Abstracts (PDF file, 1.8MB) - Society for Risk Analysis

SRA 2013 Annual Meeting Abstracts
T2-A.4 Anadon, LD*; Bosetti, V; Chan, G; Nemet, GF; Verdolini,
E; Harvard University; laura_diaz_anadon@harvard.edu
Energy technology expert elicitations: their use in models
and what can we learn from workshops and metaanalysis
Developing energy policies that are robust to a broad set of
possible future conditions typically requires characterization of
the anticipated performance of individual energy technologies.
In particular, decisions about public investments in research,
development, and demonstration (RD&D) aimed at promoting
technological change in a range of energy technologies ideally
require not only an explicit and robust consideration of the
uncertainty inherent to innovation, but also a way of
considering tradeoffs and making allocations across different
technology areas. Over the past few years several groups on
both sides of the Atlantic have developed expert elicitations and
used energy-economic models to shed light on these questions.
This presentation will draw on work from two of these groups
and will be divided into four sections. First, we will discuss the
lessons learned from the design and implementation of seven
energy-technology expert elicitations of forecasted technology
cost and performance metrics, highlighting the need for (and
difficulties associated with) matching elicitation design and
modeling approach. Second, we will present insights drawn
from an effort to use expert elicitations to optimize RD&D
investment portfolios, including results on decreasing marginal
returns to and optimal levels of overall RD&D investments, as
well as of the importance of identifying policy scenarios and
metrics for evaluation. Third, we will discuss the usefulness of
devising online elicitation tools and of combining individual
elicitations with group discussions to increase reliability and, in
the long-run, reduce costs. And fourth, we will discuss the
application of meta-analysis techniques to improve our
understanding of the impact of expert selection on elicitation
results and of the shape of the expected returns to RD&D.
T5-C.2 ANDERSON, EL; Exponent; elanderson@exponent.com
Creating a Field That Matters
Risk analysis was widely used in the field of engineering before
it was introduced as policy by the U S. Environmental
Protection Agency in 1976 for carcinogen risk assessment.
While health applications were obviously very different from
those in engineering, there were and remain overlapping
methods and approaches. The impact of the use of risk
assessment in the health field was profound and wide spread;
the regulation of exposure to suspect carcinogens was and
remains controversial and comes under close scrutiny by the
publics whose health public health agencies are required to
protect. In short order, it became obvious that the public
perception of risk was most often different from the science
based assessed risk. How to create a field that matters from
this disparate application of risk analysis formed the impetus
for the founding of our Journal, Risk Analysis: An International
Journal. The Journal became the forum for sharing and merging
interdisciplinary, scholarly research on topics in risk analysis to
inform the whole of risk analysis. While in the beginning there
was only one Editor in Chief, by 1999, it had become obvious
that at least three Area Editors were need for Engineering,
Health and Social Sciences to adequately cover the
submissions, proactively solicit interesting special collections of
papers, and oversee peer review. As the leading international
Journal on topics in risk analysis, there is little doubt that Risk
Analysis: An International Journal has played an important role
in unifying and informing methods and applications in risk
analysis. Exploring the creation of this field from the early days
to the professional based foundations of today required
imagination, determination, and interdisciplinary cooperation of
many scholars. The success of the Journal is a model for
creating a field that matters.
M2-I.2 Andrijcic, E.*; Haimes, Y.Y.; Rose-Hulman Institute of
Technology, University of Virginia; ea2r@virginia.edu
Developing a multi-phase, iterative and collaborative
decision coordination process for transportation
infrastructure management
The practice of persistent infrastructure underinvestment,
coupled with a significant growth in commercial and
non-commercial transportation demand, has left the U.S.
transportation infrastructure unable to adequately support
current and future needs. The lack of political will to allocate
the needed funds to bridge infrastructure improvement stems,
in part, from the disharmonious goals and objectives among the
various stakeholders, and political and other decision makers,
as well as the lack of appreciation of the critical
interdependencies among the myriad sub-systems of the bridge
infrastructure. To address this challenge, we present a
multi-phase, iterative and collaborative decision coordination
process that is based on the theory of intrinsic meta-modeling
via shared state variables. The developed approach enables the
harmonization of multiple models representing varied
sub-systems and stakeholders’ perspectives. The approach
provides decision makers with the ability to better visualize and
collaboratively coordinate their shared and conflicting interests
with the purpose of achieving public policy solutions for
transportation infrastructure that are satisficing to all involved
stakeholders, and sustainable over a long planning horizon. We
present an illustrative example in which we utilize the
meta-modeling coordination to explore the engineering, social,
economic, and political implications of insufficient bridge
maintenance. We focus on the evolving nature of objectives,
interest groups, organizational, political and budgetary
baselines, and requirements associated with varied
stakeholders, and show that the meta-modeling coordination
process enables all stakeholders and decision makers to plan
for future emergent changes through collaborative and
foresighted efforts. Additionally, we illustrate how the
developed process could be utilized to more equally distribute
risk ownership among all involved stakeholders.
W3-C.1 Antoniou, G; Gebrayel, A; Mhanna, P; Sarri, M;
Stylianou, K; Kouis, P*; Cyprus International Institute, Cyrus
University of Technology; pankouis@yahoo.gr
A Preliminary Characterization of Public Health Risks
from Industrial Operations in Jubail
This paper characterizes the health risks due to the emissions
of the industrial complex at Jubail, S. Arabia, one of the largest
in Middle East. Students at the Cyprus International Institute
conducted a probabilistic risk assessment using
publically-available data on the nature and production capacity
of representative facilities – i.e., a refinery, steel plant, fertilizer
manufacturer, plastics facility, and methanol plant. A
preliminary risk assessment was conducted, using the LCA
software Simapro®, to determine typical emissions and the
contributions of various pollutants. It indicated that PM2.5,
sulfur dioxide and nitrogen oxides dominated mortality impacts.
For these pollutants a comprehensive risk assessment,
reflecting Jubail conditions, was developed using Analytica®.
This coupled emissions from Simapro®, with intake fractions
for PM and its precursors adapted from Wolff (2000). It used
the probabilistic PM exposure-response coefficients from six
European epidemiologists developed by Tuomisto (2008).
Mortality was valued using US VSL estimates of Viscusi and
Aldy (2003) adapted to the region using benefits transfer with
income elasticity between 0.4 and 0.6. Uncertainty was
analyzed with 10 runs, of 5,000 iterations each, and Latin
Hypercube sampling. The analysis suggests that about 200
deaths/yr are attributable to industrial emissions from Jubail.
Only a small fraction of these occur among the residents of
Jubail. The power plant and refinery are responsible for the
most of these. Secondary sulfate is the dominant source of
health impacts. Potential benefits of pollution control are large
(nearly 1 billion US$/year), however most of these benefits
accrue to populations outside Saudi Arabia. Since the analysis
relies on publically available data, results are somewhat
tentative but could easily be refined if these generic
characterizations of industrial processes and emissions were
replaced with information site-specific processes and emissions.
December 8-11, 2013 - Baltimore, MD