A comparative study of macrobenthic community from harbours along the central west coast of India

Harbours are heavily stressed coastal habitats characterised by high concentration of contaminant and low diversity of benthic community. The west coast of India harbours most of the major harbours compared to the east coast. Very few studies have compared the macrobenthic community between different Indian harbours. The present study was therefore conducted in three important harbour (Ratnagiri, Goa, Karwar) along the central west coast of India. The paper discusses the health status of the three harbours diagnosed using various biotic indices. Sediment samples were collected using van Veen grab (0.11 m(2)) on board CRV Sagar Sukti. A total of 55 macrobenthic taxa were identified and were numerically dominated by polychaete. Biomass was high (0.14-145.7 g m(-2)) and was made largely by echiurans (>80%). Overall, polychaete dominated the macrobenthic diversity. Opportunistic P.pinnata, Notomastus sp. and Mediomastus sp., dominated the macrobenthic community responding to the increased in the harbour. Biotic indices (Polychaete:Amphipod ratio, ABC curve and geometric class abundance) and the dominance of opportunistic species indicate that, the three harbours are under stress from anthropogenic activities.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

High frequency monitoring of the coastal marine environment using the MAREL buoy

The MAREL Iroise data buoy provides physico-chemical measurements acquired in surface marine water in continuous and autonomous mode. The water is pumped 1.5 m from below the surface through a sampling pipe and flows through the measuring cell located in the floating structure. Technological innovations implemented inside the measuring cell atop the buoy allow a continuous cleaning of the sensor, while injection of chloride ions into the circuit prevents biological fouling. Specific sensors for temperature, salinity, oxygen and fluorescence investigated in this paper have been evaluated to guarantee measurement precision over a 3 month period. A bi-directional link under Internet TCP-IP protocols is used for data, alarms and remote-control transmissions with the land-based data centre. Herein, we present a 29 month record for 4 parameters measured using a MAREL buoy moored in a coastal environment (Iroise Sea, Brest, France). The accuracy of the data provided by the buoy is assessed by comparison with measurements of sea water weekly sampled at the same site as part of SOMLIT (Service d'Observation du Milieu LIToral), the French network for monitoring of the coastal environment. Some particular events (impact of intensive fresh water discharges, dynamics of a fast phytoplankton bloom) are also presented, demonstrating the worth of monitoring a highly variable environment with a high frequency continuous reliable system.     

Assessing land use impacts on flood processes in complex terrain by using GIS and modeling approach

A distributed hydrologic modeling and GIS approach is applied for the assessment of land use impact in the Steinsel sub-basin, Alzette, Grand-Duchy of Luxembourg. The assessment focuses on the runoff contributions from different land use classes and the potential impact of land use changes on runoff generation. The results show that the direct runoff from urban areas is dominant for a flood event compared with runoff from other land use areas in this catchment, and tends to increase for small floods and for the dry season floods, whereas the interflow from forested, pasture and agricultural field areas contributes to the recession flow. Significant variations in flood volume, peak discharge, time to the peak, etc., are found from the model simulation based on the three hypothetical land use change scenarios.     

Optimal charges on river effluent from lumped and distributed sources

We propose a modelling framework for the design of a Pigouvian effluent tax, in an environmental management problem implicating several economic agents located in a river basin. The proposed charging system allows for the agents' geographical position relative to the river's sections, at which environmental standards are to be enforced, and takes into account the possible different market structures within which the agents are operating. In particular, we consider industrial agents competing on an oligopolistic market, and a set of farmers acting as price takers on a large market. A regional authority's goal is to induce agents to some sort of cooperation which would result in the satisfaction of the common environmental constraints. The economic process on one side, and the pollution transport and accumulation on the other, constitute two dynamic processes in two different time scales. As the economic process is much slower than the other process we can neglect the latter's transients and concentrate on the time invariant steady state solutions to the transportation equation. The model thus constructed has some noncooperative game and optimal control problem's features with space being the ‘running’ variable. This revised version was published online in July 2006 with corrections to the Cover Date.     

Modelling the Distribution and Quality of Sand and Gravel Resources in 3D: a Case Study in the Thames Basin,UK

Three-dimensional (3D) models are often utilised to assess the presence of sand and gravel deposits. Expanding these models to provide a better indication of the suitability of the deposit as aggregate for use in construction would be advantageous. This, however, leads to statistical challenges. To be effective, models must be able to reflect the interdependencies between different criteria (e.g. depth to deposit, thickness of deposit, ratio of mineral to waste, proportion of ‘fines’) as well as the inherent uncertainty introduced because models are derived from a limited set of boreholes in a study region. Using legacy borehole data collected during a systematic survey of sand and gravel deposits in the UK, we have developed a 3D model for a 2400 km² region close to Reading, southern England. In developing the model, we have reassessed the borehole grading data to reflect modern extraction criteria and explored the most suitable statistical modelling technique. The additive log-ratio transform and the linear model of coregionalization have been applied, techniques that have been previously used to map soil texture classes in two dimensions, to assess the quality of sand and gravel deposits in the area. The application of these statistical techniques leads to a model which can be used to generate thousands of plausible realisations of the deposit which fully reflect the extent of model uncertainty. The approach offers potential to improve regional-scale mineral planning by providing an enhanced understanding of sand and gravel deposits and the extent to which they meet current extraction criteria.

     

Driver's obesity and road crash risks in the United States

Objective: We assessed obesity trends in U.S. drivers involved in fatal crashes since 1999 and distinguished whether crash risk factors were different between obese and nonobese drivers.

Methods: We included only drivers of passenger cars involved in fatal traffic crashes between January 1, 1999, and December 31, 2012. Obesity was classified according to the World Health Organization guidelines and profiled between 1999 and 2012 using the adjusted prevalence ratio (aPR) from log-binomial regression models. Differences in crash risks (e.g., driver's fatality, drunk driving, seat belt nonuse) between obese and nonobese drivers were estimated as adjusted odds ratios (aORs) using logistic regression models.

Results: A total of 753,024 U.S. drivers were involved in fatal crashes, for which obesity information was available for 534,887. About 56% (n = 299,078) were driving passenger cars. The prevalence of class I obesity increased from 10% in 1999 to 14% in 2012 (aPR = 1.50, 95% confidence interval [CI], 1.42–1.58), class II obesity from 3 to 5% (aPR = 2.22, 95% CI, 2.05–3.01), and class III obesity from 1 to 2% (aPR = 2.65; 95% CI, 2.27–3.10). Compared to nonobese controls, obese drivers had significantly higher risks for fatality (1.10 ≤ aOR ≤ 1.47), seat belt nonuse (1.00 ≤ aOR ≤ 1.21), need for extrication (1.01 ≤ aOR ≤ 1.23), and ambulance transport time ≥30 min (1.01 ≤ aOR ≤ 1.28). Compared to nonobese controls, obese drivers were less likely to drink drive (0.41 ≤ aOR ≤ 0.72) or speed >65 mph (0.78 ≤ aOR ≤ 0.93).

Conclusion: The rising national prevalence of obesity extends to U.S. drivers involved in fatal crashes and indicates the need to improve seat belt use, vehicle design, and postcrash care for this vulnerable population.     

Assessment of an accidental vapour cloud explosion: Lessons from the Indian Oil Corporation Ltd. accident at Jaipur,India

On 29 October 2009, at 19:30 IST, a devastating vapour cloud explosion occurred in a large fuel storage area at the Indian Oil Corporation (IOC) Depot in Jaipur, India, generating significant blast pressure. As a consequence of this explosion, the entire installation was destroyed, buildings in the immediate vicinity were heavily damaged, and windowpane breakages were found up to 2 km from the terminal. The IOC estimated that the total loss from the fire and explosion was approximately INR 2800 million.Ironically, as a storage site, the Jaipur terminal was not highly congested, and thus was not considered to have adequate potential for a vapour cloud explosion (VCE). Nevertheless, the prima facie evidences indicate that this was a case of VCE. Therefore, the main objective of this study is to quantify the potential overpressures due to vapour cloud explosions (VCEs) using the Process Hazard Analysis DNV Norway based PHAST 6.51 Software. The results are validated by the extent of the damage that had occurred. The estimation of the VCE shows that a maximum 1.0 bar overpressure was generated in the surrounding area. The initial assessment of the accident data roughly estimates the release mode, time, and amount of vaporized fuel. A more accurate estimate has been obtained by modelling the dispersion of vapour clouds in the surrounding atmosphere, which reveals trends and relationships for the occurrence of vapour cloud explosions.