Quantitative structure-degradation

Abstract Over 30 000 chemicals are used in commercial quanhhes and very few of these chemicals have experimental data on their environmental degradability/persistence. This chapter reviews databases which can be searched for persistence informahon and what to do when the chemical of interest does not have any data. Two general approaches are suggested (1) identify chemicals that are similar in structme and have persistence data or (2) use general quantitative structure-degradation relationships (QSDR) models. It is concluded that estimation methods are available for the most important degradation processes atmospheric oxidation, biodegradation, and hydrolysis. 

Physical Properties, Transport and Degradation of Environmental Fate and Exposure Assessments, Quantitative Structure-Activity Relationships in Environmental Sciences, VII, Chapter 13, SETAC Press, USA. 

The aliphatic alicyclic hydrocarbon precursor is not well recognized as the major aliphatic component in dissolved humic substances, although it was previously postulated to occur (II). This precursor might arise from terpenoid hydrocarbon lipids, but the data presented in this chapter favor polyunsaturated lipid precursors that are oxidatively coupled and cyclized by free-radical mechanisms (20). Degradative studies have not identified this aliphatic component in recognizable fragments. The quantitative, structural-model approach presented here combines the results of 13C NMR, NMR,... 

Clearly, molecular structure influences the reaction kinetics of organic compounds during their photocatalytic oxidation. This relationship between degradability and molecular structure may be described using quantitative structure-activity relationship (QSAR) models. QSAR models can be developed to predict kinetic rate constants for organic compounds with similar chemical structures. The following section discusses QSAR models developed by Tang and Hendrix (1998) as well as those developed by other researchers. 

Howard, P.H. and W.M. Meylan. 1997. Prediction of physical properties, transport and degradation for environmental fate and exposure assessments. In Quantitative Structure-Activity Relationships in Environmental Sciences-VII, F. Chen and G. Schuurmann, Eds., pp 185-205. SETAC Press, Pensacola, FL. 

Rorije, E., Muller, M., and Peijnenburg, W.J.G.M., Prediction of Environmental Degradation Rates for High Production Volume Chemicals (HPVC) using Quantitative Structure-Activity Relationships, Report No. 719101030, National Institute of Public Health and Environmental Protection, Bilthoven, The Netherlands, 1997. 

Environmental fate models make use of chemical properties to describe transfer, partitioning, and degradation (Mackay et al. 1992a Cahill et al. 2003). For organic chemicals, quantitative structure-property relationships (QSPRs) may be used to predict partitioning from physical-chemical properties, such as Kow and Kov Such properties may also allow for a prediction of the transfer of chemicals between compartments. Recently, some successful attempts have also been made to predict persistency of chemicals (Raymond et al. 2001), although this mainly concerns... 

While experimentally derived test data are preferred, where no experimental data are available, validated Quantitative Structure Activity Relationships (QSARs) for aquatic toxicity and log Kqw may be used in the classification process. Such validated QSARs may be used without modification to the agreed criteria, if restricted to chemicals for which their mode of action and applicability are well characterized. Reliable calculated toxicity and log Kow values should be valuable in the safety net context. QSARs for predicting ready biodegradation are not yet sufficiently accurate to predict rapid degradation. 

Abstract In sensor and microfluidic applications, the need is to have an adequate solvent resistance of polymers to prevent degradation of the substrate surface upon deposition of sensor formilations, to prevent contamination of the solvent-containing sensor formulations or contamination of organic liquid reactions in microfluidic channels. Unfortunately, no comprehensive quantitative reference solubility data of unstressed copolymers is available to date. In this study, we evaluate solvent-resistance of several polycarbonate copolymers prepared from the reaction of hydroqui-none (HQ), resorcinol (RS), and bisphenol A (BPA). Our high-throughput polymer evaluation approach permitted the construction of detailed solvent-resistance maps, the development of quantitative structure-property relationships for BPA-HQ-RS copolymers and provided new knowledge for the further development of the polymeric sensor and microfluidic components. 

All developments of quantitative structure activity relationships (QSARs)/ quantitative structure-property relationships (QSPRs)/QSDRs go through similar steps (1) collection of a database of measured values for model development and validation/evaluation, (2) selection of chemical descriptors (can include connection indices, atom, bond, or functional groups, molecular orbital calculations), (3) development of the model (develop a correlation between the chemical descriptors and the activity/property/degradation values) using a variety of statistical approaches (linear and non-linear regression, neural networks, partial least squares (PLS), etc. [9]), and (4) validate/evaluate the model for predictability (usually try to use a separate set of chemicals other than the ones used to train the model external validation) [10]. 

Covers, H. A. J., Parsons, J. R., Krop, H. B. and Cheung, C. L. (1995) Thermodynamic descriptors for (bio-)degradation, in Proceedings of the Workshop Quantitative Structure Activity Relationships for Biodegradation, [September 1994, Belgirate, Italy], Report No. 719101021, National Institute of Public Health and Environmental Protection, Bilthoven. 

Degradation by the action of microorganisms is one of the major processes that determines the fate of organic chemicals in the environment. Quantitative Structure-Activity Relationships (QSAR) methods can be applied to biodegradation. Such relationships, often referred to as Quantitative Structure-Biodegradability Relationships (QSBRs), relate the molecular structure of an organic chemical to its biodegradability and consequently aid in the prediction of environmental fate. 

Damborsky, J. 1996. A mechanistic approach to deriving quantitative structure-activity relationship models for microbial degradation of organic compounds. SAR QSAR in Environmental Research, Vol. 5, pp. 27-36. 

R. Hales, A quantitative metaUographic assessment of structural degradation of type 316 stainless steel during creep-fatigue. Fat. Eng. Mat. Struct. 3 (4) (1980) 339—356. 

---