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Journal articleRiley AI, Blangiardo M, Piel FB, et al., 2026,
A Bayesian multisource fusion model for spatiotemporal PM₂.₅ in an urban setting
, Environmetrics, Vol: 37, ISSN: 1180-4009Airborne particulate matter (PM2.5) is a major public health concern in urban environments, where population density and emission sources exacerbate exposure risks. We present a novel Bayesian spatiotemporal fusion model to estimate monthly PM2.5 concentrations over Greater London (2014–2019) at 1 km resolution. The model integrates multiple PM2.5 data sources, including outputs from two atmospheric air quality dispersion models, and predictive variables, such as vegetation and satellite aerosol optical depth, while explicitly modeling a latent spatiotemporal field. Spatial misalignment of the data is addressed through a hierarchical fusion and spatial interpolation approach to predict across the entire area. Building on stochastic partial differential equations (SPDE) within the integrated nested Laplace approximations (INLA) framework, our method introduces spatially- and temporally-varying coefficients to flexibly calibrate datasets and capture fine-scale variability. Model performance and complexityare balanced using predictive metrics such as the predictive model choice criterion and thorough cross-validation. The best performing model shows excellent fit and robust predictive performance, enabling reliable high-resolution spatiotemporal mapping of PM2.5 concentrations with the associated uncertainty. Furthermore, the model outputs, including full posterior predictive distributions, can be used to map exceedance probabilities of regulatory thresholds, supporting air quality management and targetedinterventions in vulnerable urban areas, as well as providing refined exposure estimates of PM2.5 for epidemiological applications.
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Journal articleDean TR, Abbott TH, Engberg Z, et al., 2025,
Impact of forecast stability on navigational contrail avoidance
, ENVIRONMENTAL RESEARCH: INFRASTRUCTURE AND SUSTAINABILITY, Vol: 5 -
Journal articleGavasso-Rita YL, Zaerpour M, Abdelmoaty H, et al., 2025,
Rainfed spring canola yield response to changing heat and water stress in the Canadian Prairie region
, Agricultural Water Management, Vol: 322, ISSN: 0378-3774Canola is a significant crop in Canadian agriculture and the economy. However, Canada's average temperatures have risen rapidly over the past eight decades, changing temperature patterns and water availability for canola production. This study aims to explore the impacts of air temperature and soil water availability on spring canola production from 2025 to 2050. Accordingly, this study introduces DSSAT calibration and simulation of the current hybrid InVigor®L340PC, integrating the Shared Socioeconomic Pathways. Leveraging DSSAT-Pythia, gridded simulations capture spatial variability in water and temperature stress interactions, driven by a large ensemble of climate models. The analysis reveals how precipitation and temperature changes jointly influence spring canola development. Yield projections under these conditions provide critical insights into the future viability of rainfed spring canola and inform adaptation strategies for growers and policymakers. Findings demonstrate negative impacts on exclusively rainfed spring canola production in the Canadian Prairie Region under diverse climate scenarios from 2025 to 2050. The main canola growing ecozone (Aspen Parkland) is expected to have higher air temperatures and lower soil water content if greenhouse gas emissions keep rising. An average increase of 1.5°C in air temperature and 0.025 in the water stress factor indices may result in annual yield reductions of 203 ± 4.3 and 121 ± 13.6 kg ha<sup>−1</sup>, in Lake Manitoba Plain and Aspen Parkland ecoregions, respectively. Given that future canola production is expected to continue in the same ecoregions it is recommended that adaptation and mitigation strategies are developed and adopted to improve canola production conditions in these ecoregions.
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Journal articlePonsonby J, Teoh R, Kärcher B, et al., 2025,
An updated microphysical model for particle activation in contrails: the role of volatile plume particles
, Atmospheric Chemistry and Physics, Vol: 25, Pages: 18617-18637<jats:p>Abstract. Global simulations suggest the mean annual contrail cirrus net radiative forcing is comparable to that of aviation's accumulated CO2 emissions. Currently, these simulations assume non-volatile particulate matter (nvPM) and ambient particles are the only source of condensation nuclei, omitting activation of volatile particulate matter (vPM) formed in the nascent plume. Here, we extend a microphysical model to include vPM and benchmark this against a more advanced parcel model (pyrcel) modified to treat contrail formation. We explore how the apparent emission index (EI) of contrail ice crystals (AEIice) scales with EInvPM, vPM properties, ambient temperature, and aircraft/fuel characteristics. We find model agreement within 10 %–30 % in the previously defined “soot-poor” regime. However, discrepancies increase non-linearly (up to 60 %) in the “soot-rich” regime, due to differing treatment of droplet growth. Both models predict that, in the “soot-poor” regime, AEIice approaches 1016 kg−1 for low ambient temperatures (< 210 K) and sulfur-rich vPM, which is comparable to estimates in the “soot-rich” regime. Moreover, our sensitivity analyses suggest that the point of transition between the “soot-poor” and “soot-rich” regimes is a dynamic threshold that ranges from 1013–1016 kg−1 and depends sensitively on ambient temperature and vPM properties, underlining the need for vPM emission characterisation measurements. We suggest that existing contrail simulations omitting vPM activation may underestimate AEIice, especially for flights powered by lean-burn engines. Furthermore, our results imply that, under these conditions, AEIice might be reduced by (i) reducing fuel sulfur content, (ii) minimising organic emissions, and/or (iii) avoiding cooler regions of the atmosphere.</jats:p>
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Journal articleXu H, Wang H, Prentice IC, et al., 2025,
Global variation in the ratio of sapwood to leaf area explained by optimality principles
, New Phytologist, ISSN: 0028-646X• The sapwood area supporting a given leaf area (Huber value, vH) reflects the coupling between carbon uptake and water transport and loss at a whole-plant level. Geographic variation in vH presumably reflect plant strategic adaptations but the lack of a general explanation for such variation hinders its representation in vegetation models and assessment of how its impact on the global carbon and water cycles. • Here we develop a simple hydraulic trait model to predict optimal vH by matching stem water supply and leaf water loss, and test its performance against two extensive plant hydraulic datasets. • We show that our eco-evolutionary optimality-based model explains nearly 60% of global vH variation in response to light, vapour pressure deficit, temperature and sapwood conductivity. Enhanced hydraulic efficiency with warmer temperatures reduces the sapwood area required to support a given leaf area, whereas high irradiance (supporting increased photosynthetic capacity) and drier air increase it. • This study thus provides a route to modelling variation in functional traits through the coordination of carbon uptake and water transport processes.
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Journal articleAl Khalili U, Karmpadakis I, 2025,
Breaking occurrence and dissipation in shortcrested waves in finite water
, Coastal Engineering, Vol: 202, ISSN: 0378-3839The understanding of wave breaking has long been a critical concern for engineers and scientists. However, accurately identifying the onset of breaking and quantifying the associated energy dissipation remain significant challenges. To address this, the present study develops a novel methodology to identify breaking wave events in shortcrested seas in finite water depths. This is achieved through a unique dataset which couples laboratory and numerically-generated waves. The data reflect realistic sea-states used in engineering design and cover a wide range of conditions from mild to extreme. Using the proposed algorithm, key physical properties of breaking waves are examined. In particular, the probability of wave breaking and the associated wave energy dissipation are quantified to provide a statistical description of their behaviour. Complementarily, waves exhibiting significant nonlinear amplifications are also identified and modelled in a similar manner. This enables traditional wave distributions to be decomposed into more detailed distributions of breaking and non-breaking waves. These insights are combined to define a new model that predicts crest height statistics in intermediate water depths. This new mixture model is shown to reproduce experimental measurements with high accuracy, while also providing critical additional information about wave breaking.
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Journal articleWong HL, Palacios R, Gryspeerdt E, 2025,
rojak: A Python library and tool for aviation turbulence diagnostics
, Journal of Open Source Software, Vol: 10, ISSN: 2475-9066Aviation turbulence is atmospheric turbulence occurring at length scales large enough (ap proximately 100m to 1km) to affect an aircraft (Sharman, 2016). According to the National Transport Safety Board (NTSB), turbulence experienced whilst onboard an aircraft was theleading cause of accidents from 2009 to 2018 (NTSB, 2021). Clear air turbulence (CAT) is a form of aviation turbulence which cannot be detected by the onboard weather radar. Thus, pilots are unable to preemptively avoid such regions. In order to mitigate this safety risk, CAT diagnostics are used to forecast turbulent regions such that pilots are able to tactically avoidthem.rojak is a parallelised Python library and command-line tool for using meteorological data to forecast CAT and evaluating the effectiveness of CAT diagnostics against turbulence observations. Currently, it supports,1. Computing turbulence diagnostics on meteorological data from the European Centrefor Medium-Range Weather Forecasts’s (ECMWF) ERA5 reanalysis on pressure levels(Hersbach, 2023). Moreover, it is easily extendable through a software update to supportother types of meteorological data.2. Retrieving and processing turbulence observations from Aircraft Meteorological DataRelay (AMDAR) data archived at the National Oceanic and Atmospheric Administration(NOAA)(NCEP Meteorological Assimilation Data Ingest System (MADIS), 2024) andAMDAR data collected via the Met Office MetDB system (Met Office, 2008)3. Computing 27 different turbulence diagnostics, such as the three-dimensional fronto genesis equation (Bluestein, 1993), turbulence index 1 and 2 (Ellrod & Knapp, 1992),negative vorticity advection (Sharman et al., 2006), and Brown’s Richardson tendencyequation (Brown, 1973).4. Converting turbulence diagnostic values into the eddy dissipation rate (EDR) — the International Civil Aviation Organization’s (ICAO) official metric for reporting turbulence (Meteorological Service for International Air Navigati
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Journal articleZhao J, Paschalis A, Gentine P, et al., 2025,
Limited capability of current satellite solar-induced chlorophyll fluorescence reconstructions to capture stomatal responses to environmental stresses
, Communications Earth & Environment -
Journal articleLavergne A, Harrison SP, Atsawawaranunt K, et al., 2025,
Minimal impact of recent decline in C4 vegetation abundance on atmospheric carbon isotopic composition
, Communications Earth & Environment, ISSN: 2662-4435Changes in atmospheric carbon dioxide concentrations, climate, and land management influence the abundance and distribution of C3 and C4 plants, yet their impact on the global carbon cycle remains uncertain. Here, we use a parsimonious model of C3 and C4 plant distribution, based on optimality principles, combined with a simplified representation of the global carbon cycle, to assess how shifts in plant abundances driven by carbon dioxide and climate affect global gross primary production, land-based carbon isotope discrimination, and the isotopic composition of atmospheric carbon dioxide. We estimate that the proportion of C4 plants in total biomass declined from about 16% to 12% between 1982 and 2016, despite an increase in the abundance of C4 crops. This decline reflects the reduced competitive advantage of C4 photosynthesis in a carbon dioxide-enriched atmosphere. As a result, global gross primary production rose by approximately 16.5 ± 1.8 petagrams of carbon, and land-based carbon isotope discrimination increased by 0.017 ± 0.001‰ per year. Accounting for changes in C3 and C4 abundances reduces the difference between observed and modelled trends in atmospheric carbon isotope composition, but does not fully explain the observed decrease, pointing to additional, unaccounted drivers.
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Journal articleHeon SP, Bernard H, Ewers RM, 2025,
Decomposition dynamics of an orangutan (Pongo pygmaeus morio) carcass in a tropical forest: implications for conservation practices
, Ecology and Evolution, Vol: 15, ISSN: 2045-7758Over the past decade, more than 600 rehabilitated Bornean Orangutans (Pongo pygmaeus morio) have been released into protected forests in Borneo. Releasing rehabilitant Bornean Orangutans into the wild is a standard conservation practice, yet monitoring postrelease survival remains a challenge. Limited data exist on post release survival, with many individuals classified as “missing but presumed dead” due to the absence of a carcass for confirmation. Detecting carcasses in tropical forests is particularly difficult due to dense vegetation and the narrow time frame for observing remains before complete decomposition or scavenger removal. Here, we report the first documented observation of a wild adult female Bornean Orangutan carcass decomposing process in the Danum Valley Conservation Area, Malaysian Borneo, on 21 May 2023. The approximately 30 kg carcass was monitored using camera traps and field observations. Decomposition was assessed using Payne's (1965) decomposition framework, the Total Body Score (TBS) system, and Accumulated Degree Days (ADD) to evaluate the influence of ambient temperature on decay. Decomposition progressed to the dry-remains stage within 6 days, primarily driven by vertebrate scavengers such as the Asian water monitor lizard (Varanus salvator) and blow flies (Calliphoridae). This rapid decomposition rate challenges existing knowledge on the rate of decomposition of medium-sized carcasses (> 10 kg) and suggests that the common practice of weekly monitoring for post-release orangutans may be insufficient. Understanding decomposition processes and scavenger activity in tropical forests can improve carcass detection, refine mortality estimates for released Orangutans and other endangered species, and enhance conservation strategies for this critically endangered primate.
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