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The energy intensities of the various industrial sectors differ considerably across countries. This suggests a potential for emissions reductions through improved accessibility to efficient technologies. This paper estimates an upper-bound CO2 emission mitigation potential that could theoretically be achieved by improved access to efficient technologies in industrial sectors. We develop a linear optimization framework that facilitates the exchange of sectoral production technologies based on the World Input-Output Database (WIOD), assuming perfect substitutability of technologies and homogeneity within economic sectors, while ignoring barriers to technological adoption and price driven adjustments. We consider the full global supply chain network and multiple upstream production inputs in addition to energy demand. In contrast to existing literature our framework allows to consider supply chain effects of technology replacements. We use our model to calculate emission reduction potentials for varying levels of access to technology. If best practice technologies were made available globally, CO2 emissions could theoretically be reduced by more than 10 gigatons (Gt). In fact, even second-tier production technologies would create significant global reduction potentials. We decompose sectoral emission reductions to identify contributions by changes in energy intensity, supply chain effects and changes in carbon intensities. Excluding the latter, we find that considering supply chain effects increases total mitigation potentials by 14%. The largest CO2 emission reduction potentials are found for a small set of developing countries.

We present a new strategy for the direct optimization of the values of policy functions. This approach is particularly well suited to model actors with a global perspective on the system and relies heavily on modern mathematical white-box optimization methods. We demonstrate our strategy on two classical models: market growth and World2. Each model is first transformed into an optimization problem by defining how the actor can influence the models’ dynamics and by choosing objective functions to measure improvements. To improve comparability between different runs, we also introduce a comparison measure for possible interventions. We solve the optimization problems, discuss the resulting policies and compare them to the existing results from the literature. In particular, we present a run of the World2 model which significantly improves the published “towards a global equilibrium” run with equal cost of intervention.

Sustainable manufacturing is driven by the insight that the focus on the economic dimension in current businesses and lifestyles has to be broadened to cover all three pillars of sustainability: economic development, social development, and environmental protection.

Existing models of nonrenewable resources assume that sophisticated agents compete with other sophisticated agents. This study instead uses a level-k approach to examine cases where the focal agent is uncertain about the strategy of his opponent or predicts that the opponent will act in a nonsophisticated manner. Level-0 players are randomized uniformly across all possible actions, and level-k players best respond to the action of player k-1. We study a dynamic nonrenewable resource game with a large number of actions. We are able to solve for the level-1 strategy by reducing the averaging problem to an optimization problem against a single action. We show that lower levels of strategic reasoning are close to the Walras and collusive benchmark, whereas higher level strategies converge to the Nash-Hotelling equilibrium. These results are then fitted to experimental data, suggesting that the level of sophistication of participants increased over the course of the experiment.

Worm algorithms have been very successful with the simulation of sigma models with fixed length spins which result from scalar field theories in the limit of infinite quartic coupling lambda. Here we investigate closer their algorithmic efficiency at finite and even vanishing lambda for the one component model in dimensions D = 2, 3, 4., Comment: 10 pages, 2 Figs