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INNOVATIVE RESEARCH FOR A SUSTAINABLE FUTURE
GREENSCOPE: Sustainable Process Modeling
Background
The chemical industry is
fundamental in the U.S. This sector
accounts for five percent of the U.S.
nominal gross domestic product and
six percent of the total U.S. energy
consumption, directly employs
approximately 800,000 people
nationwide, and is the source for
11% of all U.S. patents granted
annually.
The chemical industry faces
environmental and health challenges
that are common across business
sectors. From the use of
nonrenewable feedstocks, to the cost
and handling of waste disposal and
workers' exposure to toxic
substances, the industry must
overcome complex hurdles to secure
a more sustainable future.
Overview
EPA researchers are responding to
the problems outlined above by
incorporating sustainability into
process design and evaluation. EPA
researchers are developing a tool
that allows users to assess
modifications to existing and new
chemical processes to determine
whether changes in critical sub-
processes or substances will make
the overall process more or less
sustainable.
The GREENSCOPE (Gauging
Reaction Effectiveness for
Environmental Sustainability of
Chemistries with a multi-Objective
Process Evaluator) research project
focuses on developing a systematic
methodology and software tool that
can assist researchers from industry,
academia, and government agencies
in developing more sustainable
processes. In the project, the
sustainability of a process is
measured in terms of Environmental,
Efficiency, Energy and Economic
indicators (the 4 E's), with each
indicator being mathematically
defined. The indicators express
diverse aspects of performance in a
format that is easily understood,
supporting realistic usage. The
indicators enable and demonstrate
the effectiveness of the application
of green chemistry and green
engineering principles in the
sustainability context.
Sustainability Indicators
To evaluate the environmental
aspects of alternative chemistries or
technologies, GREENSCOPE
employs the Waste Reduction
(WAR) algorithm (Young and
Cabezas, 1999). The WAR
algorithm determines the potential
environmental impacts of releases
from a process in eight impact
categories: human toxicity by
ingestion and dermal/inhalation
routes, aquatic toxicity, terrestrial
toxicity, acidification, photo-
chemical oxidation, global warming
and ozone depletion. While these
potential impacts are defined as mid-
point indicators (as opposed to end-
point indicators), the measures for
the categories are well defined,
which is a substantial improvement
over arbitrary environmental or
mass-based scores.
Efficiencies for chemical reactions
are reflected in values such as
conversion and selectivity, which
track yields, product distributions,
and recycle flows needed to make a
desired amount of product. Another
measure of how green a reaction is
can be obtained from the atom
economy (i.e., how many atoms
from the feed are in the product).
These measures, which are well
known in green chemistry, are
related to environmental impacts
since the product distribution defines
what chemicals (and amounts) may
leave a process. These efficiencies
represent a bridge between the lab-
scale experiments of a chemist and
further engineering calculations.
Energy is a basic component of
chemical processes. Its use depletes
resources and creates potential
environmental impacts. Connecting
to yet another sustainability
indicator, a less efficient process can
be expected to use more energy.
Without a positive economic
performance, no industrial process is
sustainable. The economics of
processes are measured according to
their costs. For economists, this is an
oversimplified view of markets, but
for engineering calculations, the
annualized costs are significant
measures. The costs are tied into the
process through efficiencies, energy,
and environmental impacts.
Another novel aspect of the
GREENSCOPE methodology and
tool is that each indicator is placed
on a sustainability scale enclosed by
scenarios representing the best target
(100% of sustainability) and the
worst case (0% of sustainability).
This sustainability scale allows the
transformation of any indicator score
U.S. Environmental Protection Agency
Office of Research and Development
EPA 600-F11020
July 2011
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to a dimensionless form using the
worst and best scenarios.
A process that is better in
environmental, efficiency, energy,
and economic terms will most likely
be sustainable, although one can
expect that tradeoffs will need to be
made.
Below, the indicators for a
hypothetical process illustrate
measures (in blue) that fall between
0 and 100% of sustainability.
Ell
c
E42
E41
E35
E31
Data Needs
GREENSCOPE requires diverse
data. These data can be obtained
from experimental work, process
modeling, physical and
thermodynamic multi/pure
component properties, product and
process design specifications, life
cycle inventory, physical and
thermodynamic commercial
databases, and emissions, discharge,
and consumption data from agencies
such as EPA, the U.S. Department of
Energy, the U.S. Department of
Agriculture, and non-governmental
organizations such as the World
Resources Institute and the Carbon
Disclosure Project.
Results
Development of the methodology
has centered around three focal
points. The first is a taxonomy that
describes the indicators and provides
absolute scales for their evaluation.
The use of best and worst limits (100
and 0% of sustainability,
respectively) for each indicator
allows the user to know the status of
the process under study in
relation to understood values
and to strive towards
realizable targets.
A second area is advancing
definitions of data needs for
the many indicators. Each
indicator has specific data
that are necessary for its
calculation. Values needed
and data sources have been
identified. These needs can
be mapped according to the
information source (e.g.,
input stream, output stream,
external data, etc.). The user
can visualize data-indicator
relationships before choosing
indicators for evaluation.
The third focus is on case
studies. Example calculations were
performed on an alternative catalyst
for the oxidation of cyclohexane.
The results indicate how beneficial
the new catalyst technology could
be. For this and future studies, once
one knows what success would
mean, the decision to pursue
research can be made on a firmer
basis.
In addition, the scalability of
GREENSCOPE results was
addressed to ensure that optimized
sustainable designs, as well as
experimental studies at the lab scale,
would be reflected at the process
scale.
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Current and Future Research
The methodology is being applied to
the production of biodiesel.
Analyses identify where biodiesel
processes can be made more
sustainable based on environmental,
economic, efficiency, and energy
measures. Process improvements
can be suggested or those that were
made can be evaluated.
Future work will incorporate models
and experiments in an iterative
process using a GREENSCOPE
software tool to support sustainable
chemical process synthesis. An
integrated computational tool for
multi-objective chemical simulation
software will be developed.
References
Smith, R. L. and Gonzalez, M. A.
Methods for evaluating the
sustainability of green processes.
Comp. Aided Chem. Eng., 2004,
Vol. 18, 1135-1140.
Gonzalez, M. A. and Smith, R. L. A
methodology to evaluate process
sustainability. Env. Prog., 2003,
Vol. 22 (4), 269-276.
Young, D.M. and Cabezas, H.
Designing Sustainable Processes
with Simulation: The Waste
Reduction (WAR) Algorithm.
Comput. Chem. Eng., 1999, Vol. 23,
1477-1491.
Contacts
Michael A. Gonzalez, Ph.D., Office of
Research & Development, 513-569-
7998, gonzalez.michael@epa.gov
Raymond Smith, Ph.D., Office of
Research & Development, 513-569-
7161, smith.raymond@epa.gov
Gerardo Ruiz-Mercado, Ph.D., Office of
Research & Development, 513-569-
7030, ruiz-mercado.gerardo@epa.gov
U.S. Environmental Protection Agency
Office of Research and Development
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