Identification of unknown groundwater pollution sources using classical optimization with linked simulation

Identification of unknown groundwater pollution sources still remains a challenging problem. Some of the complexities include: sparse observation data, substantial variation in magnitude of the source fluxes distributed over space and time, uncertainties in the imposed initial and boundary conditions. Methodologies already developed for optimal identification of pollution sources using concentration measurements and hydraulic data suffer from a number of limitations. As an alternative, a source identification methodology is proposed that uses a classical nonlinear optimization model linked to a flow and transport simulation model. The groundwater flow and transport simulator is linked to the nonlinear optimization model as an external module. The essential link between the simulator and the optimization method are the derivatives or gradient information required for the optimization algorithm. This proposed methodology is potentially applicable to large scale study areas and does not posses some of the computational limitations of some earlier developed methodologies, using nonlinear programming with the flow and transport process governing equations embedded as equality constraints within the optimization model. Performance of the proposed source identification methodology using spatiotemporal pollutant concentration measurements are evaluated by solving illustrative problems. Two different optimization formulations models are developed. The relative importance of the model formulations is demonstrated in terms of computational efficiency. The limited performance evaluations reported here demonstrate the potential applicability of the developed methodology using nonlinear programming and linked flow and transport simulation model for a fairly large study area with multiple unknown pollution sources

Optimal dynamic monitoring network design and identification of unknown groundwater pollution sources

The identification of unknown pollution sources is a prerequisite for designing of a remediation strategy. In most of the real world situations, it is difficult to identify the pollution sources without a scientifically designed efficient monitoring network. The locations of the contaminant concentration measurement sites would determine the efficiency of the unknown source identification process to a large extent. Therefore coupled and iterative sequential source identification and dynamic monitoring network design framework is developed. The coupled approach provides a framework for necessary sequential exchange of information between monitoring network and source identification methodology. The preliminary identification of unknown sources, based on limited concentration data from existing arbitrarily located wells provides the initial rough estimate of the source fluxes. These identified source fluxes are then utilized for designing an optimal monitoring network for the first stage. Both the monitoring network and source identification process is repeated by sequential identification of sources and design of monitoring network which provides the feedback information. In the optimal source identification model, the Jacobian matrix which is the determinant for the search direction in the nonlinear optimization model links the groundwater flow-transport simulator and the optimization method. For the optimal monitoring network design, the integer programming based optimal design model requires as input, simulated sets of concentration data. In the proposed methodology, the concentration measurement data from the designed and implemented monitoring network are used as feedback information for sequential identification of unknown pollution sources. The potential applicability of the developed methodology is demonstrated for an illustrative study area

Simultaneous identification of unknown groundwater pollution sources and estimation of aquifer parameters

Pollution source identification is a common problem encountered frequently. In absence of prior information about flow and transport parameters, the performance of source identification models depends on the accuracy in estimation of these parameters. A methodology is developed for simultaneous pollution source identification and parameter estimation in groundwater systems. The groundwater flow and transport simulator is linked to the nonlinear optimization model as an external module. The simulator defines the flow and transport processes, and serves as a binding equality constraint. The Jacobian matrix which determines the search direction in the nonlinear optimization model links the groundwater flow-transport simulator and the optimization method. Performance of the proposed methodology using spatiotemporal hydraulic head values and pollutant concentration measurements is evaluated by solving illustrative problems. Two different decision model formulations are developed. The computational efficiency of these models is compared using two nonlinear optimization algorithms. The proposed methodology addresses some of the computational limitations of using the embedded optimization technique which embeds the discretized flow and transport equations as equality constraints for optimization. Solution results obtained are also found to be better than those obtained using the embedded optimization technique. The performance evaluations reported here demonstrate the potential applicability of the developed methodology for a fairly large aquifer study area with multiple unknown pollution sources

Hemotoxic and wound healing potential of coelomic fluid of sea-star Astropecten indicus

Abstract Background The coelomic fluid of echinoderms bathes all the internal organs and is a natural reservoir of various bio-active compounds. However, coelomic fluid from Indian sea-star Astropecten indicus is not well characterized for its biochemical and pharmacological profiles. Sea-star (or starfish) Astropecten indicus was collected from the coast of Goa, India during low tides. Sea-star coelomic fluid (SCF) extracted from the sea-stars was concentrated, filtered, and assayed for various hemotoxic activities such as fibrinogenolysis, fibrinolysis, hemolysis, and effects on platelet aggregation. Results Studies on effects of SCF on A-549 human lung cancer cell line showed its non-cytotoxic and wound healing abilities in vitro. SCF was found to possess fibrinogen and fibrin digesting ability at a dose of 4 μg/ml within 30 min of incubation with the substrate. Additionally, SCF could hemolyze goat RBC by 50% and human RBC by only 5%. SDS-PAGE analysis showed that SCF contains various proteins and peptides. Two protein components of SCF yielded strong fibrinolytic, fibrinogenolytic, caseinolytic, and gelatinase activities as revealed by zymography. SCF enhanced the aggregation of ADP and collagen-activated platelets in a dose-dependent manner and had a specific proteolytic activity of 2.5 μg/ml in 30 min at 37 °C as assayed using azocasein as substrate. Conclusion This study focuses on the anticoagulant, pro-platelet aggregation and cell proliferative potential of SCF in vitro and is the first report on hemotoxic and wound healing potential of coelomic fluid of Astropecten indicus

Purification and characterization of an organ specific haemorrhagic toxin from <i>Vipera russelli russelli </i>(Russell's viper) venom

114-120A haemorrhagic toxin (VRR-12) from Vipera russelli russelli (Russell's viper) venom has been purified by ionexchange chromatography on CM-Sephadex C-50 followed by size-exclusion HPLC to electrophoretically homogeneous state. It is a 12 kDa single polypeptide having 1 mole of  Zn+2 ion. This toxin induces intense intestinal haemorrhage and to a lesser extent skeletal muscle haemorrhage in mice. It does not show detectable proteolytic and esterolytic activity with selected substrates under specified conditions, haemolytic and phospholipase activity. When VRR-12, preincubated with bivalent anti serum against Saw-scaled and Russell's viper venom or EDTA was injected, haemorrhagic activity was not reduced, on the otherhand preincubation with phenylmethyl sulphonyl fluoride reduced the activity markedly. Biodistribution studies with 1251 VRR- 12 show that haemorrhagic manifestation by this toxin is not a direct function of the fraction of the totally administered toxin distributed to that tissue