Active Travel Co-Benefits of Travel Demand Management Policies that Reduce Greenhouse Gas Emissions, MTI Report 12-12

There is increasing evidence that improved health outcomes may be significant co-benefits of land use plans and transport policies that increase active transport (or walking and biking for purposeful travel) and reduce greenhouse gas emissions (GHGs) from vehicle miles traveled (VMT). A greater understanding of these benefits may broaden the constituency for regional planning that supports local and national GHG reduction goals. In this study, California’s activity-based travel demand model (ABM) is applied to (1) demonstrate how this new generation of travel models can be used to produce the active travel data (age and sex distributions) required by comparative risk assessment models to estimate health outcomes for alternative land use and transport plans and to (2) identify the magnitude of change in active travel that may be possible from land use, transit, and vehicle pricing policies for California and its five major regions for a future 2035 time horizon. The results of this study suggest that distance-based vehicle pricing may increase walking by about 10% and biking by about 17%, and concurrently GHG from VMT may be reduced by about 16%. Transit expansion and supportive development patterns may increase active travel by about 2% to 3% for both walk and bike modes while also reducing VMT by about 4% on average. The combination of all three policies may increase time spent walking by about 13% and biking by about 19%, and reduce VMT by about 19%

Transportation Futures: Policy Scenarios for Achieving Greenhouse Gas Reduction Targets, MNTRC Report 12-11

It is well established that GHG emissions must be reduced by 50% to 80% by 2050 in order to limit global temperature increase to 2°C. Achieving reductions of this magnitude in the transportation sector is a challenge and requires a multitude of policies and technology options. The research presented here analyzes three scenarios: changes in the perceived price of travel, land-use intensification, and increases in transit. Elasticity estimates are derived using an activity-based travel model for the state of California and broadly representative of the U.S. The VISION model is used to forecast changes in technology and fuel options that are currently forecast to occur in the U.S., providing a life cycle GHG forecast for the road transportation sector. Results suggest that aggressive policy action is needed, especially pricing policies, but also more on the technology side. Medium- and heavy-duty vehicles are in particular need of additional fuel or technology-based GHG reductions

High frequency of central nervous system involvement in transformed Waldenstrom macroglobulinemia

Histologicaltransformation (HT) to diffuse large B-cell lymphoma (DLBCL) is a rare event in Waldenström macroglobulinemia (WM) and is associated with a poor prognosis.1-4 It confers an inferior outcome compared with WM patients without HT.2,3 Most transformed WM patients present with elevated serum lactate dehydrogenase (LDH) levels and extranodal disease.1 Among extranodal sites, the central nervous system (CNS) is one of the most frequently involved sites identified at diagnosis of transformed WM (ranging from 13% to 18%).1,3 However, the prognostic value of CNS involvement is unknown, and the rate of CNS involvement at relapse has not been previously reported in this setting.This work was supported by Cancer Research UK [C355/A26819], FC AECC, and AIRC under the “Accelerator Award Program” [EDITOR] to M.A. and R.G.-S

Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches

Variation in general supportive and preventive intensive care management of traumatic brain injury: a survey in 66 neurotrauma centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study

Abstract Background General supportive and preventive measures in the intensive care management of traumatic brain injury (TBI) aim to prevent or limit secondary brain injury and optimize recovery. The aim of this survey was to assess and quantify variation in perceptions on intensive care unit (ICU) management of patients with TBI in European neurotrauma centers. Methods We performed a survey as part of the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. We analyzed 23 questions focused on: 1) circulatory and respiratory management; 2) fever control; 3) use of corticosteroids; 4) nutrition and glucose management; and 5) seizure prophylaxis and treatment. Results The survey was completed predominantly by intensivists (n = 33, 50%) and neurosurgeons (n = 23, 35%) from 66 centers (97% response rate). The most common cerebral perfusion pressure (CPP) target was > 60 mmHg (n = 39, 60%) and/or an individualized target (n = 25, 38%). To support CPP, crystalloid fluid loading (n = 60, 91%) was generally preferred over albumin (n = 15, 23%), and vasopressors (n = 63, 96%) over inotropes (n = 29, 44%). The most commonly reported target of partial pressure of carbon dioxide in arterial blood (PaCO2) was 36–40 mmHg (4.8–5.3 kPa) in case of controlled intracranial pressure (ICP) < 20 mmHg (n = 45, 69%) and PaCO2 target of 30–35 mmHg (4–4.7 kPa) in case of raised ICP (n = 40, 62%). Almost all respondents indicated to generally treat fever (n = 65, 98%) with paracetamol (n = 61, 92%) and/or external cooling (n = 49, 74%). Conventional glucose management (n = 43, 66%) was preferred over tight glycemic control (n = 18, 28%). More than half of the respondents indicated to aim for full caloric replacement within 7 days (n = 43, 66%) using enteral nutrition (n = 60, 92%). Indications for and duration of seizure prophylaxis varied, and levetiracetam was mostly reported as the agent of choice for both seizure prophylaxis (n = 32, 49%) and treatment (n = 40, 61%). Conclusions Practice preferences vary substantially regarding general supportive and preventive measures in TBI patients at ICUs of European neurotrauma centers. These results provide an opportunity for future comparative effectiveness research, since a more evidence-based uniformity in good practices in general ICU management could have a major impact on TBI outcome

A Review of the International Modeling Literature: Transit, Land Use, and Auto Pricing Strategies to Reduce Vehicle Miles Traveled and Greenhouse Gas Emissions

As the media document very real evidence of global climate change and the debate over humans' role precipitating this change has ended, California led the nation by passing the first global warming legislation in the U.S. California is tasked with reducing green house gas (GHG) emissions to 1990 levels by 2020 and 80% below 1990 levels by 2050. The California Air Resources Board estimates that significant GHG reductions from passenger vehicles can be achieved through improvements in vehicle technology and the low carbon fuel standard; however, these reductions will not be enough to achieve 1990 levels if current trends in vehicle kilometers traveled (VKT) continue. Currently, most operational regional models in California have limited ability to represent the effects of transit, land use, and auto pricing strategies; efforts are now underway to develop more advanced modeling tools, including activity-based travel and land use models. In the interim, this paper reviews the international modeling literature on land use, transit, and auto pricing policies to suggest a range of VKT and GHG reduction that regions might achieve if such policies were implemented. The synthesis of the literature categorizes studies, by geographic area, policy strength, and model type, to provide insight into order of magnitude estimates for 10-, 20-, 30-, and 40-years time horizons. The analysis also highlights the effects of modeling tools of differing quality, policy implementation timeframes, and variations in urban form on the relative effectiveness of policy scenarios

Travel Effects and Associated Greenhouse Gas Emissions of Automated Vehicles

In much the same way that the automobile disrupted horse and cart transportation in the 20th century, automated vehicles (AVs) hold the potential to disrupt our current system of transportation and the fabric of our built environment in the 21st century. Experts predict that vehicles could be fully automated by as early as 2025 or as late as 2035. The public sector is just beginning to understand AV technology and to grapple with how to accommodate it in our current transportation system.Research on AVs is extremely important because AVs may significantly disrupt our transportation system with potentially profound effects, both positive and negative, on our society and our environment. However, this research is very hard to do because fully AVs have yet to travel on our roads. As a result, AV research is largely conducted by extrapolating effects from current observed behavior and drawing on theory and models. Both the magnitude of the mechanism of change and secondary effects are often uncertain. Moreover, the potential for improved safety in AVs drive the mechanisms by which vehicle miles traveled (VMT), energy, and greenhouse gas (GHG) emissions may change. We really don’t know whether AVs will achieve the level of safety that will allow for completely driverless cars, very short headways, smaller vehicles, lower fuel use, and/or reduce insurance cost. We don’t know whether AV fleets will be harmonized to reduce energy and GHG emissions.In this white paper, the available evidence on the travel and environmental effects of AVs is critically reviewed to understand the potential magnitude and likelihood of estimated effects. The author outlines the mechanisms by which AVs may change travel demand and review the available evidence on their significance and size. These mechanisms include increased roadway capacity, reduced travel time burden, change in monetary costs, parking and relocation travel, induced travel demand, new traveler groups, and energy effects. They then describe the results of scenario modeling studies. Scenarios commonly include fleets of personal AVs and automated taxis with and without sharing. Travel and/or land use models are used to simulate the cumulative effects of scenarios. These models typically use travel activity data and detailed transportation networks to replicate current and predict future land use, traffic behavior, and/or vehicle activity in a real or hypothetical city or region.View the NCST Project Webpag

Verifying the Accuracy of Land Use Models Used in Transportation and Air Quality: A Case Study in the Sacramento, California Region

To help guide applications of more advanced models in policy studies, this paper presents an evaluation of model accuracy and induced demand in an integrated land use and transportation model, the 2000 Sacramento MEPLAN model. The model is currently used by the region's metropolitan planning organization (MPO) for land use projections. The accuracy of the model is assessed with validation tests that show how well the model predicts observed data over a ten-year period that are not used to estimate or calibrate the model. Forecasts are compared to observed 2000 land use and travel data to identify the magnitude of model error resulting from model functional forms and parameter specifications. Forecasts are also used to identify the model's representation of induced demand and to estimate actual induced demand. The model's representation of induced demand includes the change in land use (i.e., development and allocation) and travel (trips, distance, mode choice, and time) that results from new transportation capacity. The results illustrate how validation tests can be used to improve the application of uncertain models in policy studies requiring absolute accuracy such as conformity analysis (emissions budgets) and environmental impact analysis (level of roadway service)