Costs of air pollutants from shipping: a meta-regression analysis

ABSTRACT

This study estimated the external cost of air pollution from shipping by means of a meta-regression analysis, which has not been made before. Three pollutants, which were included in most of the primary studies, were considered: nitrogen oxides (NO_x), sulphur dioxides (SO₂) and particulate matters with a diameter of max 2.5 micrometres (PM_2.5). All primary studies included damages of health and a majority added impacts on agriculture and estimated the cost of air pollutants by transferring cost estimates from studies on costs of air emissions from transports in Europe. Different regression models and estimators were used and robust results were found of statistically significant emission elasticities of below one, i.e. total external costs increase by less than 1% when emissions increase by 1%. There was a small variation between the pollutants, with the highest elasticity for PM_2.5 and lowest for NO_x. Calculations of the marginal external cost of the pollutants showed the same pattern, with this cost being approximately six times higher for PM_2.5 than for the other pollutants. Common to all pollutants was that the marginal external cost decreases when emission increases. Another robust result was a significant increase in the cost of studies published in journals compared with other publication outlets. These findings point out some caution when transferring constant external unit cost of air pollutant from shipping, which is much applied in the literature, and the cost functions estimated in this study could thus provide a complementary transfer mechanism.     

GIS-based identification and visualization of multimodal freight transportation catchment areas

Transportation - To estimate impacts, support cost–benefit analyses, and enable project prioritization, it is necessary to identify the area of influence of a transportation infrastructure...     

A continuous network design model in stochastic user equilibrium based on sensitivity analysis

The continuous network design problem (CNDP) is known to be difficult to solve due to the intrinsic properties of non‐convexity and nonlinearity. Such kinds of CNDP can be formulated as a bi‐level programme, in which the upper level represents the designer's decisions and the lower level the travellers' responses. Formulations of this kind can be classified as either Stackelberg approaches or Nash ones according to the relationship between the upper level and the lower level parts. This paper formulates the CNDP for road expansion based on Stackelberg game where leader and follower exist, and allows for variety of travellers' behaviour in choosing their routes. In order to solve the problem by the Stackelberg approach, we need a relation between link flows and design parameters. For this purpose, we use a logit route choice model, which provides this in an explicit closed‐form function. This model is applied to two example road networks to test and briefly compare the results between the Stackelberg and Nash approaches to explore the differences between them.     

Transit assignment under crowded conditions

This paper presents a transit assignment algorithm for crowded networks. Both congestion in vehicles and queuing at stations are explicitly taken into account in predicting passenger flows for a fixed pattern of origin-destination trip demands. The overflow effects due to insufficient capacity of transit lines are considered to be concentrated at transit stations, while the in-vehicle congestion effects (or discomforts) are considered to be dependent on in-vehicle passenger volume. Overflow delay at a transit station is dependent on the number of excess passengers required to wait for the next transit car. We use a logit model to determine the split between passengers that chose to wait for the next transit car and passengers that chose to board on the alternative transit lines. The proposed algorithm predicts how passenger will choose their optimal routes under both queuing and crowded conditions.     

Active Roll Control for Passenger Cars

The development of a mathematical model of a limited bandwidth hydro-pneumatic suspension that is incorporated into a vehicle handling model is described. The combined model is used to evaluate a suitable control strategy for eliminating body roll during a cornering manoeuvre. The philosophy behind the roll control strategy has been to use feedback measurements of the body motions which do not compromise the ride control. A study of the influence of the position of the body motion feedback transducer on the effectiveness of the system to reduce the body roll is presented. Non-linear modelling of the suspension components for a 0.8g cornering manoeuvre has revealed performance limitations. Conclusions are drawn as to the effectiveness of the control scheme.     

A study of passenger discomfort measures at the Hong Kong mass transit railway system

This note investigates the important attributes relating to the crowding effects at the Mass Transit Railway (MTR) stations in Hong Kong. Data was collected at two sets of three MTR stations to study the responses of the passengers due to the discomfort at crowded vehicles and platforms. Stated preference surveys were used to study the effects of passenger discomfort measures.     

The role of professional associations in shipping

This article is in three parts. The first covers the historical development of qualifying associations. The second covers the particular role of maritime institutions that include The Royal Institution of Naval Architects, The Institute of Marine Engineering Science and Technology and The Nautical Institute. The third and final section considers the future for maritime professional associations in the context of international shipping.     

Estimation of origin‐destination matrices for a multimodal public transit network

This paper presents a procedure for the estimation of origin‐destination (O‐D) matrices for a multimodal public transit network. The system consists of a number of favored public transit modes that are obtained from a modal split process in a traditional four‐step transportation model. The demand of each favored mode is assigned to the multimodal network, which is comprised of a set of connected links of different public transit modes. An entropy maximization procedure is proposed to simultaneously estimate the O‐D demand matrices of all favored modes, which are consistent with target data sets such as the boarding counts and line segment flows that are observed directly in the network. A case study of the Hong Kong multimodal transit network is used to demonstrate the effectiveness of the proposed methodology.