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Abstract. The increased resolution of numerical weather prediction models allows nowadays addressing more realistically urban meteorology and air pollution processes. This has triggered new interest in modelling and describing experimentally the specific features and processes of urban areas. Recent developments and results performed within the EU-funded project FUMAPEX on integrated systems for forecasting urban meteorology and air pollution are reported here. Sensitivity studies with respect to optimum resolution, parametrisation of urban roughness and surface exchange fluxes and the role of urban soil layers are carried out with advanced meso- or sub-meso meteorological models. They show that sensible improvements can be achieved by higher model resolution that is accompanied with better description of urban surface features. Recommendations, especially with respect to advanced urban air quality forecasting and information systems, are given together with an assessment of the needed further research and data.

Abstract Breakthrough alternative technologies are urgently required to alleviate the critical need to decarbonise our energy supply. We showcase non-conventional approaches to battery and solar energy conversion and storage (ECS) system designs that harness key attributes of immiscible electrolyte solutions, especially the membraneless separation of redox active species and ability to electrify certain liquid–liquid interfaces. We critically evaluate the recent development of membraneless redox flow batteries based on biphasic systems, where one redox couple is confined to an immiscible ionic liquid or organic solvent phase, and the other couple to an aqueous phase. Common to all solar ECS devices are the abilities to harvest light, leading to photo-induced charge carrier separation, and separate the products of the photo-reaction, minimising recombination. We summarise recent progress towards achieving this accepted solar ECS design using immiscible electrolyte solutions in photo-ionic cells, to generate redox fuels, and biphasic “batch” water splitting, to generate solar fuels.

AbstractElectricity theft is a primary concern for utility providers, as it leads to substantial financial losses. To address the issue, a novel extreme gradient boosting (XGBoost)‐based model utilizing the consumers’ electricity consumption patterns for analysis is proposed for electricity theft detection (ETD). To remove the imbalance in the real‐world electricity consumption dataset and ensure an even distribution of theft and non‐theft data instances, six different artificially created theft attacks were used. Moreover, the utilization of the XGBoost algorithm for classification, especially to identify malicious instances of electricity theft, yielded commendable accuracy rates and a minimal occurrence of false positives. The proposed model identifies electricity theft specific to the regions, utilizing electricity consumption parameters, and other variables as input features. The authors’ model outperformed existing benchmarks like k‐neural networks, light gradient boost, random forest, support vector machine, decision tree, and AdaBoost. The simulation results using the false attacks for balancing the dataset have improved the proposed model's performance, achieving a precision, recall, and F1‐score of 96%, 95%, and 95%, respectively. The results of the detection rate and the false positive rate (FPR) of the proposed XGBoost‐based detection model have achieved 96% and 3%, respectively.

Reduction of greenhouse gas emissions and mitigation of climate change are the main aims of the global climate policy. Increased use of renewable energy is a central measure in achieving these goals. However, mitigation of climate change through increased use of renewable energy also has negative environmental impacts. Focusing merely on greenhouse gas emissions may lead to overseeing these other negative environmental impacts and thereby in unwanted side-effects. The aim of this review was to assess the overall life cycle impacts related to the production and use of the different renewable energy sources. Impacts were assessed for unit processes and for the Finnish national renewable energy targets as a whole. The review points out that in order to comprehensively understand the overall environmental impacts of the different renewable energy sources, a thorough life cycle assessment with a unified framework would be needed. Presently there is only limited information available or the published results are not comparable with each another. However, assessment using the Finnish National Renewable Energy Targets for 2020 also indicates that under the present targets, the overall environmental impacts of the renewable energy use are likely to be low. Main impacts or risks of impacts relate to the use of forest energy.

AbstractClimate change, migration, and conflict have been featured prominently in academic and policy literature. While Africa remains the major reference point, studies on key conflict hotspots fail to adequately examine empirical demonstrations of how climate change forces migration, and consequently major conflicts. Drawing on semi‐structured interviews, focus group discussions, and employing the scarcity theory in a study of Agogo (Ghana), we illustrate how regional and local climate/environmental variability and scarcity trigger and sustain migration and farmer–herder conflicts. The findings offer insights into how other non‐climatic and ecological conditions reinforce the so‐called climate‐induced conflicts, exposing the limitations of the scarcity‐theory. Importantly, this study has provided an illustrative argument centered around the contextual dynamics of the nexus between climate change and farmer–herder conflict in Agogo to contribute to national, regional, and continental discussion on this critical topic.

The paper presents some research work on applying the oxygen enrichment technique to hot stoves that was carried out in one European RFCS project. In the presented work, both theoretical and practi ...