154 research outputs found
Emission model sensitivity analysis: The value of smart phone weight-mile tax truck data
This research serves to evaluate the potential use of a system developed by the Oregon Department of
Transportation (ODOT) for emission estimates. The data collection system developed by ODOT
–
Truck
Road Use Electronics (TRUE)
–
includes a smart phone application with a Global Positioning System
(GPS) device and microprocessor.
Previous research with the
TRUE
data served to demonstrate its use
for important ancillary applications such as highly accurate trip generation rates and m
obility
performance measures. In addition, it was shown that the TRUE data has strong potential use for safety,
accessibility and connectivity, system condition and environmental stewardship performance measures.
This new research builds on that past work
and evaluates the potential use of the TRUE data for
emissions estimates that take into account truck type details, truck weight and detailed speed profiles. A
sensitivity analysis using the U.S. Environmental Protection Agency's (EPA) Motor Vehicle Emissi
on
Simulator 2010b (MOVES2010b) is performed in order to understand the level of error that might be
encountered when such detailed data are not available. The impact of grade on emissions estimates is also
considered. Results indicate that TRUE data in in
tegration with Oregon Department of Transportation
(ODOT) weight
-
mile tax (WMT) data will greatly improve the accuracy of emissions estimations at the
project and regional level
Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis
Background: Identification of reliable outcome predictors in coronavirus disease 2019 (COVID-19) is of paramount importance for improving patient's management. Methods: A systematic review of literature was conducted until 24 April 2020. From 6843 articles, 49 studies were selected for a pooled assessment; cumulative statistics for age and sex were retrieved in 587 790 and 602 234 cases. Two endpoints were defined: (a) a composite outcome including death, severe presentation, hospitalization in the intensive care unit (ICU) and/or mechanical ventilation; and (b) in-hospital mortality. We extracted numeric data on patients’ characteristics and cases with adverse outcomes and employed inverse variance random-effects models to derive pooled estimates. Results: We identified 18 and 12 factors associated with the composite endpoint and death, respectively. Among those, a history of CVD (odds ratio (OR) = 3.15, 95% confidence intervals (CIs) 2.26-4.41), acute cardiac (OR = 10.58, 5.00-22.40) or kidney (OR = 5.13, 1.78-14.83) injury, increased procalcitonin (OR = 4.8, 2.034-11.31) or D-dimer (OR = 3.7, 1.74-7.89), and thrombocytopenia (OR = 6.23, 1.031-37.67) conveyed the highest odds for the adverse composite endpoint. Advanced age, male sex, cardiovascular comorbidities, acute cardiac or kidney injury, lymphocytopenia and D-dimer conferred an increased risk of in-hospital death. With respect to the treatment of the acute phase, therapy with steroids was associated with the adverse composite endpoint (OR = 3.61, 95% CI 1.934-6.73), but not with mortality. Conclusions: Advanced age, comorbidities, abnormal inflammatory and organ injury circulating biomarkers captured patients with an adverse clinical outcome. Clinical history and laboratory profile may then help identify patients with a higher risk of in-hospital mortality
Mapping the nonlinear optical susceptibility by noncollinear second harmonic generation
We present a method, based on noncollinear second harmonic generation, to
evaluate the non-zero elements of the nonlinear optical susceptibility. At a
fixed incidence angle, the generated signal is investigated by varying the
polarization state of both fundamental beams. The resulting polarization charts
allows to verify if Kleinman symmetry rules can be applied to a given material
or to retrieve the absolute value of the nonlinear optical tensor terms, from a
reference measurement. Experimental measurements obtained from Gallium Nitride
layers are reported. The proposed method does not require an angular scan thus
is useful when the generated signal is strongly affected by sample rotationComment: To appear on Opt. Let
Exploring the Effects of Adaptive Traffic Systems
Researchers conduct an in-depth analysis of traffic performance and associated vehicular emissions, before and after the installation of a SCATS unit
Methodology for Estimating Bicyclist Acceleration and Speed Distributions at Intersections
As cities across North America install infrastructure to accommodate a growing number and variety of bicyclists, installation of bicycle-specific traffic signals is a common design element. A recent survey showed a lack of consistency in design and timing. In particular, minimum green signal timing is highly dependent on the assumed acceleration and speed performance of bicyclists, but no detailed methodology exists to estimate these performance values. However, recent American Association of State Highway and Transportation Officials (AASHTO), Caltrans and National Association of City Transportation Officials (NACTO) documents require that an adequate clearance interval shall be provided, and that in determining this minimum interval field investigation of bicyclists’ speeds is recommended. Furthermore, even if detailed video trajectories are available, the determination of a value for field speed and acceleration is not trivial because values of speeds and accelerations are a function of time and individual bicyclist performance. The purpose of this research is to develop and apply a general methodology to estimate bicyclists’ acceleration and speed for traffic signal timing applications. Utilizing physical equations of motion, this research analytically derives expressions that can be used to classify an individual bicyclist’s performance as a function of the observed acceleration profile. The analysis indicates that four basic acceleration profiles are possible and the profiles can be obtained using a parsimonious field-data collection method. The methodology is successfully applied to two intersections in Portland, OR. A detailed statistical analysis shows that the results are intuitive and that the methodology successfully categorizes bicyclists’ performance variations due to topography or demographic characteristics
Safety Effectiveness of Pedestrian Crossing Enhancements
Over the last decade, the Oregon DOT and other agencies have systematically implemented many pedestrian crossing enhancements (PCEs) across the state. This study explored the safety performance of these enhanced crossing in Oregon. Detailed data were collected on 191 crossings. Supplemental data items included crossing location information, route characteristics, surrounding land use and crossing enhancement descriptions. Pedestrian volume at the crossing locations was a highly desirable but unavailable data element. To characterize pedestrian activity, a method was developed to estimate ranges for pedestrian crosswalk activity levels based on the land use classification at the census block level and the presence of pedestrian traffic generators such as bus stops, schools, shopping centers and hospitals within a 0.25-mile radius. Each crosswalk was categorized into one of six levels of activity – very low, low, medium-low, medium, medium-high and high. Crash data for the 2007-2014 period were assembled for the safety analysis. After filtering, 62 pedestrian crashes and 746 rear-end crashes were retained for further analysis. The crash data were merged and analyzed. Crash patterns and risk ratios were explored. The most important trend observed was a shift (reduction) in the pedestrian crash severity after the installation of the crosswalk treatments. This shift was from fatal and injury A crash type to lower severity crashes of injury B and injury C. For pedestrian crashes, increases in the risk ratio were observed for increases in the number of lanes, the posted speed, and estimated pedestrian activity level. Similar trends were observed for rear-end crashes. Due to data limitations, subsequent safety analysis focused on installations of RRFB crossing enhancements. A CMF for RRFB installations was estimated. The CMFS for pedestrian crashes are 0.64 +/- 0.26 using a simple before-after analysis; for rear-end crashes: 0.93 +/- 0.22 using an empirical Bayes analysis approach
Evaluation of Transportation Microenvironments Through Assessment of Cyclysts\u27 Exposure to Traffic-Related Particulate Matter
It is well established that vehicles powered by carbon-based fuels (e.g. gasoline, diesel) have a negative impact on air quality, especially in urban centers. Traditionally, air quality conformity studies analyze the macroenvironmental impact of transportation corridors, as they relate to regional air quality management concerns. Urban residents spend a considerable amount of outdoor time in transportation microenvironments as pedestrians, bicycle commuters, people waiting to use public transport, residents and workers situated along roadways, and commuters within vehicles. An emerging area of research has shown that human health impacts within transport microenvironments can be considerable, but have not been well-characterized. As urban public policies increasingly encourage the use of multi-mode commuting in dense urban centers, decisionmakers need reliable modeling tools to predict and mitigate the health consequences of vehicle-related emissions in transportation microenvironments. This project proposes unique integration of real-time multi-modal personal exposure monitoring with real-time detailed traffic monitoring in order to develop a computer model that links traffic characteristics, emissions, built environment configuration, mode of travel and health impacts.
Existing emission and dispersion models do not take direct account of the dynamic nature of traffic and how emissions impact the health of the diversity of urban dwellers, bus commuters, pedestrians, and bicycle riders. Typical approaches use highly aggregated vehicle data and computed link speeds to assign an emission factor to the traffic, an assumed proportion of which is trucks. In addition, existing methods to assess environmental impacts tend to focus on the production source of the pollutant not the impacts, which require information on population activities and its proximity to vehicle flows. Personal exposure studies document significant air quality impacts within the transportation microenvironment but do not integrate dynamic traffic and emission analysis.
Previous research argues for a comprehensive approach. From the perspective of mitigating transportation impacts, it is significant to understand: a) exposure to the pollution, which in turn requires assessment of where people are in relation to the source of the pollutant, and b) the relation between pollution and vehicle flows. This research will target highly polluted high exposure hotspots in Portland, e.g. high traffic flows running through a major trip destination area for shopping, entertainment, education, or health care highly dependent on mode of travel, traffic levels and type, and built environment characteristics. Our approach is to conduct field studies to measure personal exposure to particulate matter as a function of transportation mode through pre-determined routes in the city. Exposure levels, position, time and rate of travel will be recorded. Simultaneously we will collect detailed traffic data that will provide type/number of vehicle, speed of travel and start/stop behavior. GIS analysis of the urban form and land use characteristics will establish built environment parameters. These data will be integrated into a built environment-travel mode-exposure model. The major scientific innovations offered by this project are: 1) integration of detailed and real-time exposure/emissions with a real-time traffic measurement approach, and 2) development of an integrated emissions and transportation model that combines traffic characteristics, emissions, built environment configuration, mode of travel and predicted health impacts. The outcomes of the research will be of importance to the general public, urban communities, departments of transportation charged with managing urban traffic, and public health authorities
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