Program Element 7: System
Integration, Prediction, and
Optimization
Fundamental research to develop conceptual and quantitative methods for describing
community dynamics, biotransformation, biodegradation, and biogeochemical dynamics processes
in complex geologic systems.
PROGRAM OBJECTIVES
To integrate scientific concepts and data from different program elements and to
develop a hierarchy of improved mathematical methods for describing coupled
biological, geochemical, geological, and transport processes. These methods will
be used, together with visualization techniques, to design and interpret laboratory
and field experiments, to establish bioremediation design principles, to predict
and optimize the effectiveness of bioremediation under many different conditions,
and to identify and quantify the largest sources of uncertainty. The overall goal
is to synthesize this information so that the effectiveness of bioremediation at
sites with complex contaminant mixtures can be predicted and optimized. Further,
bioremediation strategies can be compared with conventional remediation through a
cost-benefit analysis.
BACKGROUND
Knowledge gained in the scientific disciplines of microbiology, hydrology, and
geochemistry provides a strong scientific foundation for bioremediation. However,
the effectiveness of bioremediation cannot yet be predicted with a high degree of
confidence for complex contaminant mixtures and heterogeneous geology (Miller and
Poindexter, 1994). A key component in the inability to make accurate predictions
is the lack of a robust understanding of the dynamics that interrelate biological,
hydrological, and geochemical processes as well as the quantitative tools needed
to synthesize them. Examples of such coupled or interrelated phenomena include the
correlation among local geochemistry, moisture variation, and biological
activities; the dependence of biological activities on soil chemistry and fluid
advection and dispersion; and the transient processes involving water recharge,
nutrient transport, biological activity, chemical transformation, and migration of
products from biological activities (AgBiotech, 1991; Alfoldi, 1991). These
activities are further complicated by the heterogeneity or variability of the
physical, chemical, and biological properties of natural systems. Advances in
understanding the relationship of such activities and in dealing with
heterogeneities will provide the foundations for predicting and improving the
effectiveness of existing bioremediation technologies and for developing new and
innovative ones.
The effectiveness of bioremediation cannot yet be predicted with a high
degree of confidence for complex contaminant mixtures and heterogeneous geology.
Because of the multidisciplinary nature of the program, there will be a diversity
of scientific data (biological, chemical, geological, etc.).
Fortunately there have been many efforts in recent years on databases
and informatics. These will be used to support rapid evolution of data
and information from the program elements to promote the sharing of data
among projects and with the larger scientific community.
APPROACH
The System Integration, Prediction, and Optimization element will
develop strategies to represent mathematically the key microbial,
biotransformation, and biogeochemical processes identified in other
program elements, and to identify, adapt, or develop where necessary
predictive models (including statistical models) that can design and
interpret laboratory and field-scale experiments for intrinsic and
enhanced bioremediation. In parallel, an information system will be
developed to facilitate the synthesis of experimental data gathered by
the program at one site, preferably using existing software where
feasible. The final products of this program element are expected to
include predictive models that have been successfully tested and that
can be used to design and interpret laboratory and field-scale
experiments for intrinsic and enhanced bioremediation.
To address the need for systematic methods of integrating biological,
geochemical, geological, and transport processes associated with
contaminant mixtures in complex geologic systems, research will focus
on three areas:
These research activities will build on information gained from all program
elements and will be essential for interpreting phenomena observed in complex
natural systems. At any time, the integrated models and associated databases will
represent the current state of knowledge and will be available for predicting
optimal bioremediation strategies for a given site and site conditions and for
comparing bioremediation strategies with conventional remediation methods through
a cost-benefit analysis.
Subelement 7.1: Scientific Data Integration and
Informatics
Fundamental research on integration and informatics for multidisciplinary data and on
evaluation techniques for data quality, consistency, and validity ranges.
Objectives
To develop methods to organize, integrate, and evaluate scientific data
and information from all program elements. To provide a network-accessible information system to support the research program.
Goals
Three-Year
Define the information description and data organization, i.e., schema definition,
for different program elements and for a selected field site. Design and implement
an efficient, remotely accessible information system to support the diverse data,
using existing software where feasible.
Design and implement appropriate, accessible, and efficient information-management
systems and mechanisms.
Five-Year
Deploy and adapt the site information system at all sites. Provide networked,
shared, on-line access to public database systems for data derived from the program
elements. In addition, provide networked access to appropriate databases managed
by various program elements.
Synthesize and evaluate information and data from the various program elements,
using the accumulated data and information systems. Identify knowledge gaps and
prioritize future research activities.
Ten-Year
Maintain and provide access to a comprehensive information system that archives
experimental results related to the scientific elements of bioremediation (e.g.,
microbial community dynamics, biotransformation and biodegradation, biomolecular
engineering, and assessment methods).
Subelement 7.2: Mathematical Representation of
Community Dynamics, Biotransformation, and
Biogeochemical Processes
Fundamental research on mathematical representation of processes related to bioremediation
and the couplings and interrelationships among these processes.
Objectives
To enhance or develop mathematical (numerical and statistical)
representations of microbial community dynamics, biodegradation,
biotransformation, and biogeochemical processes as they interrelate in
terrestrial environments, and to develop integrative and scalable
models.
Goals
Three-Year
Develop improved mathematical representations (or new representations where needed)
of microbial community dynamics, biodegradation, biotransformation, and
biogeochemical processes.
Develop improved or new strategies for describing mathematically how community
dynamics, biodegradation, biotransformation, and biogeochemical processes influence
and interrelate to each other.
Five-Year
Develop mathematical and stochastic representations of microbial community
dynamics, biodegradation, biotransformation, and biogeochemical processes in
heterogeneous systems and their couplings for selected microbial communities and
contaminant mixtures.
Develop and validate larger-scale models of community dynamics, biotransformation,
and biogeochemical processes.
Ten-Year
Develop and test mathematical and stochastic representations of microbial community
dynamics, biodegradation, biotransformation, and biogeochemical processes for many
different microbial communities and contaminant mixtures.
Subelement 7.3: Integrative and Scalable
Models
Fundamental research on mathematical (numerical and statistical) models to simulate
integrated bioremediation processes in soils and geologic formations, accounting for biological,
chemical, and physical variabilities.
Objectives
Enhance or develop predictive computational and statistical models for
designing, integrating, and evaluating laboratory and field
experiments. Develop inversion methods to obtain parameter estimates
from field and laboratory experiments. Obtain or develop improved
software tools for model development and model management to cope with
the increasingly complex models.
A three-tier hierarchy of models will be constructed, with systematic
methods linking results from one model to another. The first set of
models will predict bench-scale biodegradation and biotransformation
rates in complex subsurface environments contaminated with contaminant
mixtures. The second set will focus on the coupling between in
situ transport processes and biotransformation and biodegradation at a scale
that captures the relevant biogeochemical processes and heterogeneities of natural
environments. The third set will focus on the engineering calculations needed to
implement and optimize bioremediation on a field scale. These models will include
a strong statistical component to account for biological and chemical variabilities
as a function of both space and time. Equally important to developing the models
is the design of the scaling-up concepts and processes that will link them
together. Once the models are successfully tested, they will be made available to
the environmental bioremediation industry.
Goals
Three-Year
Identify and adapt or develop where necessary predictive models -- for designing
and interpreting initial interdisciplinary, multi-investigator laboratory and field
experiments -- that can support the program. Develop concepts and strategies for
designing the next generation of predictive models in cooperation with researchers
from other program elements.
Develop concepts and strategies for scaling up from bench- and intermediate-scale
models to field-scale models by evaluating appropriate system parameters,
measurement capabilities, and computational requirements.
Five-Year
Develop next-generation predictive models for bench-, intermediate-, and field-scale bioremediation. Evaluate these models by comparison with observations made
from intrinsic and enhanced bioremediation laboratory and field experiments, thus
testing the methods for increasing the scale from bench- and intermediate-scale
models to field-scale models.
Adopt or develop model development tools which would permit rapid, concise
specification of models in terms of symbolic mathematics, and subsequent automatic
code generation. Adopt or develop model management systems for managing
collections of models and simulation runs.
Develop and apply inversion procedures for evaluating parameters from laboratory
and field experiments on bioremediation processes.
Ten-Year
Use tested predictive and inverse models for designing, optimizing, and evaluating
intrinsic and enhanced bioremediation at DOE and other mixed-contaminant sites.
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