Mercury uptake and allocation in Juncus maritimus: implications for phytoremediation and restoration of a mercury contaminated salt marsh

Juncus maritimus is the most abundant macrophyte in Laranjo bay, a Portuguese salt marsh heavily polluted by mercury (Hg). With the aim to elucidate the role of this species in the salt marsh Hg cycling and restoration, plants were harvested between March 2006 and January 2008 from four locations differing in Hg contamination. Metal uptake and distribution between plant organs were evaluated, biomass and Hg pools were also determined. Results showed that J. maritimus may influence the sediment pH and Eh, thus increasing the Hg available for uptake. Most (95-98%) of the absorbed Hg was retained belowground, phytostabilizing the metal and reducing the amount of Hg in the sediments. These results suggest that in salt marshes dominated by J. maritimus the approach could be phytostabilization, where these plants can be used to immobilize metals and store them belowground, reducing the pool of bioavailable Hg within contaminated marshes and acting as a sink rather than a source of contamination to the surrounding areas.     

Heavy metal biomonitoring and phytoremediation potentialities of aquatic macrophytes in River Nile

The concentrations of Cd, Cu, Pb, and Zn in sediments, water, and different plant organs of six aquatic vascular plant species, Ceratophyllum demersum L. Echinochloa pyramidalis (Lam.) Hitchc. & Chase; Eichhornia crassipes (Mart.) Solms-Laub; Myriophyllum spicatum L.; Phragmites australis (Cav.) Trin. ex Steud; and Typha domingensis (Pers.) Poir. ex Steud, growing naturally in the Nile system (Sohag Governorate), were investigated. The aim was to define which species and which plant organs exhibit the greatest accumulation and evaluate whether these species could be usefully employed in biomonitoring and phytoremediation programs. The recorded metals in water samples were above the standard levels of both US Environmental Protection Agency and Egyptian Environmental Affairs Agency except for Pb. The concentrations of heavy metals in water, sediments, and plants possess the same trend: Zn > Cu > Pb > Cd which reflects the biomonitoring potentialities of the investigated plant species. Generally, the variation of heavy element concentrations in water and sediments in relation to site and season, as assessed by two-way repeated measured ANOVA, was significant (p < 0.05). However, insignificant variations were observed in the concentrations of Pb and Cd in sediments in relation to season and of Cu and Zn in relation to site. Results also showed that the selectivity of the heavy elements for the investigated plants varied significantly (p < 0.05) with species variation. The accumulation capability of the investigated species could be arranged according to this pattern: C. demersum > E. crassipes > M. spicatum > E. pyramidalis > T. domingensis > P. australis. On the basis of the element concentrations, roots of all the studied species contain higher concentrations of Cu and Zn than shoots while leaves usually acquire the highest concentrations of Pb. Cd concentrations among different plant organs are comparable except in M. spicatum where the highest Cd concentrations were recorded in the leaves. Our results also demonstrated that all the studied species can accumulate more than 1,450-fold the concentration of the investigated heavy elements in water rendering them of interest for use in phytoremediation studies of polluted waters. Given the absence of systematic water quality monitoring, heavy elements in plants, rather than sediments, provide a cost-effective means for assessing heavy element accumulation in aquatic systems during plant organ lifespan.     

An integrated approach for spatio-temporal variability analysis of wetlands: a case study of Abaya and Chamo lakes, Ethiopia

Starting with the intensification of irrigation activities in the beginning of 1980s in Abaya and Chamo lakes area, the decreasing water inflow to the lakes caused denudation of the wetlands. The ecological situation in the lake region changed significantly during last four decades. The lakes and associated wetlands change have been studied using Landsat MSS (1973), Landsat TM (1986), and Ladsat ETM (2000) satellite imagery. Along with satellite imagery, other hydro-meteorological data were collected and hydro-meteorological data analyses were done to assess the variability of wetlands. From these data, lakes morphometric property estimation at different time series and water balance analysis for both lakes were done. Wetlands are mapped from the TCT image and these maps are subject to change detection to see the temporal and spatial variability of the wetlands. Moreover, the lake-morphometric area and volume variation have been studied. The result showed that between 1986 and 2000, a significant reduction has been observed but lesser than the previous decades (6.4 km(2)). The identified reason behind this change is that the free settlement and shoreline cultivation of the wetlands causing the soil erosion and eventually adds the sediment to the wetlands.     

A proposed methodology to determine accuracy of location and extent of geographically isolated wetlands

The disposal of industrial and sewage water is a problem of increasing importance throughout the world. In India, and most of the developing countries untreated sewage and industrial wastes are discharged on land or into the running water streams which is used for irrigating crops. These wastes often contain high amount of trace elements which may accumulate in soils in excessive quantities on long term use and enter the food chain through absorption by the plants. Among the trace metals, Cd has received the greater attention because of its easy absorption and accumulation in plants and animals to levels toxic for their health. The objective of this study conducted in three industrially different cities viz., Ludhiana, Jalandhar and Malerkotla was to monitor the extent of Cd accumulation in soils and plants receiving untreated sewage water. Plant and soil samples were collected from sewage and tubewell irrigated areas. Soil samples were analysed for texture, pH, EC, organic carbon (OC), CaCO(3), bioavailable DTPA-Cd and plant samples were analysed for total Cd. In sewage irrigated soils, the mean values of pH were lower but organic carbon and electrical conductivity were generally higher both in surface and sub-surface layers of all the three cities as compared to tubewell irrigated soils. The mean DTPA- extractable Cd in sewage irrigated soil was 6.3- and 4.36-fold in Ludhiana, 3.38- and 1.71-fold in Jalandhar and 3.35- and 6.67-fold in Malerkotla in 0-15 and 15-30 cm soil depth, respectively, compared with the values in tubewell irrigated soils. The accumulation of DTPA-Cd in sewage irrigated soils was restricted to 30 cm depth after which the values were generally close to values in tubewell irrigated soils. Soil pH, OC, CaCO(3), clay and silt collectively accounted for 37.1%, 65.1% and 53.9% DTPA-extractable bioavailable Cd in soils of Ludhiana, Jalandhar and Malerkotla, respectively. Lower R(2) values in Ludhiana suggest that factors other than the ones mentioned may be affecting Cd availability. At all sites plants receiving sewage irrigation had elevated levels of Cd as compared to the plants receiving tubewell irrigation. The mean Cd content of sewage irrigated plants irrespective of the city was 5.96 microg g(-1) dry matter as compared to 0.98 microg g(-1) dry matter in tubewell irrigated plants. The results suggest that the intake of Cd obtained from consumption of crops grown on sewage irrigated soils would be much higher than the tolerable limits set by WHO and may, therefore, prove potentially toxic leading to various health ailments to humans and animals.     

A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the “One Sensor at Different Scales” (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R ² of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.     

Assessment of groundwater pollution in West Delhi, India using geostatistical approach

The exploration, exploitation, and unscientific management of groundwater resources in the National Capital Territory (NCT) of Delhi, India have posed a serious threat of reduction in quantity and deterioration of quality. The objective of the study is to determine the groundwater quality and to assess the risk of groundwater pollution at Najafgarh, NCT of Delhi. The groundwater quality parameters were analyzed from the existing wells of the Najafgarh and the thematic maps were generated using geostatistical concepts. Ordinary kriging and indicator kriging methods were used as geostatistical approach for preparation of thematic maps of the groundwater quality parameters such as bicarbonate, calcium, chloride, electrical conductivity (EC), magnesium, nitrate, sodium, and sulphate with concentrations equal or greater than their respective groundwater pollution cutoff value. Experimental semivariogram values were fitted well in spherical model for the water quality parameters, such as bicarbonate, chloride, EC, magnesium, sodium, and sulphate and in exponential model for calcium and nitrate. The thematic maps of all the groundwater quality parameters exhibited an increasing trend of pollution from the northern and western part of the study area towards the southern and eastern part. The concentration was highest at the southernmost part of the study area but it could not reflect correctly the groundwater pollution status. The indicator kriging method is useful to assess the risk of groundwater pollution by giving the conditional probability of concentrations of different chemical parameters exceeding their cutoff values. Thus, risk assessment of groundwater pollution is useful for proper management of groundwater resources and minimizing the pollution threat.     

Influence of land use and climate on the load of suspended solids in catchments of Andean rivers

Understanding the interaction between anthropogenic land use and the rainfall pattern can be crucial to predict changes in total suspended solids (TSS) in streams and rivers. We assessed the effects of land use and annual rainfall on the TSS load of 19 southern Chilean catchments. The results indicated that the concentration of TSS increased in catchments with a rainy regime and greater annual precipitation. TSS load also increased as the surface of open areas increased at the catchment scale and decreased with increasing cover of glaciers and perennial snow. However, we did not find support for models with interaction terms between climate and land use. Results suggest that a regional decrease in annual rainfall accompanied by an increase in the altitude of the zero isotherms, as predicted by climate models, should have multiple effects on TSS. In particular, increased TSS load can be expected from a contraction of glaciers and perennial snow areas as well as the intensification of new crops and urban expansion.     

Synergistic effects of metal nanoparticles and a phenolic uncoupler using microdroplet-based two-dimensional approach

A droplet-based microfluidic technique for testing multiple reagent concentrations is presented. We used this experimental approach to study combined effects of gold (AuNP) and silver nanoparticles (AgNP) with the phenolic uncoupler 2,4-dinitrophenol (DNP) with respect to the growth of Escherichia coli. In order to evaluate the toxicity of binary mixtures, we first encapsulated the E. coli cells and particle mixtures inside the microdroplets using PEEK (polyetherketone) modules. Two-dimensional concentration spaces with about 500 well separated droplets were addressed. We subsequently analyzed the cell growth, the viability and the autofluorescence intensity (metabolic activity) of the bacteria with a micro-flow-through fluorometer and photometer. Dose-dependent synergistic effects were found for the binary mixture of AgNPs and DNP, which indicated a stronger interaction in the mixture than it was expected from effect summation. For the binary mixture of DNP and AuNPs in non-toxic concentrations, we found only weak synergistic effects at low DNP concentrations. Furthermore, the non-toxic tested AuNPs causes effect summation in the binary mixture with the phenolic uncoupler. In general, we demonstrated the efficiency of a droplet-based microfluidic system for fast high-throughput screenings of binary and multiple mixtures. This work also confirmed the relevance of highly resolved droplet-based assays for the miniaturization of ecotoxicological aquatic test systems.     

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.     

The design of long-term air quality monitoring networks in urban areas using a spatiotemporal approach

The implementation and maintenance of an air pollution monitoring program can be expensive and time consuming, especially when the aim is for long-term monitoring over a significant area. Consequently, it is essential that sites are optimized to provide the best representative cover while minimizing costs. In the past, there has been a tendency to locate sampling stations at pollution hot-spots. While this is acceptable for determining a maximum potential exposure or identifying the extent of a risk, there are limitations to this approach when assessing the potential impact of any future abatement strategies or determining the level of exposure outside the vicinity. This paper presents an approach in which representative air quality assessments can be undertaken for an urban area using the minimum number of measurement sites. A novel methodology is described that involves site selection to capture the maximum variance in measured pollutants, while minimizing spatiotemporal autocorrelation between the selected sites. A case study is presented for Yazd, Iran. Overall, the results show that the proposed methodology can be effective and enable the long-term monitoring of air pollution to be undertaken on a cost-effective basis in urban areas. In addition, there is the potential for the methodology to be utilized for other forms of pollution (e.g., water, soil, and noise).     

A Bayesian approach for incorporating uncertainty and data worth in environmental projects

A data worth model is presented for the analysis of alternative sampling schemes in a special project where decisions have to be made under uncertainty. This model is part of a comprehensive risk analysis algorthm with the acronym BUDA. The statistical framework in BUDA is Bayesian in nature and incorporates both parameter uncertainty and natural variability. In BUDA a project iterates among the analyst, the decision maker, and the field work. As part of the analysis, a data worth model calculates the value of a data campaign before the actual field work, thereby allowing the identification of an optimum data collection scheme. A goal function which depicts the objectives of a project is used to discriminate among different alternatives. A Latin hypercube sampling scheme is used to propagate parameter uncertainties to the goal function. In our example the uncertain parameters are the parameters which describe the geostatistical properties of saturated hydraulic conductivity in a Molasse environment. Our results indicated that failing to account for parameter uncertainty produces unrealistically optimistic results, while ignoring the spatial structure can lead to an inefficient use of the existing data.     

Quantitative modelling of crude oil toxicity using the approach of cybernetics and structured mechanisms of microbial processes

Cybernetics and structured approach to biochemical processesin microbial cells offer the status of using various cellcomponents of Azotobacter as molecular markers intoxicity assay of environmental toxicants. The intra-linkeddynamic physicochemical reactions of the basic macromolecules– DNA, protein and membrane lipids – with respect to the crudeoil in the growth environment, results in an `impulse transferfunction'. The structured effects are reduction in both DNAand protein levels, and an elevated level of lipidperoxidation products. Toxicity index (Ti) of the crude oil,at a given concentration, is the percent ratio of thesummation of the products of these `effect parameters' andtheir respective weightings, relative to control. TheEC₅₀ is the effective percent (w/v) concentration of thecrude oil at which a toxicity index of 50% was recorded, andthis corresponded with about 44% loss in nitrogen fixation ofthe diazotrophic bacterium.     

The effects of hydraulic works and wetlands function in the Salado-River basin (Buenos Aires,Argentina)

Man-made activities exert great influences on fluvial ecosystems, with lowland rivers being substantially modified through agricultural land use and populations. The recent construction of drainage canals in the upper stretch of the Salado-River basin caused the mobilization of huge amounts of salts formerly stored in the groundwater. The main aim of this work was to analyze the effect of the discharges of those canals into the Salado-River water, under different hydrologic conditions, and the role of the wetlands and shallow lakes placed along the canals’ system. Physicochemical variables were measured and water samples were taken during times of high water, mean flows, drought, and extreme drought. The environmental variables and the plankton development were related to the hydrologic regime and reached minimum values during floods because of low temperatures and dilution. Local effects on the water’s ionic composition became pronounced during droughts because of groundwater input. Nutrient concentrations were mainly associated with point wastewater discharges. Conductivity, ion concentrations, total plankton biomass, and species richness increased in the Salado-River downstream site, after the canals’ discharges. The artificial-drainage system definitely promotes the incorporation of salts into the Salado-River basin. In this scenario, a careful hydraulic management is needed to take into account this issue of secondary salinization that threatens the economic exploitation of the region. The wetlands present in this study acted as service environments not only helping to reduce salt, nutrient, and suspended-solid concentrations downstream but also contributing a plethora of species and plankton biomass into the Salado-River main course.     

Top-down and bottom-up inventory approach for above ground forest biomass and carbon monitoring in REDD framework using multi-resolution satellite data

This study deals with the future scope of REDD (Reduced Emissions from Deforestation and forest Degradation) and REDD+ regimes for measuring and monitoring the current state and dynamics of carbon stocks over time with integrated geospatial and field-based biomass inventory approach. Multi-temporal and multi-resolution geospatial synergic approach incorporating satellite sensors from moderate to high resolution with stratified random sampling design is used. The inventory process involves a continuous forest inventory to facilitate the quantification of possible CO₂ reductions over time using statistical up-scaling procedures on various levels. The combined approach was applied on a regional scale taking Himachal Pradesh (India), as a case study, with a hierarchy of forest strata representing the forest structure found in India. Biophysical modeling implemented revealed power regression model as the best fit (R ²?=?0.82) to model the relationship between Normalized Difference Vegetation Index and biomass which was further implemented to calculate multi-temporal above ground biomass and carbon sequestration. The calculated value of net carbon sequestered by the forests totaled to 11.52 million tons (Mt) over the period of 20 years at the rate of 0.58 Mt per year since 1990 while CO₂ equivalent reduced from the environment by the forests under study during 20 years comes to 42.26 Mt in the study area.     

Development and validation of rapid assessment indices of condition for coastal tidal wetlands in southern New England, USA

Desertification, land degradation in arid, semi-arid, and dry sub-humid regions, is a global environmental problem. With respect to increasing importance of desertification and its complexity, the necessity of attention to the optimal de-desertification alternatives is essential. Therefore, this work presents an analytic hierarchy process (AHP) method to objectively select the optimal de-desertification alternatives based on the results of interviews with experts in Khezr Abad region, central Iran as the case study. This model was used in Yazd Khezr Abad region to evaluate the efficiency in presentation of better alternatives related to personal and environmental situations. Obtained results indicate that the criterion "proportion and adaptation to the environment" with the weighted average of 33.6% is the most important criterion from experts viewpoints. While prevention alternatives of land usage unsuitable of reveres and conversion with 22.88% mean weight and vegetation cover development and reclamation with 21.9% mean weight are recognized ordinarily as the most important de-desertification alternatives in region. Finally, sensitivity analysis is performed in detail by varying the objective factor decision weight, the priority weight of subjective factors, and the gain factors. After the fulfillment of sensitivity analysis and determination of the most sensitive criteria and alternatives, the former classification and ranking of alternatives does not change so much, and it was observed that unsuitable land use alternative with the preference degree of 22.7% was still in the first order of priority. The final priority of livestock grazing control alternative was replaced with the alternative of modification of ground water harvesting.     

A corporate approach to social monitoring and assessment for development in a fragile environment

The prevailing corporate trend regardingdevelopment of energy resources in the tropics emphasizesfinancial gain over long-term societal benefits. Somecorporations are beginning to find a competitive advantage linkedto proactive relations with host communities and adequateprotection of fragile ecosystems. Herein, we describe a casestudy where an international energy production company workedwith stakeholders to achieve social capital and sustainabledevelopment. The strategies aimed to strengthen local capacity toimprove social welfare and to ensure conservation and wise use ofbiodiversity. We provide examples, discuss lessons learned andmake recommendations for future development projects.     

Coupling climate and economic models in a cost-benefit framework: A convex optimisation approach

In this paper, we present a general method, based on a convex optimisation technique, that facilitates the coupling of climate and economic models in a cost-benefit framework. As a demonstration of the method, we couple an economic growth model à la Ramsey adapted from DICE-99 with an efficient intermediate complexity climate model, C-GOLDSTEIN, which has highly simplified physics, but fully 3-D ocean dynamics. As in DICE-99, we assume that an economic cost is associated with global temperature change: this change is obtained from the climate model, which is driven by the GHG concentrations computed from the economic growth path. The work extends a previous paper in which these models were coupled in cost-effectiveness mode. Here we consider the more intricate cost-benefit coupling in which the climate impact is not fixed a priori. We implement the coupled model using an oracle-based optimisation technique. Each model is contained in an oracle, which supplies model output and information on its sensitivity to a master program. The algorithm Proximal-ACCPM guarantees the convergence of the procedure under sufficient convexity assumptions. Our results demonstrate the possibility of a consistent, cost-benefit, climate-damage optimisation analysis with a 3-D climate model.