ID: 53017
Title: Estimating vegetation parameter for soil erosion assessment in an alpine catchment by means of QuickBird imagery
Author: K. Meusburger, D. Banninger, C Alewell
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Issue 3, June 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Soil erosion, Mountain, Remote Sensing, Spectral unmixing, QuickBird, NDVI
Abstract: Soil erosion rates in alpine regions are related to high spatial variability complicating assessment of risk and damages. A crucial parameter triggering soil erosion that can be derived from satellite imagery is fractional vegetation cover (FVC). The objective of this study is to assess the applicability of normalized differenced vegetation index (NDVI), linear spectral unmixing (LSU) and mixture tuned matched filtering (MTMF) in estimating abundance of vegetation cover in alpine terrain. To account for the small scale heterogeneity of the alpine landscape we used high resolved multispectral QuickBird imagery (pixel resolution = 2.4m) of a site in the Urseren Valley, Central Swiss Alps (67 km2). A supervised land-cover classification was applied (total accuracy 93.3%) prior to the analysis in order to stratify the image. The regression between ground truth FVC assessment and NDVI as well as MTMF-derived vegetation abundance was significant (r2= 0.64, r2= 0.71, respectively). Best results were achieved for LSU (r2=0.85). For both spectral unmixing approaches failed to estimate bare soil abundance (r2= 0.39 for LSU, r2 = 0.28 for MTMF) due to the high spectral variability of bare soil at the study site and the low spectral resolution of the QuickBird imagery. The LSU-derived FVC map successfully identified erosion features (e.g. land-slides) and areas prone to soil erosion. FVC represents an important but often neglected parameter for soil erosion risk assessment in alpine grasslands.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53016
Title: Non-point source pollution in Indian agriculture: Estimation of nitrogen losses from rice crop using remote sensing and GIS
Author: Abha Chhabra, K.R. Manjunath, Sushma Panigrahy
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Issue 3, June 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Nitrogenous fertilizers, Rice crop, Leaching loss, Ammonia volatilization loss, Indo-Gangetic plain region
Abstract: The paper presents a detailed understanding of nitrogenous fertilizer use in Indian agriculture and estimation of seasonal nitrogen looses from rice crop in Ind0-Gangetic plain region, the ' food bowl ' of the Indian sub-continent. An integrated methodology was developed for quantification of different forms of nitrogen losses from rice crop using remote sensing derived inputs, field data of fertilizer application,collateral data of soil and rainfall and nitrogen loss coefficients derived from published nitrogen dynamics studies. The spatial patterns of nitrogen losses in autumn or ' kharif ' and spring or ' rabi ' season rice at 1 x 1 km grid were generated using image processing and GIS. The nitrogen losses through leaching in form of urea-N, ammonium -N (NH4-N) and nitrate-N (NO3-N) are dominant over ammonia volatilization loss. The study results indicate that nitrogen loss through leaching in kharif and rabi rice is of the order of 34.9% and 39.8% of the applied nitrogenous fertilizer in the Indo-Gangetic plain region. This study provides a significant insight to the role of nitrogenous fertilizer as a major non-point source pollutant from agriculture.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53015
Title: Estimation of gross primary production in wheat from in situ measurements
Author: Chaoyang Wu, Xiuzhen Han, Jinsheng Ni, Zheng Niu, Wenjiang Huang
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Issue 3, June 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Gross primary production, Vegetation index, LAI, Wheat, PAR
Abstract: Gross Primary Production (GPP) is a parameter of significant importance for carbon cycle and climate change research. Remote sensing combined with other climate and meteorological data offers a convenient tool for large scale GPP estimation. This paper presents a study of GPP estimation using three methods wiht in situ measurements of canopy reflectance, LAI, and the photosynthetically active radiation (PAR). First, because LAI is considered as an indicator of the factor of absorbed PAR (fAPAR), it provides reasonable estimates of GPP for all types of wheat with coefficient of determination R2 of 0.7353. The second method uses four kinds of vegetation indices (VIs) to estimate GPP because these indices are suggested to be reliable candidates in the estimation of light use efficiency (LUE). Good determination coefficients were acquired in estimating GPP with R2 ranging from the lowest of 0.7604 for NDVI to the highest of 0.8505 for EVI. A new method was proposed for the estimation of GPP following the Monteith logic, which considering GPP as a product of VI x VI x PAR. Results indicated that this method can provide the best estimates of GPP as determination coefficient R2 increased largely compared to the other two methods. EVI x EVI x PAR was demonstrated to be the most suitable for the estimation of GPP with the highest R2 of 0.9207, which was about 10% larger as compared to GPP estimated from the single EVI. These results will be helpful for the development of new models of GPP estimation with all remote sensing inputs.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53014
Title: Ground movements caused by deep underground mining in Guan-Zhuang iron mine, Luzhong, China
Author: Wen -Xiu Li, Lei Wen, Xiao-Min Liu
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Issue 3, June 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Deep mining, Iron ore, GPS data, Ground movement, Regional horizontal displacement
Abstract: It is difficult to calculate the accurate ground movement due to deep underground mining because of the complexity of the geotechnical environment. Guan-Zhuang iron mine is a pillarless sublevel caving mine operated by Luzhong Metallurgical Mining Company, south-east of Jinan, PR China. It mines the Zhangjiawa Seam at a depth of approximately 520m. Although the towers are outside the conventional ' angle of draw ' subsidence influence criteria, and have seen only negligible verticle displacement as a result of deep mining, there has been widespread evidence of regional horizontal displacement of the land surface, large distances away from the mining area. Possible explanations of these displacements include one or a combination of mechanisms such as pre-mining stress relaxation, regional joint patterns, soft rock strata, displacement toward active goaf areas. Luzhong Metallurgical Mining Company have been making precise measurements of distances near the shaft towers in the Guan-Zhuang iron mine since 2003. The results show horizontal displacements of up to 96 mm occur even when underground mining is about 0.8 km from the survey displacements. From an analysis of these and other survey results it is concluded that mining effects extend a long way from deep mining.The results also show that ground horizontal displacements are typically at least as great as the vertical component, that the maximum horizontal displacement occurs soon after undermining.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53013
Title: Estimating chlorophyll content of crops from hyprspectral data using a normalized area over reflectance curve (NAOC)
Author: Jesus Delegido, Luis Alonso, Gonzalo Gonzalez, Jose Moreno
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Issue 3, June 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Chlorophyll, Hyperspectral remote sensing, Leaf area index, fCOVER, Proba/CHRIS, CASI
Abstract: The Normalized Area Over reflectance Curve (NAOC) is proposed as a new index for remote sensing estimation of the leaf chlorophyll content of heterogeneous areas with different crops, different canopies and different types of bare soil. This index is based on the calculation of the area over the reflectance curve obtained by high spectral resolution reflectance measurements, determined, from the integral of the red-near-infrared interval, divided by the maximum reflectance in the spectral region. For this, use has been made of the experimental data of teh SPARC campaigns, where in situ measurements were made of leaf chlorophyll content, LAI and fCOVER of 9 different crops- thus, yielding 300 different values with broad variability of these biophysical parameters. In addition, Proba/CHRIS hyperspectral images were obtained simultaneously to the ground measurements. By comparing the spectra of each pixel with its experimental leaf chlorophyll value, the NAOC was proven to exhibit a linear correlation to chlorophyll content. Calculating the correlation between these variables in the 600-800 nm interval, the best correlation was obtained by computing the integral of the spectral reflectance curve between 643 and 795 nm, which practically covers the spectral range of maximum chlorophyll adsborption (at around 670 nm) and maximum leaf reflectance in the infrared (750-800 nm). Based on a Proba/CHRIS image, a chlorophyll map was generated using NAOC and compared with the land-use (crops classification) map. The method yielded a leaf chlorophyll content map of the study area, comprising a large heterogeneous zone. An analysis was made to determine whether the method also serves to estimate the total chlorophyll content of a canopy, multiplying the leaf chlorophyll content by the LAI. To validate the method, use was made of the data from another campaign (SEN2FLEX), in which measurements were made of different biophysical parameters of 7 crops, and hyperspectral images were obtained with the CASI imaging radiometer from an aircraft. Applying the method to a CASI image, a map of leaf chlorophyll content was obtained, which on, establishing comparisons with the experimental data allowed us to estimate chlorophyll with a root mean square error of 4.2?g/cm2, similar or smaller than other methods but with the improvement of applicability to a larger set of different crop types.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53012
Title: Predicting plant water content in Eucalyptus grandis forest stands in KwaZulu-Natal, South Africa using field spectra resampled to the Sumbandila Satellite Sensor
Author: Z.Oumar, O. Mutanga
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Issue 3, June 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Spectroscopy, Neural networks, Sumbandila satellite
Abstract: The measurement of plant water content is essential to assess stress and disturbance in forest plantations. Traditional techniques to assess plant water content are costly, time consuming and spatially restrictive. Remote sensing techniques offer the alternative of a non-destructive and instantaneous method of assessing plant water content over large spatial scales where ground measurements would be impossible on a regular basis. In the context of South Africa, due to the cost and availability of imagery, studies focusing on the estimation of plant water content using remote sensing data have been limited. With the scheduled launch of the South African satellite SumbandilaSat evident in 2009, it is imperative to test the utility of this satellite in estimating plant water content. This study resamples field spectral data measured from a field spectrometer to the band settings of the SumbandilaSat in order to test its potential in estimating plant water content in a Eucalyptus plantation. The resampled SumbandilaSat wavebands were input into a neural network due to its ability to model non-linearity in a dataset and its inherent ability to perform better than conventional linear models. The integrated approach involving neural networks and the resampled field spectral data successfully predicted plant water content with a correlation coefficient of 0.74 and a root mean square error (RMSE) of 1.41% on an independent test dataset outperforming the traditional multiple regression method of estimation. The best-trained neural network algorithm that was chosen for assessing the relationship between plant water content and the SumbandilaSat bands was based on a few points only and more research is required to test the robustness and effectiveness of this sensor in estimating plant water content across different species and seasons. This is critical for monitoring plantation health in South Africa using a cheaply available local sensor containing key vegetation wavelengths.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53011
Title: Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours
Author: Salman Ahmadi, M.J. Valadan Zoej, Hamid Ebadi, Hamid Abrishami Moghaddam, Ali Mohammadzadeh
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Issue 3, June 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Building boundary extraction, active contours, level set, aerial images
Abstract: To present a new method for building boundary detection and extraction based on teh active contour model, is the main objective of this research. Classical models of this type are associated with several shortcomings; they require extensive intialization, they are sensitive to noise, and adjustment issues often become problematic with complex images. In this research a new model of active contours has been proposed that is optimized for the automatic building extraction. This new active contour model, in comparison to the classical ones, can detect and extract the building boundaries more accurately, and is capable of avoiding detection of the boundaries of features in the neighborhood of buildings such as streets and trees. Finally, the detected building boundaries are generalized to obtain a regular shape for building boundaries. Tests with our proposed model demonstrate excellent accuracy in terms of building boundary extraction. However, due to the radiometric similarity between building roofs and the image background, our system fails to recognize a few buildings.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53010
Title: Texture-based classification of sub-Antarctic vegetation communities on Heard Island
Author: Humphrey Murray, Arko Lucieer, Raymond Williams
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Issue 3, June 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Vegetation mapping, Multispectral classification, Grey level co-occurrence matrix (GLCM), Texture-based classification, Sub-Antarctic Heard Island, IKONOS imagery
Abstract: This study was the first to use high-resolution IKONOS imagery to classify vegetation communities on sub-Antarctic Heard Island. We focused on the use of texture measures, in addition to standard multispectral information, to improve the classification of sub-Antarctic vegetation communities. Heard Island ' s pristine and rapidly changing environment makes it a relevant and exiciting location to study the regional effects of climate change. This study uses IKONOS imagery to provide automated, up-to-date, and non-invasive means to map vegetation as an important indicator for environmental change. Three classification techniques were compared: multispectral classification, texture based classification, and a combination of both. Texture features were calculated using the Grey Level Co-occurrence Matrix (GLCM). We investigated the effect of the texture window size on classification accuracy. The combined approach produced a higher accuracy than using multispectral bands alone. It was also found that the selection of GLCM texture features is critical. The highest accuracy (85%) was produced using all original spectral bands and three uncorrelated texture features. Incorporating texture improved classification accuracy by 6%.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53009
Title: Toward accountable land use mapping: Using geocomputation to improve classification accuracy and reveal uncertainty
Author: Johan Beekhuizen, Keith C. Clarke
Editor: Alfred Stein
Year: 2010
Publisher: Elsevier, Vol 12, Issue 3, June 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: International Journal of Applied Earth Observation and Geoinformation
Keywords: Land use, Land cover, Classification, Geocomputation, Texture, uncertainty
Abstract: The classification of satellite imagery into land use/cover maps is a major challenge in the field of remote sensing. This research aimed at improving the classification accuracy while also revealing uncertain areas by employing a geocomputational approach. We computed numerous land use maps by considering both image texture and band ratio information in the classification procedure. For each land use class, those classifications with the highest class-accuracy were selected and combined into class-probability maps. By selecting the land use class with highest probability for each pixel, we created a hard classification. We stored the corresponding class probabilities in a separate map, indicating the spatial uncertainity in the hard classification. By combining the uncertainty map and the hard classification we created a probability-based land use map, containing spatial estimates of the uncertainty. The technique was tested for both ASTER and Landsat 5 satellite imagery of Gorizia, Italy, and resulted in a 34% and 31% increase, respectively, in the kappa coefficient of classification accuracy. We believe that geocomputational classification methods can be used generally to improve land use and land cover classification from imagery, and to help incorporate classification uncertainty into the resultant map themes.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53008
Title: Sustaining industrial activity and ecological quality: the potential role of an ecosystem services approach
Author: Lorraine Maltby, Achim Paetzold and Philip Warren
Editor: Lesley C. Batty and Kevin B. Hallberg
Year: 2010
Publisher: Cambridge University Press, 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Ecology of Industrial Pollution
Keywords: Industrialisation, Environmetal Impact, Sheffield ' s metal industries, environmental degradation
Abstract: Modern societies benefit greatly from the products of industry and ecosystems provide the raw materials and energy required to produce them. Societies also benefit from a wide range of other ecosystem services including the supply of food, fuel, fibre adn water, the regulation of disease and climate, recreational opportunities and aesthetic enjoyment. However there is a potential conflict between these two types of benefits as increased industrialisation is often associated with increased release of hazardous chemicals or habitat modification, which have the potential to degrade ecosystem services, including those required for continued industrial production and development. Here we consider the relatioship between industrialisation and environemental impact using the development of Sheffield ' s metal industries as a case study. We then go on to explore the broader question of ecological quality and how it is defined, before outlining a quality assessment framework based on ecosystem services that may provide a tool for managing ecosystems for the optimal delivery of services Finally, we consider the globa aspects of economic development, industrialisation and environmental degradation.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 53007
Title: Large-scale mine site restoration of Australian eucalypt forests after bauxite mining: soil management and ecosystem development
Author: Mark Tibbett
Editor: Lesley C. Batty and Kevin B. Hallberg
Year: 2010
Publisher: Cambridge University Press, 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Ecology of Industrial Pollution
Keywords: Bauxite mining, Australia, Rehabilitation, Restoration
Abstract: Mining is essential to provide the resources for modern industrial societies but can result in a catastrophic destruction of pre-mining ecosystems. In Australia, these are often natural ecosystems, commonly pristine and with significant endemism in the flora and fauna. In all cases, the mining of bauxite ore in Australia occurs in areas covered by eucalyptus forests or open woodland. Five major bauxite mines are in operation in Australia and these are (From NE to SW) Weipa (Rio Tinto) where the natural vegetation is an open Eucalyptus tetradonta (Darwin Stringybark) woodland, Gove (Rio Tinto), a mixed E. tetradonta and E. miniata woodland (both adjacent to the Gulf of Carpentaria) and Huntly, Willowdale (Alcoa) and Boddington (Worsley) mining in the unique E. marginata (Jarrah) forest region of Western Australia. Bauxite mining is an important economic activity for Australia, and it is an industry in which it leads the world. Australia is the world ' s largest bauxite producer, mining 40% of the world ' s bauxite ore. Australia ' s aluminium industry is worth over $7.8 billion (in 2004) in export earnings and employs over 16 000 people directly and many more in associated service industries. Australia has, therefore, made the decision to sacrifice some of its unique forested areas in order to maintain economic prosperity for its people. In order to minimise the negative effect of bauxite mining, typically a form of strip mining or open cast mining, stringent measures (including financial instruments) have been put in place by the state and federal governments whereby the mining companies are required to restore the natural forest into sustainable ecosystems that reflects the original forest prior to mining as much as possible. As mining results in such a catastrophic destruction of the entire terrestrial ecosystems, including the regolith and associated hydrology, there is a tacti acceptance that complete restoration on human time scales is not achievable. Therefore the term ' rehabilitation ' is often used to describe the restoration processes and targets in the local literature. Australia has developed some world leading practices in mine site restoration after bauxite mining (Bell 2001; Mulligan et al. 2006). Restoration techniques are underpinned by two key practices: (i) incremental rehabilitation, restoring land progressively to forest after it has been mined out (Fourie & Tibbett 2006; Koch 2007a) and (ii) integrating mining with restoration, a practice that requires joint planning by both ecological and mining engineers (Hinz 1002; Koch 2007a).
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 53006
Title: Manchester Ship Canal and Salford Quays: Industrial legacy and ecologica restoration
Author: Adrian E. Williams, Rachel J. Waterfall, Keith N. White and Keith Hendry
Editor: Lesley C. Batty and Kevin B. Hallberg
Year: 2010
Publisher: Cambridge University Press, 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Ecology of Industrial Pollution
Keywords: Manchester Ship Canal (MSC), River Irwell, Water quality management stratergies
Abstract: The upper reaches of the Manchester Ship Canal (MSC) and associated dock basins have been polluted by operational discharges, surface water runoff as well as upstream inputs from the River Irwell. The resulting poor water quality has been exacerbated by the deep (7m) water column and limited water exchange. In this chapter, we describe the water quality management strategies put in place since the late 1980s to address poor water quality, specifically oxygenation of the water column of the MSC and isolation of the docks from the canal followed by destratification of the water column and habitat diversification. We then examine the effectiveness of these strategies in improving water quality, increasing biodiversity and enhancing the recreational potential of the enclosed dock basins and the MSC.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 53005
Title: Ecological recovery in a river polluted to its sources: the River Tame in the English Midlands
Author: Terry E. L. Langford, Peter. J. Shaw, Shelley R. Howard, Alastair J.D. Ferguson, David Ottewell and Rowland Eley
Editor: Lesley C. Batty and Kevin B. Hallberg
Year: 2010
Publisher: Cambridge University Press, 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Ecology of Industrial Pollution
Keywords: Rivers, Chemical changes, biological changes, Ecological recovery
Abstract: In many industrialised regions particularly in Britain, rivers have been impounded for use by mills, polluted by multiple point sources and channelised to the very source over many centuries (e.g., Bracegirdle 1973; Lester 1975; Harkness 1982; Holland & Harding 1984; Haslam 1991). Since the 1960s, the ecological recovery of such historically polluted and disturbed rivers in Britain has been remarkable. Long reaches of once black, foetid, fishless watercourses, some almost completely devoid of macroscopic biota, have been transformed into clear streams and rivers with diverse floras and faunas and prolific fish populations. This transformation is perceived to have been the result of a number of factors, including law, public pressure, new technologies, new infrastructure and changes in the economy and industry. Even so, ecological recovery is still poorly advanced in some rivers and the reasons for this have not been explained in any detail. This short chapter uses sets of long-term chemical and biological data from three sites on a Midland river in a preliminary analysis of the possible reasons for the variable rates of ecological recovery and the relationship between the long-term chemical and biological changes in the river. It is part of a series of longer term studies of the problems associated with ecological recovery of polluted rivers (e.g. Langford et al. 2009).
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 53004
Title: The microbial ecology of remediating industrially contaminated land: Sorting out the bugs in the system
Author: Ken KIllham
Editor: Lesley C. Batty and Kevin B. Hallberg
Year: 2010
Publisher: Cambridge University Press, 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Ecology of Industrial Pollution
Keywords: Microbial ecology, Bioremediation
Abstract: Understanding and manipulating the microbial ecology of contaminated land are increasingly critical steps towards meeting the challenge of remediating the considerable legacy of industrial pollution in the UK and worldwide. Understanding the microbial ecology of contaminated land is key to its remediation in two ways. First, the microbial community in the soil, occasionally enhanced through inoculation, can be exploited to bioremediate (through either in situ or ex situ approaches) contaminated sites (Alexander 1999; Atlas & Philp 2005). This is an increasingly attractive, environmentally sustainable option as excavation and landfill of contaminated site waste become both increasingly expensive (both through landfill tax increases, ever-increasing transport costs and the introduction of the aggregate levy on material brought in as fill), fewer landfill sites are available (in Scotland, for example, there are no hazardous landfills and material must be transported great distances, further adding to disposal costs) and environmental regulators rightly press for more sustainable approaches to site clean-up. Second, the indigenous microbial communities of sites are often impacted by the contamination, particularly where toxic contaminants such as free phase solvents and available heavy metals are present, and part of the remediation challenges is to restore soil/aquifer biological function. Because of the wide range of microbial functions carried out tin the soil, in particular, this restoration may be linked, for example, to carbon and nutrient (N.P and S) cycling or to the wide range of plant-microbe interactions on which ecosystem health depends. In this chapter, two aspects of the microbial ecology of remediating industrially contaminated soils are considered: Key soil bacteria, such as those involved in the biodegradation of organic contaminants and in key soil functions, have been selected for construction of biosensors to assess the extent and impact of contamination, to support the bioremediation process and to establish restoration of soil health.
Location: 215
Literature cited 1: None
Literature cited 2: None
ID: 53003
Title: The microbial ecology of land and water contaminated with radioactive waste: towards the development of bioremediation options for the nuclear industry
Author: Andrea Geissler, Sonja Selenska-Pobell, Katherine Morris, Ian T. Burke, Francis R. Livens and Jonathan R. Lloyd
Editor: Lesley C. Batty and Kevin B. Hallberg
Year: 2010
Publisher: Cambridge University Press, 2010
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: Ecology of Industrial Pollution
Keywords: Radionuclides, Microorganisms, Technetium, Uranium, Bioreduction
Abstract: The release of radionuclides from nuclear and mining sites and their subsequent mobility in the enviornment is a subject of intense public concern and has promoted much recent research into the environmental fate of radioactive waste (Lloyd & Renshaw 2005b). Naturally occurring radionuclides can input significant quantities of radioactivity into the environment while both natural and artificial/manmade radionuclides have also been released as a consequence of nuclear weapons testing in the 1950s and 1960s, and via accidental release, e.g., from Chernobyl in 1986. The major burden of anthropogenic environmental radioactivity, however, is from the nuclear facilities themselves and includes the continuing controlled discharge of process effluents produced by industrial activities allied to the generation of nuclear power.
Wastes containing radionuclides are produced at the many steps in the nuclear fuel cycle, and vary considerably from low level, high-volume radioactive effluents produced during uranium mining to the intensely radioactive plant, fuel and liquid wastes produced from reactor operation and fuel reprocessing (Lloyd & Renshaw 2005 b). The stewardship of these contaminated waste-streams needs a much deeper understanding of the biological and chemical factors controlling the mobility of radionuclides in the environment. Indeed, this is highly relevant on a global stage as anthropogenic radionuclides have been dispersed to the environment both by accident and as part of a controlled/monitored release, e.g., in effluents. Micro-organisms have adapted to live even in radioactively contaminated environments (Selenska-Pobell 2002; Lloyd 2003; Fredrickson et al. 2004; Ruggiero et al. 2005; Akob et al 2007) and they can affect radionuclide speciation via a number of mechanisms which are potentially useful for scalable, cost-effective bioremediation of sediments and waters impacted by nuclear waste (Keith-Roach & Livens 2002; Lloyd 2003; Suzuki et al. 2003; Lloyd & Renshaw 2005a; Brodie et al. 2006; Fomina et al 2007). The aim of this chapter is to give an overview of known interactions of microorganisms with key radionuclides, focusing on potential roles in controlling radionuclide mobility in the subsurface. We will then discuss the influence of microbial processes on the immobilisation of radionuclides described in recent laboratory sutdies from our groups, focusing on two priority contaminants: technetium and uranium. The former studies address the impact of bioreduction strategies on solubility and include work on stimulated bioreduction strategies on solubility and include work on stimulated bioreduction (achieved via added organic electron donor) on technetium solubility, while the latter studies demonstrate the immobilisation of uranium in sediments from a uranium mining waste pile without the addition of a carbon source. Finally, due to the widespread use of nitric acid in the nuclear sector, the multiple influences of nitrate and nitrate- reducing bacteria on the solubility of radionuclides will be discussed, especially where the activities of these organisms impact on the biogeochemistry of uranium and technetium.
Location: 215
Literature cited 1: None
Literature cited 2: None