Risk-relevant indices for the characterization of persistence of chemicals in a multimedia environment

The present research study proposes a new set of appropriately defined indices for the characterization of persistence of chemicals in a multimedia environment that prominently figures as a key exposure-based indicator within contemporary frameworks of chemical hazard and risk assessment, as well as recent international regulatory initiatives. Effectively overcoming some of the limitations associated with traditional approaches that could lead to a potential misclassification of chemical substances, the proposed set of persistence indices retain also a conceptually insightful and computational appeal. Conceptually inspired by certain measures/indices for the characteristic time found in classic dynamic systems theory, and technically relying on notions and methods from the theory of matrices, the new performance indices can be easily calculated on the basis of a dynamic multimedia environmental model and the aid of a software package such as MATLAB. In particular, an extension of the notion of equivalence width as a quantitative proxy of overall persistence is introduced, that captures the dynamic history of the chemical's environmental behavior, while remaining independent of the particular release pattern and discharge conditions (thus overcoming the standardization difficulties encountered when a large number of chemicals need to be first screened and classified in a tiered hazard assessment methodology). Furthermore, a second persistence index is introduced whose value can be analytically calculated through the solution of a simple Lyapunov matrix equation bearing some resemblance to certain measures of system resilience used in theoretical biology and ecology, yet inspired by system-theoretic notions associated with the Lyapunov framework of analysis in systems science. Furthermore, for both persistence measures a comparison is made with the slowest time-constant associated with the specific chemical dynamics in a multimedia environment, and upper and lower bounds are established. Finally, the proposed persistence indices are calculated on the basis of a standard dynamic multimedia environmental model for various representative cases involving chemicals of particular interest.

[1]  Stephen R. Carpenter,et al.  Predictive Indices of Ecosystem Resilience in Models of North Temperate Lakes , 1994 .

[2]  R. A. Wright,et al.  Optimization of quadratic performance indexes for nonlinear control systems , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[3]  R. E. Kalman,et al.  Control System Analysis and Design Via the “Second Method” of Lyapunov: I—Continuous-Time Systems , 1960 .

[4]  Konrad Hungerbühler,et al.  Measures of overall persistence and the temporal remote state. , 2004, Environmental science & technology.

[5]  A. Gorban,et al.  Invariant Manifolds for Physical and Chemical Kinetics , 2005 .

[6]  Konrad Hungerbühler,et al.  Joint Persistence of Transformation Products in Chemicals Assessment: Case Studies and Uncertainty Analysis , 2003, Risk analysis : an official publication of the Society for Risk Analysis.

[7]  Martin Scheringer,et al.  Persistence and Spatial Range as Endpoints of an Exposure-Based Assessment of Organic Chemicals , 1996 .

[8]  Daniel A. Crowl,et al.  Chemical Process Safety: Fundamentals with Applications , 2001 .

[9]  Thomas E. McKone,et al.  General Formulation of Characteristic Time for Persistent Chemicals in a Multimedia Environment , 1999 .

[10]  U. Müller-Herold A Simple General Limiting Law for the Overall Decay of Organic Compounds with Global Pollution Potential , 1996 .

[11]  Ken Geiser,et al.  The precautionary principle stimulus for solutions- and alternatives-based environmental policy , 2004 .

[12]  R. Levins,et al.  The precautionary principle in environmental science. , 2001, Environmental health perspectives.

[13]  John Cairns,et al.  Estimating the hazard of chemical substances to aquatic life , 2004, Hydrobiologia.

[14]  H. Caswell,et al.  ALTERNATIVES TO RESILIENCE FOR MEASURING THE RESPONSES OF ECOLOGICAL SYSTEMS TO PERTURBATIONS , 1997 .

[15]  Costas Kravaris,et al.  Optimal controller tuning for nonlinear processes , 2005, Autom..

[16]  Robert S. Boethling,et al.  Screening for persistent organic pollutants: Techniques to provide a scientific basis for POPs criteria in international negotiations , 1999 .

[17]  D. Mackay,et al.  Complexity in multimedia mass balance models: When are simple models adequate and when are more complex models necessary? , 2003, Environmental toxicology and chemistry.

[18]  Chi-Tsong Chen,et al.  Linear System Theory and Design , 1995 .

[19]  K. Hirai,et al.  Upper and lower bounds on the solution of the algebraic Riccati equation , 1979 .

[20]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[21]  Todd Gouin,et al.  Screening Chemicals for Persistence in the Environment , 2000 .

[22]  Panos G. Georgopoulos,et al.  Integrated Exposure and Dose Modeling and Analysis System. 1. Formulation and Testing of Microenvironmental and Pharmacokinetic Components , 1997 .

[23]  Martin Scheringer,et al.  Characterization of the Environmental Distribution Behavior of Organic Chemicals by Means of Persistence and Spatial Range , 1997 .

[24]  S. Wiggins Introduction to Applied Nonlinear Dynamical Systems and Chaos , 1989 .

[25]  Martin Scheringer,et al.  Persistence and spatial range of environmental chemicals: , 2002 .