Pollution history of a tropical estuary revealed by combined hydrodynamic modelling and sediment geochemistry

Hydrodynamic modelling of water movement in Hunts Bay, a protected part of Kingston Harbour, Jamaica, shows that depth averaged tidal flows are very low. In the northeast corner of Hunts Bay, water is essentially stagnant. Even under high flow conditions, much of the Bay bottom water is ‘bypassed' by buoyant, lower salinity surface flows. The muddy sediments of Hunts Bay reflect these sluggish to stagnant conditions; sediment cores from the northeast corner of the Bay contain progressively higher amounts of organic matter in their upper parts (last 15–20 years sedimentation). Combined C/N ratios and stable carbon isotope compositions of this organic matter imply a sewage origin. Both lead and chromium metal concentrations and enrichment factors relative to average crustal shales show geographically related patterns that reflect hydrodynamic circulation predicted by modelling. In particular, metal concentrations and enrichment factors are highest at the northern end of the bay, especially in the northeast corner. Modelling confirms that stagnant conditions would occur in the northeast part of the bay even without the presence of a major causeway. The causeway may contribute to low flow conditions, but is not the principal cause of organic contamination, which is simply an excessive input of sewage.     

Appraisal of investments in European nodal centres for goods – freight villages: A comparative analysis

The paper presents and analyses appraisal methods used for the assessment of potential investments in Nodal Centers for Goods (also called Freight Villages), which constitute an essential element of the Trans-European Network for Intermodal Transport. A methodological procedure is applied to identify the underlying factors that influence the choice of an appraisal method, without assessing or comparing the appraisal methods themselves. Following this procedure, issues addressed by the methods are grouped into three broad dimensions and with the use of non-parametric statistical tests, existing relationships are identified between nodal centres' characteristics, the appraisal methods, as well as the actors involved in the decision process. On applying the above procedure to European Nodal Centres for goods, it is found that the choice of appraisal method and the decision criteria for the investment are linked primarily to the nodal centre's size, catchment area, and the support or absence of political approval for the investment. The results of the analysis can be particularly useful at the policy making level, serving as non-formal "qualitative guidelines" to identify the appraisal method to be applied, as well as the options and impacts to be considered. This revised version was published online in June 2006 with corrections to the Cover Date.     

Market segmentation as a mechanism in allowing for variability of traveller behaviour

A major problem with aggregate transport planning models is the accounting of variability in traveller behaviour when the basic unit of analysis is the geographical traffic zone. In an attempt to allow for this variance, recent attention has been given to the role of socio-economic (user and household) characteristics in systematically identifying a homogeneous grouping of travellers with respect to the issue under study rather than restricting the grouping definition according to physical geographical criteria alone. This homogeneous grouping criterion combined eventually with a necessity to represent travel demand in a spatial context, can assist in improving our ability to explain real travel patterns by the development of an improved aggregation condition. The emphasis is on modelling homogeneous groups of travellers separately, and then relating the individual sets of results to each other to obtain an aggregate prediction of behaviour via a knowledge of the representativeness of each group contained in the total sample. This paper presents a technique to identify the relative homogeneity of travellers in accordance with a specified criterion, and illustrates its use with individual household data for the Sydney Metropolitan Area. The paper concludes with a discussion of the advantages of segmentation in operational transport planning, in particular with reference to the aggregation of disaggregate behavioural travel choice models, or movement from a micro-model of individual choice behaviour to an aggregate model of travel demanu.     

An analysis of trip length and land use patterns in the Greater Athens Area

The research described in this paper is an attempt to quantify the impact of a certain distribution of land uses upon trip characteristics — notably trip lengths. The idea is to relate trip lengths classified by mode and purpose to the distance of one trip end from the conurbation centre. The latter is defined as the point which represents a reasonable estimate of the place where the economic, administrative, and cultural life of the urban area is centered.By relating trip lengths to the distance of one trip end from the centre, one could obtain a relation which in effect would be a quantitative expression of the relation between transport and land use. The first application of this idea was in London using the 1966 journey to work data, and it gave quite satisfactory results.The area examined in this research is the Greater Athens Area. The method of analysis is similar to that followed in London so the results of the two studies can be compared. Only work trips are considered for four modes: car, bus, train and all modes (total). It is found that in the case of Athens too, when distance of the workplace from the centre is considered, trip lengths change in smoothly varying ways and a series of mathematical curves can be fitted to the data with an acceptable degree of accuracy. These curves are of the Gamma family having a constant spread factor and varying scale factors for each mode considered. When the distance of the residence end of the trip from the centre is considered, the trip length distributions are not very smooth, a clear mathematical curve cannot be fitted, but again a considerable degree of order can be detected. In addition to the above results a discussion is given on their meaning and the possibilities for future research. In fact the results so far are considered to be the first stage of a more extended research programme which will eventually connect trip length distributions to income and other economic or social parameters in an urban area.The author wishes to express his thanks and appreciation for the comments and constructive criticism made on the various drafts of this paper by M.J.M.     

Do new sources of traffic data make the application of Chaos Theory to traffic management a realistic possibility?

Current signal systems for managing road traffic in many urban areas around the world lack a coordinated approach to detecting the spatial and temporal evolution of congestion across control regions within city networks. This severely inhibits these systems’ ability to detect reliably, on a strategic level, the onset of congestion and implement effective preventative action. As traffic is a time-dependent and non-linear system, Chaos Theory is a prime candidate for application to Urban Traffic Control (UTC) to improve congestion and pollution management. Previous applications have been restricted to relatively uncomplicated motorway and inter-urban networks, arguably where the associated problems of congestion and vehicle emissions are less severe, due to a general unavailability of high-resolution temporal and spatial data that preserve the variability in short-term traffic patterns required for Chaos Theory to work to its full potential. This paper argues that this restriction can now be overcome due to the emergence of new sources of high-resolution data and large data storage capabilities. Consequently, this opens up the real possibility for a new generation of UTC systems that are better able to detect the dynamic states of traffic and therefore more effectively prevent the onset of traffic congestion in urban areas worldwide.     

Cohort analysis of driving cessation and limitation among older adults

Automobiles are central to participation in economic, social, and cultural activities in the United States. The ability to drive as one ages is fundamental to the quality of life among older adults. Driving rates decline significantly with age. Researchers using cross-sectional data have studied the reasons former drivers have stopped driving, but few have followed individuals over time to examine changes in relationships among driving cessation, socio-demographics, and health conditions. We used longitudinal data from a national sample of 20,000 observations from the University of Michigan Health and Retirement Study (HRS) to examine relationships among demographic variables, health conditions, and driving reduction and driving cessation. Longitudinal data allow analysis of generational differences in behavior, a major advantage over cross-sectional data which only allow comparisons of different people at one point in time. We found, like many other studies, that personal decisions to limit and eventually stop driving vary with sex, age, and health conditions. In addition, unlike most previous studies, we also found that those relationships differ by birth cohort with younger cohorts less likely to stop and limit their driving than their older counterparts. The findings indicate an evolution in the association between driving cessation and its causes.

     

A study of the Alboran sea mesoscale system by means of empirical orthogonal function decomposition of satellite data

This paper presents the results of a combined empirical orthogonal function (EOF) analysis of Advanced Very High Resolution Radiometer (AVHRR) sea surface temperature (SST) data and sea-viewing wide field-of-view sensor (SeaWiFS) chlorophyll concentration data over the Alboran Sea (Western Mediterranean), covering a period of 1 year (November 1997–October 1998). The aim of this study is to go beyond the limited temporal extent of available in situ measurements by inferring the temporal and spatial variability of the Alboran Gyre system from long temporal series of satellite observations, in order to gain insight on the interactions between the circulation and the biological activity in the system. In this context, EOF decomposition permits concise and synoptic representation of the effects of physical and biological phenomena traced by SST and chlorophyll concentration. Thus, it is possible to focus the analysis on the most significant phenomena and to understand better the complex interactions between physics and biology at the mesoscale. The results of the EOF analysis of AVHRR-SST and SeaWiFS-chlorophyll concentration data are presented and discussed in detail. These improve and complement the knowledge acquired during the in situ observational campaigns of the MAST-III Observations and Modelling of Eddy scale Geostrophic and Ageostrophic motion (OMEGA) Project.     

Risk management methods for the liner shipping industry: the case of the Bunker Adjustment Factor

Through the implementation of the Bunker Adjustment Factor (BAF), a shipowner is able to transfer the risk of fuel price fluctuation to the shipper. This and other surcharges are generally undesired by shippers who must pay this fee. The research presented provides an alternative method of risk management that is more effective than the current method, while responding to customer service demands for simplified tariffs. By strategic use of commodity futures, the shipowner is able to better reduce his/her risk exposure, transferring it to willing parties at the futures exchanges, thereby eliminating the need for the bunker surcharge.     

Application of a SEEK filter to a 1D biogeochemical model of the Ligurian Sea: Twin experiments and real in-situ data assimilation

The Singular Evolutive Extended Kalman (SEEK) filter has been implemented to assimilate in-situ data in a 1D coupled physical-ecosystem model of the Ligurian Sea. The biogeochemical model describes the partly decoupled nitrogen and carbon cycles of the pelagic food web. The GHER hydrodynamic model (1D version) is used to represent the physical forcings. The data assimilation scheme (SEEK filter) parameterizes the error statistics by means of a set of empirical orthogonal functions (EOFs). Twin experiments are first performed with the aim to choose the suitable experimental protocol (observation and estimation vectors, number of EOFs, frequency of the assimilation,…) and to assess the SEEK filter performances. This protocol is then applied to perform real data assimilation experiments using the DYFAMED data base. By assimilating phytoplankton observations, the method has allowed to improve not only the representation of the phytoplankton community, but also of other variables such as zooplankton and bacteria that evolve with model dynamics and that are not corrected by the data assimilation scheme. The validation of the assimilation method and the improvement of model results are studied by means of suitable error measurements.