Effect of some heavy metals and soil humic substances on the phytochelatin production in wild plants from silver mine areas of Guanajuato, Mexico

Phytochelatins (PCs) were determined in the wild plants, focusing on their relationship with the levels of heavy metals and humic substances (HS) in soil. Ricinus communis and Tithonia diversifolia were collected from several sites in Guanajuato city (Mexico), which had long been the silver and gold mining center. The analysis of PCs in root extracts was carried out by liquid chromatography (derivatization with monobromobimane). Total Ag, Cd, Cu and Pb in plant roots and in soil samples, as well as soil HS were determined. The association of metals with HS in soils was evaluated by size exclusion chromatography (SEC) with UV and ICP-MS detection. The results obtained revealed the induction of PCs in R. communis but not in T. diversifolia. The levels of Cd and Pb in plant roots presented strong positive correlation with PC-2 (r = 0.9395, p = 0.005; r = 0.9573, p = 0.003, respectively), indicating that these two metals promote PCs induction in R. communis. On the other hand, the inverse correlation was found between soil HS and metal levels in roots of R. communis (Cu > Pb > Cd > Ag), in agreement with the decreasing affinity of these metals to HS. Importantly, the inverse correlation between soil HS and plant PC-2 was observed (r = −0.7825, p = 0.066). These results suggest that metals strongly bound to HS could be less bioavailable to plants, which in turn would limit their role in the induction of PCs. Indeed, the SEC elution profiles showed Pb but not Cd association with HS and the correlation between metal in soil and PC-2 in plant was statistically significant only for Cd (r = 0.7857, p = 0.064). Based on these results it is proposed that the role of heavy metals in PCs induction would depend on their uptake by R. communis, which apparently is controlled by the association of metals with soil HS. This work provides further evidence on the role of environmental conditions in the accumulation of heavy metals and phytochelatin production in plants.     

Ozonation of oil sands process water removes naphthenic acids and toxicity

Naphthenic acids are naturally-occurring, aliphatic or alicyclic carboxylic acids found in petroleum. Water used to extract bitumen from the Athabasca oil sands becomes toxic to various organisms due to the presence of naphthenic acids released from the bitumen. Natural biodegradation was expected to be the most cost-effective method for reducing the toxicity of the oil sands process water (OSPW). However, naphthenic acids are poorly biodegraded in the holding ponds located on properties leased by the oil sands companies. In the present study, chemical oxidation using ozone was investigated as an option for mitigation of this toxicity. Ozonation of sediment-free OSPW was conducted using proprietary technology manufactured by Seair Diffusion Systems Inc. Ozonation for 50min generated a non-toxic effluent (based on the Microtox bioassay) and decreased the naphthenic acids concentration by approximately 70%. After 130min of ozonation, the residual naphthenic acids concentration was 2mgl(-1): <5% of the initial concentration in the filtered OSPW. Total organic carbon did not change with 130min of ozonation, whereas chemical oxygen demand decreased by approximately 50% and 5-d biochemical oxygen demand increased from an initial value of 2mgl(-1) to a final value of 15mgl(-1). GC-MS analysis showed that ozonation resulted in an overall decrease in the proportion of high molecular weight naphthenic acids (n> or = 22).     

Agricultural Chemicals in the Alluvial Aquifer of a Typical County of the Arkansas Delta

Statistical methods and a Geographic Information System (GIS) were used to investigate potential indicators of ground water vulnerability to agricultural chemical contamination in a representative area of the Mississippi River alluvial aquifer. A total of 47 wells were sampled for analysis of nitrate, phosphorus, potassium, and 13 pesticides commonly-used in the area. Ten soil and hydrogeologic variables and five ground water vulnerability indices were examined to explain the variations of chemical concentrations. The results showed that no individual soil or hydrogeologic variables or their linear combinations could explain more than 25% of the variation of the chemical concentrations. A quadratic response surface model with the values of confining unit thickness, slope, soil permeability, depth to ground water, and recharge rate accounted for 62% of the variation of nitrate, 43% of P, and 83% of K, suggesting that the interactions among soil and hydrogeologic variables were significant. Observed trends of decreasing nitrate and P concentrations with increasing well depth and/or depth to ground water seemed to correlate with carbonate equilibrium in the aquifer and more reduced environment with depth. In view of uncertainties involved, it was recognized that the limitations associated with input data resolution used in GIS and the formulation of leaching indices limited their use for predicting ground water vulnerability. Misuse of pesticides could be another factor that would complicate the relationships between pesticide concentrations and the vulnerability indices.     

Use of Scale Invariance in Evaluating Judgement Indicators

Indicators are used to draw conclusions about ecological endpoints when these endpoints cannot be measured directly. In many cases, inferences about an endpoint are only possible because assumptions have been made about the relationship between indicator and endpoint; we refer to such indicators as judgement indicators. The validity of inferences made using a judgement indicator can be gauged by examining the known or assumed form of the general relationship between indicator and endpoint. The rules for this kind of inference are a consequence of scale invariance, which originates from measurement theory. For simple indicators comprised of a single indicator measurement, the inferences allowed – equivalence, rank, equality of intervals, and equality of ratios – depend on whether the data are nominal, ordinal, interval, or ratio scaled. For composite indicators containing two or more simple indicators, inferences are also affected by the mathematical form of combination; e.g., whether the terms are summed or multiplied. Standardizing simple or composite indicators can allow inferences about the relative importance of observations, based on the natural range of occurrence. Scale invariance is a particularly important consideration in landscape assessments, since these often make use of judgement indicators.     

Effect of two major N-nitroso hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) metabolites on earthworm reproductive success

Soil and topical tests were employed to investigate the effect of two N-nitroso metabolites of RDX (hexahydro-1,3,5-trinitro-1,3,5-triazine) on earthworm reproduction. The lowest observed effect concentration (LOEC) for cocoon production and hatching was 50mg/kg for both hexahydro-1-nitroso-3,5-dinitro-1,3,5-triazine (MNX) and hexahydro-1,3,5-trinitroso-1,3,5-triazine (TNX) in soil. MNX and TNX also significantly affected cocoon hatching in soil (p<0.001) and in topical tests (p=0.001). The LOECs for cocoon hatching were 1 and 10mg/kg for MNX and TNX in soil, respectively, and 10mg/L in the topical test. Greater than 100mg/kg MNX and TNX completely inhibited cocoon hatching. In soil, the EC20 values for MNX were 8.7 and 8.8mg/kg for cocoon and juvenile production, respectively, compared to 9.2 and 9.1mg/kg for TNX, respectively. The EC20 values for the total number of cocoon hatchlings were 3.1 and 4.7mg/kg for MNX and TNX, respectively, in soil and 4.5 and 3.1mg/L in the topical test. Both MNX and TNX inhibited cocoon production and hatching, suggesting that they may have a negative affect on soil ecosystems at contaminated sites.     

Retooling the ethanol industry: thermophilic anaerobic digestion of thin stillage for methane production and pollution prevention.

Anaerobic digestion of corn ethanol thin stillage was tested at thermophilic temperature (55 degrees C) with two completely stirred tank reactors. The thin stillage wastestream was organically concentrated with 100 g/L total chemical oxygen demand and 60 g/L volatiles solids and a low pH of approximately 4.0. Steady-state was achieved at 30-, 20-, and 15-day hydraulic retention times (HRTs) and digester failure at a 12-day HRT. Significant reduction of volatile solids was achieved, with a maximum reduction (89.8%) at the 20-day HRT. Methane yield ranged from 0.6 to 0.7 L methane/g volatile solids removed during steady-state operation. Effluent volatile fatty acids below 200 mg/L as acetic acid were achieved at 20- and 30-day HRTs. Ultrasonic pretreatment was used for one digester, although no significant improvement was observed. Ethanol plant natural gas consumption could be reduced 43 to 59% with the methane produced, while saving an estimated $7 to $17 million ($10 million likely) for a facility producing 360 million L ethanol/y.     

Autotrophic denitrification using hydrogen oxidizing bacteria in continuous flow biofilm reactor

Autotrophic denitrification was investigated in five bench‐scale upflow attached growth reactors using hydrogen oxidizing bacteria under anoxic conditions. The performance of sand, granular activated carbon (GAC), crushed pumice, crushed volcanic rock, and plastic media were evaluated as the support material. The reactors were inoculated with acclimated cultures obtained from domestic sewage treatment plant. A synthetic solution containing nitrate was used as the influent. The reactor performance was evaluated by measuring influent and effluent nitrate concentration. The design parameters demonstrated that the effectiveness of autotrophic denitrification is comparable to that of the heterotrophic process and may be utilized economically for drinking water treatment either as the main process or as a supplemental process for ion exchange regenerant treatment.     

Co-injection of air and steam for the prevention of the downward migration of DNAPLs during steam enhanced extraction: an experimental evaluation of optimum injection ratio predictions

When steam is injected into soil containing a dense volatile non-aqueous phase liquid contaminant, the DNAPL vaporized within the heated soil region condenses and accumulates ahead of the steam condensation front. If enough DNAPL accumulates, gravitational forces can overcome trapping forces allowing the liquid contaminant to flow downward. By injecting air with steam, a portion of the DNAPL vapor remains suspended in equilibrium with the air, decreasing liquid contaminant accumulation ahead of the steam condensation front, and thus reducing the possibility of downward migration. In a previous work, a theoretical model was developed to predict the optimum injection ratio of air to steam that would eliminate accumulation of DNAPL ahead of the temperature front and thus minimize the potential for downward migration. In this work, the theoretical model is summarized, and an experiment is presented in order to evaluate the optimum injection ratio prediction. In the experiment, a two-dimensional water saturated sand pack is contaminated with a known mass of TCE (DNAPL). The system is then remediated by co-injecting air and steam at the predicted optimum injection ratio, calculated based on the average contaminant soil concentration in the sand pack. Results for the co-injection of air and steam are compared to results for the injection of pure steam or pure air. Injection at the predicted optimum injection ratio for a volumetric average NAPL saturation, reduced accumulation of the contaminant ahead of the condensation front by over 90%, as compared to steam injection alone. This indicates that the optimum injection ratio prediction is a valuable tool for limiting the spreading of DNAPL during steam-enhanced extraction. Injection at the optimum injection ratio resulted in earlier recovery of contaminant than for steam injection alone. Co-injection of steam and air is also shown to result in much higher recovery rates than air injection alone.     

Assessing Landscape Condition Relative to Water Resources in the Western United States: A Strategic Approach

The Environmental Monitoring and Assessment Program (EMAP) is proposing an ambitious agenda to assess the status of streams and estuaries in a 12-State area of the western United States by the end of 2003. Additionally, EMAP is proposing to access landscape conditions as they relate to stream and estuary conditions across the west. The goal of this landscape project is to develop a landscape model that can be used to identify the relative risks of streams and estuaries to potential declines due to watershed-scale, landscape conditions across the west. To do so, requires an understanding of quantitative relationships between landscape composition and pattern metrics and parameters of stream and estuary conditions. This paper describes a strategic approach for evaluating the degree to which landscape composition and pattern influence stream and estuary condition, and the development and implementation of a spatially-distributed, landscape analysis approach.     

Predicting Water Quality Impaired Stream Segments using Landscape-Scale Data and a Regional Geostatistical Model: A Case Study in Maryland

In the United States, probability-based water quality surveys are typically used to meet the requirements of Section 305(b) of the Clean Water Act. The survey design allows an inference to be generated concerning regional stream condition, but it cannot be used to identify water quality impaired stream segments. Therefore, a rapid and cost-efficient method is needed to locate potentially impaired stream segments throughout large areas. We fit a set of geostatistical models to 312 samples of dissolved organic carbon (DOC) collected in 1996 for the Maryland Biological Stream Survey using coarse-scale watershed characteristics. The models were developed using two distance measures, straight-line distance (SLD) and weighted asymmetric hydrologic distance (WAHD). We used the Corrected Spatial Akaike Information Criterion and the mean square prediction error to compare models. The SLD models predicted more variability in DOC than models based on WAHD for every autocovariance model except the spherical model. The SLD model based on the Mariah autocovariance model showed the best fit (r² = 0.72). DOC demonstrated a positive relationship with the watershed attributes percent water, percent wetlands, and mean minimum temperature, but was negatively correlated to percent felsic rock type. We used universal kriging to generate predictions and prediction variances for 3083 stream segments throughout Maryland. The model predicted that 90.2% of stream kilometers had DOC values less than 5 mg/l, 6.7% were between 5 and 8 mg/l, and 3.1% of streams produced values greater than 8 mg/l. The geostatistical model generated more accurate DOC predictions than previous models, but did not fit the data equally well throughout the state. Consequently, it may be necessary to develop more than one geostatistical model to predict stream DOC throughout Maryland. Our methodology is an improvement over previous methods because additional field sampling is not necessary, inferences about regional stream condition can be made, and it can be used to locate potentially impaired stream segments. Further, the model results can be displayed visually, which allows results to be presented to a wide variety of audiences easily.