• Energy Research
• 2025-2025close
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Scenarios to stabilize global climate and meet international climate agreements require rapid reductions in human carbon dioxide (CO2) emissions, often augmented by substantial carbon dioxide removal (CDR) from the atmosphere. While some ocean-based removal techniques show potential promise as part of a broader CDR and decarbonization portfolio, no marine approach is ready yet for deployment at scale because of gaps in both scientific and engineering knowledge. Marine CDR spans a wide range of biotic and abiotic methods, with both common and technique-specific limitations. Further targeted research is needed on CDR efficacy, permanence, and additionality as well as on robust validation methods—measurement, monitoring, reporting, and verification—that are essential to demonstrate the safe removal and long-term storage of CO2. Engineering studies are needed on constraints including scalability, costs, resource inputs, energy demands, and technical readiness. Research on possible co-benefits, ocean acidification effects, environmental and social impacts, and governance is also required.

Abstract The Transpolar Drift (TPD) plays a crucial role in regulating Arctic climate and ecosystems by transporting fresh water and key substances, such as terrestrial nutrients and pollutants, from the Siberian Shelf across the Arctic Ocean to the North Atlantic. However, year-round observations of the TPD remain scarce, creating significant knowledge gaps regarding the influence of sea ice drift and ocean surface circulation on the transport pathways of Siberian fresh water and associated matter. Using geochemical provenance tracer data collected over a complete seasonal cycle, our study reveals substantial spatiotemporal variability in the dispersal pathways of Siberian matter along the TPD. This variability reflects dynamic shifts in contributions of individual Siberian rivers as they integrate into a large-scale current system, followed by their rapid and extensive redistribution through a combination of seasonal ice–ocean exchanges and divergent ice drift. These findings emphasize the complexity of Arctic ice–ocean transport pathways and highlight the challenges of forecasting their dynamics in light of anticipated changes in sea ice extent, river discharge, and surface circulation patterns.

Abstract Expanding electric vehicle (EV) charging infrastructure is essential for transitioning to an electrified mobility system. With rising EV adoption rates, firms face increasing regulatory pressure to build up workplace charging facilities for their employees. However, the impact of EV charging loads on businesses’ specific electricity consumption profiles remains largely unknown. Our study addresses this challenge by presenting a mathematical optimisation model, available via an open-source web application, that empowers business executives to manage energy consumption effectively, enabling them to assess peak loads, charging costs and carbon emissions specific to their power profiles and employee needs. Using real-world data from a global car manufacturer in South East England, UK, we demonstrate that smart charging strategies can reduce peak loads by 28% and decrease charging costs and emissions by 9% compared to convenience charging. Our methodology is widely applicable across industries and geographies, offering data-driven insights for planning EV workplace charging infrastructure.

Abstract In new residential neighborhoods, planners often implement mobility concepts consisting of various measures and instruments, which intend to serve as alternatives for private cars and thus limit the negative external effects of motorized transport. However, there is a lack of studies regarding the impacts of such concepts. Accordingly, we analyze which actual effects mobility measures have on transport and land consumption. Investigating a newly developed low-car neighborhood with 361 households in Berlin, Germany, we surveyed the residents (45 survey participants) and simulated transport. Our results show that planning ideal and lived reality differ—new residents bring more cars than expected and planning intentions differ from what residents want and use. Only strong measures may change mobility behavior but better information and mobility management could help to increase awareness, acceptance and use of new mobility options.

In the current context of growing electrification of the transport sector, offering rental and sharing programs for electric vehicles is considered one of the strategies to achieve decarbonization targets. Such programs should be supported by suitable optimization tools to manage the vehicle fleet, and make rental provision profitable for its operator. In this paper, we consider a rental system having a single station for electric vehicle pickup and delivery. For this system, we address the operational problem of simultaneously assigning rental requests to vehicles and determining the charging policies during inactivity intervals. The objective is to maximize the profit for the operator by minimizing the costs for electricity. The considered problem is complicated by uncertainty regarding the battery energy level when a vehicle returns to the station. This leads to a chance-constrained programming formulation, where the request-to-vehicle assignment and charging policies are determined by minimizing electricity costs while ensuring that the energy demand of the served requests is met with a prescribed high probability. Since the formulated mixed-integer problem with probabilistic constraints is hard to solve, a suboptimal approach is proposed, consisting of two sequential steps. In the first step, request-to-vehicle assignment is accomplished via a suitably designed heuristic procedure. Then, for a given assignment, the charging policy of each vehicle is determined by solving a relaxed chance-constrained problem. Numerical results are presented to assess the performance of both the assignment procedure and the optimization problem which determines the electric vehicle charging policies.

Population growth in coastal tourist areas is leading to enhanced waste production, raising concerns about potential nutrient release increases and the resulting impact on marine ecosystems through eutrophication. Knowledge of the specific impacts of eutrophication on plankton communities in many of these regions is limited, highlighting the need for further research and appropriate environmental management strategies. To help address these gaps, we conducted a 30-day mesocosm study in the coastal waters of Gran Canaria, Canary Islands, a major European tourist destination, and the third most densely populated autonomous community in Spain. With the aim of assessing the effects of nutrient input on biomass, primary production (PP) and recycling processes by phytoplankton, zooplankton, and bacterioplankton, we simulated three nutrient discharge intensities (Low, Medium, and High), with daily additions of 0.1, 1, and 10 μmol L-1 of nitrate, respectively, along with phosphate and silicate. We observed that PP, chlorophyll a (Chl-a), and biomass increased linearly with nutrient input, except in the High treatment, where CO2 depletion (2500 μmol L-1) resulted in reduced PP. Despite limitations in nitrogen (Control, Low, and Medium) or carbon (High) availability across treatments, which led to stabilized or decreased PP rates and dissolved organic carbon (DOC) concentrations, bacterial degradation remained active in all treatments. This microbial activity resulted in an accumulation of recalcitrant chromophoric dissolved organic matter (CDOM), indicating the resilience of carbon recycling processes under varying nutrient conditions. Furthermore, a clear succession was evident in all enriched treatments, transitioning from an oligotrophic condition dominated by pico- and nanophytoplankton to a eutrophic state primarily composed of diatoms. However, under CO2 depletion, diatoms experienced a decline in the High treatment, leading to the proliferation of potentially mixotrophic dinoflagellates. Microzooplankton was less sensitive than mesozooplankton to the decrease in prey availability and high pH caused by CO2 depletion. Interestingly, the Medium treatment showed high efficiency in terms of PP, despite reaching CO2 levels near of 1.0 μmol L-1 by the end of the experiment. PP rates increased from 10 to 100 μg C·L-1·d-1 during the first week and remained stable as diatoms predominated throughout the study period. These findings provide valuable insights into the responses of plankton communities to varying nutrient inputs and emphasize the importance of considering the effects of DIC depletion, along with changes in total alkalinity, in eutrophication scenarios as well as in ocean alkalinity enhancement experiments aimed at reducing carbon dioxide emissions.