Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.     

Incorporating natural capital into economy-wide impact analysis: a case study from Alberta

Traditionally, decision-makers have relied on economic impactestimates derived from conventional economy-wide models. Conventional models lack the environmental linkages necessary for examining environmental stewardship and economic sustainability, and in particular the ability to assess the impact of policies on natural capital. This study investigatesenvironmentally extended economic impact estimation on a regionalscale using a case study region in the province of Alberta knownas the Foothills Model Forest (FMF). Conventional economic impactmodels are environmentally extended in pursuit of enhancingpolicy analysis and local decision-making. It is found that theflexibility of the computable general equilibrium (CGE) modelingapproach offers potential for environmental extension, with a solid grounding in economic theory. The CGE approach may be the tool of the future for more complete integrated environment andeconomic impact assessment.     

Distribution of Iron, Manganese, Zinc and Atrazine in Groundwater in Parts of Palar and Cheyyar River Basins, South India

A study was carried out in a part of Palar and Cheyyar river basin to evaluate the current status of iron, manganese, zinc and atrazine concentrations, their origin and distribution in groundwater. Groundwater samples were collected during post-monsoon (March 1998 and February 1999) and pre-monsoon (June 1999) periods from 41 sampling wells distributed throughout the study area. The groundwater samples were analyzed for trace metals using AAS and atrazine using HPLC. The concentration of the trace elements in groundwater is predominant during pre-monsoon period. Distribution pattern indicates that the concentration of these elements increases from west to northeast and towards Palar river. Lower concentrations in the central part may be due to recharge of fresh water from the lakes located here. During most of the months, as there is no flow in Palar river, the concentrations of trace elements in groundwater are high. Drinking water standards indicate that Mn and Zn cross the permissible limit recommended by EPA during the pre-monsoon period. A comparison of groundwater data with trace element chemistry of rock samples shows the abundance of trace elements both in the rock and water in the order of Fe > Mn > Zn and Fe > Zn > Mn. This indicates that iron in groundwater is derived from lithogenic origin. Further, Fe, Mn and Zn have good correlation in rock samples, while it is reverse in the case of water samples, indicating the non-lithogenic origin of Mn and Zn. Atrazine (a herbicide) was not detected in any of the groundwater samples in the study area, perhaps due to low-application rate and adsorption in the soil materials.     

Fly-ash-induced oxidative stress and tolerance in Prosopis juliflora L. grown on different amended substrates

Field experiments were conducted to study the impact of metal accumulation on malondialdehyde (MDA), cysteine and non-protein thiol (NPSH) contents in the plants of Prosopis juliflora grown on the fly ash (FA) amended with soil, blue green algae (BGA) biofertilizer, farm yard manure, press mud and Rhizobium inoculation. The analysis of data revealed that the level of MDA, cysteine and NPSH was higher in the roots of the plant than leaves, which was found positively correlated with metal accumulation. An increase of 361.14, 64.25 and 305.62% in MDA, cysteine and NPSH contents, respectively was observed after 45 days in the roots of the plants grown in 100% FA as compared to 100% garden soil (GS). The level of MDA, cysteine and NPSH was found less in the plants grown on various amendments of FA showing ameliorating effect on the toxicity induced due to the accumulation of metals. The decrease in MDA, cysteine and NPSH contents was higher in Rhizobium-inoculated plants as compared to uninoculated plants grown on 100% FA. The results showed a high tolerance potential of the plant, which is further increased by inoculating the plant with FA-tolerant Rhizobium showing feasibility of using P. juliflora in environmental monitoring of FA landfills.     

Environmental quality control and environmental games

Conclusion  In this paper we have considered a specific environmental game emphasizing both control-prevention efforts and the propensity to pollute by a firm which adopts a given pollution abatement technology. A random payoff game was constructed and solved under a risk neutral assumption and quadratic utilities for both the firm and the environmental controller. The game thus defined, provides a wide range of interpretations and potential approaches for selecting a control-inspection policies to prevent environmental risks. There are of course many facets to this problem, which could be considered and have not been considered in sufficient depth. For example, more complex control mechanisms and liabilities, the effects of insurance and risk sharing, the application of cooperative efforts and subvention of pollution abatement investments (through tax incentives and their like), etc. have not been considered [5,7]. These are topics for further research. The basic presumption of this paper is that it is very difficult to fully enforce pollution prevention by firms, as a result, some controls are needed to ensure that firms be controlled so that appropriate efforts are carried.     

Should foliar cadmium concentrations be expressed on a dry weight or dry ash weight basis?

Foliar analysis is a valuable tool for evaluating the pollution status of forests. However, the use of foliar diagnosis in large-scale surveys is a complicated process owing to the high variability within the crown. The method used to express foliar concentrations has often been found to diminish the variability. The effect of the method used to express element concentrations on the spatial variability of cadmium (Cd) in the leaves of crack willow (Salix fragilis L.) was investigated by sampling the leaves of one willow at 292 locations in the crown, each sampling location having a volume of 0.027 m3 (0.3 m x 0.3 m x 0.3 m). Cadmium showed a distinct spatial trend in the crown of the tree. Concentrations as low as 2.4 mg kg(-1) dry weight (DW) or 23.1 mg kg(-1) dry ash weight (DAW) were obtained in the top of the crown, and 10.6 mg kg(-1) DW or 73.0 mg kg(-1) DAW in the bottom of the crown. The lower relative standard deviation and weaker correlation with the sampling height support the use of DAW in large-scale surveys especially. The lower variability of the DAW Cd concentration makes this variable less sensitive to fluctuations caused by differences in growing conditions and sampling methodology. However, the majority of publications in this field report metal concentrations on a DW basis. Therefore, the restrictions set on the use of results expressed on a DAW basis in large-scale surveys of foliar metal concentrations have to be offset against the advantages offered by a reduction of the variability in metal concentrations.     

Cadmium and Lead Levels in Fish (Tilapia Nilotica) Tissues as Biological Indicator for Lake Water Pollution

Cadmium and lead were determined in different tissues (muscle,gill, stomach, intestine, liver, vertebral column and scales) of Tilapia nilotica from the High Dam Lake, Aswan (Egypt) to assess the lake water pollution with those toxic metals. Fish samples were chosen from different ages and weights to be analyzed along with samples of the aquatic plant(Najas armeta), sediment and lake water.The results showed that cadmium and lead concentrations were higher in fish scales and vertebral column than in the other parts of the fish. Cadmium and lead levels in High Dam lake water and fish (Tilapia nilotica) were a result of the pollution which uptakes from aquatic plants, sediments andgasoline containing lead that leaks from fishery boats. Tilapia nilotica fish was used as a good bio-assay indicator for the lake pollution with cadmium and lead. The fish musclesin this study were in the safety baseline levels for man consumption.     

Collaborative study to improve the quality control of rare earth element determinations in environmental matrices

In order to control the quality of rare earth determinations in environmental matrices, the Standards, Measurements and Testing Programme (formerly Community Bureau of Reference, BCR) of the European Commission has started a project, the final aim of which is to certify four types of matrices (tuna muscle, mussel tissue, aquatic plant and estuarine sediment) for their contents of a range of rare earth elements (Sc, Y and the lanthanides: La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu). The elements U and Th were added to the study. The first part of this project consisted of an interlaboratory study which aimed to test the feasibility of preparation of environmental reference materials and to detect and remove most of the pitfalls observed in rare earth determinations. This paper presents the preparation of the four matrices for the intercomparison study and for the candidate reference material. The main results are presented of the interlaboratory study that was carried out prior to the certification campaign. This collaborative trial is the first attempt ever carried out at this scale to evaluate the state-of-the-art of rare earth determinations in the environment. Its impact on the improvement of chemical measurements will have positive effects on the comparability of data necessary for environmental monitoring.     

Modeling rhizofiltration: heavy-metal uptake by plant roots

The discovery of phytoaccumulation potential of plant species has led to its application for remediation of heavy-metal-contaminated soil and wastewater, which is termed as phytoextraction/rhizofiltration. For prediction, analysis, planning and cost-effective design of such systems, mathematical models not only are used as a screening tool but also provide optimal parameters like harvesting time, irrigation schedule, etc. Several laboratory and field scale studies have been carried out in the past, and mathematical expressions have been developed by various researchers for different phenomena like metal adsorption in soil, plant root growth with time, moisture and metal uptake by plant root, moisture movement in unsaturated zone, soil moisture relationship, etc. The complete design of any such phytoremediation program would require the knowledge of behavior of heavy-metal movement in soil, water and plant root system. In this paper, a model for simulating heavy-metal dynamics in soil, water and plant root system is developed and discussed. The governing non-linear partial differential equation is solved numerically by implicit finite difference method using Picard's iterative technique, and the formulation has been illustrated using a characteristic example. The source code is written in MATLAB.