Inland water level and its dynamics are key components in the global water cycle and land surface hydrology, significantly influencing climate variability and water resource management. Satellite observations, in particular altimetry missions, provide inland water level time series for nearly three decades. Space-based remote sensing is regarded as a cost-effective technique that provides measurements of global coverage and homogeneous accuracy in contrast to in-situ sensors. The advent of Open-Loop Tracking Command (OLTC), and Synthetic Aperture Radar (SAR) mode strengthened the use of altimetry missions for inland water level monitoring. However, it is still very challenging to obtain accurate measurements of water level over narrow rivers and small lakes. This scoping systematic literature review summarizes and disseminates the research findings, highlights major results, and presents the limitations regarding inland water level monitoring from satellite observations between 2018 and 2022. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline and through a double screening process, 48 scientific publications were selected meeting the eligibility criteria. To summarize the achievements of the previous 5 years, we present fundamental statistical results of the publications, such as the annual number of publications, scientific journals, keywords, and study regions per continent and type of inland water body. Also, publications associated with specific satellite missions were analyzed. The findings show that Sentinel-3 is the dominant satellite mission, while the ICESat-2 laser altimetry mission has exhibited a high growth trend. Furthermore, publications including radar altimetry missions were charted based on the retracking algorithms, presenting the novel and improved methods of the last five years. Moreover, this review confirms that there is a lack of research on the collaboration of altimetry data with machine learning techniques.

Recent advances in Earth Observation (EO) placed Citizen Science (CS) in the highest position, declaring their essential provision of information in every discipline that serves the SDGs, and the 2050 climate neutrality targets. However, so far, none of the published literature reviews has investigated the models and tools that assimilate these data sources. Following this gap of knowledge, we synthesised this scoping systematic literature review (SSLR) with a will to cover this limitation and highlight the benefits and the future directions that remain uncovered. Adopting the SSLR guidelines, a double and two-level screening hybrid process found 66 articles to meet the eligibility criteria, presenting methods, where data were fused and evaluated regarding their performance, scalability level and computational efficiency. Subsequent reference is given on EO-data, their corresponding conversions, the citizens’ participation digital tools, and Data Fusion (DF) models that are predominately exploited. Preliminary results showcased a preference in the multispectral satellite sensors, with the microwave sensors to be used as a supplementary data source. Approaches such as the “brute-force approach” and the super-resolution models indicate an effective way to overcome the spatio-temporal gaps and the so far reliance on commercial satellite sensors. Passive crowdsensing observations are foreseen to gain a greater audience as, described in, most cases as a low-cost and easily applicable solution even in the unprecedented COVID-19 pandemic. Immersive platforms and decentralised systems should have a vital role in citizens’ engagement and training process. Reviewing the DF models, the majority of the selected articles followed a data-driven method with the traditional algorithms to still hold significant attention. An exception is revealed in the smaller-scale studies, which showed a preference for deep learning models. Several studies enhanced their methods with the active-, and transfer-learning approaches, constructing a scalable model. In the end, we strongly support that the interaction with citizens is of paramount importance to achieve a climate-neutral Earth.

Online marketplaces enable cooperation between potential stakeholders by supporting offer and demand identification at the secondary raw material markets. The use of marketplaces facilitates communication between supply chain actors operating within the same or different industry sectors and enables detection of ways to close the loop of their products. This research investigated which criteria to use for the circular cooperation matching of companies in the context of a marketplace. These criteria were used for the development of a circular economy (CE) matchmaking framework based on a multi-level approach and relevance scoring between the users. The multi-level approach is based on the following criteria: (i) the compliance with circular economy principles, (ii) the material flows analysis, (iii) the greenhouse gas (GHG) emissions from transport. Based on those aspects a Total Relevance Score (TRS) between the stakeholders is calculated. The Total Relevance Score indicates the possibility for successful circular cooperation between two partners who are willing to close their loops with the best possible match. The logic behind the proposed circular economy matchmaking framework is illustrated by four cases using data collected from companies. Recommendations for further deployment are proposed. The developed framework, by incorporating circular economy principles for the first time within the matching algorithm, provides the opportunity for interested stakeholders for more tailored matching and increases their possibilities of finding a perfect match on the secondary raw materials market in terms of circularity. A similar approach has not yet been reported in the literature. The circular economy matchmaking framework constitutes a theoretical basis of an online marketplace to be developed.

Background: Industrial symbiosis (IS) primarily involves interfirm utilization of industrial residual resources. An important factor determining the success of IS is the identification and matching of cooperation opportunities. Digital tools, including IS platforms, are considered facilitators of this process. This systematic literature review addresses the research question: ‘ Which are the most important data points of an IS platform and how can they be used for the promotion of IS?’. Methods: The review is based on scientific publications from the following academic research databases: ScienceDirect, Scopus, SpringerLink, Wiley Online Library, AISel and IEEE (via Google Scholar), and grey literature obtained through a customized Google search technique, last performed on 9/3/2021. Records were included according to their scientific content, namely if the document: i) examined the identification of synergies utilizing ICT tools, ii) data requirements or platform related information were presented or iii) the impact of a digital tool in promoting IS was discussed. Exclusion criteria were: articles not written in English, not peer-reviewed, published before 2016 or document type other than scientific article, conference paper or EU project deliverable. Two independent reviewers performed title scanning and abstract reading of the documents to reduce the risk of bias. Results: The total number of records included after abstract and full text reading was 32. The main results of this review suggest that two significant types of data points are encountered in IS platforms; i) data required for synergy identification and ii) platform related information. Conclusions: A possible limitation of the study is a minor risk of bias due to one reviewer performing full text reading and synthesis of results; however, they reported to and consulted with the supervising reviewer. Overall, the results indicate that several types of data points are required for effective matching and successful promotion of IS through digital tools.

This systematic literature review delves into various wood waste valorization and classification approaches, aiming to evaluate their efficacy in fostering sustainable wood resource management while enhancing the economic value of wood waste. By synthesizing findings from a diverse array of research studies, the review highlights the multifaceted nature of wood waste valorization, emphasizing the critical role of sorting and separation technologies in ensuring high-quality recovery of materials. It also identifies the wood classification practices in Europe, which are crucial for creating a harmonized valorization framework that aligns technological advancements with regulatory standards. The analysis reveals that integrating these components—technologies, sorting methods, and classification practices can significantly improve the overall efficiency and effectiveness of wood waste management. Furthermore, the review identifies existing gaps in research and practice, providing actionable recommendations for stakeholders aiming to optimize wood valorization waste systems. These recommendations emphasize the necessity for a holistic approach and a clearly defined, comprehensive framework for wood valorization that considers all elements involved in the process. By addressing these areas, the review not only aims to contribute to the body of knowledge in wood waste valorization but also seeks to promote sustainable practices that benefit both the environment and the economy, paving the way for a more circular approach to wood resource utilization.