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ReportClarke B, Barnes C, Sparks N, et al., 2024,
Climate change key driver of catastrophic impacts of Hurricane Helene that devastated both coastal and inland communities
, Publisher: Centre for Environmental Policy -
Journal articleAliaga-Samanez A, Romero D, Murray K, et al., 2024,
Climate change is aggravating dengue and yellow fever transmission risk
, Ecography, Vol: 2024, ISSN: 0906-7590Dengue and yellow fever have complex cycles, involving urban and sylvatic mosquitoes, and non-human primate hosts. To date, efforts to assess the effect of climate change on these diseases have neglected the combination of such crucial factors. Recent studies only considered urban vectors. This is the first study to include them together with sylvatic vectors and the distribution of primates to analyse the effect of climate change on these diseases. We used previously published models, based on machine learning algorithms and fuzzy logic, to identify areas where climatic favourability for the relevant transmission agents could change: 1) favourable areas for the circulation of the viruses due to the environment and to non-human primate distributions; 2) the favourability for urban and sylvatic vectors. We obtained projections of future transmission risk for two future periods and for each disease, and implemented uncertainty analyses to test for predictions reliability. Areas currently favourable for both diseases could keep being climatically favourable, while global favourability could increase a 7% for yellow fever and a 10% increase for dengue. Areas likely to be more affected in the future for dengue include West Africa, South Asia, the Gulf of Mexico, Central America and the Amazon basin. A possible spread of dengue could take place into Europe, the Mediterranean basin, the UK and Portugal; and, in Asia, into northern China. For yellow fever, climate could become more favourable in Central and Southeast Africa; India; and in north and southeast South America, including Brazil, Paraguay, Bolivia, Peru, Colombia and Venezuela. In Brazil, favourability for yellow fever will probably increase in the south, the west and the east. Areas where the transmission risk spread is consistent to the dispersal of vectors are highlighted in respect of areas where the expected spread is directly attributable to environmental changes. Both scenarios could involve different prev
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Journal articleCastrillejo M, Hansman RL, Graven HD, et al., 2024,
Comparability of radiocarbon measurements in dissolved inorganic carbon of seawater produced at ETH-Zurich
, Radiocarbon: an international journal of cosmogenic isotope research, Vol: 66, Pages: 1054-1063, ISSN: 0033-8222Radiocarbon observations (Δ14C) in dissolved inorganic carbon (DIC) of seawater provide useful information about ocean carbon cycling and ocean circulation. To deliver high-quality observations, the Laboratory of Ion Beam Physics (LIP) at ETH-Zurich developed a new simplified method allowing the rapid analysis of radiocarbon in DIC of small seawater samples, which is continually assessed by following internal quality controls. However, a comparison with externally produced 14C measurements to better establish an equivalency between methods was still missing. Here, we make the first intercomparison with the National Ocean Sciences Accelerator Mass Spectrometry (NOSAMS) facility based on 14 duplicate seawater samples collected in 2020. We also compare with prior deep-water observations from the 1970s to 1990s. The results show a very good agreement in both comparisons. The mean Δ14C of 12 duplicate samples measured by LIP and NOSAMS were statistically identical within one sigma uncertainty while two other duplicate samples agreed within two sigma. Based on this small number of duplicate samples, LIP values appear to be slightly lower than the NOSAMS values, but more measurements will be needed for confirmation. We also comment on storage and preservation techniques used in this study, including the freezing of samples collected in foil bags.
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Journal articleMajeed A, Quint JK, Bhatt S, et al., 2024,
Non-pharmaceutical interventions: evaluating challenges and priorities for future health shocks
, BMJ, Vol: 387, ISSN: 0959-8138 -
Journal articleFargette N, Eastwood JP, Waters CL, et al., 2024,
Statistical study of energy transport and conversion in electron diffusion regions at earth's dayside magnetopause
, Journal of Geophysical Research: Space Physics, Vol: 129, ISSN: 2169-9380The electron diffusion region (EDR) is a key region for magnetic reconnection, but the typical energy transport and conversion in EDRs is still not well understood. In this work, we perform a statistical study of 80 previously published near X-line events identified at the dayside magnetopause in Magnetospheric Multiscale data. We find 44 events that clearly present all commonly accepted EDR signatures and use this database to investigate energy flux partition and energy conversion. We find that energy partition is changed inside EDRs, with a 71%–29% allocation of particle energy flux density between electrons and ions respectively. The electron enthalpy flux density is found to dominate locally at all EDRs and is predominantly oriented in the out-of-plane direction, perpendicular to the reconnecting magnetic field. We also examine the transition from electron- to ion-dominated energy flux partition further from the EDR, finding this typically occurs at scales of the order of the ion inertial length, larger than the typical EDR size. We then investigate energy conversion and transport and highlight complex processes, with potential non-steady-state energy accumulation and release near the EDR. We discuss the implications of our results for reconnection energy conversion, and for magnetopause dynamics in general.
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Journal articleBelcher RN, Murray KA, Reeves JP, et al., 2024,
Socioeconomic deprivation modifies green space and mental health associations: a within-person study
, Environment International, Vol: 192, ISSN: 0160-4120Living in an area with good availability and accessibility of residential green spaces such as parks, woodlands, and residential gardens can improve mental health and reduce the global disease burden. Unlike for physical health, it is not well understood if mental health and green space associations might be modified by local area deprivation. Existing evidence for this association comes from cross-sectional studies, widely considered vulnerable to confounding and bias. Individual time-invariant mental health status, personality, and other factors may result in positive effect modification on green space and mental health associations in more deprived areas. We use fixed-effects models that remove time-invariant confounding by calculating differences within-persons to eliminate this bias and add to the existing evidence. We modelled changes in mental health status, green space, and deprivation (relative to the within-person mean) within 54,666 individuals with a combined total of 300,710 mental health scores from one of the world’s largest panel surveys: “Understanding Society” in the UK. We found a positive effect of increasing residential green space on mental health and this was positively modified and intensified by area deprivation before and after adjusting for confounding. Our results support providing green space to protect against the negative impact of socioeconomic deprivation on health, particularly for those moving from a less deprived to a more deprived area.
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Journal articleMills MB, Both S, Jotan P, et al., 2024,
From tree to plot: investigating stem CO<sub>2</sub> efflux and its drivers along a logging gradient in Sabah, Malaysian Borneo
, NEW PHYTOLOGIST, Vol: 244, Pages: 91-103, ISSN: 0028-646X -
Journal articleHuybrechts I, Chimera B, Hanley-Cook GT, et al., 2024,
Food biodiversity and gastrointestinal cancer risk in nine European countries: analysis within a prospective cohort study
, European Journal of Cancer, Vol: 210, ISSN: 0959-8049BackgroundFood biodiversity in human diets has potential co-benefits for both public health and sustainable food systems. However, current evidence on the potential relationship between food biodiversity and cancer risk, and particularly gastrointestinal cancers typically related to diet, remains limited. This study evaluated how dietary species richness (DSR) was associated with gastrointestinal cancer risk in a pan-European population.MethodsAssociations between DSR and subsequent gastrointestinal cancer risk were examined among 450,111 adults enrolled in the European Prospective Investigation into Cancer and Nutrition cohort (EPIC, initiated in 1992), free of cancer at baseline. Usual dietary intakes were assessed at recruitment with country-specific dietary questionnaires. DSR of an individual’s yearly diet was calculated based on the absolute number of unique biological species in each food and drink item. Associations between DSR and cancer risk were assessed by multivariable Cox proportional hazards regression models.FindingsDuring a median follow-up time of 14.1 years (SD=3.9), 10,705 participants were diagnosed with gastrointestinal cancer. Hazard ratios (HRs) and 95 % confidence intervals (CIs) comparing overall gastrointestinal cancer risk in the highest versus lowest quintiles of DSR indicated inverse associations in multivariable-adjusted models [HR (95 % CI): 0.77 (0.69–0.87); P-value < 0·0001] (Table 2). Specifically, inverse associations were observed between DSR and oesophageal squamous cell carcinoma, proximal colon, colorectal, and liver cancer risk (p-trend<0.05 for all cancer types).InterpretationGreater food biodiversity in the diet may lower the risk of certain gastrointestinal cancers. Further research is needed to replicate these novel findings and to understand potential mechanisms.
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Journal articleMurray-Watson R, Gryspeerdt E, 2024,
Air mass history linked to the development of Arctic mixed-phase clouds
, Atmospheric Chemistry and Physics, Vol: 24, Pages: 11115-11132, ISSN: 1680-7316Clouds formed during marine cold-air outbreaks (MCAOs) exhibit a distinct transition from stratocumulus decks near the ice edge to broken cumuliform fields further downwind. The mechanisms associated with ice formation are believed to be crucial in driving this transition, yet the factors influencing such formation remain unclear. Through Lagrangian trajectories collocated with satellite data, this study investigates the development of mixed-phase clouds using these outbreaks. Cloud formed in MCAOs are characterized by a swift shift from liquid to ice-containing states, contrasting with non-MCAO clouds also moving off the ice edge. These mixed-phase clouds are predominantly observed at temperatures below −20 °C near the ice edge. However, further into the outbreak, they become dominant at temperatures as high as −13 °C. This shift is consistent with the influence of biological ice-nucleating particles (INPs), which become more prevalent as the air mass ages over the ocean. The evolution of these clouds is closely linked to the history of the air mass, especially the length of time it spends over snow- and ice-covered surfaces – terrains may that be deficient in INPs. This connection also accounts for the observed seasonal variations in the development of Arctic clouds, both within and outside of MCAO events. The findings highlight the importance of understanding both local marine aerosol sources near the ice edge and the overarching INP distribution in the Arctic for modelling of cloud phase in the region.
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Journal articleWaters C, Eastwood J, Fargette N, et al., 2024,
Classifying magnetic reconnection regions using k-means clustering: applications to energy partition
, JGR: Space Physics, Vol: 129, ISSN: 2169-9402Magnetic reconnection is a fundamental plasma process which facilitates the conversion of magnetic energy to particle energies. This local process both contributes to and is affected by a larger system, being dependent on plasma conditions and transporting energy around the system, such as Earth's magnetosphere. When studying the reconnection process with in situ spacecraft data, it can be difficult to determine where spacecraft are in relation to the reconnection structure. In this work, we use k-means clustering, an unsupervised machine learning technique, to identify regions in a 2.5-D PIC simulation of symmetric magnetic reconnection with conditions comparable to those observed in Earth’s magnetotail. This allows energy flux densities to be attributed to these regions. The ion enthalpy flux density is the most dominant form of energy flux density in the outflows, agreeing with previous studies. Poynting flux density may be dominant at some points in the outflows and is only half that of the Poynting flux density in the separatrices. The proportion of outflowing particle energy flux decreases as guide field increases. We find that k-means is beneficial for analysing data and comparing between simulations and in situ data. This demonstrates an approach which may be applied to large volumes of data to determine statistically different regions within phenomena in simulations and could be extended to in situ observations, applicable to future multi-point missions.
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