Perspectives on subnational carbon and climate footprints: A case study of Southampton, UK

Sub-national governments are increasingly interested in local-level climate change management. Carbon- (CO2 and CH4) and climate-footprints—(Kyoto Basket GHGs) (effectively single impact category LCA metrics, for global warming potential) provide an opportunity to develop models to facilitate effective mitigation. Three approaches are available for the footprinting of sub-national communities. Territorial-based approaches, which focus on production emissions within the geo-political boundaries, are useful for highlighting local emission sources but do not reflect the transboundary nature of sub-national community infrastructures. Transboundary approaches, which extend territorial footprints through the inclusion of key cross boundary flows of materials and energy, are more representative of community structures and processes but there are concerns regarding comparability between studies. The third option, consumption-based, considers global GHG emissions that result from final consumption (households, governments, and investment). Using a case study of Southampton, UK, this chapter develops the data and methods required for a sub-national territorial, transboundary, and consumption-based carbon and climate footprints. The results and implication of each footprinting perspective are discussed in the context of emerging international standards. The study clearly shows that the carbon footprint (CO2 and CH4 only) offers a low-cost, low-data, universal metric of anthropogenic GHG emission and subsequent management

The 30/20 GHz fixed communications systems service demand assessment. Volume 2: Main report

A forecast of demand for telecommunications services through the year 2000 is presented with particular reference to demand for satellite communications. Estimates of demand are provided for voice, video, and data services and for various subcategories of these services. The results are converted to a common digital measure in terms of terabits per year and aggregated to obtain total demand projections

A Method for Evaluating and Prioritizing Candidate Intersections for Transit Signal Priority Implementation

Transit agencies seeking to improve transit service delivery are increasingly considering the deployment of transit signal priority (TSP). However, the impact of TSP on transit service and on the general traffic stream is a function of many factors, including intersection geometry, signal timings, traffic demands, TSP strategies and parameters, transit vehicle headways, timing when transit vehicles arrive at the intersection, etc. Previous studies have shown that depending on these factors, the net impact of TSP in terms of vehicle or person delay can be positive or negative. Furthermore, due to financial constraints, transit agencies are often able to deploy TSP at only a portion of all of the candidate intersections. Consequently, there is a need to estimate the impact of TSP prior to implementation in order to assist in determining at which intersections TSP should be deployed. Currently, the impacts of TSP are often estimated using microscopic simulation models. However, the application of these models is resource intensive and requires specialized expertise that is often not available in-house to transit agencies. In this thesis, an analytical model was proposed for estimating the delay impacts of green extension and early green (red truncation) TSP strategies. The proposed model is validated with analytical model reported in the literature and microscopic simulation model. This is followed by model sensitivity analysis. A software module is developed using the proposed model. The usefulness of the model is illustrated through its application to estimate the TSP performance. Finally, a prioritization is conducted on sixteen intersections with different geometric and operational traffic strategies. The overall results indicate that the proposed model is suitable for both estimating the pre-deployment and post-deployment TSP performance. The proposed model is suitable for implementation within a spreadsheet and requires considerably less effort, and less technical expertise, to apply than a typical micro-simulation model and therefore is a more suitable tool for transit agencies to use for prioritising TSP deployment

Shannon's measure of information, path averages and the origins of random utility models in transport itinerary or mode choice analysis

We interpret the often mentioned difference between Logsum and average utility in terms of Shannon's (1948) information measure S, leading to a Path Aggregation THeorem (PATH). It states that, in transport networks where unique measures of the utility of multiple paths are required for demand model formulation purposes and the true path choice model is Multinomial Logit (MNL), constructs based on weighted averages of path characteristics derived from multipath assignments always underestimate the utility of multiple paths, a deficit exactly equal to S (corresponding to minus-one times entropy) if the weights are the path choice probabilities. We study the properties of this S measure of aggregation error, along with those arising from other types of averages of path characteristics, outlining some implications for demand estimation and project appraisal. Notably, the validity of the PATH does not depend on the specific contents of the representative utility functions (RUF) associated to paths, such as their mathematical form or their eventual inclusion of alternative-generic constants (AGC). We show by simulation that averaging modes or sub-modes ― a frequent feature of traffic modeling studies ― can lead to important error in terms of level of traffic and welfare measurement. Concerning the mathematical form of the RUF, we recall that, after the publication of Abraham's 1961 random utility model (RUM) of road path choice deriving the Probit specification based on the Gaussian error distribution (and another specification based on the Rectangular error distribution), French engineers used this seminal approach as justification of road path choice formulae then in current use and assigned the name "Abraham's Law" to a particular standard one, effectively a "Logarithmic Logit" close to the logarithmic RUF carefully specified for Logit mode choice by Warner in 1962. For transit problems, the preference went to a linear RUF, as evidenced in Barbier's casual binomial Probit application to bus and metro, published in 1966, which may have inspired the later generalizations by Domencich and McFadden. In view of many founders' conscientiously crafted nonlinear Logit formulations, and more generally of the repeatedly demonstrated presence of nonlinearity in RUF path and mode specifications since their careful work 50 years ago, we analyze the impact of such nonlinearity on S. This impact is tractable through a comparison of measures S2 and S1 associated with two path choice models differing only in RUF form, as determined by Box-Cox transformations applied to their level-of-service (LOS) variables. We show that, although the difference between measures S2 and S1 may reach a minimum or a maximum with changes in LOS, the solution for such a turning point cannot be established analytically but requires numerical methods: the demonstrable impact on S of nonlinearity, or asymmetry of Logit curve response, is tractable, but only at non trivial computational cost. We point out that the path aggregation issue, whereby aggregation of paths by Logsums differs from aggregation of their characteristics by averages, is not limited to public transit (PT) projects with more or less "common" lines competing in dense urban transit networks (our particular Paris predicament motivating the analysis) but also arises in other modes whenever distinct itineraries or lines compete within a single mode. Concerning dense urban PT networks, we hypothesize that Logsums based on multiple path assignments treating all transit means (about 10 in our problem) as one modal network should, using Ockham's razor, be simpler than the insertion of a layer of choice hierarchies among such urban means based on non nested specifications embodying assumptions on the identity of "higher" and "lower" means, the latter reasserting the multiple path access problems the hierarchies were designed to solve in the first place. Concerning road networks, the proper accounting of multiple path use to avoid Shannon aggregation error points to an abandonment of Wardrop's equilibrium in favor of Logit choice. This completed shift should favor transit when it is the minority mode

Spatial analysis of passenger vehicle use and ownership and its impact on the sustainability of highway infrastructure funding

Across the United States, the sustainability of highway funding is at risk due to increasing need and uncertainty in the factors that drive revenue. Past studies on highway funding sustainability have identified that the root cause of changing highway revenue are the shifts in social demographics and economic characteristics. Unfortunately, from the revenue perspective (the focus of this dissertation), the ability of previous research to account for these factors has been rather limited in two ways; first, the inability to accurately assess current regional vehicle use (a typical prerequisite for statistical modeling of highway revenues) due to difficulties associated with collecting data for local roads; second, the inability to directly account for the spatial dependence and heterogeneity that inherently characterize vehicle use, vehicle ownership, and socioeconomic attributes. ^ In addressing these issues, this dissertation focuses on revenue uncertainty and investigates the socioeconomic factors that influence passenger vehicle use and ownership and, by extension, the revenue generated from this class of vehicles. Spatial econometric models were used to capture the complex spatial trends that characterize the relationship between the influential factors and vehicle use and ownership. The models were used to estimate the impact of long-term socioeconomic changes on highway revenue from passenger vehicles. ^ This dissertation developed a unified framework incorporating spatial econometric modeling of regional vehicle use and ownership. This dissertation showed that vehicle use and ownership exhibit spatial dependence and heterogeneity which is caused by the influence of neighboring regions and unobserved spatial factors. Therefore, the research accounted duly for spatial heterogeneity and dependence, resulting in a more accurate and unbiased estimation. Also, the research yielded results suggesting that vehicle use and ownership are a function of the characteristics of a region as well as it neighbors. ^ The unified framework includes a robust methodology to estimate the current vehicle miles traveled (VMT) for all roads within a geographic region. The methodological approach uses spatial interpolation to impute unknown road segment values, overcoming an issue that typically impairs the traditional link-specific approach for estimating VMT. ^ This dissertation determines that, in order for the current level of funding from state gas tax revenue to be sustainable, the gas tax would have to be annually increased between 2.59% to 3.41%, depending on the forecast socioeconomic conditions. This annual increase in gas tax would allow agencies to recoup the effective fuel tax losses due changing vehicle use and ownership, inflation, and increased fuel economies. Unlike revenue from fuel taxes, revenue from passenger vehicle VMT fees is not susceptible to changing vehicle fuel efficiencies. To ensure funding sustainability, an annual VMT fee increase between 1.66% to 2.48%, depending on the socioeconomic conditions, is required; this would account for fluctuations in vehicle use and counteract the impact of inflation. The dissertation also determined that, in the likely event that a state is unable to collect VMT fees from out-of-state drivers (vehicles registered outside of the state), the fees would need to be increased by 12% to ensure funding sustainability

A comparison of bobcat (Lynx rufus) habitat suitability models derived from radio telemetry and incidental observations

Habitat suitability models derived from data obtained from radio telemetry and citizen observations were developed to evaluate habitat selection of monitored bobcats, compare statewide habitat suitability models and maps developed using locations from telemetry and citizen observations, and produce statewide population estimates. In the winter of 2009-2010, adult bobcats were captured in southwest New Hampshire and equipped with GPS tracking collars. GPS locations were used to calculate home ranges and to build habitat suitability models using resource selection functions (RSF) following a used vs. available design. RSFs were also applied to recent reported statewide sightings. Comparisons between these two approaches did not support the use of solicited sightings to manage a statewide bobcat population. Statewide abundance estimates were made using a telemetry model and habitat-area requirements

An economic assessment of STOL aircraft potential including terminal area environmental considerations, volume 1

The results of an economic and environmental study of short haul airline systems using short takeoff and landing (STOL) aircraft are presented. The STOL system characteristics were optimized for maximum patronage at a specified return on investment, while maintaining noise impact compatibility with the terminal area. Supporting studies of aircraft air pollution and hub airport congestion relief were also performed. The STOL concept specified for this study was an Augmentor Wing turbofan aircraft having a field length capability of 2,000 ft. and an effective perceived noise level of 95 EPNdB at 500 ft. sideline distance. An economic and environmental assessment of the defined STOL system and a summary of the methodology, STOL system characteristics and arena characteristics are provided