Intertemporal accounting of climate change - Harmonizing economic efficiency and climate stewardship

Continuing a discussion on the intertemporal accounting of climate-change damages initiated by Nordhaus, Heal and Brown in response to the recent demonstration of Hasselmann et al. that standard exponential discounting applied uniformly to all goods and services invariably leads to a `climate catastrophe' in cost-benefit analyses, it is argued that (1) there exists no economically satisfactory alternative to cost-benefit analysis for the determination of optimal climate protection strategies, and (2) it is essential to allow for the different long-term evolution of climate damage costs relative to mitigation costs in determining the optimal cost-benefit solution. A climate catastrophe can be avoided only if it is assumed that climate damage costs increase significantly in the long term relative to mitigation costs. Cost-benefit analysis is regarded here in the generalized sense of optimizing a social welfare function that incorporates all relevant `quality-of-life' factors, including not only consumption and the value of the environment, but also the ethical values of equitable intertemporal and intrasocietal distribution. Thus, economic efficiency and climate stewardship are not regarded as conflicting goals, but as synonyms for a single encompassing economic optimization exercise. The same reasoning applies generally to the problem of sustainable development. To quantify the concept of sustainable development in cost-benefit analyses, the projected time evolution of the future values of natural resources and the environment (judged by the present generation, acting as representative agents of future generations) must be related to the time-evolution of all other relevant quality-of-life factors. Different ethical interpretations of the concept of sustainable development can be readily operationalized by incorporation in a generalized cost-benefit analysis in which the evolution paths of all relevant material and ethical values are explicitly specified

Sensor Deployment for Network-like Environments

This paper considers the problem of optimally deploying omnidirectional sensors, with potentially limited sensing radius, in a network-like environment. This model provides a compact and effective description of complex environments as well as a proper representation of road or river networks. We present a two-step procedure based on a discrete-time gradient ascent algorithm to find a local optimum for this problem. The first step performs a coarse optimization where sensors are allowed to move in the plane, to vary their sensing radius and to make use of a reduced model of the environment called collapsed network. It is made up of a finite discrete set of points, barycenters, produced by collapsing network edges. Sensors can be also clustered to reduce the complexity of this phase. The sensors' positions found in the first step are then projected on the network and used in the second finer optimization, where sensors are constrained to move only on the network. The second step can be performed on-line, in a distributed fashion, by sensors moving in the real environment, and can make use of the full network as well as of the collapsed one. The adoption of a less constrained initial optimization has the merit of reducing the negative impact of the presence of a large number of local optima. The effectiveness of the presented procedure is illustrated by a simulated deployment problem in an airport environment