“Emission game”: some applications of the theory of games to the problem of CO2 emission

If there are no doubts that we must reduce the total emission of carbon dioxide, then the problem of how much different countries should be allowed to contribute to this amount remains a serious one. We suggest this problem to be considered as a non-antagonistic game (in Germeier's sense). A game of this kind is called an “emission game”. Suppose that there are n independent actors (countries or regions), each of them releasing a certain amount of CO₂ per year (in carbon units) into the atmosphere, and that the emission would be reduced by each actor. Each actor has his own aim: to minimise the loss in the Gross Domestic Product (GDP) caused by the reduction of emissions. On the other hand, taking into account that it is impossible to estimate more or less precisely the impact of the climate change on GDP for each country today, a common strategy will be to reduce the climate change. Since one of the main leading factors in global warming is the greenhouse effect, then the common aim will be to reduce the sum of emissions. This is a typical conflict situation. How to resolve it? We can weigh the “egoistic” and “altruistic” criteria for each actor introducing the so-called “coefficients of egoism”. This coefficient is very large, if the actor uses a very egoistic strategy, and conversely, if the actor is a “super-altruist”, then the corresponding coefficient is very small. Using these coefficients we get the general solution of the game in a form of some Pareto's equilibrium. The solution is stable and efficient.     

Impacts of ocean CO2 disposal on marine life: II. Probabilistic plume exposure model used with a time‐varying dose‐response analysis

A method to evaluate aquatic mortality given a pollutant distribution is presented and applied to several sample low pH plumes representing various ocean CO₂ disposal schemes. The method is an improvement over current analysis because it integrates the mortality due to timevarying exposure to low pH with the probabilistic experiences of passive organisms subject to turbulent lateral diffusion as they pass through the plume. For the examples presented, the plume was discretized laterally into lanes and longitudinally by time steps, and a random walk model accounting for the scaledependent nature of relative diffusion was used to simulate the organism pathways over one time step. From these simulations, the probability that an organism will be in a given lane, , one time step after it starts from an initial lane, , was determined for all combinations of and . These probabilities were used to find the number of organisms following each of the possible pathways, and the mortality to the organisms due to their time varying exposure to low pH was determined by using the toxicity model described in part I of this paper. The integrated method allows the impact of the plume to be described in terms of total organism mortality as well as spatial deficit of organisms.