Correlation between automotive CO, HC, NO, and PM emission factors from on-road remote sensing: implications for inspection and maintenance programs

Carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO) emission factors (EFs) are measured with a commercial vehicle emissions remote sensing system (VERSS) during a large-scale vehicle exhaust emissions study in Las Vegas. Particulate matter (PM) EFs are simultaneously measured for individual vehicles with a newly developed PM-VERSS based on ultraviolet backscatter light detection and ranging (Lidar). The effectiveness of CO and HC EFs as proxy for NO and PM EFs for spark-ignition vehicles is evaluated. Poor correlations were found between EFs for pollutants on an individual vehicle basis indicating that high EFs for one or more pollutants cannot be used as a predictor of high EFs for other pollutants. Stronger functional relationships became evident after averaging the EF data in bins based on rank-order of a single pollutant EF. Low overlap between the highest 10% emitters for CO, HC, NO, and PM was found. These results imply that for an effective reduction of the four pollutants, inspection and maintenance (I/M) programs, including clean screening, should measure all four pollutants individually. Fleet average CO and HC concentrations determined by gaseous VERSS were compared with fleet average CO and HC concentrations measured at low-idle and at high-idle during local I/M tests for spark-ignition vehicles. The fleet average CO concentrations measured by I/M tests at either idle were about half of those measured by remote sensing. The fleet average high-idle HC concentration measured by I/M tests was about half of that measured by VERSS while low-idle I/M and VERSS HC average concentrations were in better agreement. For a typical vehicle trip, most of the fuel is burned during non-idle conditions. I/M measurements collected during idling conditions may not be a good indicator of a vehicle’s potential to be a high emitter. VERSS measurements, when the vehicle is under a load, should more effectively identify high emitting vehicles that have a large contribution to the mobile emissions inventory.     

Exploring active transportation investments and associated benefits for municipal budgets: a scoping review

Municipalities play an important role in the planning and development of communities that support active transportation (AT), which refers to human-powered modes of travel, such as walking and cycling. Municipal-level stakeholders involved in land-use and transportation infrastructure planning consider multiple social, environmental and economic considerations to inform decision-making and investments in AT. Evidence around the fiscal benefits of AT investment for local governments has not been systematically identified. This scoping review sought to explore the existing evidence regarding investments in AT and opportunities for savings on municipal expenditures and revenue generation. In total, 7060 records were located and screened; of which 162 full-text articles were reviewed. Ultimately, 23 articles met our inclusion criteria and were included in this review. The available evidence focuses on potential economic benefits of AT in the areas of tax revenues, property values, consumer spending and employment, all of which are relevant sources of revenue generation in municipal operating budgets. An evidence gap was identified regarding AT infrastructure investments and benefits corresponding to municipal expenditures (e.g. maintenance cost savings). Notably, a large portion of literature was published after 2009, suggesting that municipal-level evidence on the fiscal benefits of AT investments may just be emerging.     

Load Transfer Analysis of a Bus Bay Section Under Standard Rollover Test Using <Emphasis Type="Italic">U</Emphasis>*<Subscript>M</Subscript> Index

Bus rollover accidents are receiving increasing attention due to the associated high fatality rate. In order to improve the bus structural performance during the rollover collision, it is necessary to investigate how the impact force is transferred within the bus superstructure. This paper introduced a method for studying the load transfer behavior of the bus superstructure during the standard rollover test by using the U * _M index. A bus bay section was used as the sample structure to demonstrate the proposed method. The result of the paper reveals that the load transfer analysis based on the U * _M index can provide engineers with the insight of the structural issues and the direction to improve the structural performance, which cannot be accomplished through the conventional finite element analysis.     

Prospects for computer aided railway scheduling: perspectives from users and parallels from mass transit

Railway scheduling faces new challenges as competition and, in many parts of the world, privatisation require ever better results, both in terms of minimising the resources used and maximising the performance achieved by those resources. It is therefore surprising that in practice railway scheduling tasks appear to be performed largely without the use of optimizing models. This paper takes two different perspectives, a case study of user needs from the UK railway industry and a comparative analysis with mass transit scheduling systems, to consider why this might be and assesses what the future prospects are for computer aided railway scheduling.

A number of conclusions are drawn: that optimization models need to be integrated with software packages that meet schedulers' data management needs; that researchers need to work with commercial developers to achieve this integration; that there needs to be an emphasis on extending models to cover more real‐life circumstances; and that solutions with international applicability should be sought.     

Improving assimilation of SeaWiFS data by the application of bias correction with a local SEIK filter

Ocean-biogeochemical models show typically significant errors in the representation of chlorophyll concentrations. The model state can be improved by the assimilation of satellite chlorophyll data with algorithms based on the Kalman filter. However, these algorithms do usually not account for the possibility that the model prediction contains systematic errors in the form of model bias. Accounting explicitly for model biases can improve the assimilation performance. To study the effect of bias estimation on the estimation of surface chlorophyll concentrations, chlorophyll data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) are assimilated on a daily basis into the NASA Ocean Biogeochemical Model (NOBM). The assimilation is performed by the ensemble-based SEIK filter combined with an online bias correction scheme. The SEIK filter is simplified here by the use of a static error covariance matrix. The performance of the filter algorithm is assessed by comparison with independent in situ data over the 7-year period 1998–2004. The bias correction results in significant improvements of the surface chlorophyll concentrations compared to the assimilation without bias estimation. With bias estimation, the daily surface chlorophyll estimates from the assimilation show about 3.3% lower error than SeaWiFS data. In contrast, the error in the global surface chlorophyll estimate without bias estimation is 10.9% larger than the error of SeaWiFS data.     

A model study with light-dependent mortality rates of copepod stages

This paper is based on an advanced ecosystem model of the Baltic Sea (ERGOM [J. Mar. Sys. 25 (3–4) (2005) 405]), but with an increased resolution of the zooplankton stage variable [J. Plankton Res. 23 (2001) 1217; ICES Marine Science 219 (2003) 208]. The model copepods are represented by five stages: eggs, an aggregated variable of nauplii, two aggregated groups of copepodites and adults. The transfer among the stages, i.e., hatching, molting and reproduction, is controlled by food availability and temperature.As usual, the model food web is truncated at the level of zooplankton. The study explores the effects of different parametrization of zooplankton mortality and looks in particular on light-dependent rates. The light climate may serve a proxy for the effects of visual feeding of fish larvae and fish. Different choices of the mortality parameters can result in remarkable differences in abundances and biomass of the model zooplankton and in the timing of its development.It is found that the different choices of mortality affect the development of populations in several ways: Relative small initial differences of abundances at the beginning of the spring bloom are important for the development of the model populations. Higher mortality rates are less important at food rich conditions than at scarce resources. At low phytoplankton levels, the individual development of the copepods through the stages can be faster for elevated mortality rates because then less animals have to share the available food.     

Uncertainty quantification in vehicle dynamics

ABSTRACT

This paper presents a review of various works that highlight the importance of introducing the variability of the road-track/vehicle system into dynamic simulations as soon as this latter is meant to be predictive. The first section of the paper presents the Uncertainty Quantification, Verification and Validation method (UQ-VV). This latter proposes tools to model uncertainties, to associate a confidence to the prediction of quantities of interest and to estimate the probability of occurrence of different scenarios. The method is illustrated by various examples mainly from the rail domain but also from the road sector. The second section summarises application examples of predictive modelling, robust optimisation and calibration.     

Examining the effect of speed,roadside features,and roadway geometry on crash experience along a rural corridor

This paper presents a current investigation into crash experience along a 15.7-mile rural corridor in southwest Montana with the aim of better understanding crash causal factors along the corridor. The study utilized ten years of crash data, geometric data, and observed freeflow speed data along the corridor. A systematic approach was used where every tenth of a mile was described in term of the crash experience, speed, alignment, and roadside features. Using bivariate and multivariate statistical anal-yses, the study investigated the crash experience along the corridor as well as some of the underlying relationships which could explain some of the crash causal factors. Results show a strong association between crash rates and horizontal curvatures even for flat curves that can be negotiated at speeds above the posted speed limit, per the highway design equations. Higher crash rates were also found to be associated with the difference between the observed free-flow speeds and the speed dictated by the curve radius or sight distance as per the design equations. Further, results strongly support the safety benefits of guardrails as evidenced by the lower crash rates and severities. The presence of fixed objects and the steepness of side slopes were also found to have an effect on crash rates and severities.     

Assessing the effects of a mixed-mode design in a longitudinal household travel survey

The German Mobility Panel (MOP) is a national household travel survey, which has been collecting data on travel behavior in Germany since 1994. One of the MOP’s central assets is its ability to provide time-series data on travel behavior. Thus, the comparability of survey results from different years is a major objective of the survey method used. Declining survey participation rates in the last decade in various socio-demographic groups resulted in the implementation of a mixed-mode design for the MOP in 2013, both for the sampling stage (landline and mobile phone recruitment) and the data collection stage (paper and web). In this study, we analyze whether the adaptations in the survey mode do indeed improve the results and, if so, why and to what degree. Ideally, the survey mode adaptions have increased the representativeness of the MOP. However, measurement biases due to the mixed-mode design are also conceivable. To decompose survey mode effects, we applied the propensity score weighting method. This method imputes the hypothetical responses participants would have given in different survey modes; disparities between actual responses and hypothetical responses under another mode are then traced back to the mixed-mode design. Our analysis indicates that trip-rate biases on shopping, leisure, and short trips are partly caused by the mixed-mode design; in contrast, quantities of time spent in the transportation system, trips made by car and public transportation, and commuting trips are hardly biased.