A robust sequential CO2 emissions strategy based on optimal control of atmospheric CO2 concentrations.

This paper formally introduces the concept of mitigation as a stochastic control problem. This is illustrated by applying a digital state variable feedback control approach known as Non-Minimum State Space (NMSS) control to the problem of specifying carbon emissions to control atmospheric CO2 concentrations in the presence of uncertainty. It is shown that the control approach naturally lends itself to integrating both anticipatory and reflexive mitigation strategies within a single unified framework. The framework explicitly considers the closed-loop nature of climate mitigation, and employs a policy orientated optimisation procedure to specify the properties of this closed-loop system. The product of this exercise is a control law that is suitably conditioned to regulate atmospheric CO2 concentrations through assimilating online information within a 25-year review cycle framework. It is shown that the optimal control law is also robust when faced with significant levels of uncertainty about the functioning of the global carbon cycle