Landscape scale patterns in the character of natural organic matter in a Swedish boreal stream network

This paper defines landscape-scale patterns in the character of natural organic matter (NOM) and tests for relationships to catchment soil, vegetation and topography. The drainage network of a boreal catchment, subcatchment size 0.12–78km2, in Northern Sweden was sampled in August 2002 during a period of stable low water flow. The NOM was characterized with UV/Vis spectroscopy, fluorescence, XAD-8 fractionation (%humic substances), gel permeation chromatography (apparent molecular weight), and elemental composition (C:N). The largest spatial variation was found for C:N, absorbance ratio, and specific visible absorptivity. The lowest variation was in fluorescence index, %humic substances and molecular retention time. But the variation in total organic carbon (TOC), iron and aluminium concentration was more than twice that of C:N. Between headwater and downstream sites no significant changes were distinguished in the NOM character. At stream reaches, junctions and lakes little change (<10%) in NOM character was observed. Common factor analysis and partial least squares regression (PLS) revealed that the spatial variation in surface coverage of lakes and mires could explain some of the variation of TOC and NOM character. Our suggestion is that the mosaic of landscape elements (different amounts of water from lakes, forest soil and mires) delivers NOM with varying characteristics to a channel network that mixes conservatively downstream, with possible small changes at some 20 stream reaches, junctions and lake

Strategy for instant neutralisation and metal immobilisation in ARD

Abstract For ARD filters, reactive barriers are often the methods of choice. Some problems are recognised though; iron precipitation cause hydraulic changes and inhibition of neutralising phases. Instead of filter/barrier installation alkalinity is suggested to be added in an aqueous phase (leach beds). Addition of a highly alkaline solution to different ARD results in a rapid, almost instant neutralisation, precipitation of metals (Fe, Al) as well as almost quantitative coprecipitation and sorption of trace metals at near neutral pH. Generation of alkalinity on-site, added to ARD as an aqueous phase, would be a fast and simple ARD treatment method

Using GIS to create synthetic disease outbreaks

BACKGROUND: The ability to detect disease outbreaks in their early stages is a key component of efficient disease control and prevention. With the increased availability of electronic health-care data and spatio-temporal analysis techniques, there is great potential to develop algorithms to enable more effective disease surveillance. However, to ensure that the algorithms are effective they need to be evaluated. The objective of this research was to develop a transparent user-friendly method to simulate spatial-temporal disease outbreak data for outbreak detection algorithm evaluation. A state-transition model which simulates disease outbreaks in daily time steps using specified disease-specific parameters was developed to model the spread of infectious diseases transmitted by person-to-person contact. The software was developed using the MapBasic programming language for the MapInfo Professional geographic information system environment. RESULTS: The simulation model developed is a generalised and flexible model which utilises the underlying distribution of the population and incorporates patterns of disease spread that can be customised to represent a range of infectious diseases and geographic locations. This model provides a means to explore the ability of outbreak detection algorithms to detect a variety of events across a large number of stochastic replications where the influence of uncertainty can be controlled. The software also allows historical data which is free from known outbreaks to be combined with simulated outbreak data to produce files for algorithm performance assessment. CONCLUSION: This simulation model provides a flexible method to generate data which may be useful for the evaluation and comparison of outbreak detection algorithm performance

Retention of 2,4,6-trinitrotoluene and heavy metals from industrial waste water by using the low cost adsorbent pine bark in a batch experiment

Pine bark is a low cost sorbent originating from the forest industry. In recent years, it has been found to show promise as an adsorbent for metals and organic substances in contaminated water, especially landfill leachates and storm water. This study aims to investigate if pine bark can replace commercial adsorbents such as active carbon. An industrial effluent, collected from a treatment plant of a demilitarization factory, was diluted to form concentration ranges of contaminants and shaken with pine bark for 24 hours. Metals (e.g. Pb, Zn, Cd, As and Ni) and explosives, e. g., 2,4,6-trinitrotoluene (TNT), were analysed before and after treatment. The aim of the experiment was twofold; firstly, it was to investigate whether metals are efficiently removed in the presence of explosives and secondly, if adsorption of explosive substances to pine bark was possible. Langmuir and Freundlich isotherms were used to describe the adsorption process where this was possible. It was found that metal uptake was possible in the presence of TNT and other explosive contaminants. The uptake of TNT was satisfactory with up to 80% of the TNT adsorbed by pine bark