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Combined Mechanistic and Structural-relationship Approach for Modeling Photooxidative Degradation of Benzene-structured Pollutants in Water Matrix

Substituted benzenes represent a large group of chemicals produced worldwide and consequently found in various industrial wastestreams. Many of those aromatics, particularly chloro-and nitro- substituted, are designated as priority pollutants by USEPA and European Commission due to their bio- recalcitrance, high toxicity, and potential carcinogenic and mutagenic effect. Thus, their elimination from wastestreams is required. Among various types of advanced oxidation processes (AOPs), photochemical processes being destructive and low- or non-waste generating technologies have the potential for biodegradability improvement and detoxification of industrial wastestreams. When appropriate wastewater treatment technologies are considered, the prediction of system behavior by simulating the processes occurring within is of particular value. This can be very challenging in the case of AOPs, since they encompass chemical reactions characteristic for AOP type, as well as reactions describing the radical chain mechanism in water matrix. Determination of the reaction rates in mechanistic model for reactions of organic parent pollutants and formed by-products with reactive species generated within the system is necessary. Empirical mathematical modeling ; artificial neural networks (ANN) and response surface modeling (RSM), offer a simple alternative to this problem. However, they don’t consider degradation mechanisms and pathways of organics making them fairly limited comparing to mechanistic and structural-relationship modeling which provide valuable information on the system behavior and its suitability for biodegradation. The aim of the study was to develop a model predicting the photooxidative degradation of various benzene-structured pollutants (overall 30 compounds) with various substituents by UV/H2O2 process. The phenomenological modeling combining mechanistic model, including the chemistry of studied process and reaction rates of studied pollutants with hydroxyl radicals, and QSAR modeling tools, providing new parameters based on structural-relationship, was applied. In such manner complicated degradation schemes are bridged by simplified degradation pathway dependent on parent pollutant structural characteristics, yielding high accuracy in simulating the overall system behavior.

wastewater; aromatics; photooxidation; mechanistic modeling; structural-relationship modeling

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