Food supply mechanisms for cold-water corals along a continental shelf edge

In recent years it has been documented that deep-water coral reefs of the species Lophelia pertusa are a major benthic habitat in Norwegian waters. However, basic information about the biology and ecology of this species is still unknown. Lophelia live and thrive under special environmental conditions of which factors such as temperature, water depth, water movement and food supply are important. The present work explores the hypothesis that Lophelia forms reefs in places where the encounter rate of food particles is sufficiently high and stable over long periods of time for continuous growth. This is done by relating the distribution of reefs with the results of numerical ocean modelling.Numerical simulations have been performed with an idealized bottom topography similar to what is found outside parts of the Norwegian coast. In the simulations the model is first forced with an along slope jet and then with an idealized atmospheric low pressure. The model results show that the encounter rates between the particles and the water layer near the seabed are particularly high close to the shelf break. This may indicate that many Lophelia reefs are located along the shelf edges because the supply of food is particularly good in these areas.A sensitivity study of the particle supply in the area close to the seabed for increasing latitude has also been done. This shows that the Ekman transport in the benthic layer tends to create a steady supply of food for benthic organisms near the shelf edge away from the equator.     

Assessment of wind quality for oceanographic modelling in semi-enclosed basins

The quality of surface winds derived from four meteorological models is assessed in the semi-enclosed Adriatic Sea over a 2-month period: a global hydrostatic model ECMWF T511 (40 km resolution), a hydrostatic limited area model LAMBO (20 km), and two non-hydrostatic limited area models: LAMI (7 km) and COAMPS™ (4 km). These wind models are used to drive a 2 km resolution wave model (SWAN) of the Adriatic, and wind and wave results are compared with observations at the ISMAR oceanographic tower off Venice. Waves are also compared at buoy locations near Ancona and Ortona. Consistently with earlier studies, the ECMWF fields underestimate the wind magnitude and do not reproduce the known spatial structure of strong wind events. The results show that the higher-resolution, limited area models LAMI and COAMPS exhibit better amplitude response than the coarser ECMWF: there is a 3- to 4-fold reduction of the wind underestimation at the platform (from 36% to 8–11%). The wave response is also improved with LAMI and COAMPS: there is a 2-fold reduction in the underestimation of wave heights at the platform. These non-hydrostatic models also produce wind fields with more realistic small-scale, spatial structure during strong wind events. The temporal correlation between observed and modelled wind, however, is highest with the global ECMWF model due to the fact that large-scale features can be predicted deterministically, whereas small-scale features can only be predicted stochastically. Models with less small-scale structure have better correlation because they have less “noise.” This explanation is supported by increased correlation between modelled and observed waves, the waves representing a smoothing of the wind over fetch and duration. Although there is room for improvement, the high-resolution, non-hydrostatic models (LAMI and COAMPS) offer significant advantages for driving oceanographic simulations in semi-enclosed basins such as the Adriatic Sea.     

A numerical investigation of phytoplankton and Pseudocalanus elongatus dynamics in the spring bloom time in the Gda sk Gulf

A nutrient–phytoplankton–zooplankton–detritus (1D-NPZD) ‘phytoplankton {Phyt} and Pseudocalanus elongatus {Zoop} dynamics in the spring bloom time in the Gda sk Gulf. The 1D-NPZD model consists of three coupled, partial second-order differential equations of the diffusion type for phytoplankton {Phyt}, zooplankton {Zoop}, nutrients {Nutr} and one ordinary first-order differential equation for benthic detritus pool {Detr}, together with initial and boundary conditions. In this model, the {Zoop} is presented by only one species of copepod (P. elongatus) and {Zoop} is composed of six cohorts of copepods with weights (W_i) and numbers (Z_i); where . The calculations were made for 90 days (March, April, May) for two stations at Gda sk Gulf with a vertical space step of 0.5m and a time step of 900 s. The flow field and water temperature used as the inputs in the biological model 1D-NPZD were reproduced by the prognostic numerical simulation technique using hydrographic climatological data. The results of the numerical investigations described here were compared with the mean observed values of surface chlorophyll-a and depth integrated P. elongatus biomass for 10 years, 1980–1990. The slight differences between the calculated and mean observed values of surface chlorophyll-a and zooplankton biomass are ca. 10–60 mg C m⁻³ and ca. 5–23 mg C m⁻², respectively, depending on the location of the hydrographic station. The 1D-NPZD model with a high-resolution zooplankton module for P. elongatus can be used to describe the temporal patterns for phytoplankton biomass and P. elongatus in the centre of the Gda sk Gulf.     

The effect of prices and income on car travel in the UK

The objective of this paper is to analyse the factors determining household car travel, and specifically the effects of household income and the prices of cars and motor fuels, and to explore the intertemporal pattern of adjustment. The question of asymmetry in the response to rising and falling income is also addressed. Such asymmetry may be caused by habit or resistance to change or the tendency to acquire habits to consume more easily than to abandon them. The impact of prices, the speed of adjustment and the resistance to change will be important in determining the possibility of influencing travel behaviour and specifically car use. The study utilises repeated cross-section data from the annual UK Family Expenditure Surveys and employs a pseudo-panel methodology. The results are compared with those for car ownership estimated on the basis of similar models.     

Future aspects in marine ecosystem modelling

Existing ecosystem models are briefly presented and summarised. The problem of coupling physical and biological models as well as aspects of prediction and predictability are discussed. The general perception that marine ecosystems are inherently unpredictable due to non-linearity becomes questionable if the response of climate variability in marine ecosystems is analysed. Many authors have shown correlations between climate variability and the variability of abundance or biomass of marine organisms such as phytoplankton, zooplankton, benthos or fish recruitment in different parts of the world ocean. In the northern hemisphere, certain species show a linear response to climate variability mainly during winter and spring. However, the underlying mechanisms are not well understood. Often, a phase lag can be observed between climate variability and the reaction of organisms. The identification of a plausible mediator between climate and biology is difficult, since all possible physicochemical mechanisms having a direct or indirect influence on the variability of abundance or biomass of marine organisms have to be considered as mediator.The understanding of the reason of the phase lag, which possibly implies a “biological memory”, and the identification of all possible mediators are necessary to predict the response of marine organisms to climate variability. The identification of mediators will result in an improvement of coupled models, a deeper understanding of physical–biological interaction and the improvement of predictive capability of marine ecosystem models.     

Use of Bayesian inference method to model vehicular air pollution in local urban areas

Traffic Related Air Pollution (TRAP) studies are usually investigated using different categories such as air pollution exposure for health impacts, urban transportation network design to mitigate pollution, environmental impacts of pollution, etc. All of these subfields often rely on a robust air pollution model, which also necessitates an accurate prediction of future pollutants. As is widely accepted by the heath authorities, TRAP is considered to be the major health issue in urban areas, and it is difficult to keep pollution at harmless levels if the time sequenced dynamic pollution and traffic parameters are not identified and modelled efficiently. In our work here, artificial intelligence techniques, such as Bayesian Networks with an optimized configuration, are used to deliver a probabilistic traffic data analysis and predictive modelling for air pollution (SO₂, NO₂ and CO) at very local scale of an urban region with up to 85% accuracy. The main challenge for traditional data analysis is a lack of capability to reveal the hidden links between distant data attributes (e.g. pollution sources, dynamic traffic parameters, etc.), whereas some subtle effects of these parameters or events may play an important role in pollution on a long-term basis. This study focuses on the optimisation of Bayesian Networks to unveil hidden links and to increase the prediction accuracy of TRAP considering its further association with a predictive GIS system.     

Analysis and optimisation of objective vehicle dynamics testing in winter conditions

Objective testing of vehicle handling in winter conditions has not been implemented yet because of its low repeatability and its low signal-to-noise ratio. Enabling this testing, by identifying robust manoeuvres and metrics, was the aim of this study. This has been achieved by using both experimental data, gathered with steering-robot tests on ice, and simulation models of different complexities. Simple bicycle models with brush and MF-tyre models were built, both optimally parameterised against the experimental data. The brush model presented a better balance in complexity performance. This model was also implemented in a Kalman filter to reduce measurement noise; however, a simpler low-pass filter showed almost similar results at lower cost. A more advanced full vehicle model was built in VI-CarRealTime, based on kinematics and compliance data, damper measurements, and real tyre measurements in winter conditions. This model offered better results and was therefore chosen to optimise the initial manoeuvres through test design and simulations. A sensitivity analysis (ANOVA) of the experimental data allowed one to classify the robustness of the metrics. Finally, to validate the results, the proposed and the initial manoeuvres were tested back to back in a new winter campaign.     

Estimation of the determinants of bicycle mode share for the journey to work using census data

A model is presented that relates the proportion of bicycle journeys to work for English and Welsh electoral wards to relevant socio-economic, transport and physical variables. A number of previous studies have exploited existing disaggregate data sets. This study uses UK 2001 census data, is based on a logistic regression model and provides complementary evidence based on aggregate data for the determinants of cycle choice. It suggests a saturation level for bicycle use of 43%. Smaller proportions cycle in wards with more females and higher car ownership. The physical condition of the highway, rainfall and temperature each have an effect on the proportion that cycles to work, but the most significant physical variable is hilliness. The proportion of bicycle route that is off-road is shown to be significant, although it displays a low elasticity (+0.049) and this contrasts with more significant changes usually forecast by models constructed from stated preference based data. Forecasting shows the trend in car ownership has a significant effect on cycle use and offsets the positive effect of the provision of off-road routes for cycle traffic but only in districts that are moderately hilly or hilly. The provision of infrastructure alone appears insufficient to engender higher levels of cycling.

Stability measurement of high-speed vehicles

Vehicle rollover represents a significant percentage of single-vehicle accidents and accounts for over 9000 fatalities and over 200,000 non-fatal injuries each year. Previous research has yielded rollover stability control systems that are effective in on-road conditions. Accident statistics show, however, that over 90% of rollovers involve road departure, during which a vehicle may encounter sloped and rough terrain while travelling at high speed. A critical element of most rollover stability control systems is a metric that monitors a vehicle's nearness to rollover. Most metrics, however, are designed for use on flat, level surfaces characteristic of on-road terrain. In this paper, a new stability metric, termed the stability moment, is proposed that is accurate on terrain surfaces with arbitrary geometry, which allows it to be used in road departure scenarios. The metric is based on an estimate of the distribution of wheel–terrain contact forces. The metric can be calculated on line in real time, using only practical, low-cost sensors. The metric is compared in simulations and experimental studies to existing stability metrics and is shown to exhibit superior performance, particularly in off-road conditions.     

Communicating something confidential while travelling by train: the use of a telephone conversation versus silent modes

Wireless ICTs are often used in public transport. Using survey data collected amongst 98 train travellers this article aims to gain insight into important factors that affect train travellers’ intentions to communicate with distant others while travelling. More specifically, the focus is on the decision-making process that leads to the intention to choose for a confidential conversation either via ‘audible’ mobile phone or via ‘silent’ SMS/e-mail. An approach that is related to the Extended Model of Goal-directed Behaviour (EMGB) is applied. Structural equation modelling results indicate that in particular past SMS behaviour, the desire to communicate (goal desire), the perceived efficacy and controllability influence the intention to conduct a confidential phone conversation in the train. The influence of the social environment (e.g. eavesdropping) seems to be less important. Several EMGB constructs are strongly influenced by age. It seems that older respondents have more negative attitudes towards telephoning while travelling by train, and find it more difficult to call other people in such a situation. Finally, they have a lower intention than younger respondents to conduct a confidential conversation over the phone while travelling.