Mechanical and leaching behaviour of slag-cement and lime-activated slag stabilised/solidified contaminated soil.

Stabilisation/solidification (S/S) is an effective technique for reducing the leachability of contaminants in soils. Very few studies have investigated the use of ground granulated blast furnace slag (GGBS) for S/S treatment of contaminated soils, although it has been shown to be effective in ground improvement. This study sought to investigate the potential of GGBS activated by cement and lime for S/S treatment of a mixed contaminated soil. A sandy soil spiked with 3000mg/kg each of a cocktail of heavy metals (Cd, Ni, Zn, Cu and Pb) and 10,000mg/kg of diesel was treated with binder blends of one part hydrated lime to four parts GGBS (lime-slag), and one part cement to nine parts GGBS (slag-cement). Three binder dosages, 5, 10 and 20% (m/m) were used and contaminated soil-cement samples were compacted to their optimum water contents. The effectiveness of the treatment was assessed using unconfined compressive strength (UCS), permeability and acid neutralisation capacity (ANC) tests with determination of contaminant leachability at the different acid additions. UCS values of up to 800kPa were recorded at 28days. The lowest coefficient of permeability recorded was 5×10(-9)m/s. With up to 20% binder dosage, the leachability of the contaminants was reduced to meet relevant environmental quality standards and landfill waste acceptance criteria. The pH-dependent leachability of the metals decreased over time. The results show that GGBS activated by cement and lime would be effective in reducing the leachability of contaminants in contaminated soils.

Marine pollution and zooplankton: some recent trends in marine pollution studies

The presence of even very minute quantities of pollutants may become harmful either due to their direct effect on zooplankton or indirectly due to the transfer of the pollutants to other trophic levels through zooplankton. The recent trend in marine pollution studies is therefore to find out the effects of very minute quantities of these pollutants on marine zooplankton and the methods of their accumulation and transfer to the organisms of higher trophic level including man. A review of laboratory and field studies concerning the effects of pollutants such as hydrocarbons, crude oil, heavy metals, pesticides and heated waste water on the survival, breeding, movement, faecal pellet production, growth and development on marine zooplankton is presented.

A baseline report of water quality and invertebrate assessment in River Hohwa, Lake Albert: final report

Tullow Oil plc is to launch an onshore Early Production System (EPS) of oil drilling rated at 4,000 barrels of oil per day by 2009. The location of the EPS is in the Kaiso-Tonya area of Block 2 Oil Exploration Zone along Lake Albert within the Albertine graben. Tullow Oil plc contracted Environmental Resources Management (ERM) Southern Africa (Pty) Ltd in conjunction with Environmental Assessment Consult Limited (EACL) to undertake an Environmental Impact Assessment (EIA) for pre-construction and operation of the proposed EPS. ERM in association with EACL requested National Fisheries Resources Research Institute (NaFIRRI) to conduct a baseline survey of water quality and invertebrates in River Hohwa. This study was requested as part of an earlier baseline survey conducted at the Kaiso-Ngassa spit oil exploration area in Block 2. It was conducted at five selected sites (Fig. 1 & Table 1) within the Hohwa River basin in the Kaiso-Tonya Exploration Area 2. The study was pertinent because the targeted oil wells for EPS are upstream this river which drains the Kaiso-Ngassa valley into Ngassa lagoon.

Infrastructure facilities for deep-sea and off-shore fishing

The author presents a brief account of the infrastructure facilities required for the fishing industry. He describes those facilities presently available in Sri Lanka, and those that are under construction, and gives a few suggestions indicating the nature of infrastructure facilities that are vital to the local situation at its present stage of development. The principal facilities discussed are (1) fish landing places; (2) unloading handling facilities; (3) vessel servicing facilities; and (4) navigation aids.

Shrimp extract from prawn waste

A method has been described for the preparation of protein extract from prawn waste. The process consists of extracting the protein from minced fresh prawn head and shell waste by treatment with mild alkali and neutralisation and concentration of the filtrate into a semisolid consistency. The yield of the final product is about 20% of the weight of fresh prawn waste.

Ecological impact of Mahshahr petrochemical activities on abundance and diversity of macrobenthic fauna in Zangi Creek (Persian Gulf)

The Moosa Creek extends from its opening into the Persian Gulf, with some sub narrow creeks leading to it. Zangi creek is one of the main branches of Moosa creek. The creek contains numerous sources of organic pollution, including sewage outlet flows and boat waste. After establishing the Petrochemical special Economic Zone (PETZONE) in 1997 near to the Zangi Creek, the pipelines, streets and railway made it distinct from eastern and western parts of this creek. Industrial activities have released sludge and effluents in this creek along these years. A survey of the Zangi creek was performed, assessing water properties, organic pollution, and the population density, distribution and diversity of macrobenthic fauna through bi-monthly sampling from July 2006 to September 2007. Samples were collected from water near the bottom and sediment at 7 stations include 2 stations inside the distinct Zangi creek and 4 stations along a transect with 1 km distances between them in eastern free part and one reference station located at the Persian Gulf entrance to the Moosa creek. The environmental parameters such as temperature, salinity, pH, dissolved oxygen, COD, turbidity, EC and heavy metals include Hg, Cd, Pb, Ni as well as percentage silt-clay and total organic matter of the sediment were measured. The faunal population density and their distribution are discussed in relation to the environmental changes. Results showed spatial heterogeneity in faunal distribution of the Zangi creek. Nine groups of macrofauna were identified out of distinct zangi creek. Polychaets formed the dominant group (48%) followed by bivalves (13%), gastropods (10%), Decapods (2%), Tanaids (5%), and all other groups (22%). The distinct creek was heavily polluted without any macrofauna communities probably as a consequence of the high pH, COD, low salinity and heavy metals contamination specially Cd and Pb. The other stations near to the disposal site were found with macrofauna communities commonly tolerant to organic pollution, At 3 km east of the disposal site, macrofauna is comparable to the surrounded creek, whereas macrofauna still indicate environmental degradation. Farther a way, faunal density decreases and equilibrium taxa gradually replace opportunistic species, while the other stations were far from polluted area contained lower pollution and relatively healthy macrofauna. The mean biomass of macrobenthic fauna were estimated for the whole studied area. The results are considered in Minimum density and biomass in surrounded creek and maximum density and biomass in 3 km of surrounded area. Biodiversity Indices were low in surrounded creek. The Shanon-weaver information index was used to describe the spatially variations in diversity. Macrofauna density, shanon and simpson index were significantly variable between surrounded and free parts of Zangi creek (p<0.05). The numerical abundance of macrobenthose varied from 221. m-2 in polluted area to 4346 m-2 in free part of Zangi creek. The Shanon-weaver information index varied from 0.4 in distinct area to 2.9 in reference station. The physico- chemical changes between distinct and free creeks showed significant variations such as pH, salinity and EC. Salinity and EC were significantly positive correlate to macrofauna density, whereas pH and TOM percentage indicated significantly negative correlation to density. Heavy metals concentrations in sediments were higher than water samples. Concentration pattern of heavy metals in sediments and water samples were Ni>Pb>Cd>Hg. Salinity and pH were significantly correlated to metals in sediments (p<0.01). No significant correlation were found between Macrofauna density and heavy metals (p<0.05).

Capture fisheries in Uganda: why Bujagali hydro-power project and ecological monitoring?

Human use of water resow-ces in Uganda has grown and intensified along with population growth and increasing demand to meet the diverse human needs. In the case of Uganda's rivers, the main uses include fisheries, hydropower generation, abstraction for potable water supply, discharge of sewage and navigation. All these uses can disrupt the integrity of the aquatic ecosystem and may affect the survival of the diversity of organisms. In consideration of the need to increase electricity to meet demand, the Bujagali Hydro-power Project (BHPP) and the National Environment Management Authority (NEMA) recognised the importance of safeguards to mitigate impacts of the project. The National Fisheries Resources Research Institute (NaFIRRI) was assigned the role of providing baseline information on the aquatic ecosystem of the Upper Victoria Nile and to follow up the findings with a monitoring framework during construction and post-commissioning phases.

Near-complete transuranic waste incineration in a thorium fuelled pressurised water reactor

The production of long-lived transuranic (TRU) waste is a major disadvantage of fission-based nuclear power. Incineration, and virtual elimination, of waste stockpiles is possible in a thorium (Th) fuelled critical or subcritical fast reactor. Fuel cycles producing a net decrease in TRUs are possible in conventional pressurised water reactors (PWRs). However, minor actinides (MAs) have a detrimental effect on reactivity and stability, ultimately limiting the quality and quantity of waste that can be incinerated. In this paper, we propose using a thorium-retained-actinides fuel cycle in PWRs, where the reactor is fuelled with a mixture of thorium and TRU waste, and after discharge all actinides are reprocessed and returned to the reactor. To investigate the feasibility and performance of this fuel cycle an assembly-level analysis for a one-batch reloading strategy was completed over 125 years of operation using WIMS 9. This one-batch analysis was performed for simplicity, but allowed an indicative assessment of the performance of a four-batch fuel management strategy. The build-up of 233U in the reactor allowed continued reactive and stable operation, until all significant actinide populations had reached pseudo-equilibrium in the reactor. It was therefore possible to achieve near-complete transuranic waste incineration, even for fuels with significant MA content. The average incineration rate was initially around 330 kg per GW th year and tended towards 250 kg per GW th year over several decades: a performance comparable to that achieved in a fast reactor. Using multiple batch fuel management, competitive or improved end-of-cycle burn-up appears achievable. The void coefficient (VC), moderator temperature coefficient (MTC) and Doppler coefficient remained negative. The quantity of soluble boron required for a fixed fuel cycle length was comparable to that for enriched uranium fuel, and acceptable amounts can be added without causing a positive VC or MTC. This analysis is limited by the consideration of a single fuel assembly, and it will be necessary to perform a full core coupled neutronic-thermal-hydraulic analysis to determine if the design in its current form is feasible. In particular, the potential for positive VCs if the core is highly or locally voided is a cause for concern. However, these results provide a compelling case for further work on concept feasibility and fuel management, which is in progress. © 2011 Elsevier Ltd. All rights reserved.

Liquid crystal multi-mode lenses and axicons based on electronic phase shift control

We report on the principle of operation, construction and testing of a liquid crystal lens which is controlled by distributing voltages across the control electrodes, which are in turn controlled by adjusting the phase of the applied voltages. As well as (positive and negative) defocus, then lenses can be used to control tip/tilt, astigmatism, and to create variable axicons. © 2007 Optical Society of America.

Concrete column recognition in images and videos

The automated detection of structural elements (e.g., columns and beams) from visual data can be used to facilitate many construction and maintenance applications. The research in this area is under initial investigation. The existing methods solely rely on color and texture information, which makes them unable to identify each structural element if these elements connect each other and are made of the same material. The paper presents a novel method of automated concrete column detection from visual data. The method overcomes the limitation by combining columns’ boundary information with their color and texture cues. It starts from recognizing long vertical lines in an image/video frame through edge detection and Hough transform. The bounding rectangle for each pair of lines is then constructed. When the rectangle resembles the shape of a column and the color and texture contained in the pair of lines are matched with one of the concrete samples in knowledge base, a concrete column surface is assumed to be located. This way, one concrete column in images/videos is detected. The method was tested using real images/videos. The results are compared with the manual detection ones to indicate the method’s validity.

Construction site image retrieval based on material cluster recognition

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. This capability is a product of the technological breakthroughs in the area of image processing that has allowed for the development of a large number of digital imaging applications in all industries. In this paper, an automated and content based construction site image retrieval method is presented. This method is based on image retrieval techniques, and specifically those related with material and object identification and matches known material samples with material clusters within the image content. The results demonstrate the suitability of this method for construction site image retrieval purposes and reveal the capability of existing image processing technologies to accurately identify a wealth of materials from construction site images.

Identification of Materials from Construction Site Images Using Content Based Image Retrieval Techniques

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. Examples include surface cracks detection, assessment of fire-damaged mortar, fatigue evaluation of asphalt mixes, aggregate shape measurements, velocimentry, vehicles detection, pore size distribution in geotextiles, damage detection and others. This capability is a product of the technological breakthroughs in the area of Image and Video Processing that has allowed for the development of a large number of digital imaging applications in all industries ranging from the well established medical diagnostic tools (magnetic resonance imaging, spectroscopy and nuclear medical imaging) to image searching mechanisms (image matching, content based image retrieval). Content based image retrieval techniques can also assist in the automated recognition of materials in construction site images and thus enable the development of reliable methods for image classification and retrieval. The amount of original imaging information produced yearly in the construction industry during the last decade has experienced a tremendous growth. Digital cameras and image databases are gradually replacing traditional photography while owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks. However, construction companies tend to store images without following any standardized indexing protocols, thus making the manual searching and retrieval a tedious and time-consuming effort. Alternatively, material and object identification techniques can be used for the development of automated, content based, construction site image retrieval methodology. These methods can utilize automatic material or object based indexing to remove the user from the time-consuming and tedious manual classification process. In this paper, a novel material identification methodology is presented. This method utilizes content based image retrieval concepts to match known material samples with material clusters within the image content. The results demonstrate the suitability of this methodology for construction site image retrieval purposes and reveal the capability of existing image processing technologies to accurately identify a wealth of materials from construction site images.

Shape Recognition of Linear Construction Entities from Construction Site Images

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. This capability is a product of the technological breakthroughs in the area of Image Processing that has allowed for the development of a large number of digital imaging applications in all industries. In this paper, an automated and content based shape recognition model is presented. This model was devised to enhance the recognition capabilities of our existing material based image retrieval model. The shape recognition model is based on clustering techniques, and specifically those related with material and object segmentation. The model detects the borders of each previously detected material depicted in the image, examines its linearity (length/width ratio) and detects its orientation (horizontal/vertical). The results emonstrate the suitability of this model for construction site image retrieval purposes and reveal the capability of existing clustering technologies to accurately identify the shape of a wealth of materials from construction site images.

Content Based Integration of Construction Site Images in AEC/FM Model Based Systems

The Architecture, Engineering, Construction and Facilities Management (AEC/FM) industry is rapidly becoming a multidisciplinary, multinational and multi-billion dollar economy, involving large numbers of actors working concurrently at different locations and using heterogeneous software and hardware technologies. Since the beginning of the last decade, a great deal of effort has been spent within the field of construction IT in order to integrate data and information from most computer tools used to carry out engineering projects. For this purpose, a number of integration models have been developed, like web-centric systems and construction project modeling, a useful approach in representing construction projects and integrating data from various civil engineering applications. In the modern, distributed and dynamic construction environment it is important to retrieve and exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research demonstrated that a major hurdle in AEC/FM data integration in such systems is caused by its variety of data types and that a significant part of the data is stored in semi-structured or unstructured formats. Therefore, new integrative approaches are needed to handle non-structured data types like images and text files. This research is focused on the integration of construction site images. These images are a significant part of the construction documentation with thousands stored in site photographs logs of large scale projects. However, locating and identifying such data needed for the important decision making processes is a very hard and time-consuming task, while so far, there are no automated methods for associating them with other related objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.

Material-Based Construction Site Image Retrieval

The technological advancements in digital imaging, the widespread popularity of digital cameras, and the increasing demand by owners and contractors for detailed and complete site photograph logs have triggered an ever-increasing growth in the rate of construction image data collection, with thousands of images being stored for each project. However, the sheer volume of images and the difficulties in accurately and manually indexing them have generated a pressing need for methods that can index and retrieve images with minimal or no user intervention. This paper reports recent developments from research efforts in the indexing and retrieval of construction site images in architecture, engineering, construction, and facilities management image database systems. The limitations and benefits of the existing methodologies will be presented, as well as an explanation of the reasons for the development of a novel image retrieval approach that not only can recognize construction materials within the image content in order to index images, but also can be compatible with existing retrieval methods, enabling enhanced results.