Water characterization and early contamination detection in highly varying stochastic background water, based on Machine Learning methodology for processing real-time UV-Spectrophotometry.

Water is a resource that affects every aspect of life. Intentional (terrorist or wartime events) or accidental water contamination events could have a tremendous impact on public health, behavior and morale. Quick detection of such events can mitigate their effects and reduce the potential damage. Continuous on-line monitoring is the first line of defense for reducing contamination associated damage. One of the available tools for such detection is the UV-absorbance spectrophotometry, where the absorbance spectra are compared against a set of normal and contaminated water fingerprints. However, as there are many factors at play that affect this comparison, it is an elusive and tedious task. Further, the comparison against a set of known fingerprints is futile when the water in the supply system are a mix, with varying proportions, of water from different sources, which differ significantly in their physicochemical characteristics. This study presents a new scheme for early detection of contamination events through UV absorbance under unknown routine conditions. The detection mechanism is based on a new affinity measure, Fitness, and a procedure similar to Gram based amplification, which result in a flexible mechanism to alert if a contamination is present. The method was shown to be most effective when applied to a set of comprehensive experiments, which examined the absorbance of various contaminants in drinking water in lab and real-life configurations. Four datasets, which contained real readings from either laboratory experiments or monitoring station of an operational water supply system were used. To extend the testbed even further, an artificial dataset, simulating a vast array of proportions between specific water sources is also presented. The results show, that for all datasets, high detection rates, while maintaining low levels of false alarms, were obtained by the algorithm.

Chemical degradation of 2,2-bis(bromomethyl)propan-1,3-diol (DBNPG) in alkaline conditions.

The mechanism and kinetics of the spontaneous decomposition of 2,2-bis(bromomethyl)propan-1,3-diol (DBNPG) and its decomposition daughter products were determined in aqueous solution at a temperatures range between 30 and 70 degrees C and pH from 7.0 to 9.5. DBNPG decomposition in basic aqueous solutions involves release of bromide ions through a sequential formation of 3-bromomethyl-3-hydroxymethyloxetane (BMHMO) and 2,6-dioxaspiro[3.3]heptane (DOH). DBNPG decomposition into BMHMO is a two-stage reaction. The first stage is an acid/base equilibrium, in which an alkoxide is formed. In the second stage, DBNPG predominantly undergoes an intramolecular nucleophilic substitution to form the BMHMO. The transformation rate increases with the pH and the energy barrier for the degradation is 98 kJ mol(-1). Good agreement was found between the rate coefficients derived from variations in the organic molecules concentrations and those determined from the changes in the Br(-) concentration. DBNPG is one of the most abundant pollutants in a studied polluted aquitard underneath industrial park in the northern Negev, Israel, and together with its by-products pose an environmental hazard. DBNPG half-life is estimated to be about 65 years. This implies that high concentrations of DBNPG will persist in the aquifer long after the elimination of all its sources.

Retardation of organo-bromides in a fractured chalk aquitard.

This study investigates the mechanisms controlling the distribution of 3-bromo-2,2-bis(bromomethyl)propanol (TBNPA) and 2,2-bis(bromomethyl)propan-1,3-diol (DBNPG) in a fractured chalk aquitard. An extensive monitoring program showed a systematic decrease in the TBNPA/DBNPG ratio with distance from the contamination source. Sorption of TBNPA on the white and/or gray chalks comprising the aquitard is approximately one order of magnitude greater than that of DBNPG. This results in more efficient removal of TBNPA from the fracture into the porous matrix and thus decreases the TBNPA/DBNPG ratio in the fracture water. Mathematical modeling of solute transport in the fracture domain illustrates the probable importance of sorption in controlling the spatial variation in TBNPA and DBNPG ratio.

Chemical transformation of 3-bromo-2,2-bis(bromomethyl)-propanol under basic conditions.

The mechanism of the spontaneous decomposition of 3-bromo-2,2-bis(bromomethyl)propanol (TBNPA) and the kinetics of the reaction of the parent compound and two subsequent products were determined in aqueous solution at temperatures from 30 to 70 degrees C and pH from 7.0 to 9.5. TBNPA is decomposed by a sequence of reactions that form 3,3-bis(bromomethyl)oxetane (BBMO), 3-bromomethyl-3-hydroxymethyloxetane (BMHMO), and 2,6-dioxaspiro[3.3]-heptane (DOH), releasing one bromide ion at each stage. The pseudo-first-order rate constant of the decomposition of TBNPA increases linearlywith the pH. The apparent activation energy of this transformation (98+/-2 KJ/mol) was calculated from the change of the effective second-order rate constant with temperature. The pseudoactivation energies of BBMO and BMHMO were estimated to be 109 and 151 KJ/mol, respectively. Good agreement was found between the rate coefficients derived from changes in the organic molecules concentrations and those determined from the changes in the Br- concentrations. TBNPA is the most abundant semivolatile organic pollutant in the aquitard studied, and together with its byproducts they posess an environmental hazard. TBNPA half-life is estimated to be about 100 years. This implies that high concentrations of TBNPA will persist in the aquifer long after the elimination of all its sources.