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Agenda -Part 2. 11:25-11:30Overview on Part 2 11:30-11:45Insurance managers - Daniel Hoffmann and Granger Morgan 11:45-12:00Questions and Discussion 12:00-12:15Forest, fisheries and ecosystem managers in the Pacific Northwest and Western Canada -Tim McDaniels

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Agenda -Part 2

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Agenda part 2

Agenda -Part 2

11:25-11:30Overview on Part 2

11:30-11:45Insurance managers

- Daniel Hoffmann and Granger Morgan

11:45-12:00Questions and Discussion

12:00-12:15Forest, fisheries and ecosystem managers in the Pacific Northwest and Western Canada

-Tim McDaniels

12:15-12:30Questions and Discussion

12:30-13:00Lunch


Part 2 studies of decision making in four specific contexts

Part 2: Studies of Decision Makingin Four Specific Contexts

  • We've proposed to study four specific decision contexts.

  • The point of this part of the project is to examine a set of specific settings in which climate is likely to be very important, and the decision-making implications of our limited ability to make predictions about future climate can be worked out in detail.

  • For that reason we have been very careful to select settings in which we think climate will play an important role:

    • •insurance industry (potential large liability exposures)

    • •the high arctic (anticipated large climate changes).

    • •high latitude forest and fishery resources (anticipated substantial impacts).

    • •power industry (probably will take the brunt to early serious controls).


Climate is only one variable

Climate is only one variable

While we have been careful to select decision contexts in which we believe that future climate is likely to be a major factor, it is important to remember that even in these cases climate is not the only thing that will change over coming decades.

Indeed, often, even in these cases, climate is likely to be of second order importance compared with other important variables such as new technology, changing public policy, changing economic relationships, and social and instructional infrastructure.


Decision case studies cont

Decision case studies…(Cont.)

While climate, and possible future climate policy, can impose stress on social, economic and ecological systems, so too can many other factors.

Just as there are limits to our ability to make predictions about future climate, so too there are limits both to our ability to identify likely sources of future stress, and to make meaningful predictions about those stresses.

However, with some effort, at least some of these can be identified, and when possible, be generalized.


Decision case studies cont1

Decision case studies…(Cont.)

Typically, we will not use detailed scenarios but rather will use simpler parametric methods.

Thus, for example, if future natural gas prices look to be critical to a specific class of decisions, in the projects in Part 2 we will not develop long detailed stories about how those prices might be shaped by future technology and by developments in the US, Europe, the Middle East and the Former Soviet Union but will simply truncate the causal chain, posit a range of possible future oil prices, and work from there.

Later of course, outputs from Part 3 may help us refine this treatment.


Decision case studies cont2

Decision case studies…(Cont.)

Once results from the climate science elicitation studies from Part 1 become available, we will use them, along with the other sector-specific information we have developed, to begin to create a set of decision support tools that are appropriate given the limitations on the predictive information that we are likely to be able to acquire.

As results become available from the work in Part 3 of the Center's research, these tools will be modified to incorporate additional information and uncertainty about climate policy and its impacts.

Different tools will be developed in different contexts depending upon the details of the sector and the problems they face.


Agenda part 21

Agenda -Part 2

11:25-11:30Overview on Part 2

11:30-11:45Insurance managers

- Daniel Hoffmann and Granger Morgan

11:45-12:00Questions and Discussion

12:00-12:15Forest, fisheries and ecosystem managers in the Pacific Northwest and Western Canada

-Tim McDaniels

12:15-12:30Questions and Discussion

12:30-13:00Lunch


Agenda part 2

Climate Change and Global Warming –

Risks to the Insurance Industry


Agenda part 2

Climate Change and Global Warming –

A Fact to Reckon With

1870 Rhone Glacier, Switzerland 1999


And the same here grinnell glacier and lake 1910 to 1977

… and the same here : Grinnell Glacier and Lake (1910 to 1977)

Pretty soon we will have to settle for Non-Glacier National Park!


Overview the insurance industry

Overview - The Insurance Industry

  • Primary Insurance Carriers

    • Business Area: short- and medium-term risk

    • Products: Health & Life, P&C

    • Backstop provided by Reinsurance Carriers

  • Reinsurance Carriers

    • Business Area: Backstop for primary carriers;

    • Long-term, catastrophic, specialty, and high exposure risks

    • Products: CAT insurance, high excess, specialty products (BI, D&O, ART, derivatives, guaranties, bonds), asset management


Financials of the insurance industry

Financials of the Insurance Industry

  • Revenue and Assets

    • Revenues from premium and investments

    • Premium Revenues: US$2.2T global

    • Assets (U.S. Life Insurance companies only):

      • Total: US$2.8T

      • Real Property Holdings: US$60B

      • Equal to ~15% of total assets and reserves of major pension funds and retirement programs

    • Return on premium: mostly negative (ratio ~1.06)

    • Return on Investments/Assets = Profitability

    • (Source: Innovest, personal communication, 2003)


The dawning in the insurance industry

The Dawning in the Insurance Industry

“The insurance business is first in line to be affected by climate change. It is clear that global warming could bankrupt the industry …”

Franklin Nutter,President,

Reinsurance Association of America, 2003

Why…?

-Climate Change is a global phenomenon,

-The Insurance Industry is a global player


Awareness of the insurance industry

Awareness of the Insurance Industry

  • Primary Insurance Companies

    • Late in awareness

      • Reason: Revenue and Assets

    • Awareness increases due to exposures in liability coverage

  • Reinsurance Industry

    • Highly aware overall, as risk research/quantification has shown increased exposure

    • Leaders: Munich Re and Swiss Re

    • Implementation of programs to

      • Limit risks

      • Assess business opportunities


Agenda part 2

Source: J. Holdren, KSG, Harvard University


Potential climate change cost

Potential Climate Change Cost


Threats to the insurance industry

Threats to the Insurance Industry

  • Liquidity Risks

  • Investment Portfolio Risks


Exposure of the insurance industry

Exposure of the Insurance Industry

  • Property and Casualty (P&C) Insurance

    Physical Damage to Property due to increased Frequency and/or Severityrelating to:

    • Flooding – as a result of increased precipitation, rise in sea level and change of weather patterns;

    • Storms – as a result of change in ocean currents/weather patterns

    • Compounding loss effect – as a result of increasing population, infrastructure density, increase in property value, and event characteristics


Exposure of the insurance industry1

Naturalcatastrophes

11 September loss(liability and life)

Exposure of the Insurance Industry

in billion US$, 2001 prices. Source: Swiss Re sigma

2001 11 Sept

  • Upward trend expected to continue:

  • higher insurance penetration

  • growing values

  • value concentration in coastal areas

  • changing hazard cycles and trends, e.g. natural & man-made climate change

60

1992 Hurricane Andrew

1999 Storms Lothar/Martin

50

Total Estimated Loss: US$38 to 50B, incl. third party liability

1994 Northridge Earthquake

40

30

20

10

0

1970

1975

1980

1985

1990

1995

2000

Man-made catastrophes

11Septemberloss(property and business interruption)

Worldwide economic losses due to natural disasters appear to be doubling every 10 years and next decade will reach US$150B

  • Source UNEP Financial Initiatives Climate Working Group Report 2002


The reinsurers speak

The Reinsurers Speak …

Relating to P&C exposure, Munich Re reported that natural disasters caused US$55B in damage in 2002, primarily related to weather-induced property damages across France, Austria, Poland and Italy.

Percentage Distribution Worldwide

Source: http://www.munichre.com/pdf/natcat_natural_catastrophes_2002_e.pdf


Exposure of the insurance industry2

Exposure of the Insurance Industry

2. Health and Life Insurance

Increased risk to human health as a result of

weather/climate patterns:

  • Thermal Stress

  • Natural Disasters

  • Vector-borne Diseases (see next slide)

  • Mortality Rates


Exposure of the insurance industry3

Exposure of the Insurance Industry

  • Other Exposure

  • As a result of change in frequency and severity of events

  • due to climate change, unpredictability of loss exposure

  • relating to the following exposures:

    • Business Interruption

    • Agro/crop loss

    • Existing CAT coverage

    • Weather derivatives

    • Project finance

    • Directors & Officers (D&O)

    • Errors & Omission (E&O)

    • Technology relating to carbon mitigation and associated technologies


In summary

In Summary

“It is estimated that US$2.7 trillion of the $10 trillion U.S. economy is susceptible to weather-related loss of revenue, meaning that an enormous number of companies have "off balance sheet" risks related to climate”

John Dutton, Dean Emeritus

Penn State's College of Earth and Mineral Sciences

Of this amount…

the exposure for the global insurance industry is approximately US$800 billion to US$1 trillion, a significant Liquidity Risk!


Agenda part 2

Can there be any other potential

threats to the insurance industry…?

You betcha!


Yes and they might be big

Yes, … and they might be big!

Do you recall Dean Dutton’s statement?

“It is estimated that US$2.7 trillion of the $10 trillion U.S. economy is susceptible to weather-related loss of revenue, meaning that an

enormous number of companies have "off balance sheet" risks related to climate”


Threats to the insurance industry1

Threats to the Insurance Industry

  • Liquidity Risks

  • Investment Portfolio Risks


The insurance industry

The Insurance Industry…

  • …is a major investor as well as a Third Party Administrator.

    • U.S. life insurance companies ALONE

      • Have assets in excess of US$ 2.8T

      • Account for 14% of the total assets/reserves of major pension funds and retirement programs

      • Have fiduciary responsibilities as a Third Party Administrator for approx. US$300B in assets under management

    • … and because the above is for U.S. life insurance companies only, that is only the tip of the iceberg


Exposure of the insurance industry4

Exposure of the Insurance Industry

  • 4. Value of Assets

  • Unless, rigorously evaluated from a prospective threat

  • emanating from emission of greenhouse gases (GHG)

  • resulting in climate change, the value of the assets could

  • be impaired due to:

  • Direct but Hidden (Off-Balance Sheet) Carbon Liabilities affecting the market value of the assets’ securities

    • As a result of potential disclosure requirements/regulation of GHG, the carbon exposure of GHG-emitting companies could be as high as 35%, resulting in a financial risk of up to 10% of current market value (Source: Innovest, personal communication, 2003)

    • Extra cost associated with climate change: The water industry could face additional cost of $47B by 2050 and $1T by 2070

    • (Source: J.T. Houghton, Climate Change 2001, Oxford University Press)


Exposure of the insurance industry5

Exposure of the Insurance Industry

  • 4. Value of Assets – Part II

  • Indirect Effects of Climate Change, affecting the market value of the assets’ securities

    • As a result of more complex climate variations and its effects, increase of cost to doing business (COGS), resulting in increase of Assets’ liabilities.

      • Ex 1: Fishing Industry – As a result of current changes, increase COGS to new fishing areas/potential loss of fishing at all.

      • Ex 2: Agriculture/Food – As a result of temperature and precipitation changes, increasing unpredictability of crop yield, resulting in loss of market share

      • Ex 3: Basic high energy consuming Industry (Steel, Chemicals) – As a result of increased energy cost, emanating from the power companies, COGS will increase

    • => Increased COGS will result in Loss in Market Value of Assets


Exposure of the insurance industry6

Exposure of the Insurance Industry

  • 5. Value of Insurance Industry’s Securities

  • The largest and ultimate threat to the Insurance industry and, thus in the value of its own securities is based on a timing issue.

    • In fact the timing issue relating to climate change, if not properly prepared for by the insurance industry at large, may become its death knell.

    • The ultimate threat is the compounding effect of a

  • CONVERGENCE

  • of liquidity (underwriting) exposure

  • AND

  • of investment portfolio exposure


Who is aware of this

Who is Aware of this?

… Insurance Analysts

As a result of larger exposures of the industry in 2001, insurance analyst at Lehman Brothers lowered earning estimates to account for “higher-than normal level of catastrophes”

(FT.com, April 27, 2001)

Can you imagine the reaction when Convergence starts to affect the Industry?


And increasingly the insurance industry

… and Increasingly the Insurance Industry

“The insurance business is first in line to be affected by climate change. It is clear that global warming could bankrupt the industry …”

Franklin Nutter, President

Reinsurance Association of America


Plans for research on insurance

Plans for Research on Insurance

Building on the initial results of the other work of the Center we will prepare a background paper in which we will develop a preliminary taxonomy of the climate-related risks and opportunities that confront the insurance industry, and suggest a preliminary set of decision analytic and other tools that could help the industry to better understand and think about these issues.

In refining this paper we will be assisted by several industry experts including Richard (Rich) Soja and Peter Thompson in Chubb's global property underwriting department in Warren NJ, and Mike Ewbank an energy underwriting specialist in Chubb's Chicago IL office, Howard Kunruther at Wharton, and a number of Daniel Hoffmann's professional contacts.


First expert workshop

First Expert Workshop

We will then convene a small invitational workshop with participants drawn from leading insurance, reinsurance, capital investment and risk assessment firms.

We will use the workshop to revise and refine the taxonomy and define an appropriate set of analytical needs. The result will form the basis of the research agenda for years two and three, during which, in collaboration with several experts from the industry, we will undertake a program of systematic analysis and tool development. With assistance from Paul Fischbeck, this may include work that makes use of real options.


Insurance cont

Insurance…(Cont.)

While much of this work may involve the application of existing analytical methods, given the high, and likely irreducible, levels of some of the relevant uncertainties, it seems probable that there will also be a need for the development of new tools and methods (such as those employed in our previous work on mixed levels of uncertainty and bounding analysis).

However, the specifics should be driven by the needs identified by key actors in the industry.


Examples of possible analysis

Examples of Possible Analysis

How adequate are current efforts to rate the climate-related vulnerabilities for investments by major industrial sector? What could be done to improve such measures?

How soon, and to what extent, will it be possible to know the contribution that climate change makes to weather related losses? (How big would they have to be to be detectable? How does this compare with what we can hope to know?)

What are specific insurance/investment risks in the arctic (shipping in NW passage; structures on permafrost); to NW timber holdings; to power company's asset values?


Examples cont

Examples …(Cont.)

Losses from catastrophic weather events 1950-2000

  • While many in the industry believe that recent escalating weather related losses are driven by climate change, many of the climate data don't support this conclusion.

  • We need to look at:

    • adequacy of risk assessment tools;

    • the way those assessments are being used;

    • risk portfolios.

Atlantic hurricane frequency 1948-2001

Source: IPCC (above); NOAA (below).


Second expert workshop

Second Expert Workshop

  • At the end of year three, with preliminary results in hand, we will convene a second workshop at which we will expose our work to critical review by experts from across the industry, and seek advice on how it should be revised, redirected, and extended.

  • We will communicate our results and seek input and involvement from the expert and lay communities concerned with insurance/investment matters via:

    • •The two workshops described.

    • •Professional and popular publication.

    • •Briefings to relevant government and private-sector decision makers.


Agenda cont

Agenda…(Cont.)

* * * * * Part 2 * * * * *

11:30-11:45Insurance managers

- Daniel Hoffmann and Granger Morgan

11:45-12:00Questions and Discussion

12:00-12:15Forest, fisheries and ecosystem managers in the Pacific Northwest and Western Canada

-Tim McDaniels

12:15-12:30Questions and Discussion

12:30-13:00Lunch

13:00-13:15Arctic-region decision makers

- Hadi Dowlatabadi

13:15-14:00Questions and Discussion


Agenda part 22

Agenda -Part 2

11:25-11:30Overview on Part 2

11:30-11:45Insurance managers

- Daniel Hoffmann and Granger Morgan

11:45-12:00Questions and Discussion

12:00-12:15Forest, fisheries and ecosystem managers in the Pacific Northwest and Western Canada

-Tim McDaniels

12:15-12:30Questions and Discussion

12:30-13:00Lunch


Basic issue

Basic Issue

How to manage ecosystem harvests (forestry, fisheries), and the dual objective of maintaining rich ecosystems and biodiversity, given irreducible uncertainties about climate, and a host of other uncertainties regarding ecological systems, resource productivity, values, markets, and many other important influences?


Context

Context

  • Forestry: how we harvest the eco-productivity of non-agricultural land ecosystems

  • Fisheries: how we harvest aquatic ecosystems

  • Given the scale of harvest systems, these economic harvest flows potentially conflict with ecosystem and biodiversity preservation

  • a constant tradeoff for managers, affected publics, NGOs, concerns about eco-service flows

  • Forest land is more privately owned in WA and Oregon, nearly all public in BC


More context

More context

  • These harvest systems are always subject to massive uncertainties:

    • scientific, social, economic and institutional

  • Management has been, in technical terms, as if uncertainties were minimal ; linked to short term political and economic objectives

  • Growing involvement of civil society advocating stronger preservation orientation, growing emphasis on new institutional structures to address conflicts


Recognizing irreducible uncertainties

Recognizing Irreducible Uncertainties

  • Acknowledging IU about climate means we face issues of uncertainty about biodiversity preservation, and continuity of economic flows in these systems much more directly and likely with much greater potential loss over next century or so.

  • How to design, compare, build broader technical and societal support for management alternatives given this context?


Feedbacks and interrelated effects

Feedbacks and interrelated effects

  • Climate (specifically winter temperature) affects pine beetle infestations

  • Infestations kill trees over huge areas, change land cover, create massive fire hazards, but still allow harvest

  • Will change species mix, age classes

  • Accelerates and then reduces harvests

  • Creates massive ecosystem change in parks


Interrelated effects cont

Interrelated effects (cont.)

  • Glacial runoff will decline (to zero?) in coming decades

  • Effects on habitat at mid-high elevations will be fast and huge

  • Reduced Sp/Su flows in major rivers

  • Columbia River example: changes in storage requirements, fish flows, flood control, fish production could all be substantial

  • These are already enormously contentious, complex decision processes, subject to heavy constraints


Decision analysis challenges

Decision Analysis Challenges

  • Value tradeoffs: biodiversity objectives, economic objectives, flexibility, learning

  • Creating alternatives: characterizing complexity; robust, adaptive approaches; societal learning, across whole domains and regions

  • Decision processes that involve civil society groups, managers and technical specialists


Our basic approach

Our basic approach

  • Model archetypes of management decisions in each domain

    • Influence diagrams, consequence tables, expert elicitations, some DA modeling

  • Define robust strategies that characterize different fundamental approaches and illustrate consequences

  • Foster a greater emphasis on learning and adaptation as a generic response to uncertainty

  • Engage managers, experts and civil society groups in comparison, discussion of strategies


Information needed from part 1

Information Needed From Part 1

  • Limits on confidence regarding what will be known about the rate of and extent of climate change over next 100 years for PNW and BC

  • Implications for extreme weather events, average temperature, rainfall

  • This will be input to mental model characterizations of experts regarding the implications of these uncertainties for particular kinds of resource management decisions


Values as crucial input

Values as crucial input

  • We will use value-structuring methods to clarify what matters for important resource management decisions, in the views of a range of interested parties

  • We can use the values to develop new, more widely supported strategies

  • Values define information needed for assessment, evaluation


Information needed to foster more adaptive resource management decisions

Information needed to foster more adaptive resource management decisions

  • For a given kind of decision (say, forestry response to pest infestations)

  • When, where, how are decisions made now?

  • Time scale of information collection, feedback, revising decisions, for key variables

  • Role of analysis, discourse in current processes

  • Incentives, penalties for adaptive approaches

  • Institutional advantages and obstacles

  • Fostering better decision processes


Adaptive management and decision processes

Adaptive Management and Decision Processes

  • We have worked on ways to improve stakeholder decision processes for AM

    • McDaniels and Gregory, Learning as an objective in structured risk management decision processes, ES&T, forthcoming.

  • We are conducting a major project to design an AM plan for salmon aquaculture in BC, involving all stakeholders


Layers of decisions

Layers of Decisions

  • Resource management decisions are often viewed on a site basis (for salmon fisheries, on a “opening” basis)

  • The relationship between the narrowest level of decisions and broader decisions (say, at the area or regional level) is only starting to be explored in terms of approaches to management and regulation (McDaniels and Dowlatabadi, 2004)

  • These layers of management decisions will be an important issue in design of adaptive strategies


Property rights and first nations

Property Rights and First Nations

  • In Canada, First Nations (native people) have been granted quasi property rights to be consulted about and share in benefits of resource harvests. In US, rights are more limited in some contexts, greater in others

  • We can directly address issues of native involvement in fisheries decisions and IU due to our work with the BCAFC


Involving managers ngos and communities

Involving Managers, NGOs and Communities

  • We will establish an advisory group from Washington and BC for this specific component

  • Its purposes will be:

    • Advise on issues of scope and emphasis

    • Help provide access to technical experts for mental models work, understanding key decisions

    • Provide advice on key tradeoffs and strategy design from various perspectives

    • Provide contacts for mechanisms to communicate our findings to interested parties


Synthesis workshops

Synthesis Workshops

  • We plan to hold decision synthesis workshops in the final years of the project involving a wide range of stakeholders

  • Their purpose will be to characterize the results of our work, in terms of its design, process, findings, and the management strategies, potential consequences and tradeoffs

  • We will seek preferences for alternatives, feedback on the issues and management practices involved and the chance to communicate broadly


Agenda cont1

Agenda…(Cont.)

* * * * * Part 2 * * * * *

11:30-11:45Insurance managers

- Daniel Hoffmann and Granger Morgan

11:45-12:00Questions and Discussion

12:00-12:15Forest, fisheries and ecosystem managers in the Pacific Northwest and Western Canada

-Tim McDaniels

12:15-12:30Questions and Discussion

12:30-13:00Lunch

13:00-13:15Arctic-region decision makers

- Hadi Dowlatabadi

13:15-14:00Questions and Discussion


The arctic region

The Arctic Region

The challenge of reconciling rapidly evolving environmental and social conditions with management paradigms that emphasize restoration of “the natural state”


Overview

Overview

  • NADW is a key factor in determination of atmospheric and oceanic fluxes and sea-ice cover in the circumpolar region.

  • These have defined:

    • the ecology;

    • the flow and fate of pollutants in the region, and;

    • The opportunities for resource exploitation.

  • The local decision-makers have two classes of irreducible uncertainties to cope with:

    • The gross uncertainties in evolution of the NADW and its impacts on the flows that shape the arctic environment.

    • The higher order uncertainties in interactions that these will precipitated within and across social and environmental processes.


Nunavut government objectives

Nunavut Government objectives

  • Managing environmental conditions and biodiversity through good science and Inuit Qaujimanituqangit [i.e. Traditional Ecological Knowledge.]

  • Building Healthy Communities.

  • Ensuring the wise use of resources in a manner that will protect and enhance the environment now and for future generations.

  • Developing and supporting sustainable economies.

    • Provide the support needed for people to pursue sustainable livelihoods both in the traditional and wage economy.


Ocean currents

Ocean Currents

Based on: Macdonald, R.W. and J.M. Bewers, 1996. Contaminants in the arctic marine environment: priorities for protection. ICES J. mar. Sci. 53: 537-563.


Air mass flows

Air Mass Flows

Based on: mean air mass position: Li, S.M., R.W. Talbot, L.A. Barrie, R.C. Harriss, C.I. Davidson and J.-L. Jaffrezo, 1993. Seasonal and geographical variations of methane sulphanic acid in the Arctic troposphere. Atmos. Environ. 27A: 3011-3024.


Nox emissions

NOx Emissions

Based on: Benkovitz, C.M., T.M. Schultz, J.M. Pacyna, L. Tarrason, J. Dignon, E.C. Voldner, P.A. Spiro, A.L. Jernnifer and T.E. Graedel, 1995. Gridded inventories of anthropogenic emissions of sulfur and nitrogen. J. geophys. Res. 101: 29239.


Pops in the environment

POPs in the Environment

POPs are found in all compartments of the Arctic environment. The figure shows how these are partitioned in the bio-geo-chemical system and where bioaccumulation leads to human health.


Ice cover

IceCover

Comparison of the averages of Arctic sea ice for the month of Sept. from 1973-1976 (left) to the averages for the month of Sept. from 1999-2002 (right).

Source: NASA 2003.


Oil gas

Oil & Gas

Source: AMAP 1998. AMAP Assessment Report: Arctic Pollution Issues. Arctic Monitoring and Assessment Programme (AMAP.


Ethnic profiles

EthnicProfiles

Source: AMAP 1998. AMAP Assessment Report: Arctic Pollution Issues.


Issues

Issues

  • Environmental change

    • Climate change, pollution flow and fate

  • Economic viability

    • Biological resources, mineral resources and new employment opportunities.

  • Cultural identity

    • Traditional Ecological Knowledge, population movements

  • Politics

    • Governance, International relations

  • Health

    • Traditional activity patterns and diet, desk jobs and imported foods

  • Disasters and their management


A long history of seeking to establish sustainable communities

Nunavut

A Long History of Seeking to Establish Sustainable Communities

Yukon & Alaska


Agenda part 2

Configuration of Communities = interaction of (drivers, local conditions, constraints) over time

Drivers

Local Conditions

Constraints

Food

Access to…

Limited resources

+

Cultural discord

Religion

+

Distant, unstable markets

Commercial trade

+

Economic dependence

Non-renewable resource extraction

+

Human capacity

+

Opportunities for diversification

Military

Scientific research


Agenda part 2

Food

Access to…

Limited resources

+

Cultural discord

Religion

+

Distant, unstable markets

Commercial trade

+

Economic dependence

Non-renewable resource extraction

+

Human capacity

+

Opportunities for diversification

Military

Scientific research

Example of unknowns: Impact of climate change on drivers & constraints

Drivers

Local Conditions

Constraints

Climate Change


Proposed research

Proposed Research

  • Applied:

    • Developing indicators of the: vitality and persistence of Arctic communities

    • Assessing the importance of natural and introduced attractors in the long-term prosperity of communities.

    • Helping local authorities design and implement adaptive management strategies that permit more rapid learning and response across Arctic communities. E.g.:

      • Support for traditional economy

      • Support for infrastructure development and wage economy

  • Theoretical:

    • Characterizing use by dates for knowledge (modern and traditional).

    • Developing an algorithm for calculation of high-order interactions without enumeration.


Outreach and community involvement

Outreach and community involvement

  • We will seek involvement from the expert and lay communities concerned with arctic development via:

    • •Local research institutions:

      • Nunavut Research Institute

      • Canada Climate Impact Adaptations Research Network (C-CAIRN) North

      • Canadian Polar Commission

      • DewLine to SeaLane project (MCRI proposal with Arctic Institute of North America).

    • •and partner communities:

      • Pangnirtung

      • Cambridge Bay

      • Bathurst Inlet


Agenda part 2 cont

Agenda - Part 2…(Cont.)

13:00-13:15Arctic-region decision makers

- Hadi Dowlatabadi

13:15-14:00Questions and Discussion

14:00-14:20Electric utility managers facing capital investment decisions about generation and 3P versus 4P

- Paul Fischbeck and Jay Apt

14:20-14:35Questions and Discussion

14:35-15:00Break/Executive Session


Agenda part 2 cont1

Agenda - Part 2…(Cont.)

13:00-13:15Arctic-region decision makers

- Hadi Dowlatabadi

13:15-14:00Questions and Discussion

14:00-14:20Electric utility managers facing capital investment decisions about generation and 3P versus 4P

- Paul Fischbeck and Jay Apt

14:20-14:35Questions and Discussion

14:35-15:00Break/Executive Session


Why electric power

Why Electric Power?

  • $250 billion annual sales

    • Larger than telecom, computers, s/w, autos

    • $3 trillion physical assets

    • 4,700 generation units

    • Over 3,000 Utilities in the US

  • Enormous economic leverage

    • August blackout: $6 billion

  • Enormous uncertainty in billion dollar decisions from incorporation of externalities


Power plants

Power Plants

> 3000 MW2,000-3,000 MW1,000-2,000 MW450-1,000 MW

< 450 MW

DC

.

Voltage

765kV

Power Plants

Beaver Valley


Power generation investments

US Net Generation

15 new plants per year

Power Generation Investments

  • Large capital investments (~$750 M for 1 unit)

    • Once committed, often expensive to modify

    • Long lifetime: 50 years +

    • Very large proportion of electricity cost (~60%)

  • Critical factors

    • Systems of different plants

    • Environmental regulations

    • Power market structure

    • Uncertain financing

    • Technology breakthroughs


Indirect influence of climate change

Indirect Influence of Climate Change

Regulations

Perception of

change

Changes in

climate

Valuing

externalities

Emissions control

& plant technology

Demand for

power

Cost of power

Power market

structure

Capital investment

in power generation


Amplifiers of uncertainty

Amplifiers of Uncertainty

  • Perception of climate change

    • Influenced by scientific understanding

    • Complex combinations of stakeholders

    • International, national, and regional pressures

    • Conflicting goals

      • “Precautionary behavior and future generations” or “Job creation”

  • Regulations

    • Political solutions to environmental problems

    • Large uncertainties in predicting future regulations

    • Not necessarily stable

      • Criteria for upgrading coal power plants without adding emission controls changes with administration


Agenda part 2

CO2

Regulatory Uncertainty:

Timeline of Power Plant Emission Regulation

emissions rate

(lb./mmBtu)

State and Local smoke control laws, Federal research

1977 CAAA

1990 CAAA

1970 CAAA

NOX

Acid Rain Group 2

NSPS

OTC NOX Budget

Hg

A. R. Group 1

Acid Rain

BACT/LAER

RACT

SO2

NOX SIP CALL

BACT/LAER

NSPS

Typical uncontrolled emissions rates

NSPS

MACT

1990

1965

1970

1975

1980

1985

1995

2000

2005

2010


The future is not clear

Baseline (2002)

40

Sweeney (2007)

30

Jeffords (2007)

Waxman (2007)

20

Bush (2018)

10

0

SO2 (M tons)

NOx (M tons)

Hg (tons)

The Future is Not Clear

Kerry 2008?

Note: EPA may have authority and intent to impose Jeffords-like limits, but may have to use rigid command-and-control policies to do so.

Sources: EPA, White House


Traditional 3p emissions control technologies

Traditional 3P Emissions Control Technologies

  • SO2

    • Fuel switch (away from high sulfur coal)

    • Flue gas desulfurization (several different kinds)

  • NOX

    • Combustion: LNB, OFA, Lean Burn

    • Post-combustion: SNCR, SCR

  • Mercury (Hg)

    • Fuel switching (coal) and coal cleaning limited

    • Traditional technologies have uncertain effects

      • FF, FGD, and SCR are effective at removing various forms of Hg

    • Hg-specific control technologies

      • Sorbent injection and capture.

      • FGD enhancements (SCR+FGD ?)

    • Final disposal of Hg-containing ash or sorbent

      Carnegie Mellon’s Center for Energy and Environmental Studies (CEES) has developed relevant performance and cost models (ICEM).


Utility managers and co 2

Utility Managers and CO2

  • Granger Morgan asked two audiences of utility executives, “How many do not believe the US will have significant carbon regulation by 2020?” Only one hand went up at the 2002 EPRI workshop and four at a 250-person meeting at Alliant Energy.

    • EPRI’s Board then charged EPRI with developing a new strategic plan related to climate change.

  • The CEOs of Cinergy, Excelon, and Alliant all are on record as believing carbon caps are inevitable. They do not know how to approach investment with this uncertainty.


Co 2 control technologies

CO2 “Control” Technologies

  • Conservation, efficiency and renewables

    • Traditional emission controls reduce efficiency

  • Low-carbon fossil fuels (e.g., natural gas)

    • What price? Sufficient? Imports?

  • Carbon ‘sinks’

    • Sufficient? How permanent?

  • Carbon capture and sequestration (CCS)

    • What price? How acceptable?

  • Geo-engineering

    • How feasible? How acceptable?


The big questions about 3p 4p

The Big Questions About 3P/4P

  • What are effects of timing, level, and forms of regulation?

  • How to balance costs and benefits?

  • How to induce sufficient technological innovation to meet the goals at lowest social dislocation?

  • How to keep the existing, coal-fired power plants available to produce low-cost power?

  • What sort of power plants (using what sort of fuels) to invest in for the future?

Bottomline: Uncertainty about future regulations can have

measurable costs for power generation owners/operators


Agenda part 2

Risk

  • Risk is the set of triplets: R = {(si, pi, xi)}

    • si What can happen?

    • pi How likely is it to happen?

    • xi If it does happen, what are the consequences?

  • For short-term decisions, all three can be assessed with confidence.

  • For long-term decisions, confidence that the set of scenarios is exhaustive disappears.

  • But, it is still possible to make predictions about the distribution of consequences.

    • Limiting factors caused by physical/economic properties

    • Long-term averaging because of mean-regressing processes


Scenarios in power generation modeling

Scenarios in Power Generation Modeling

  • Scenarios are the typical way that future uncertainties are modeled out to 25 or 50 years

    • A set of deterministic forecasts (5-10) is created to span the variable space

    • Solutions for each scenario are determined

    • Robustness claims are inferred

  • Limitations

    • Are the scenarios a representative set?

    • Are the scenarios equally likely?

    • How much uncertainty is there within each scenario?

    • How can they be used to support decisions?


Industry typically makes strategic decisions via scenarios

Industry Typically Makes Strategic Decisions via Scenarios

Specify a few futures, with deterministic values for fuel, NOx price, interest rate, etc.

With full recognition of the underlying uncertainties, the decision surface can be understood.


Two research questions

Two Research Questions

  • How will different climate change estimates and their associated uncertainties influence perceptions and in turn, regulations?

  • Given the uncertainty of future regulations, what is the impact on decision making for power generation assets?


Evolving regulations and standards

Evolving Regulations and Standards

  • Database of approximately 250 regulations over 40 years dealing with transportation fuels

  • Research conducted in the Center for the Study and Improvement of Regulation (CSIR) by David Stikkers

  • Evolution of standards over time

    • Within a regulation (between proposed to final)

    • Between regulations (challenged, revised, updated/follow-on)

    • Initiating/motivating events

    • Influence of stakeholders

    • Impact of uncertainty

  • Preliminary stringency results

    • Reduced during regulation making

    • Increased between regulations

    • Varies with amount of uncertainty

    • Decreases lead to challenges


Important questions

Important Questions

  • As climate change predictions evolve, what happens to the ensuing regulations?

  • What combination of “evidence” would lead to precautionary regulations?

    • Reject guaranteed short-term gains to prevent unlikely long-term losses

    • Related to other ongoing studies

  • What type of climate change predictions would cause a tightening/relaxation of regulations?

    • Leaded gasoline (it’s worst than previous thought)

    • MTBE (requirement, ultimate need for, clean-up)

  • Can the same set of predictions lead to very different regulations?

    • Influence of other factors (election results)

  • How is this uncertainty modeled?

  • How are investment decisions made given this uncertainty


Expert elicitation protocol

Expert Elicitation Protocol

  • Experts

    • Utility executives

    • Regulators

  • Conditional on the results from Part 1 (given a climate change forecast), quantify the distributions of the resulting regulations

    • Timing (immediate to delayed)

    • Stringency (none to high)

    • Technology (performance-based to prescriptive)

  • Protocol based on Morgan and Keith

    • Capturing uncertainties

    • Use of scenarios to expand thinking

  • Relying on significant existing contacts in CEIC and CSIR


Valuing generation assets given uncertainty

Valuing Generation Assets Given Uncertainty

  • Different levels of analysis are possible

    • Deterministic: Suppose you know everything

    • Game theory: Multiple decision makers

    • Monte Carlo: Adding uncertainties

    • Portfolio: Assets cannot be valued in isolation

    • Real options: Determining the value of creating future decisions

  • Each provides some level of insight, but without a system-level framing that includes uncertainty, analyses can lead to valuation errors


Deterministic analysis optimal configuration by scenario

Deterministic Analysis:Optimal Configuration by Scenario

  • Scenarios well defined (allowance and fuel costs, caps)

  • Lists of possible control configurations for each plant

  • Find the configuration that works best with a scenario


Dominant strategy regret table

Dominant Strategy Regret Table

Going with the dominant optimal configuration

for each plant will provide relatively good results

in 4 out of 7 scenarios


Appreciating the importance of uncertainty through sensitivity

Appreciating the Importance of Uncertainty through Sensitivity

One unit under one scenario

Practical outreach: this convinced the utility that adding

uncertainty to scenario analysis was both do-able and important!


Adding the uncertainty

Adding the Uncertainty

  • Missing key pieces of knowledge.

    • Which pollutants will be controlled?

    • When will the controls be required?

    • At what level will the limits be set?

    • What type of regulatory instruments will be used?

  • Plant owners cannot wait for all uncertainty to be resolved before making investment decisions.

  • A strategy that is optimal under one regulatory scenario could be very expensive under others.

    • Lack of regulatory knowledge can be expensive.

    • Improving knowledge about future regulations can have economic savings for the plant operator and the industry.

  • How robust are certain choices?

    • May be being wrong doesn’t cost that much.


Multi period decision model

Multi-period Decision Model

  • Scenarios and belief in them evolve over time.

    • Even as some uncertainty is resolved, new questions arise

  • It takes time to install a new technology.

  • Belief about future regulations evolves in different ways

    • Informed/Uninformed/Mistaken

  • Decision maker has to decide when to take action.

  • Decision is dependent on:

    • Belief in the likelihood of the various scenarios

    • Scenario-specific values (reductions, allowance costs, fuel prices)

    • Configuration parameters (capital costs, heat rate, O&M)

  • If the decision maker waits until “correct” scenario is revealed, then benefits are delayed.


Optimal configurations

Optimal Configurations

Given a final “correct” scenario and a knowledge evolution,

what configuration will minimize expected NPV costs?

Knowledge evolution makes a difference.

With less informed forecasts of the future,

unnecessary equipment is installed and/or timing is off.


Portfolio analysis

Portfolio Analysis

  • The value of generation assets vary based on what’s happening in the market

    • Changes in fuel prices/demand

    • Specifics of regulations

    • Location on the grid

  • The value of some plants would change in very similar ways while others would not

    • A sulfur regulation would negatively affect the value of a coal plant and positively affect the value of a gas plant

  • The fact that plant values are not perfectly correlated allows investors to reduce their risk by using techniques from economic portfolio theory

  • We have developed techniques for incorporating the complexity of the power grid and distributions of future key factors to display power generation assets in a “risk-return” space.


Dmuu and portfolios

DMUU and Portfolios

  • By combining assets, investments on the “efficient frontier” can be found

  • This can be done at generation-technology scale or an individual plant scale

  • The value of adding an asset varies based on what is in the portfolio


Effects of climate regulatory uncertainty

Return

Variance

Effects of Climate/regulatory Uncertainty

  • If, because of climate/regulatory uncertainty, we don’t know precisely the expected future return and standard deviation of an asset, then it follows that the efficient frontier must actually be a distribution of frontiers and there is, similarly, a distribution of optimal portfolios

  • What is the impact on portfolio value?


The environmental frontier portfolio optimization and 3p co 2

The “Environmental Frontier”Portfolio Optimization and 3P+CO2

  • Until now, the criteria have been exclusively finance-oriented

  • However, portfolios can be constructed to satisfy any number of criteria

  • The Regulator’s Perspective: Emissions in the objective function

    • Minimize emissions such that risk and return are within acceptable parameters

  • The Firm’s Perspective: Emissions in the constraints

    • Maximize Sharpe ratio such that emissions do not exceed a certain level

  • The Consumer’s Perspective

    • Minimize total expenditures such that reserve margin levels are sufficient to prevent service interruptions


Trading credits and expanding the efficient frontier

Trading Credits and Expanding the Efficient Frontier

  • In the basic model, all assets are power plants

  • Suppose new assets – emissions credits – are introduced

  • The introduction of these assets into the feasible set Pareto-improves market participants

  • In our model, this can be seen directly by noting that the efficient environmental frontier expands “northwest”

    • More efficient combinations of assets are possible

    • On a regional level, the dollar size of the Pareto gain can be quantified


Initial center tasks

Initial Center Tasks

  • Develop a protocol for assessing from experts the impact of climate uncertainty on future regulations

    • Will be directly tied to results from Part 1

    • Will allow investigation of the effects of improved understanding (reduce uncertainty) of climate uncertainty

  • Develop portfolio-level models that will permit an economic analysis of climate-induced regulatory uncertainty.

    • Include probability distribution functions for generation plant parameters, economic dispatch, and non-deterministic frontier

  • With this framework

    • Quantify the cost of regulatory uncertainty and regulatory predictability

    • Evaluate risk-mitigation programs

  • Use feedback from real-world decision makers to develop decision support tools.


Outreach

Outreach

  • We will communicate our results and seek input and involvement from the electric power community via:

    • Annual presentations to the EPRI RAC.

    • Annual reports to the CEIC and CSIR advisory boards.

    • Using CEIC and CSIR contacts, provide detailed briefings and research collaborations with individual utilities.

    • Periodic briefings to PUC commissioners via the EPRI Advisory Board.

    • Presentations to NGOs (e.g. CECA), political leaders, FERC.

  • Underlying structure of the research is directly relevant for other large-scale industries that would be affected by climate-related regulations (e.g., petro-chemical and automotive manufacturers).

    • Using CSIR contacts, provide briefing to other industries


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