Heavy metal concentrations in litteral sediments from the Beagle Channel,Tierra del Fuego,Argentina

For the first time the concentration of trace metals (Fe, Pb, Cu, Zn, Cd and total Hg) of sediments from the coastal zone of the Beagle Channel (Tierra del Fuego, in Southern Argentina) were measured. Atomic absorption spectrophotometry was utilized in order to determine the metal contents. The level of metals as observed in the sediments was recognized as the natural background, even though the use of normalization of lead, copper, and zinc to iron allowed the identification of the main sources of metal pollution for this environment. In order to develop future environmental monitoring programmes for the area of Ushuaia city and the Beagle Channel, the present results need to be considered.     

Transition index maps for urban growth simulation: application of artificial neural networks,weight of evidence and fuzzy multi-criteria evaluation

Transition index maps (TIMs) are key products in urban growth simulation models. However, their operationalization is still conflicting. Our aim was to compare the prediction accuracy of three TIM-based spatially explicit land cover change (LCC) models in the mega city of Mumbai, India. These LCC models include two data-driven approaches, namely artificial neural networks (ANNs) and weight of evidence (WOE), and one knowledge-based approach which integrates an analytical hierarchical process with fuzzy membership functions (FAHP). Using the relative operating characteristics (ROC), the performance of these three LCC models were evaluated. The results showed 85%, 75%, and 73% accuracy for the ANN, FAHP, and WOE. The ANN was clearly superior compared to the other LCC models when simulating urban growth for the year 2010; hence, ANN was used to predict urban growth for 2020 and 2030. Projected urban growth maps were assessed using statistical measures, including figure of merit, average spatial distance deviation, producer accuracy, and overall accuracy. Based on our findings, we recomend ANNs as an and accurate method for simulating future patterns of urban growth.     

Effluent trading in river systems through stochastic decision-making process: a case study

Environmental Science and Pollution Research - The objective of this paper is to provide an efficient framework for effluent trading in river systems. The proposed framework consists of two...     

Plant species affect colonization patterns and metabolic activity of associated endophytes during phytoremediation of crude oil-contaminated soil

Plants coupled with endophytic bacteria hold great potential for the remediation of polluted environment. The colonization patterns and activity of inoculated endophytes in rhizosphere and endosphere of host plant are among the primary factors that may influence the phytoremediation process. However, these colonization patterns and metabolic activity of the inoculated endophytes are in turn controlled by none other than the host plant itself. The present study aims to determine such an interaction specifically for plant-endophyte systems remediating crude oil-contaminated soil. A consortium (AP) of two oil-degrading endophytic bacteria (Acinetobacter sp. strain BRSI56 and Pseudomonas aeruginosa strain BRRI54) was inoculated to two grasses, Brachiaria mutica and Leptochloa fusca, vegetated in crude oil-contaminated soil. Colonization patterns and metabolic activity of the endophytes were monitored in the rhizosphere and endosphere of the plants. Bacterial augmentation enhanced plant growth and crude oil degradation. Maximum crude oil degradation (78 %) was achieved with B. mutica plants inoculated with AP consortium. This degradation was significantly higher than those treatments, where plants and bacteria were used individually or L. fusca and endophytes were used in combination. Moreover, colonization and metabolic activity of the endophytes were higher in the rhizosphere and endosphere of B. mutica than L. fusca. The plant species affected not only colonization pattern and biofilm formation of the inoculated bacteria in the rhizosphere and endosphere of the host plant but also affected the expression of alkane hydroxylase gene, alkB. Hence, the investigation revealed that plant species can affect colonization patterns and metabolic activity of inoculated endophytic bacteria and ultimately the phytoremediation process.     

Impact of Hazardous Exposure to Metals in the Nile and Delta Lakes on the Catfish, Clarias lazera

The impact of metal pollution in the Nile and Delta lakes was studied in Clarias lazera. Lake Edku is grouped as the site highest in metal concentrations. Compared to Lakes Maryût and Edku, the Nile stations displayed lower levels of metal contamination signifying their selection as reference sites. Metals were accumulated most by the liver, less by muscles and least by serum. Iron showed the highest bioconcentration factors (BCF) in liver, muscles or serum compared to other metals. Even after the refinement of the surrounding water, fish seem to uphold the metals that have been previously ingested. Mercury, in particular, seems to eventually reside in muscles rather than in liver. The positive relationship between total serum protein and metal contents may indicate the formation of specific metal-binding proteins. Meanwhile, serum hyperalbuminemia in polluted fish is probably a shock response towards the high stress index induced by metals. The hypothesis that most of serum copper is bound to ceruloplasmin is documented also in C. lazera. Moderate, but not extennsive, exposure to metals was quite stimulatory to liver alkaline phosphatase (AP) biosynthesis. AP could, thus, be considered as a promising bioindicator for assessing sublethal water intoxicosis.     

GIS aided prediction of CO2 emission dispersion from geothermal electricity production

CO₂ is the dominant constituent of non-condensable gases in the steam phase of most geothermal fluids. This paper attempts to present the results of a study conducted to develop prediction modeling of CO₂ dispersion in the surrounding atmosphere from a planned 50 MWe geothermal power plant prior to its production. Dispersion models are widely used for predicting future concentrations of environmental emissions on a range of geographic scales. The dispersion type for gases and their average removal rate depends on the meteorological conditions such as wind direction, wind speed, precipitation, atmospheric stability, and surface roughness and topography. Geographic Information System (GIS) capabilities were used for quality visualization of the model outputs and presenting an accurate numerical copy of the study area. The results by the prediction model show that the natural transfer of CO₂ will be from the power plant toward east and northeast and CO₂ concentration trends after the power plant utilization will be similar to the background conditions with minor changes. This dispersion test was carried out to validate and field test the GIS aided dispersion modeling approach described in the paper and the procedure may be applicable for other studies assessing the emission dispersion of pollutants from a point source.     

Evaluation of education and water resource types on some wheat land features, using Fars Comprehensive Agricultural Database (case study; Pasargad, Iran)

Fars Comprehensive Agricultural Database was created to remove bottlenecks and constrains of province for decision makers in a way that leads to sustainable agriculture. Regarding Fars agricultural comprehensive information database, and the importance of wheat as the strategic commodity, this study was conducted in Ali-Abad-e-Kamin (Pasargad, Iran) to assess two most important managerial factors affecting other agricultural factors. Therefore, in this study, besides evaluating the effect of water resource on wheat yield and other traits, education impacts were analyzed and evaluated as well. Data were collected regarding cadastre land use information derived from satellite imagery combined with GIS potencies, and also a comprehensive questionnaire was completed to collect local field information. Results revealed that educational level has significant effect on crop yield, fields’ area and seed consumption rate and also effect of water resource showed significant difference for crop yield, fields’ area. Finally, interactive effect of water resource and educational level showed significant difference just for wheat yield. Also, as a result, higher education positively results in improved wheat yield, lands’ area and seed consumption rate. On the other hand, river as a type of sustainable water resource with karstic geological formations positively affected wheat yield, lands’ area and farms distance from village. Overall, transferring knowledge from relevant organization resulting in higher productivity seems to be necessary.     

Levels of heavy metals in tissues of shingi fish (Heteropneustes fossilis) from Buriganga River, Bangladesh

Heavy metal pollution was reported in commercially valuable freshwater edible fish in the Buriganga River, Bangladesh. The concentrations of As, Pb, Cd, Cr, Zn, and Cu were investigated in the muscle, gill, stomach, intestine, and liver of Heteropneustes fossilis caught at three stations to assess the degree of fish pollution by heavy metals. Significant differences in concentrations of analyzed elements were observed among different tissues, but not among the stations. The ranges of the measured concentrations (μg/g dry weight) in the tissues of H. fossilis were as follows: arsenic concentration was (0.2–0.4), (0.82–0.90), (3.29–3.99), (2.20–2.80), and (2.41–2.90), that of lead was (1.79–2.20), (4.95–6.55), (10.36–13.38), (5.74–9.70), and (18.20–18.79), that of cadmium was (0.3–0.4), (2.87–4.27), (1.03–1.63), (1.55–4.59), and (2.25–5.50), that of chromium was (1.40–1.70), (3.52–3.72), (2.28–5.29), (2.77–3.79), and (4.25–8.65), that of zinc was (24.47–28.82), (16.82–18.80), (20.22–22.20), (22.86–26.68), and (60.82–67.80), and that of copper was (7.80–8.50), (6.22–6.81), (38.21–44.25), (17.07–21.03), and (43.24–47.30) in the muscle, gill, stomach, intestine, and liver, respectively. This research showed that the liver appeared to be the main heavy metal storage tissue, while the muscle had the lowest levels of analyzed metals. The concentrations of metal in the muscles not exceeded the acceptable levels for a food source for human consumption.     

Remotely-Sensed Active Fire Data for Protected Area Management: Eight-Year Patterns in the Manas National Park, India

The Terai-Duar savanna and grasslands, which once extended along most of the Himalayan foothills, now only remain in a number of protected areas. Within these localities, grassland burning is a major issue, but data on frequency and distribution of fires are limited. Here, we analysed the incidence of active fires, which only occur during the dry season (Nov.–Mar.), within a significant area of Terai grasslands: the Manas National Park (MNP), India. We obtained locations of 781 fires during the 2000–2008 dry seasons, from the Fire Information for Resource Management System (FIRMS) that delivers global MODIS hotspot/fire locations using remote sensing and GIS technologies. Annual number of fires rose significantly from around 20 at the start of the study period to over 90 after 2002, with most (85%) detected between December and January. Over half of the fires occurred in tall grasslands, but fire density was highest in wetland and riverine vegetation, dry at the time. Most burning took place near rivers, roads and the park boundary, suggesting anthropogenic origins. A kernel density map of all recorded fires indicated three heavily burnt areas in the MNP, all within the tall grasslands. Our study demonstrates, despite some technical caveats linked to fire detection technology, which is improving, that remote fire data can be a practical tool in understanding fire concentration and burning temporal patterns in highly vulnerable habitats, useful in guiding management.