Microsoft Word - SustainabilityReport_BCC.doc

of living despite possible cuts in energy usage. See for example the discussion of

greenhouse gas emissions discussed later.

• To improve the security of supplies} and increase energy independence by
  stabilizing and robustifying energy sources to terrorist attacks and natural
  disasters.


• To aim at a more socially equitable distribution} of the benefits of energy
  consumption, and control the socio-political impacts of the current dependence of
  most of the sectors of the economy on oil production.


• To stimulate and encourage the young generations of talented researchers to get
  engaged in sustainability issues.

Regardless of the order in which we prioritize these objectives, a clear sense of
urgency emerges: we must act now, we cannot afford to wait. Energy investments are
highly capital intensive. Both long-term and short-term energy investments incur
significant risks, which can be mitigated using modern (hedging) strategies. How do we
design these instruments, and what are the implications in terms of managing risk?

Strategies

In order to design strategies and balance these goals, the following questions need to be
addressed:

• How can we reduce usage while maintaining and even increasing standards of
  living? How do we quantify externalities and put figures on the impact on quality
  of life?


• How do we transform supplies? By introducing new sources? By better
  managing existing ones? How can that be done with minimal impact on the
  environment?


• How can we optimize efficiency?

Computation is increasingly essential to all aspects of our lives. We are on the cusp
of achieving very significant improvements in the energy consumption of computation in
terms of “millions of instructions per second per watt.” Significant sources of gain will
come from dramatic improvements in the efficiency of standalone computers-- processor
efficiency, wireless radio efficiency, display efficiency, sleep modes, etc.
Another area of potential gain involves the development of entirely new
computational algorithms that have energy minimization as a goal. Since the dawn of
computing, we have analyzed and optimized algorithms for their running time and
memory usage requirements. We have come to understand tradeoffs between these
two -- it is often possible to improve running time at a cost of memory space, and vice
versa. Energy consumption represents a third dimension.

Mathematical Challenges

We now consider the different kinds of new methods and investments that need to be
made in order to enable the development of new mathematics necessary to tackle
issues raised by sustainable energy. Right at the onset, it is important to emphasize that,
while mathematics is the underlying discipline that cuts across theory, modeling,
simulation, understanding and prediction of sustainability issues, across all energy