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- Handling climate change education at universities: an overviewPublication . Filho, Walter Leal; Sima, Mihaela; Sharifi, Ayyoob; Luetz, Johannes M.; Lange Salvia, Amanda; Mifsud, Mark; Olooto, Felicia; Djekic, Ilija; Anholon, Rosley; Rampasso, Izabela Simon; Donkor, Felix Kwabena; Dinis, Maria Alzira Pimenta; Klavins, Maris; Finnveden, Göran; Chari, Martin Munashe; Molthan-Hill, Petra; Mifsud, Alexandra; Sen, Salil K; Lokupitiya, ErandathieBackground Climate change is a problem which is global in nature, and whose effects go across a wide range of disciplines. It is therefore important that this theme is taken into account as part of universities´ teaching and research programs. Methods A three-tiered approach was used, consisting of a bibliometric analysis, an online survey and a set of case studies, which allow a profile to be built, as to how a sample of universities from 45 countries handle climate change as part of their teaching programs. Results This paper reports on a study which aimed at identifying the extent to which matters related to climate change are addressed within the teaching and research practices at universities, with a focus on the training needs of teaching staff. It consists of a bibliometric analysis, combined with an online worldwide survey aimed at ascertaining the degree of involvement from universities in reducing their own carbon footprint, and the ways they offer training provisions on the topic. This is complemented by a set of 12 case studies from universities round the world, illustrating current trends on how universities handle climate change. Apart from reporting on the outcomes of the study, the paper highlights what some universities are doing to handle climate issues, and discusses the implications of the research.. Conclusions The paper lists some items via which universities may better educate and train their students on how to handle the many challenges posed by climate change.
- Climate change mitigation and adaptation in practicePublication . Leal Filho, Walter; Kovaleva, Marina; Dinis, Maria Alzira Pimenta; Luetz, Johannes; Alves, Fátima; Yaffa, Sidat; Nagy, Gustavo J.; Yayeh Ayal, Desalegn; Kalungu, Jokastah; Leal Filho, Walter; Kovaleva, Marina; Dinis, Maria Alzira Pimenta; Luetz, Johannes M.; Alves, Fátima; J. Nagy, Gustavo; Yaffa, Sidat; Yayeh Ayal, Desalegn; Kalungu, JokastahThis book is part of the Climate Change Management Series. It includes the works focusing on climate change policies and technologies that support the implementation of climate change mitigation and adaptation strategies. The included works also discuss methodological approaches and experiences showing how the principles of climate change adaptation may be implemented in practice across various geographical regions. The book includes high-quality, interdisciplinary contributions on the scientific, social, economic, political aspects of climate change mitigation and adaptation solutions which makes it available to a wide audience professionals and practitioners.
- Artificial intelligence and climate change: the potential roles of foundation modelsPublication . Leal Filho, Walter; Kovaleva, Marina; Ng, Artie; Nagy, Gustavo; Luetz, Johannes; Dinis, Maria Alzira PimentaArtificial intelligence (AI) is being developed fast and applied in several areas including education and healthcare with excellent potential for use in fields that require complex analytics, particularly in the case of climate change. Recent developments in AI, such as ChatGPT and OpenAI, machine vision technologies and deep learning, among others, may be deployed in various contexts, including climate change. Of specific interest is the role played by foundation models (FMs), which may help to augment intelligence on climate change and reduce the social risks of adaptation and mitigation initiatives. This article discusses the potential applications of FMs in climate change research and management and illustrates the need for further studies. FMs, built on large unlabelled data sets and enabled by transfer learning, offer versatility in handling complex tasks. Specifically, FMs can aid in climate data analysis, modelling future scenarios, assessing risks, and supporting decision-making processes. Despite their potential, challenges such as data privacy, algorithm bias, and energy consumption require careful consideration. The article emphasizes the importance of interdisciplinary efforts to address these challenges and maximize the positive impact of FMs in mitigation and adaptation. AI, including advanced models like FMs, holds significant promise for addressing climate change challenges.