing. The traffic flow data collected were compared to manually collected vehicle speed and traffic counts and a statistical analysis was done to evaluate the accuracy of the sensor system. The analysis found no significant difference between the data generated by the sensor system and the data collected manually at a 95% confidence interval. However, the testing scenarios were limited and so further analysis is necessary to determine the applicability in more congested urban areas. The proposed sensor system, with its simple technology and low cost, will be suitable for saturated deployment to form a densely distributed sensor network and can provide unique support for efficient traffic incident management. Additionally, because it may be quickly installed in the field without the need of elaborate fixtures, it may be deployed for use in temporary traffic management applications such as traffic management in road work zones or during special events.     

Coming Soon to a Fjord Near You: Future Jellyfish Scenarios in a Changing Climate

Over the last decades, a dense population of the deep-sea/oceanic scyphozoan jellyfish Periphylla periphylla has established itself as top predator in the Trondheimsfjord in Norway, which has caused the traditional fisheries in this fjord to suffer. This was, however, not the first fjord this jellyfish invaded, and data suggest that it will not be the last one, either. With warmer temperatures, the jellyfish is moving northward in Norway, but not all fjords are created equal, and it is not thriving or taking up residence just anywhere. The current article explores three fjords in which Periphylla periphylla has become the top predator and outcompeted former ones. The main question of interest is why the jellyfish becomes dominant in one fjord and not another. The next question is which other Norwegian fjords further north exist with similar characteristics where we therefore would expect Periphylla periphylla to proliferate in the future. The latter is important from a policy and adaptation perspective for the local community of people, since the proliferation of the species unmistakably leads to fewer fish for commercial harvest and potentially less attractive waters for tourism purposes. Results show that three northern fjords, the Skjerstadfjorden the Holandsfjorden, and Stordjupna in the Vestfjord appear to be particularly vulnerable to a future Periphylla periphylla invasion.