Plymouth Marine Laboratory

• We use photo-elicitation to understand coastal resident’s perceptions of tidal energy. • We assess how key environmental values and attributes influence these perceptions. • Participants were positive about tidal energy and recognised its sustainable nature. • Participants resolved a range of self-interest and altruistic trade-offs to reach their perceptions. • Impacts on the local environment and wildlife were key influences on perceptions. Early consideration of potential societal issues, including public acceptance, is important for the effective implementation of energy policies and technologies. Conversely, lack of public acceptance can act as a barrier to their uptake, and deployment of renewable technologies has frequently been marked by public opposition at the local level. Levels of support for renewable energy are currently high, although expressions of public support do not always translate into approval for local developments, and there is significant variability in acceptance depending on a wide range of attributes. This paper provides novel insights into potential contributing factors to public acceptance of tidal energy amongst residents of coastal communities along a major inlet in the UK with high potential for tidal energy development. Adopting a largely qualitative empirical approach, nineteen participants from three coastal towns took part in photo-elicitation interviews that utilised self-taken photographs to drive discussions around local environmental (marine and coastal) attributes of importance and how these might influence participants’ attitudes toward tidal energy. Selected data from a previous related energy survey provided a mixed-methods lens to reinforce specific issues raised by participants. Key findings on participants’ perceptions of tidal energy included overall general positivity toward this technology, as well as recognition of its significance for sustainable energy. A range of trade-offs between issues of personal importance and the wider significance of tidal energy were also apparent. The perceived impacts of developments on environmental attributes of greatest importance to participants were thematically analysed revealing particular concerns regarding local environmental impacts and impacts on wildlife. Presented as key influencing issues on participant’s perceptions of tidal energy developments, this new qualitative data improves our understanding of the issues that can lead to acceptance or rejection of proposals and are thus of relevance to a range of users, including decision-makers, consultants and developers.

Abstract. The University of York's laser-induced fluorescence (LIF) instrument for measuring sulfur dioxide (SO2) was compared to a commercial pulsed fluorescence (PF) analyser and iodide chemical ionisation mass spectrometer (I−CIMS) aboard the UK FAAM research aircraft in both remote and ship-polluted marine environments. In high SO2 concentration plumes, the LIF instrument and PF analyser compared well, but LIF was the only instrument capable of SO2 measurements in the remote marine boundary layer due to its campaign limit of detection (LoD, 3σ) of 0.07 ppb at 10 s compared with 0.4 ppb for the PF analyser. Quantification of SO2 using I−CIMS was challenging due to a significant interference, but good signal correlation with the other instruments was observed in polluted air masses. A comparison of response time was also made, for which the I−CIMS and LIF instrument proved much faster than the PF analyser with 3 e-folding times of 0.6, 2 and 17 s respectively. This work demonstrates the importance of sensitive instrumentation like the LIF system for quantifying low concentrations of SO2, such as over remote marine environments, at the time resolutions required for a fast moving platform. This is particularly relevant now as a result of more stringent sulfur emission regulations for shipping, and likely more so in the future as anthropogenic SO2 concentrations continue to decline.

Abstract Pteropods are promising proxy archives for paleoceanographic reconstructions but remain underexplored. Previous oxygen isotope analyses indicated that Heliconoides inflatus calcifies at shallow depths (50–75 m), suggesting its potential to record surface-ocean conditions. Here, we evaluate for the first time the applicability of Li/Mg thermometry in pteropod shells, a temperature proxy widely used in coral studies. We show that, in addition to recording environmental variability through shell carbon and oxygen isotopic composition, H. inflatus shells reliably track seawater temperature via their Li/Mg ratios. Li/Mg ratios decrease exponentially with increasing temperature, enabling temperature reconstructions with an average precision of ±1–2 °C. Pteropod shells (species Heliconoides inflatus , formerly known as Limacina inflata ) were collected along a latitudinal transect in the Atlantic Ocean (31° N to 38° S), covering a temperature range of nearly 15 °C. The global distribution and abundance of this annual species in sediments makes it a suitable alternative for palaeotemperature reconstruction. The utility of pteropod shells extends further to seasonal paleotemperature reconstruction, as seasonal temperature variability is captured in the elemental ratios from the embryonic to later (adult) sections of the shell. These results, in combination with a basin-scale distribution, make the Li/Mg thermometer in pteropods an exciting new tool in paleoceanography and further cement this group as new proxy archives.

Abstract Nowcasting developing convection is a crucial component of early warning systems in the tropics. While machine learning has proven effective for radar-based nowcasting, the lack of radar coverage across much of the tropics creates a significant capability gap. This study presents Simple Initiation and Intensification Nowcasting Neural Network (SII-NowNet), a machine learning tool that uses satellite brightness temperatures to produce probabilistic nowcasts of intensifying and initiating convection in the tropics. SII-NowNet is first demonstrated over Sumatra, Indonesia—a densely populated tropical island with frequent convective activity. For nowcasts of intensifying convection, SII-NowNet outperforms an optical flow model for lead times of 1–6 h but begins to overpredict events beyond 3 h, indicating its limit of capability. For nowcasts of initiating convection, SII-NowNet’s limit of capability is reached at 2 h, beyond which it overpredicts events and is outperformed by climatology. SII-NowNet is trained on 8661 samples (12 months of data), but sensitivity testing shows that the number of samples can be reduced to 3 weeks for intensification and 3 months for initiation, before it is outperformed by climatology. This has practical implications for the implementation and further development of SII-NowNet in resource-constrained settings. To exemplify generalizability in other tropical regions, SII-NowNet is tested over New Guinea, Zambia, Congo, and West Africa. Without retraining or region-specific tuning, SII-NowNet achieves skill scores comparable to those over Sumatra. Overall, SII-NowNet’s promising results, combined with ease of applicability across the tropics, make it a valuable tool for future operational nowcasting. Significance Statement In the tropics, short-term forecasts of destructive, rapidly developing storms are critical components of early warning systems—essential for protecting lives and minimizing impacts. However, many regions face challenges in accurate forecasting due to limited access to ground-based meteorological observations. This study presents a machine learning tool that uses freely and continuously available satellite data—covering the entire tropics—to forecast storm development several hours in advance. The tool performs well in five distinct tropical regions and requires minimal computational resources, showing its suitability for implementation in resource-constrained settings. Furthermore, the results highlight the challenges in capturing newly initiating storms—a focus for future studies. Continued work on the tool will focus on testing its performance in additional tropical regions.