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Lionel Carreira

Blurred image of a green laser used as background for stylistic purposes.
Emeritus Professor
  • Ph.D., Massachusetts Institute of Technology, 1969
Research Interests:

Professor Carreira's research focuses on the fate and transport of metals and organics in the environment with a particular emphasis on speciation. These research efforts involve both the development and application of a novel program called SPARC (SPARC Performs Automated Reasoning in Chemistry). The SPARC program was created to address the gap in predictive chemical fate modeling. Regulatory mandates have created the need for efficient models for exposure and impact assessment of human and ecological systems to chemicals imposed directly or indirectly by human activities. These assessments must deal with increasingly larger spatial scales of analysis, more complex ecological scenarios, and a broader array of contaminants or mixtures. In addition to providing potential impact/risk assessments, these models must also provide management and regulatory options. These developments have placed new urgency on the need for enhanced predictive modeling capability. While great strides have been made in engineering modeling technology addressing chemical fate and transport in the environment, predictive capability is more often than not limited by the lack of fundamental chemical properties (e.g., physical and chemical constants required in chemical process modeling). There accrues an increasing demand on physical and biological scientists and engineers to provide effective techniques for quantifying the release, fate, and potential environmental damage resulting from pollutants. Historically, Federal health and safety regulators have relied on field monitoring, toxicological test data and expert scientific knowledge to condemn or vindicate a given chemical. Recent emphasis, however, on more quantitative and comprehensive risk/benefit analyses has required the development of more sophisticated evaluation methods. These methods must be capable of forecasting pollutant behavior over wide ranges of environmental conditions, often without the benefit of measured data specific to the chemical or ecosystem in question. The SPARC system consists of an integrated array of modularized intra- and intermolecular interaction models that can be related (through the appropriate thermodynamic relationships) to a wide range of physical and chemical process parameters. The span in chemical parameter prediction (currently operational or under development) includes: (1) equilibrium constants for complex speciation (ionization and tautomerization) and interphase distribution (gas/liquid, liquid/liquid, solubilities) and (2) rate constants for reactivity (solvolysis and redox). Predictive capability extends to essentially any organic solute and derives strictly from molecular structure input. Solvents capability includes water and essentially any organic solvent or mixtures thereof. Reaction conditions (temperature, pressure, pH, and ionic strength) span ranges typical of environmental application. Calculate a PhysicoChemical Property

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