A semi-empirical dynamic soil acidification model for use in spatially explicit integrated assessment models for Europe

A semi-empirical soil acidification model was developed for use in integrated assessment models on a European scale. The model simulates the time development of base saturation and aluminium concentration using an empirical relationship with pH. An accompanying data set was developed by overlaying European maps of soils, land use, climate and altitude followed by a procedure that aggragates the input data over soil-texture combinations in each EMEP 150 km x 150 km grid cell. Model tests show that themodel gives results comparable to the SMART model, although it overestimates initial base saturation in some areas with high acid input and simulates a faster recovery from acidification than SMART

Modelling the recovery of acid-sensitive Finnish headwater lakes under present emission reduction agreements

International audienceAbstract: Over the past two decades, substantial reductions in the deposition of acidifying substances (primarily sulphur) have occurred in most parts of Europe and, following recent agreements, this trend is likely to continue. The question arises as to how have sensitive ecosystems reacted, and will react in the future, to these reduced inputs of acidity? In this paper, the SMART dynamic acidification model predicts the possible recovery of 36 acid-sensitive Finnish headwater lakes, for which both catchment soil and water quality measurements were available. The model was calibrated to measurements by adjusting poorly known parameters; it was then used to simulate soil and water chemistry until 2030 under the ?current legislation scenario' resulting from implementing current European emission reduction agreements. Whereas most of the catchment soils show very little change in base saturation, the positive trends in lake ANC and the negative trends in lake sulphate concentrations, observed over the past decade, continue into the future, albeit at a slower pace. The model predicts that, during 2010?30, all lakes will have reached a positive ANC, a pre-requisite for the recovery of fish populations. Keywords: acidification, lake, catchment, recovery, SMART model, Finland</p

Network Externalities and the Dynamics of Markets

The evolution of markets on which network externalities prevail can be expected to differ from "classical markets" where no such externalities exist. We suggest a flexible formal model that describes the dynamics od types of markets. This leads to a stochastic version of the well known replicator dynamics. Based on this approach we analyze the limit behavior of different market types where consumers use stochastic decision rules. We show that market shares converge to the set of equilibria with probability one, where, even under network externalities, several technologies can coexist. On the other hand, even if no network externalities prevail it is possible that only one technology stays in the market. This paper contributes to the work on generalized urn schemes and path dependent processes going on at IIASA

Abatement of Air Pollutants and Cogeneration: Search for an Optimal Solution

In this paper atmospheric diffusion modelling and nonlinear optimization techniques are used for the analysis of minimum cost alternatives of air pollution control strategies. Two cases are considered: a) control of air pollution from a large point source and b) reduction of existing pollution levels in an urban area utilizing the heat cogenerated by a thermal power plant for district heating. As to a) a program has been built to compute the minimum cost function for the chosen abatement techniques (including stack height) under the constraint of keeping the ground level concentration of N pollutants (gaseous or particulates) at specified values. Cost functions for stack height and abatement techniques are input to the program. As an example, results are presented for the control of two different pollutants controlled by two abatement techniques plus stack height. As to b) an interactive program has been developed to identify minimum cost network for heat conveyance necessary to supply a set of residential areas to achieve a given reduction of pollution in the urban area. Results are presented for the city of Vienna

The Rise of Complex Beliefs Dynamics

We prove that complex beliefs dynamics may emerge in linear stochastic models as the outcome of bounded rationality learning. If agents believe in a misspecified law of motion (which is correctly specified at the Rational Expectations Equilibria of the model) and update their beliefs observing the evolving economy, their beliefs can follow in the limit a beliefs cycle which is not a self-fulfilling solution of the model. The stochastic process induced by the learning rule is analyzed by means of an associated ordinary differential equation (ODE). The existence of a uniformly asymptotically stable attractor for the ODE implies the existence of a beliefs attractor, to which the learning process converges. We prove almost sure convergence by assuming that agents employ a projection facility and convergence with positive probability dropping this assumption. The rise of a limit cycle and of even more complex attractors is established in some monetary economics models assuming that agents update their beliefs with the Recursive Ordinary Least Squares and the Least Mean Squares algorithm

Remarks on NonHamiltonian Statistical Mechanics: Lyapunov Exponents and Phase-Space Dimensionality Loss

The dissipation associated with nonequilibrium flow processes is reflected by the formation of strange attractor distributions in phase space. The information dimension of these attractors is less than that of the equilibrium phase space, corresponding to the extreme rarity of nonequilibrium states. Here we take advantage of a simple model for heat conduction to demonstrate that the nonequilibrium dimensionality loss can definitely exceed the number of phase-space dimensions required to thermostat an otherwise Hamiltonian system.Comment: 5 pages, 2 figures, minor typos correcte

Covariant hydrodynamic Lyapunov modes and strong stochasticity threshold in Hamiltonian lattices

We scrutinize the reliability of covariant and Gram-Schmidt Lyapunov vectors for capturing hydrodynamic Lyapunov modes (HLMs) in one-dimensional Hamiltonian lattices. We show that,in contrast with previous claims, HLMs do exist for any energy density, so that strong chaos is not essential for the appearance of genuine (covariant) HLMs. In contrast, Gram-Schmidt Lyapunov vectors lead to misleading results concerning the existence of HLMs in the case of weak chaos.Comment: 4 pages, 4 figures. Accepted for publication in Physical Review

Emergence of order in selection-mutation dynamics

We characterize the time evolution of a d-dimensional probability distribution by the value of its final entropy. If it is near the maximally-possible value we call the evolution mixing, if it is near zero we say it is purifying. The evolution is determined by the simplest non-linear equation and contains a d times d matrix as input. Since we are not interested in a particular evolution but in the general features of evolutions of this type, we take the matrix elements as uniformly-distributed random numbers between zero and some specified upper bound. Computer simulations show how the final entropies are distributed over this field of random numbers. The result is that the distribution crowds at the maximum entropy, if the upper bound is unity. If we restrict the dynamical matrices to certain regions in matrix space, for instance to diagonal or triangular matrices, then the entropy distribution is maximal near zero, and the dynamics typically becomes purifying.Comment: 8 pages, 8 figure