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Journal articleWarder SC, Piggott MD, 2025,
The future of offshore wind power production: Wake and climate impacts
, Applied Energy, Vol: 380, ISSN: 0306-2619Rapid deployment of offshore wind is expected within the coming decades to help meet climate goals. With offshore wind turbine lifetimes of 25–30 years, and new offshore leases spanning 60 years, it is vital to consider long-term changes in potential wind power resource at the farm planning stage. Such changes may arise from multiple sources, including climate change, and increasing wake-induced power losses. In this work, we investigate and compare these two sources of long-term change in wind power, for a case study consisting of 21 wind farms within the German Bight. Consistent with previous studies, we find a small but significant reduction in wind resource due to climate change by the end of the 21st century under the high-emission RCP8.5 scenario, compared with a historical period, with a mean power reduction (over an ensemble of seven climate models) of 2.1%. To assess the impact of wake-induced losses due to increasingly dense farm build-out, we model wakes within the German Bight region using an engineering wake model, under various stages of (planned) build-out corresponding to the years 2010–2027. By identifying clusters of wind farms, we decompose wake effects into long-range (inter-cluster), medium-range (intra-cluster) and short-range (intra-farm) effects. Inter-cluster wake-induced losses increase from 0 for the 2010 scenario to 2.5% for the 2027 scenario, with intra-cluster losses also increasing from 0 to 4.3%. Intra-farm losses are relatively constant, at around 13%. While the evolution of wake effects therefore outweighs the climate effect, and impacts over a shorter timescale, both factors are significant. We also find evidence of an interaction between the climate and wake effects. Both climate change and evolving wake effects must therefore be considered within resource assessment and wind farm planning.
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Journal articledo Prado AH, Mair D, Garefalakis P, et al., 2025,
The influence of grain size sorting on the roughness parametrization of gravel riverbeds
, Geomorphology, Vol: 471, ISSN: 0169-555XGrain size and surface roughness play crucial roles in modelling flow resistance and boundary shear stress in fluvial systems. However, the impact of grain size sorting on surface roughness, particularly for gravel-bed rivers composed of poorly-sorted sediments, has yet to be elucidated. Here we utilize a stochastic model to simulate generic riverbed surfaces, investigating the influence of sediment sorting on roughness. Through comparison with field-acquired data, we explore the relationships between grain size, sorting, presence of textural patches, and local roughness. Our analysis reveals significant spatial roughness variations on surfaces with poorer sorting conditions, driven by stochastic grain arrangements. Notably, surfaces with poorly sorted grains exhibit meter-scale patches, each with distinct roughness attributes. Consequently, upon characterizing the roughness of riverbeds made up of m-scale gravel bars, the sorting of the grains needs to be considered to account for the complexity of the relationships between water flow and riverbed.
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Journal articleMohammadpour A, Paluszny A, Zimmerman RW, 2025,
A robust 3D finite element framework for monolithically coupled thermo-hydro-mechanical analysis of fracture growth with frictional contact in porous media
, Computer Methods in Applied Mechanics and Engineering, Vol: 434, ISSN: 0045-7825This paper presents the formulation of a robust integrated framework for the coupled multiphysics and multiple fracture growth analysis in porous media. The finite element-based thermo-hydro-mechanical method for fracture growth with frictional contact (THMf-g) simultaneously solves monolithically coupled equations, incorporating contact and frictional constraints from fracture sliding. It also implements an adaptive process to update fields and geometries during fracture growth, effectively modeling emerging new surfaces. The thermo-hydro-mechanical fields are derived from fundamental principles of mass, momentum, and energy conservation and discretized numerically using the finite element method. Fractures are represented as sub-dimensional surfaces embedded within the volume of the porous medium. The growth of multiple fracture is modeled based on stress intensity factors at fracture tips, with fracture aperture and permeability emerging as dynamic properties of the system. The main novelty of this work lies in extending the implicitly solved monolithic coupling to include frictional and growth modeling for multiple non-planar fractures of emerging geometry in three dimensions. This includes the direct incorporation of cubic terms in the fracture flow equations and convection terms in the heat transfer equations, adopting an incremental method to solve these coupled, nonlinear equations. To ensure energy conservation, the heat equations are resolved using an implicit scheme, establishing a velocity dependency on pressure fields and introducing quadratic terms into the heat equation. Furthermore, the heat transfer equation has been revised to account for the work done on the fluid, enhancing the accuracy of thermal modeling. A contact mechanics leader–follower strategy tracks a conformal mesh split at each fracture, accounting explicitly for permeability changes during deformation and growth, effectively reducing computational complexity and cost. The iterat
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Journal articlePang B, Cheng S, Huang Y, et al., 2025,
Fire-Image-DenseNet (FIDN) for predicting wildfire burnt area using remote sensing data
, Computers and Geosciences, Vol: 195, ISSN: 0098-3004Predicting the extent of massive wildfires once ignited is essential to reduce the subsequent socioeconomic losses and environmental damage, but challenging because of the complexity of fire behavior. Existing physics-based models are limited in predicting large or long-duration wildfire events. Here, we develop a deep-learning-based predictive model, Fire-Image-DenseNet (FIDN), that uses spatial features derived from both near real-time and reanalysis data on the environmental and meteorological drivers of wildfire. We trained and tested this model using more than 300 individual wildfires that occurred between 2012 and 2019 in the western US. In contrast to existing models, the performance of FIDN does not degrade with fire size or duration. Furthermore, it predicts final burnt area accurately even in very heterogeneous landscapes in terms of fuel density and flammability. The FIDN model showed higher accuracy, with a mean squared error (MSE) about 82% and 67% lower than those of the predictive models based on cellular automata (CA) and the minimum travel time (MTT) approaches, respectively. Its structural similarity index measure (SSIM) averages 97%, outperforming the CA and FlamMap MTT models by 6% and 2%, respectively. Additionally, FIDN is approximately three orders of magnitude faster than both CA and MTT models. The enhanced computational efficiency and accuracy advancements offer vital insights for strategic planning and resource allocation for firefighting operations.
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Journal articleBeevers S, 2025,
Climate change policies reduce air pollution and increase physical activity:Benefits, costs, inequalities, and indoor exposures
, Environment International, ISSN: 0160-4120 -
Journal articleWariri O, Utazi CE, Okomo U, et al., 2025,
Multi-level determinants of timely routine childhood vaccinations in The Gambia: Findings from a nationwide analysis
, Vaccine, Vol: 43, ISSN: 0264-410XIntroduction: Achieving the ambitious goals of the Immunisation Agenda 2030 (IA2030) requires a deeper understanding of factors influencing under-vaccination, including timely vaccination. This study investigates the demand- and supply-side determinants influencing the timely uptake of key childhood vaccines scheduled throughout the first year of life in The Gambia. Methods: We used two nationally-representative datasets: the 2019–20 Gambian Demographic and Health Survey and the 2019 national immunisation facility mapping. Using Bayesian multi-level binary logistic regression models, we identified key factors significantly associated with timely vaccination for five key vaccines: birth dose of hepatitis-B (HepB0), first, second, and third doses of the pentavalent vaccine (Penta1, Penta2, Penta3), and first-dose of measles-containing vaccine (MCV1) in children aged 12–35 months. We report the adjusted Odds Ratios (aORs) and 95 % Credible Intervals (95 % CIs) in each case. Results: We found that demand-side factors, such as ethnicity, household wealth status, maternal education, maternal parity, and the duration of the household's residency in its current location, were the most common drivers of timely childhood vaccination. However, supply-side factors such as travel time to the nearest immunisation clinic, availability of cold-storage and staffing numbers in the nearest immunisation clinic were also significant determinants. Furthermore, the determinants varied across specific vaccines and the timing of doses. For example, delivery in a health facility (aOR = 1.58, 95 %CI: 1.02–2.53), living less than 30 min (aOR = 2.11, 95 %CI: 1.2–8.84) and living between 30 and 60 min (aOR = 3.68, 95 %CI: 1.1–14.99) from a fixed-immunisation clinic was associated with timely HepB0, a time-sensitive vaccine that must be administered within 24 h of birth. On the other hand, children who received Penta1 and Penta2 on time were three- to five-fold more
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Journal articleBenmoufok EF, Warder SC, Zhu E, et al., 2024,
Improving wind power modelling through granular spatial and temporal bias correction of reanalysis data
, Energy, Vol: 313, ISSN: 0360-5442There is a need for efficient methods to simulate wind power output to assist the expected rapid uptake of new wind farms. Reanalysis products provide our best estimate for the previous state of the atmosphere and are popular due to their global coverage and convenience. However, these models are known to misestimate wind power output by up to ±50% due to significant spatial biases. Previous work applied bias correction methods to improve power simulations. However, there has been no assessment of the spatial and temporal resolution that these bias correction factors should be derived at for the best accuracy. In this paper, we investigate the impact of the spatial and temporal resolution by grouping turbines into a varying number of clusters and varying the frequency at which correction factors are calculated across a year. The correction factors are used to simulate the power output of 4,834 turbines across Denmark resulting in monthly capacity factors. The best correction scenario decreased the error of simulated outputs by 43%. Increasing the spatial resolution of bias correction reduced the error by up to 11%. Correction factors with a bimonthly (every two months) frequency decreased the error by 3% from the time-independent correction factors.
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Journal articleJagtap SS, Childs PRN, Stettler MEJ, 2024,
Conceptual design-optimisation of a subsonic hydrogen-powered long-range blended-wing-body aircraft
, International Journal of Hydrogen Energy, Vol: 96, Pages: 639-651, ISSN: 0360-3199The adoption of liquid hydrogen (LH2) holds promise for decarbonising long-range aviation. LH2 aircraft could weigh less than Jet-A aircraft, thereby reducing the thrust requirement. However, the lower volumetric energy density of LH2 can adversely impact the aerodynamic performance and energy consumption of tube-wing aircraft. In a first, this work conducts an energy performance modelling of a futuristic (2030+) LH2 blended-wing-body (BWB) aircraft (301 passengers and 13,890 km) using conceptual aircraft design-optimisation approach employing weight-sizing methods, while considering the realistic gravimetric and volumetric energy density effects of LH2 on aircraft design, and the resulting reduction in aircraft thrust requirement. This study shows that at the design point the futuristic LH2 BWB aircraft reduces the specific energy consumption (SEC, MJ/tonne-km) by 51.7–53.5% and 7.3–10.8%, compared to (Jet-A) Boeing 777-200LR and Jet-A BWB, respectively. At the off-design points, this study shows that by increasing the load factor for a given range and/or increasing range for all load factor cases, the SEC (or energy efficiency) of this LH2 BWB concept improves. The results of this work will inform future studies on use-phase emissions and contrails modelling, LH2 aircraft operations for contrail reduction, estimation of operating costs, and lifecycle climate impacts.
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ReportJennings N, Paterson P, Whitmarsh L, et al., 2024,
How have the UK public been affected by extreme heat and what do they think about the risks that it poses in the future?
The Intergovernmental Panel on Climate Change’s Sixth Assessment report concluded that the frequency and intensity of heatwaves and extreme heat has increased globally as a result of climate change. Such extremes of temperature negatively affect people’s physical and mental health.These slides summarise findings from a nationally representative sample (on the basis of age, gender and ethnicity) of 897 people who were asked to share their experience of heatwaves and very hot weather in the UK. The survey was conducted via the platform Prolific.com between 2-4 October 2024.
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Journal articleHarrison JA, Pearce PM, Yang F, et al., 2024,
Evaluating potential power output of terrestrial thermoradiative diodes with atmospheric modelling
, iScience, Vol: 27, ISSN: 2589-0042A thermoradiative diode is a device that can generate power through thermal emission from the warm Earth to the cold night sky. Accurate assessment of the potential power output requires knowledge of the downwelling radiation from the atmosphere. Here, accurate modelling of this radiation is used alongside a detailed balance model of a diode at the Earth’s surface temperature to evaluate its performance under nine different atmospheric conditions. In the radiative limit, these conditions yield power densities between 0.34 and 6.5 W.m-2, with optimal bandgaps near 0.094 eV. Restricting the angles of emission and absorption to less than a full hemisphere can marginally increase the power output. Accounting for non-radiative processes, we suggest that if a 0.094 eV device would have radiative efficiencies more than two orders of magnitude lower than a diode with a bandgap near 0.25 eV, the higher bandgap material is preferred.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.
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