Freshwater leeches (Hirudinea) as a screening tool for detecting organic contaminants in the environment

In earlier work, we found that leeches from an industrially polluted creek bioaccumulated chlorophenols to much higher concentrations than other resident benthic invertebrates and fish. We suggested that leeches may have significant potential as biomonitors for these and other organic contaminants in the environment. In this study, we compared the bioaccumulation and depuration of 16 organic compounds, including eight chlorophenols (CPs), lindane, DDT and four derivatives, benzothiazole (BT) and 2-(Methylthio)benzothiazole (MMBT) for three species of leeches. Dina dubia had the highest bioaccumulation capacity for most contaminants, but residues persisted longest in Erpobdella punctata. Helobdella stagnalis appeared capable of degrading some compounds. Half lives of CPs, DDT and DDT derivatives were generally longer than one month. In contrast, half lives were only 1 day for lindane, 1–2.5 days for MMBT and 7 days for BT despite very high initial tissue concentrations of the latter two compounds. Bioconcentration factors for contaminants in leeches were higher than those reported for other aquatic organisms. Half lives for lindane, DDT and DDT derivatives were consistent with the literature for other organisms, but half lives for CPs were much longer. The results suggest that leeches would be excellent biomonitors of both continuous and intermittent contamination of a waterway with CPs and DDT, as they retain these compounds for long periods after exposure. Their usefulness as a screening tool for lindane and benzothiazoles would be limited to chronically contaminated environments.     

The use of sensor arrays for environmental monitoring: interests and limitations

Continuous, in situ monitoring of air, water and land quality is fundamental to most environmental applications. Low cost and non-invasive chemical sensor arrays provide a suitable technique for in situ monitoring. Their ability and performance under realistic conditions is discussed in this paper. Published studies report promising results despite a number of limitations that are associated with both the technology itself and its application in ever changing ambient conditions. Early investigations include the analysis of single substances as well as odour and wastewater organic load monitoring. Reported applications typically highlight the sensitivity of the currently available sensors to changes in temperature, humidity and flow rate. Two types of approaches are recommended to deal with these effects: either working under fixed experimental conditions or measuring the external parameters to numerically compensate for their change. The main challenge associated with the use of non-specific sensor arrays lies in establishing a relationship between the measured multivariate signals and the standards metrics that are traditionally used for quality assessment of gas mixtures. For instance, odour monitoring requires calibration against olfactometric measurements while investigations of wastewater samples still need to be correlated with organic pollution parameters such as BOD, COD or TOC. On the other hand, results obtained in the field have demonstrated how sensor arrays can be readily used as simple alarm devices or as early warning systems based on a general air/water quality index.     

A tool for rapid screening of direct DNA agents using reaction rates and relative interaction potency: towards screening environmental contaminants for hazard

DNA damage represents a potential biomarker for determining the exposure risk to chemicals and may provide early warning data for identifying chemical hazards to human health. Here, we have demonstrated a simple chromatography-based method that can be used to rapidly screen for the presence of chemical hazards as well as to determine parameters relevant to hazard assessment. In this proof-of-principle study, a simple in vitro system was used to determine the interaction of pollutants and probable carcinogens, phenyl glycidyl ether (PGE), tetrachlorohydroquinone (Cl(4)HQ), methylmethane sulfonate (MMS), styrene-7,8-oxide (SO), and benzo[a]pyrene-7,8-dihydrodiol-9,10-epoxide (BPDE), a metabolite of benzo[a]pyrene (B[a]P), with single- and double-stranded DNA probes. Differences in potency and reaction kinetics were studied for chemical and DNA type. A relative interaction potency equivalency (PEQ) of a chemical was determined by ratio of interaction potency of a chemical to BPDE as the reference chemical in the reaction with single- and double-stranded oligodeoxynucleotides. PEQs were found to be BPDE > PGE > SO > MMS > Cl(4)HQ for single-stranded oligodeoxynucleotides while they were found to be BPDE > PGE > Cl(4)HQ > MMS > SO for double-stranded oligodeoxynucleotides. Kinetics evaluation revealed that BPDE reacted with both DNA probes at a significantly faster rate, as compared to the remaining test chemicals. Equilibrium was reached within an hour for BPDE, but required a minimum of 48 h for the remaining chemicals. First-order rate constants were (1.61 ± 0.2) × 10(-3) s(-1) and (3.18 ± 0.4) × 10(-4) s(-1) for reaction of BPDE with double- and single-stranded DNA, respectively. The remaining chemicals possessed rate constants from 2 to 13 × 10(-6) s(-1) with a relative kinetic order for reaction with DNA of BPDE ? MMS > SO > PGE > Cl(4)HQ for ds-DNA and BPDE ? SO ≈ Cl(4)HQ ≈ MMS > PGE for ss-DNA. We further found that the reaction potency, defined by dose-response between chemical pollutants and DNA, depends on the form of DNA present for reaction. Noteworthy, we found that relative PEQ did not follow the same kinetic trends. However, our preliminary findings suggest that reaction kinetics, in combination with relative interaction potency, may be a significant parameter that can be used to evaluate the hazard level of environmental pollutants.     

Testing taxonomic resolution levels for detecting environmental impacts using macrobenthic assemblages in tropical waters

Delta regions of the Cauvery River basin are one of the significant areas of rice production in India. In spite of large-scale utilization of the river basin for irrigation and drinking purposes, the lack of appropriate water management has seemingly deteriorated the water quality due to increasing anthropogenic activities. To assess the extent of deterioration, physicochemical characteristics of surface water were analyzed monthly in select regions of Cauvery Delta River basin, India, during July 2007 to December 2007. Total dissolved solids, chemical oxygen demand, and phosphate recorded maximum levels of 1,638, 96, and 0.43 mg/l, respectively, exceeding the permissible levels at certain sampling stations. Monsoonal rains in Cauvery River basin and the subsequent increase in river flow rate influences certain parameters like dissolved solids, phosphate, and dissolved oxygen. Agricultural runoff from watershed, sewage, and industrial effluents are suspected as probable factors of water pollution.     

A statistical F test for the natural attenuation of contaminants in groundwater

Natural attenuation (NA) is a catchall explanation for the overall decay and slowed movement of the contaminants in the subsurface. One direct support to NA is to demonstrate that contaminant concentrations from monitoring wells located near the source are decreasing over time. The decrease is summarily expressed in terms of an apparent half-life that is determinedfrom the line best fitting the observed log-transformed concentration data and time. This simple (time-only) decay modelassumes other factors are invariant, and so is flawed when complicating factors – such as a fluctuating water table – are present. A history of the water-table fluctuation can track changes in important NA factors like recharge, groundwater flow direction and velocity, as well as other non-NA factors like volume of water in and purged from the well before a sample is collected. When the trend in the concentrations is better associated with the water table rising or falling, any conclusionabout degradation rate may be premature. We develop simple regressions to predict contaminant concentration (c) by two line models: one involving time (c c(t)), and another involving groundwater elevation (c c(z)). We develop a third model that includesboth factors (c c(t, z)). Using an F-test to compare the fits to the models, we determine which modelis statistically better in explaining the observed concentrations. We applied the test to sites where benzene degradation rates had previously been estimated. The F-testcan be used to determine the suitability of applying non-parametric statistics, like the Mann-Kendall, to the concentration data, because the result from the F-test canindicate instability of the contaminant plume that may bemasked when the water table fluctuates.     

A risk-based screening approach for prioritizing contaminants and exposure pathways at Superfund sites

Contamination at Superfund sites can involve mixtures of chemicals and radionuclides in a variety of environmental media. Determining priorities for evaluation and remediation of various contaminants is an important part of the initial phases of any site investigation. An effective screening analysis at the beginning of the project can help by identifying both those situations in need of immediate remedial attention and those which require further sampling and evaluation. The screening approach discussed here is made up of two sets of calculations designed to provide upper- and lower-bound estimates of health risk to individuals likely to receive the highest exposures. This approach allows rapid identification of contaminants which pose a negligible risk and can be assigned a low priority for remedial attention or which pose a substantial risk and should be given the highest priority for appropriate remediation efforts. Contaminants designated as neither high- nor low-priority should be investigated in more detail prior to making decisions regarding the need for or method of remediation. The utility of this approach has already been demonstrated in the evaluation of contamination in the Clinch and Tennessee River systems originating from historical operations of atomic weapons and energy research facilities near Oak Ridge, Tennessee.     

A two-stage DEA approach for environmental efficiency measurement

The slacks-based measure (SBM) model based on the constant returns to scale has achieved some good results in addressing the undesirable outputs, such as waste water and water gas, in measuring environmental efficiency. However, the traditional SBM model cannot deal with the scenario in which desirable outputs are constant. Based on the axiomatic theory of productivity, this paper carries out a systematic research on the SBM model considering undesirable outputs, and further expands the SBM model from the perspective of network analysis. The new model can not only perform efficiency evaluation considering undesirable outputs, but also calculate desirable and undesirable outputs separately. The latter advantage successfully solves the "dependence" problem of outputs, that is, we can not increase the desirable outputs without producing any undesirable outputs. The following illustration shows that the efficiency values obtained by two-stage approach are smaller than those obtained by the traditional SBM model. Our approach provides a more profound analysis on how to improve environmental efficiency of the decision making units.     

A novel environmental indicator for monitoring of pesticides

The identification of an indicator for monitoring pesticides is a very effective analytical approach because it allows one to schedule and simplify the analytical routine. In this study, a new indicator has been designed, which has to be able to define a scale of priorities in the pesticides monitoring. A starting equation was developed involving the escaping tendency of a given substance from a phase (based on the Mackay model I level). The reliability of the indicator was tested by application to a model system, consisting of a defined and limited area, choosing water as matrix over a period of 6 years. A group of marker compounds was also defined to implement the predictive efficacy of the indicator. The results obtained by modeling were compared to those obtained by experimentation of the same model system. The indicator was subsequently and appropriately modified creating a new equation, including a kinetic factor, which considers the environmental degradation processes. The effect of the rectified indicator was consistent with the sales data list of compounds, when applied to the markers. The indicator developed in this study, tested as a model on specific area-phase-period (Province of Siena, water phase, 2000?C2006), is applicable to any other area-phase-period, adjusting the partition value of the Mackay model for the case under study.     

A quantitative methodology for indexing environmental sensitivity and pollution potential

A methodology for rating the suitability of sites forthe location of industrial facilities is formulated and appliedto the case of a coal-fired power plant location. The methodologycomprises two major interlinked components: the environmentalplant location indexing component, which involves theidentification, scaling and weighting of environmentalsensitivity factors; and the impact analysis component, whichinvolves the superimposition of the pollution generation impactsof an industrial facility on spatially gridded zones of variousenvironmental sensitivities. For each rectangular areal unitdefined by a square grid, the Unit Pollution Potential Index isdetermined by the severity and distribution of key environmentalsensitivity factors and the coverage of superimposed pollutanteffects as determined by contaminant fate and transport models.For any alternative site of a planned facility, the summation ofthe unit indices over the area of influence of the facilityprovides the quantitative Pollution Index, which can be used as abasis for comparison of alternative sites for planned facilities.For this paper, this methodology is applied to the hypotheticalcase of the siting of a coal-fired power plant in thenortheastern region of the United States, in which threealternative sites are considered. The three sites: A, B and Cyielded indices of 47.83, 47.91 and 47.6, respectively, indicatingthat site C is the most suitable for siting the power plant.     

A new market instrument for sustainable economic and environmental development

The regenerative capacity of ecosystems provides a regulatory basis for sustainable economic growth and development. A natural valuation of an ecosystem's services will arise in a market for developmental rights in the ecosystem using a unit of tradable 'right': E-Scrip. The amount of e-scrip needed for a development may be set by Environmental Assessment. The capacity of the ecosystem to regenerate with developmental pressure may be represented by an independent trader or Factor Proxy for the Environment who provides e-scrip to the market.     

Application of laser-based ion mobility (IM) spectrometry for the analysis of polycyclic aromatic compounds (PAC) and petroleum products in soils

The capability of laser-based IM spectrometry to detect PAC and petroleum products (oils) in model matrices, laboratory reference (LR) materials and in real-world contaminated soil samples was demonstrated. Quantitative IM investigations of PAC-doped PVC films yielded detection limits in the ppm range for single PAC. The potential of IM spectrometry for in situ analysis was demonstrated by the analysis of PAC-containing certified reference (CR) material, and of petroleum product-containing LR materials and real-world soil samples. The calibration of IM signals obtained from oil-doped LR materials was also possible, and detection of oils with concentrations below 100 mg kg(-1) was achieved. The in situ analysis of real-world contaminated soils with the IM and LIF techniques was in good accordance with ex situ reference investigations.     

A review of techniques for parameter sensitivity analysis of environmental models

Mathematical models are utilized to approximate various highly complex engineering, physical, environmental, social, and economic phenomena. Model parameters exerting the most influence on model results are identified through a sensitivity analysis. A comprehensive review is presented of more than a dozen sensitivity analysis methods. This review is intended for those not intimately familiar with statistics or the techniques utilized for sensitivity analysis of computer models. The most fundamental of sensitivity techniques utilizes partial differentiation whereas the simplest approach requires varying parameter values one-at-a-time. Correlation analysis is used to determine relationships between independent and dependent variables. Regression analysis provides the most comprehensive sensitivity measure and is commonly utilized to build response surfaces that approximate complex models.     

A DSS for sustainable development and environmental protection of agricultural regions

This paper presents a decision support system (DSS) for sustainable development and environmental protection of agricultural regions developed in the framework of the Interreg-Archimed project entitled WaterMap (development and utilization of vulnerability maps for the monitoring and management of groundwater resources in the ARCHIMED areas). Its aim is to optimize the production plan of an agricultural region taking in account the available resources, the environmental parameters, and the vulnerability map of the region. The DSS is based on an optimization multicriteria model. The spatial integration of vulnerability maps in the DSS enables regional authorities to design policies for optimal agricultural development and groundwater protection from the agricultural land uses. The DSS can further be used to simulate different scenarios and policies by the local stakeholders due to changes on different social, economic, and environmental parameters. In this way, they can achieve alternative production plans and agricultural land uses as well as to estimate economic, social, and environmental impacts of different policies. The DSS is computerized and supported by a set of relational databases. The corresponding software has been developed in a Microsoft Windows XP platform, using Microsoft Visual Basic, Microsoft Access, and the LINDO library. For demonstration reasons, the paper includes an application of the DSS in a region of Northern Greece.     

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.     

A monitoring of environmental effects from household greywater reuse for garden irrigation

The option of reusing greywater is proving to be increasingly attractive to address the water shortage issue in many arid and semiarid countries. Greywater represents a constant resource, since an approximately constant amount of greywater is generated from kitchen, laundries, bathroom in every household daily, independent of the weather. However, the use of greywater for irrigation in particular for household gardening may pose major hazards that have not been studied thoroughly. In this study, a 1-year monitoring was conducted in four selected households in Perth, Western Australia. The aim of the monitoring works is to investigate the variability in the greywater flow and quality, and to understand its impact in the surrounding environments. Case studies were selected based on different family structure including number, ages of the occupants, and greywater system they used. Samples of greywater effluent (showers, laundries, bathtub, and sinks), leachate, soil, and plants at each case study were collected between October 2008 and December 2009 which covered the high (spring/summer) and low (autumn/winter) production of greywater. Physical and chemical tests were based on the literature and expected components of laundry and bathroom greywater particularly on greywater components likely to have detrimental impacts on soils, plants, and other water bodies. Monitoring results showed the greywater quality values for BOD, TSS, and pH which sometimes fell outside the range as stipulated in the guidelines. The soil analyses results showed that salinity, SAR, and the organic content of the soil increased as a function of time and affected the plant growth. Nutrient leaching or losses from soil irrigated with greywater shows the movement of nutrients and the sole impact from greywater in uncontrolled plots in case studies is difficult to predicted due to the influence of land dynamics and activities. Investigative and research monitoring was used to understand greywater irrigation in households. Greywater quality is very site specific and difficult to predetermine or control except for the use of some recommended household products when using greywater. Investigative and research monitoring was indicated that greywater quality is very site specific and difficult to predetermine or control except for the use of some recommended household products when using greywater.     

A new method for environmental site assessment of urban solid waste landfills

Regarding various types of pollutant, waste management requires high attention. Environmental site selection study, prior to landfill operation, and subsequently, monitoring and maintaining of the location, are of foremost points in landfill site selection process. By means of these studies, it is possible to control the undesirable impacts caused by landfills. Study ahead aims at examination of effectiveness of a new method called Monavari 95–2 in landfill site assessment. For this purpose, two landfills Rasht and Andisheh, which are, respectively, located on humid and arid areas, were selected as case studies. Then, the results obtained from both sites were compared with each other to find out the weaknesses and strengths of each site. Compared with others similar methods, much more criteria (53 parameters) can be considered within this method, so the results will be more calculable. According to this method, Rasht landfill (site H) is classified as unacceptable landfill site i.e. there is an urgent need for a new suitable site for landfill, while Andishe Landfill (site D) is ranked as acceptable landfill site but needs environmental management program to handle the existing weaknesses.     

A national framework for monitoring and reporting on environmental sustainability in Canada

In 1991, a collaborative project to revise the terrestrial component of a national ecological framework was undertaken with a wide range of stakeholders. This spatial framework consists of multiple, nested levels of ecological generalization with linkages to existing federal and provincial scientific databases. The broadest level of generalization is the ecozone. Macroclimate, major vegetation types and subcontinental scale physiographic formations constitute the definitive components of these major ecosystems. Ecozones are subdivided into approximately 200 ecoregions which are based on properties like regional physiography, surficial geology, climate, vegetation, soil, water and fauna. The ecozone and ecoregion levels of the framework have been depicted on a national map coverage at 1:7 500 000 scale. Ecoregions have been subdivided into ecodistricts based primarily on landform, parent material, topography, soils, waterbodies and vegetation at a scale (1:2 000 000) useful for environmental resource management, monitoring and modelling activities. Nested within the ecodistricts are the polygons that make up the Soil Landscapes of Canada series of 1:1 000 000 scale soil maps. The framework is supported by an ARC-INFO GIS at Agriculture Canada. The data model allows linkage to associated databases on climate, land use and socio-economic attributes.     

A cost-precision model for marine environmental monitoring,based on time-integrated averages

Ongoing marine monitoring programs are seldom designed to detect changes in the environment between different years, mainly due to the high number of samples required for a sufficient statistical precision. We here show that pooling over time (time integration) of seasonal measurements provides an efficient method of reducing variability, thereby improving the precision and power in detecting inter-annual differences. Such data from weekly environmental sensor profiles at 21 stations in the northern Bothnian Sea was used in a cost-precision spatio-temporal allocation model. Time-integrated averages for six different variables over 6 months from a rather heterogeneous area showed low variability between stations (coefficient of variation, CV, range of 0.6–12.4%) compared to variability between stations in a single day (CV range 2.4–88.6%), or variability over time for a single station (CV range 0.4–110.7%). Reduced sampling frequency from weekly to approximately monthly sampling did not change the results markedly, whereas lower frequency differed more from results with weekly sampling. With monthly sampling, high precision and power of estimates could therefore be achieved with a low number of stations. With input of cost factors like ship time, labor, and analyses, the model can predict the cost for a given required precision in the time-integrated average of each variable by optimizing sampling allocation. A following power analysis can provide information on minimum sample size to detect differences between years with a required power. Alternatively, the model can predict the precision of annual means for the included variables when the program has a pre-defined budget. Use of time-integrated results from sampling stations with different areal coverage and environmental heterogeneity can thus be an efficient strategy to detect environmental differences between single years, as well as a long-term temporal trend. Use of the presented allocation model will then help to minimize the cost and effort of a monitoring program.