The MESSAGEix Integrated Assessment Model and the ix modeling platform (ixmp)

The MESSAGE Integrated Assessment Model (IAM) developed by IIASA has been a central tool of energy-environment-economy systems analysis in the global scientific and policy arena. It played a major role in the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC); it provided marker scenarios of the Representative Concentration Pathways (RCPs) and the Shared Socio-Economic Pathways (SSPs); and it underpinned the analysis of the Global Energy Assessment (GEA). Alas, to provide relevant analysis for current and future challenges, numerical models of human and earth systems need to support higher spatial and temporal resolution, facilitate integration of data sources and methodologies across disciplines, and become open and transparent regarding the underlying data, methods, and the scientific workflow. In this manuscript, we present the building blocks of a new framework for an integrated assessment modeling platform; the \ecosystem" comprises: i) an open-source GAMS implementation of the MESSAGE energy++ system model integrated with the MACRO economic model; ii) a Java/database backend for version-controlled data management, iii) interfaces for the scientific programming languages Python & R for efficient input data and results processing workflows; and iv) a web-browser-based user interface for model/scenario management and intuitive \drag-and-drop" visualization of results. The framework aims to facilitate the highest level of openness for scientific analysis, bridging the need for transparency with efficient data processing and powerful numerical solvers. The platform is geared towards easy integration of data sources and models across disciplines, spatial scales and temporal disaggregation levels. All tools apply best-practice in collaborative software development, and comprehensive documentation of all building blocks and scripts is generated directly from the GAMS equations and the Java/Python/R source code

Cardiovascular magnetic resonance feature tracking in pigs: a reproducibility and sample size calculation study

Cardiovascular magnetic resonance feature tracking (CMR-FT) is a novel technique for non-invasive assessment of myocardial motion and deformation. Although CMR-FT is standardized in humans, literature on comparative analysis from animal models is scarce. In this study, we measured the reproducibility of global strain under various inotropic states and the sample size needed to test its relative changes in pigs. Ten anesthetized healthy Landrace pigs were investigated. After baseline (BL), two further steps were performed: (I) dobutamine-induced hyper-contractility (Dob) and (II) verapamil-induced hypocontractility (Ver). Global longitudinal (GLS), circumferential (GCS) and radial strain (GRS) were assessed. This study shows a good to excellent inter- and intra-observer reproducibility of CMR-FT in pigs under various inotropic states. The highest inter-observer reproducibility was observed for GLS at both BL (ICC 0.88) and Ver (ICC 0.79). According to the sample size calculation for GLS, a small number of animals could be used for future trials

Estimation of the Global Health Impacts of Air Pollution

Air pollution is increasingly recognized as a significant contributor to global health outcomes. A methodological framework for evaluating the global health related outcomes of outdoor and indoor (household) air pollution is presented and validated for the year 2005. Ambient concentrations of PM2.5 re estimated with a combination of energy and atmospheric models, with detailed representation of urban and rural spatial exposures. Populations dependent on solid fuels are established with household survey data. Health impacts for outdoor and household air pollution are independently calculated using the fractions of disease that can be attributed to ambient air pollution exposure and solid fuel use. Estimated ambient pollution concentrations indicate that more than 80% of the population exceeds the WHO Air Quality Guidelines in 2005. In addition, 3.26 billion people were found to use solid fuel for cooking in three regions of Sub Saharan Africa, South Asia and Pacific Asia in 2005. Outdoor air pollution results in 2.7 million deaths or 23 million DALYs while household air pollution from solid fuel use and related indoor smoke results in 2.1 million deaths or 41.6 million DALYs. The higher morbidity from household air pollution can be attributed to children below the age of five in Sub Saharan Africa and South Asia. The burden of disease from air pollution is found to be significant, thus indicating the importance of policy interventions

Estimation of total collagen volume: a T1 mapping versus histological comparison study in healthy Landrace pigs

Right ventricular biopsy represents the gold standard for the assessment of myocardial fibrosis and collagen content. This invasive technique, however, is accompanied by perioperative complications and poor reproducibility. Extracellular volume (ECV) measured through cardiovascular magnetic resonance (CMR) has emerged as a valid surrogate method to assess fibrosis non-invasively. Nonetheless, ECV provides an overestimation of collagen concentration since it also considers interstitial space. Our study aims to investigate the feasibility of estimating total collagen volume (TCV) through CMR by comparing it with the TCV measured at histology. Seven healthy Landrace pigs were acutely instrumented closed-chest and transported to the MRI facility for measurements. For each protocol, CMR imaging at 3T was acquired. MEDIS software was used to analyze T1 mapping and ECV for both the left ventricular myocardium (LVmyo) and left ventricular septum (LVseptum). ECV was then used to estimate TCVCMR at LVmyo and LVseptum following previously published formulas. Tissues were prepared following an established protocol and stained with picrosirius red to analyze the TCVhisto in LVmyo and LVseptum. TCV measured at LVmyo and LVseptum with both histology (8 ± 5 ml and 7 ± 3 ml, respectively) and T1-Mapping (9 ± 5 ml and 8 ± 6 ml, respectively) did not show any regional differences. TCVhisto and TCVCMR showed a good level of data agreement by Bland–Altman analysis. Estimation of TCV through CMR may be a promising way to non-invasively assess myocardial collagen content and may be useful to track disease progression or treatment response

+1,5° C: Wieviel Treibhausgase dürfen wir noch emittieren? CCCA Fact Sheet #40

Um die globale Erwärmung und somit die Auswirkungen des Klimawandels, wie im Pariser Übereinkommen festgelegt, auf +1,5 °C bzw. unter +2 °C gegenüber dem vorindustriellen Niveau (1850-1900) zu begrenzen muss für die Klimaneutralitätsziele die Gesamtmenge an Treibhausgas (THG)-Emissionen entsprechend beschränkt werden. Unter aktuellen Maßnahmenplänen, ohne zusätzliche Schritte, bewegen wir uns noch in diesem Jahrhundert auf +2,8 °C zu, was deutlich größere Schäden und Verluste zur Folge hätte. Das Factsheet basiert auf der umfangreichen Ausarbeitung in: CCCA (2022): +1,5° C: Wieviel Treibhausgase dürfen wir noch emittieren? Hintergrundpapier zu globalen und nationalen Treibhausgasbudgets. K. Steininger, T. Schinko, H. Rieder, H. Kromp-Kolb, S. Kienberger, G. Kirchengast, C. Michl, I. Schwarzl, S. Lambert. Wien: CCC

Building collaboration in multi-agent systems using reinforcement learning

© Springer Nature Switzerland AG 2018. This paper presents a proof-of concept study for demonstrating the viability of building collaboration among multiple agents through standard Q learning algorithm embedded in particle swarm optimisation. Collaboration is formulated to be achieved among the agents via competition, where the agents are expected to balance their action in such a way that none of them drifts away of the team and none intervene any fellow neighbours territory, either. Particles are devised with Q learning for self training to learn how to act as members of a swarm and how to produce collaborative/collective behaviours. The produced experimental results are supportive to the proposed idea suggesting that a substantive collaboration can be build via proposed learning algorithm

Looking under the hood: A comparison of techno-economic assumptions across national and global integrated assessment models

Integrated assessment models are extensively used in the analysis of climate change mitigation and are informing national decision makers as well as contribute to international scientific assessments. This paper conducts a comprehensive review of techno-economic assumptions in the electricity sector among fifteen different global and national integrated assessment models. Particular focus is given to six major economies in the world: Brazil, China, the EU, India, Japan and the US. The comparison reveals that techno-economic characteristics are quite different across integrated assessment models, both for the base year and future years. It is, however, important to recognize that techno-economic assessments from the literature exhibit an equally large range of parameters as the integrated assessment models reviewed. Beyond numerical differences, the representation of technologies also differs among models, which needs to be taken into account when comparing numerical parameters. While desirable, it seems difficult to fully harmonize techno-economic parameters across a broader range of models due to structural differences in the representation of technology. Therefore, making techno-economic parameters available in the future, together with of the technology representation as well as the exact definitions of the parameters should become the standard approach as it allows an open discussion of appropriate assumptions. © 2019 The Author

The marker quantification of the Shared Socioeconomic Pathway 2: a middle-of-the-road scenario for the 21st century

Studies of global environmental change make extensive use of scenarios to explore how the future can evolve under a consistent set of assumptions. The recently developed Shared Socioeconomic Pathways (SSPs) create a framework for the study of climate-related scenario outcomes. Their five narratives span a wide range of worlds that vary in their challenges for climate change mitigation and adaptation. Here we provide background on the quantification that has been selected to serve as the reference, or ‘marker’, implementation for SSP2. The SSP2 narrative describes a middle-of-the-road development in the mitigation and adaptation challenges space. We explain how the narrative has been translated into quantitative assumptions in the IIASA Integrated Assessment Modelling Framework. We show that our SSP2 marker implementation occupies a central position for key metrics along the mitigation and adaptation challenge dimensions. For many dimensions the SSP2 marker implementation also reflects an extension of the historical experience, particularly in terms of carbon and energy intensity improvements in its baseline. This leads to a steady emissions increase over the 21st century, with projected end-of-century warming nearing 4 °C relative to preindustrial levels. On the other hand, SSP2 also shows that global-mean temperature increase can be limited to below 2 °C, pending stringent climate policies throughout the world. The added value of the SSP2 marker implementation for the wider scientific community is that it can serve as a starting point to further explore integrated solutions for achieving multiple societal objectives in light of the climate adaptation and mitigation challenges that society could face over the 21st century