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Comprehensive and reliable information on anthropogenic sources of greenhouse gas emissions is required to track progress towards keeping warming well below 2°C as agreed upon in the Paris Agreement. Here we provide a dataset on anthropogenic GHG emissions 1970-2019 with a broad country and sector coverage. We build the dataset from recent releases from the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with information on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three available bookkeeping models.

These data are part of a data portal that accompanies the special issue ‘Climate change adaptation needs a science of culture,’ published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit: https://doi.org/10.5061/dryad.bnzs7h4h4. This code represents a computational model investigating the dynamics of coupled and decoupled resource use and efficiency gains. It can be used to simulate the effects of exploration-exploitation strategies on efficiency, consumption and sustainability, considering different levels of direct and indirect rebound effects. The model simulates a population of agents who make decisions on whether to explore or exploit a natural resource. These agents become more efficient over time based on their chosen strategy, affecting resource consumption. Different scenarios are considered, including various rebound effects, which influence how efficiency gains impact resource use. The key elements of the model include agents' uncertainty about the efficiency of their actions, the operationalization of efficiency as a reward, and the calculation of resource consumption based on efficiency gains and rebound effects. The model provides insights into how agents' decisions and resource use evolve over time under different conditions. This computational framework offers a valuable tool for exploring the complex dynamics of resource consumption and management in the face of environmental challenges. It can be applied to gain a deeper understanding of the Jevons Paradox and its implications for sustainable resource use. This computational model simulates the dynamics of exploration and exploitation strategies within a population of agents. These agents make decisions on whether to explore new solutions or exploit existing ones, with a focus on maximizing efficiency. The model employs a N-armed bandit problem approach, where agents select actions to maximize efficiency gains. Efficiency is operationalized as a reward, and agents use sample means to estimate expected efficiency. A balance between exploration and exploitation is maintained through a probability-based algorithm. The code also encompasses resource domains, representing different resources and their dynamics, along with computations of resource consumption, existing resources, and sustainability indices. The simulations consider various parameter combinations to examine the model's behavior. Overall, the code serves as a tool for studying the interplay between exploration, exploitation, efficiency, and resource consumption within a population of agents across different scenarios, making it valuable for investigating the effects of rebound effects on resource consumption and sustainability. The simulations run a comprehensive set of parameter combinations to explore the model's behavior thoroughly. # Code from: Efficiency traps beyond the climate crisis: Exploration-exploitation tradeoffs and rebound effects. Python scripts to run the model, as described in: Segovia-Martin J, Creutzig F, Winters J. 2023 Efficiency traps beyond the climate crisis: exploration–exploitation tradeoffs and rebound effects. Phil. Trans. R. Soc. B 378: 20220405. https://doi.org/10.1098/rstb.2022.0405 The code and supplementary materials are all freely accessible at the following link: [https://github.com/School-of-Collective-Intelligence/Jevons-Paradox-and-Cultural-Evolution](https://github.com/School-of-Collective-Intelligence/Jevons-Paradox-and-Cultural-Evolution) The simulator can be accessed via the following links: [https://jevons-collectiveintelligence.pythonanywhere.com/](https://jevons-collectiveintelligence.pythonanywhere.com/) or [https://jsegoviamartin.pythonanywhere.com/](https://jsegoviamartin.pythonanywhere.com/) The DOI of this Dryad repository: [https://doi.org/10.5061/dryad.qjq2bvqnk](https://doi.org/10.5061/dryad.qjq2bvqnk) ##

The present paper tries to address up to what extent corporate social responsibility (CSR) might advance socio-ecological sustainability of the products with a geographical indication (GI), mainly in developing countries. To this end it would be addressed how agricultural firms became financialized in recent decades. It would be then presented how CSR practices have recently emerged to address this issue and whether they have been successful or not. Finally, it would be highlighted the potential of GI certification practices as part of CSR practices that could potentially boost sustainability for agricultural firms in developing countries.

D'ici 2050, l'agriculture devra répondre à une augmentation de la demande alimentaire, due à une augmentation de la population qui devrait atteindre alors les 9 milliards. A l'échelle nationale, cela représente des enjeux de compétitivité et de croissance économique. Par ailleurs, afin d'assurer cette augmentation de la production, il y a deux solutions : augmenter la proportion des terres agricoles au détriment des écosystèmes naturels; et augmenter la productivité agricole. A travers une revue d'articles agronomiques et économiques, nous montrons l'importance de considérer la qualité du sol dans la productivité et la durabilité des exploitations agricoles. Cependant les pratiques agricoles préservant la qualité du sol ne sont pas largement adoptées, ce particulièrement en France. Une analyse économique de ces enjeux permet d'appréhender le processus de décision des agriculteurs, et de déterminer quelles sont les stratégies optimales permettant de répondre à ces enjeux. Nous proposons un modèle de contrôle optimal qui illustre les liens entre les pratiques agricoles et la qualité du sol, quand la qualité du sol est considérée comme un facteur de production endogène. L'intérêt et l'originalité de cet article est d'associer différentes disciplines pour étudier le rôle de la qualité du sol dans la durabilité et la rentabilité des exploitations. Agriculture is facing an expected increase in food production demand, caused by an increased global population of 9 billion people by the middle of this century. At national scale, competitiveness and economic growth issues are at stake. To insure this increase in production, there are two solutions: extend the proportion of agricultural lands at the expense of natural ecosystems; and increase agricultural productivity. Through a review of agronomic and economic articles, we show the importance of considering soil quality in the productivity and sustainability of farms. However, farming practices preserving soil quality are not widely adopted, particularly in France. An economic analysis of these issues provide an understanding of farmers' decision making process, and indicate what the optimal strategies can be to cope with these challenges. We propose an optimal control model that illustrates the links between farming practices and soil quality when soil quality is considered as an endogenous production factor. The interest and originality of this article is to associate different disciplines to investigate the role of soil quality in the sustainability and profitability of farms.

In the proposed paper, data and expertise were collected to provide information and arguments about several issues: about the main criteria of good bread in terms of environmental, nutritional, sensory and sanitary aspects; then, about ways to achieve them in the wheat-to-bread chain, while maintaining affordable prices. Computation for determining the best compromise between the various desired criteria is a challenge, since not all of them are compatible. Several scenarios are explored to highlight tensions between desired criteria, problem formulation and solution analysis such as best- and worst-case scenarios. Hence the approach demonstrates the interest of information systems and computational methods for decision support in agricultural and food policies.

The aim of this work was to gain insight and knowledge with the basic concepts of the Bitcoinnetwork and its relation to energy consumption. Precisely, the ambition of this literature-based research was to identify key determinants of the network ́s energy intensiveness. After an extensive review of the relevant literature on the topic, key principles of Bitcoin ́s electricity consumption were derived.With regards to environmental sustainability concerns, it was found that the network ́sproperties, in theory, allow for improvements of the unit economics of renewable energy production facilities and renewable intensive energy grids. Such applications, however, are dependent on the unforecastable market dynamics of the Bitcoin price.In a contextualization approach it was attempted to categorize the electricity consumption levels of the Bitcoin network based on the services offered with similar but not comparable entities.This approach finds that energy consumption does not provide a conclusive and instructive comparative parameter to determine whether energy consumption levels of the Bitcoin network.The paper concludes with advocating for location dependent policy approaches that encourage the strategic deployment of Bitcoin mining hardware to minimize environmental and economic opportunity cost.

Description of the subject. Extracellular enzymes from filamentous fungi are increasingly used in eco-friendly biotransformation processes. Their relevant technological role and their stability towards extreme process conditions make of them the first sustainable solution for the elaboration of bio-based products from biomass conversion. Objectives. This paper describes the isolation of filamentous fungi from decaying plant material in the region of Meknes (northern central Morocco) and the assessment of their ability to breakdown lignocellulose. The objective is to select performant fungi with enzymatic machinery adapted to local environment and with potential for the breakdown of the regional specific lignocellulosic by-products into potentially high-value molecules. Method. Cereals, decaying wood, olive-pomace and -pulp and their composts were used to isolate lignocellulolytic fungi. One hundred twenty-seven pure strains were isolated and screened at 25 °C on selective media with cellulose or lignin as the sole carbon source. Performant strains were validated for the production of ligno-cellulolytic enzymes and identified using molecular technique. Results. Twenty-eight fungi had mycelial diameter on cellulose ≥ 6 cm and cellulolytic index ≥ 0.9. Twenty-two strains had the same profile on lignin medium. The production of endoglucanase, lignin peroxidase and manganese peroxidase enzymes was confirmed in performant strains using qualitative assay and molecular identification revealed that the best performing fungi were Mucor circinelloides, Mucor racemosus, Penicillium brasilianum, Penicillium crustosum, Paecilomyces sp., Fusarium oxysporum, Fusarium solani, Aspergillus fischeri, Curvularia spicifera, Humicola grisea, Trichoderma atroviride and Cosmospora viridescens. Measurement of ligno-cellulolytic activities revealed that Penicillium and Fusarium strains mainly from wood decay and compost had the best profiles among performing strains. Conclusions. Isolated fungi are high decomposers of biomass and represent a prominent solution to develop green bioprocesses in the region.

Until today, herbicide-tolerant (HT) transgenic crops have been the most widely used type of transgenic crops. In 2008, worldwide, 63% of all agricultural land devoted to transgenic crops involved HT transgenic ones, and the percentage was higher (85%) when the herbicide-tolerant trait was stacked with another. In addition, other HT crops are foreseen within the next five years if we are to believe the "pipeline" of the companies involved along with field trials. However, herbicide-tolerant crops have been criticized, particularly in Europe, because of the type of trait introduced: herbicide tolerance. Indeed, this trait leads the crops to depend on a herbicide (generally glyphosate) instead of freeing them from some pesticides through a better use of their biological capacities and a valorisation of life processes as biotechnology was expected to do. Therefore, how can we explain the widespread use of HT transgenic crops and what are their fallouts? At first the paper presents the extent of surface areas dedicated to these crops and the factors that have led to the development of these herbicide-tolerant crops. Then, the case of glyphosate-tolerant soybeans in the USA is studied in more detail. Its agro-environmental impacts, particularly with regard to trends in the use of herbicides, are analyzed. Thirdly, we address the factors of adoption, economic performance, benefits, and drawbacks of this soybean as well as its prospects. Finally, the conclusion questions the contribution of HT soybean to more sustainable agriculture. IAAE 2009 International Conference