Exploring low-carbon futures: A web service approach to linking diverse climate-energy-economy models

© 2019 by the authors. The use of simulation models is essential when exploring transitions to low-carbon futures and climate change mitigation and adaptation policies. There are many models developed to understand socio-environmental processes and interactions, and analyze alternative scenarios, but hardly one single model can serve all the needs. There is much expectation in climate-energy research that constructing new purposeful models out of existing models used as building blocks can meet particular needs of research and policy analysis. Integration of existing models, however, implies sophisticated coordination of inputs and outputs across different scales, definitions, data and software. This paper presents an online integration platform which links various independent models to enhance their scope and functionality. We illustrate the functionality of this web platform using several simulation models developed as standalone tools for analyzing energy, climate and economy dynamics. The models differ in levels of complexity, assumptions, modeling paradigms and programming languages, and operate at different temporal and spatial scales, from individual to global. To illustrate the integration process and the internal details of our integration framework we link an Integrated Assessment Model (GCAM), a Computable General Equilibrium model (EXIOMOD), and an Agent Based Model (BENCH). This toolkit is generic for similar integrated modeling studies. It still requires extensive pre-integration assessment to identify the ‘appropriate’ models and links between them. After that, using the web service approach we can streamline module coupling, enabling interoperability between different systems and providing open access to information for a wider community of users

Purinergic signalling links mechanical breath profile and alveolar mechanics with the pro-inflammatory innate immune response causing ventilation-induced lung injury

Severe pulmonary infection or vigorous cyclic deformation of the alveolar epithelial type I (AT I) cells by mechanical ventilation leads to massive extracellular ATP release. High levels of extracellular ATP saturate the ATP hydrolysis enzymes CD39 and CD73 resulting in persistent high ATP levels despite the conversion to adenosine. Above a certain level, extracellular ATP molecules act as danger-associated molecular patterns (DAMPs) and activate the pro-inflammatory response of the innate immunity through purinergic receptors on the surface of the immune cells. This results in lung tissue inflammation, capillary leakage, interstitial and alveolar oedema and lung injury reducing the production of surfactant by the damaged AT II cells and deactivating the surfactant function by the concomitant extravasated serum proteins through capillary leakage followed by a substantial increase in alveolar surface tension and alveolar collapse. The resulting inhomogeneous ventilation of the lungs is an important mechanism in the development of ventilation-induced lung injury. The high levels of extracellular ATP and the upregulation of ecto-enzymes and soluble enzymes that hydrolyse ATP to adenosine (CD39 and CD73) increase the extracellular adenosine levels that inhibit the innate and adaptive immune responses rendering the host susceptible to infection by invading microorganisms. Moreover, high levels of extracellular adenosine increase the expression, the production and the activation of pro-fibrotic proteins (such as TGF-β, α-SMA, etc.) followed by the establishment of lung fibrosis

An overview of the model integration process: From pre-integration assessment to testing

© 2016 Elsevier Ltd Integration of models requires linking models which can be developed using different tools, methodologies, and assumptions. We performed a literature review with the aim of improving our understanding of model integration process, and also presenting better strategies for building integrated modeling systems. We identified five different phases to characterize integration process: pre-integration assessment, preparation of models for integration, orchestration of models during simulation, data interoperability, and testing. Commonly, there is little reuse of existing frameworks beyond the development teams and not much sharing of science components across frameworks. We believe this must change to enable researchers and assessors to form complex workflows that leverage the current environmental science available. In this paper, we characterize the model integration process and compare integration practices of different groups. We highlight key strategies, features, standards, and practices that can be employed by developers to increase reuse and interoperability of science software components and systems

Designing the Distributed Model Integration Framework – DMIF

© 2017 Elsevier Ltd We describe and discuss the design and prototype of the Distributed Model Integration Framework (DMIF) that links models deployed on different hardware and software platforms. We used distributed computing and service-oriented development approaches to address the different aspects of interoperability. Reusable web service wrappers were developed for technical interoperability models created in NetLogo and GAMS modeling languages. We investigated automated semantic mapping of text-based input-output data and attribute names of components using word overlap semantic matching algorithms and using an openly available lexical database. We also incorporated automated unit conversion in semantic mediation by using openly available ontologies. DMIF helps to avoid significant amount of reinvention by framework developers, and opens up the modeling process for many stakeholders who are not prepared to deal with the technical difficulties associated with installing, configuring, and running various models. As a proof of concept, we implemented our design to integrate several climate-energy-economy models