Real-world gaseous and particle emissions of a Bi-fuel gasoline/CNG Euro 6 passenger car

The objective of the present study is the assessment of the environmental impact of a bivalent (bi-fuel) vehicle, running either on gasoline or compressed natural gas (CNG). To that aim, a Euro 6 passenger car was tested under various real-world driving conditions. In order to cover the full range of conventional powertrains currently in the market, the tests were also repeated on a Euro 6 diesel passenger car. Both cars were driven in two routes, the first complying with the regulation limits and the second going beyond them. Carbon monoxide (CO), nitrogen oxides (NO_x) and particle number (PN) emissions were recorded using a Portable Emissions Measurement System (PEMS). Apart from the aggregated emission levels, in g/km, the exact emission location along the route was also assessed. Natural gas proved beneficial for CO and PN emissions, the level of which always remained below the respective legislation limits. On the other hand, under the dynamic driving conditions with gasoline, the relevant limits were exceeded. Cold start, occurring at the beginning of the urban part, and motorway driving were identified as major contributors to total emissions, especially in gasoline mode. However, the application of natural gas was associated with a penalty in NO_x emissions, which were significantly increased as compared to gasoline. Local peaks within the urban part were identified in CNG mode. In any case, the diesel vehicle was by far the highest NO_x emitter.     

Factors affecting consumer assessment of eco-labeled vehicles

A statewide sample of Maine registered vehicle owners is used to examine factors that affect their assessments of eco-labeled conventionally fueled passenger vehicles. The study focuses on developing an empirical and theoretical framework with which to model vehicle choice decisions under eco-labeled conditions. Particular attention is paid to how eco-information may affect the two-stage vehicle purchase process. The study builds upon environmental economic and psychology literature in examining the role of personal characteristics such as perceived effectiveness of consumer purchase decisions and perceptions of the eco-labeled products as factors in the vehicle purchase decision. It was found that environmental attributes of an eco-labeled passenger vehicle are significant in the purchase decision. The eco-information is considered in the vehicle purchase decision, but is generally not considered at the class-level decision.     

The socio-economics of travel behavior and environmental burdens: A Detroit,Michigan regional context

The transportation industry—particularly light-duty vehicles—is a significant contributor of greenhouse gasses, accounting for about one-third of overall emissions in the U.S. Research to date has studied various factors that impact travel behavior of residents with varying socio-economic characteristics. However, research on the socio-economic characteristics of residents and their impact on environmental burdens within a single urban region, as measured by fuel consumption and vehicular emissions, is recognized as under-represented in the U.S. planning and transportation literature. This study focuses on the Detroit region, Michigan, a unique case study due to the scale of suburbanization and urban decline, yet representative of many mid-western cities. The article explores how socio-economic characteristics impact travel patterns and environmental burdens within six Detroit region neighborhoods. Data on individual travel behavior and personal vehicle characteristics gathered from a mail survey enabled an analysis into how associated environmental burdens varied with socio-economic composition. The analysis explores contributions to environmental burdens between poorer urban and wealthier suburban populations.     

Environmental,functional and economic criteria for comparing “target roundabouts” with one- or two-level roundabout intersections

The article describes a criterion based on functional, environmental and economic aspects for comparing conventional roundabouts with innovative one- or two-level roundabouts. We compared the performances of eight roundabout types, differing in geometric layout, number of lanes and traffic flow regulation from each other, with regard to vehicle delays and CO₂, NO_x, PM_2.5 and PM₁₀ pollutant emissions. Recently-designed roundabouts – target roundabouts and flyover roundabouts – have also been studied for their undoubted practical interest. By means of closed-form capacity models and CORINAIR methodology, several traffic simulations were carried out to examine a typical annual traffic demand curve in a suburban context, three different distribution test matrices for traffic flows (ρ1, ρ2, ρ3) and maximum annual traffic flow values Q_max ranging between 1300 and 3300 veh/h.Estimating vehicle delays and annual pollutant emissions, along with construction and management costs, allowed obtaining overall costs for each roundabout examined, in function of traffic demand and several other parameters. Thanks to these analyses, we identified the roundabout types which best suit to each traffic condition.     

Transport discussion amidst climate challenges: Analysing student,media, and expert framings through the environmental protection process model

The article examines media representations and views of experts and high school students on the future of transport with a particular focus on its implications for emissions of greenhouse gases. Focusing on Finland, it explores which key features and boundary conditions related to the climate policies of transport are framed as important or negligible. The analysis was based on the comprehensive environmental protection process model. Results show that the need for radical change was recognised both by students and experts but at the same time, rather cynical views regarding the possibilities to achieve these changes were presented by the media, experts, and students. Long-term impacts and visions were underrepresented in discussions, with the focus being mainly on short-term concerns and incremental changes.     

Design and development of a hybrid artificial bee colony algorithm for the environmental vehicle routing problem

The vehicle routing problem (VRP) is a critical and vital problem in logistics for the design of an effective and efficient transportation network, within which the capacitated vehicle routing problem (CVRP) has been widely studied for several decades due to the practical relevance of logistics operation. However, CVRP with the objectives of minimizing the overall traveling distance or the traveling time cannot meet the latest requirements of green logistics, which concern more about the influence on the environment. This paper studies CVRP from an environmental perspective and introduces a new model called environmental vehicle routing problem (EVRP) with the aim of reducing the adverse effect on the environment caused by the routing of vehicles. In this research, the environmental influence is measured through the amount of the emission carbon dioxide, which is a widely acknowledged criteria and accounts for the major influence on environment. A hybrid artificial bee colony algorithm (ABC) is designed to solve the EVRP model, and the performance of the hybrid algorithm is evaluated through comparing with well-known CVRP instances. The computational results from numerical experiments suggest that the hybrid ABC algorithm outperforms the original ABC algorithm by 5% on average. The transformation from CVRP to EVRP can be recognized through the differentiation of their corresponding optimal solutions, which provides practical insights for operation management in green logistics.     

Achieving environmental sustainability beyond technological improvements: Potential role of high-speed rail in the United States of America

In order to reduce energy use and cut emissions that contribute to climate change, countries need to radically reinvent their fossil-fuel intensive transportation systems. As a major consumer of energy and contributor to greenhouse gas (GHG) emissions, the U.S. transportation sector faces extraordinary challenges in the twenty-first century. Transportation in the U.S. depends heavily on fossil-fuel dependent cars and planes to the near exclusion of more energy-efficient electric trains. In order to address this concern, some policy makers refer to “technological optimism” which seeks no systemic change but instead focuses on employing technology to reduce the energy demand and environmental impact of the status quo. On the other hand, some researchers suggest a systematic paradigm shift away from cars and planes to intermodal systems that improve the sustainability of the system as a whole. High-speed rail (HSR) is arguably such an investment that can further this shift and help to achieve a more diversified and balanced transportation system. In this respect, by largely examining the role of the U.S. cars and planes “culture” in the economy, this paper elaborates on how building a HSR system may help U.S. advance towards environmental sustainability in transportation, make a break from the status quo, and create a more balanced, multimodal transportation system that will improve the quality and efficiency of travel.     

Road characteristics and environment factors associated with motorcycle fatal crashes in Malaysia

This study aims to determine risk factors contributing to traffic crashes in 9,176 fatal cases involving motorcycle in Malaysia between 2010 and 2012. For this purpose, both multinomial and mixed models of motorcycle fatal crash outcome based on the number of vehicle involved are estimated. The corresponding model predicts the probability of three fatal crash outcomes: motorcycle single-vehicle fatal crash, motorcycle fatal crash involving another vehicle and motorcycle fatal crash involving two or more vehicles. Several road characteristic and environmental factors are considered including type of road in the hierarchy, location, road geometry, posted speed limit, road marking type, lighting, time of day and weather conditions during the fatal crash. The estimation results suggest that curve road sections, no road marking, smooth, rut and corrugation of road surface and wee hours, i.e. between 00.00 am to 6 am, increase the probability of motorcycle single-vehicle fatal crashes. As for the motorcycle fatal crashes involving multiple vehicles, factors such as expressway, primary and secondary roads, speed limit more than 70 km/h, roads with non-permissible marking, i.e. double lane line and daylight condition are found to cause an increase the probability of their occurrence. The estimation results also suggest that time of day (between 7 pm to 12 pm) has an increasing impact on the probability of motorcycle single-vehicle fatal crashes and motorcycle fatal crashes involving two or more vehicles. Whilst the multinomial logit model was found as more parsimonious, the mixed logit model is likely to capture the unobserved heterogeneity in fatal motorcycle crashes based on the number of vehicles involved due to the underreporting data with two random effect parameters including 70 km/h speed limit and double lane line road marking.     

动力定位船控位能力计算软件平台构建研究

围绕环境载荷计算和推进器推力分配两大关键问题,对控位能力计算软件平台功能实现进行设计。通过对环境载荷计算、推进器配置、推力分配、动力定位能力图绘制等功能进行集成,完成界面友好的控位能力计算软件平台。最后通过实例验证了自研软件的稳定性与输出结果的可靠性。     

Bayesian calibration of mechanistic aquatic biogeochemical models and benefits for environmental management

Aquatic biogeochemical models have been an indispensable tool for addressing pressing environmental issues, e.g., understanding oceanic response to climate change, elucidation of the interplay between plankton dynamics and atmospheric CO₂ levels, and examination of alternative management schemes for eutrophication control. Their ability to form the scientific basis for environmental management decisions can be undermined by the underlying structural and parametric uncertainty. In this study, we outline how we can attain realistic predictive links between management actions and ecosystem response through a probabilistic framework that accommodates rigorous uncertainty analysis of a variety of error sources, i.e., measurement error, parameter uncertainty, discrepancy between model and natural system. Because model uncertainty analysis essentially aims to quantify the joint probability distribution of model parameters and to make inference about this distribution, we believe that the iterative nature of Bayes' Theorem is a logical means to incorporate existing knowledge and update the joint distribution as new information becomes available. The statistical methodology begins with the characterization of parameter uncertainty in the form of probability distributions, then water quality data are used to update the distributions, and yield posterior parameter estimates along with predictive uncertainty bounds. Our illustration is based on a six state variable (nitrate, ammonium, dissolved organic nitrogen, phytoplankton, zooplankton, and bacteria) ecological model developed for gaining insight into the mechanisms that drive plankton dynamics in a coastal embayment; the Gulf of Gera, Island of Lesvos, Greece. The lack of analytical expressions for the posterior parameter distributions was overcome using Markov chain Monte Carlo simulations; a convenient way to obtain representative samples of parameter values. The Bayesian calibration resulted in realistic reproduction of the key temporal patterns of the system, offered insights into the degree of information the data contain about model inputs, and also allowed the quantification of the dependence structure among the parameter estimates. Finally, our study uses two synthetic datasets to examine the ability of the updated model to provide estimates of predictive uncertainty for water quality variables of environmental management interest.