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OtherHvidtfeldt UA, Chen J, Rodopoulou S, et al., 2025,
Data from Breast Cancer Incidence in Relation to Long-Term Low-Level Exposure to Air Pollution in the ELAPSE Pooled Cohort
<jats:p><div>AbstractBackground:<p>Established risk factors for breast cancer include genetic disposition, reproductive factors, hormone therapy, and lifestyle-related factors such as alcohol consumption, physical inactivity, smoking, and obesity. More recently a role of environmental exposures, including air pollution, has also been suggested. The aim of this study, was to investigate the relationship between long-term air pollution exposure and breast cancer incidence.</p>Methods:<p>We conducted a pooled analysis among six European cohorts (<i>n</i> = 199,719) on the association between long-term residential levels of ambient nitrogen dioxide (NO<sub>2</sub>), fine particles (PM<sub>2.5</sub>), black carbon (BC), and ozone in the warm season (O<sub>3</sub>) and breast cancer incidence in women. The selected cohorts represented the lower range of air pollutant concentrations in Europe. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level.</p>Results:<p>During 3,592,885 person-years of follow-up, we observed a total of 9,659 incident breast cancer cases. The results of the fully adjusted linear analyses showed a HR (95% confidence interval) of 1.03 (1.00–1.06) per 10 μg/m³ NO<sub>2</sub>, 1.06 (1.01–1.11) per 5 μg/m³ PM<sub>2.5</sub>, 1.03 (0.99–1.06) per 0.5 10<sup>−5</sup> m<sup>−1</sup> BC, and 0.98 (0.94–1.01) per 10 μg/m³ O<sub>3</sub>. The effect estimates were most pronounced in the group of middle-aged women (50–54 years) and among never smokers.</p>Conclusions:<p>The resu
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OtherHvidtfeldt UA, Chen J, Rodopoulou S, et al., 2025,
Figure S2 from Breast Cancer Incidence in Relation to Long-Term Low-Level Exposure to Air Pollution in the ELAPSE Pooled Cohort
<jats:p><p>Supplementary Figure S2 shows the results of the two-pollutant models of single and co-pollutants and breast cancer</p></jats:p>
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Conference paperLin J, Gryspeerdt E, Clark R, 2025,
Cloud-stereo: a dataset and benchmark for reconstructing atmospheric clouds from stereo images
, BMVC 2025, Publisher: The British Machine Vision Association and Society for Pattern RecognitionObtaining accurate measurements of clouds is a critical problem in atmospheric physics, as accurate modeling of cloud properties allows us to better understand and predict climate change. Stereo camera networks have shown promise in obtaining such measurements, being able to reconstruct detailed cloud fields over multi-km$^2$ domains. However, previous studies on cloud stereo depth estimation have been limited to using traditional (non-learned) matching techniques, due to the absence of suitable training datasets for this challenging domain. In this work, we present a novel dataset (Cloud-Stereo) specifically tailored for cloud depth estimation. The Cloud-Stereo dataset includes: 1) a synthetic dataset for training, comprising 3000 stereo pairs and simulated dense LiDAR depth data, and 2) a high-accuracy real-world dataset consisting of $\approx 120k$ frames acquired from a stereo camera and Doppler Aerosol LiDAR for testing. Using our dataset we benchmark existing learning and non-learning based stereo depth estimation approaches, and demonstrate that fine-tuning on our dataset can lead to significant accuracy improvement for learned methods. We believe this dataset will enable the training of future, more accurate, methods for cloud field reconstruction, enhancing a unique measurement capability for developing and evaluating atmospheric models. The dataset is available at https://cloud-stereo.jacob-lin.com/.
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Journal articleWilliams RG, Goodwin P, Ceppi P, et al., 2025,
A normalised framework for the Zero Emissions Commitment
, BIOGEOSCIENCES, Vol: 22, Pages: 7167-7186, ISSN: 1726-4170 -
Journal articleDriver OGA, Stettler MEJ, Gryspeerdt E, 2025,
The ice supersaturation biases limiting contrail modelling are structured around extratropical depressions
, Atmospheric Chemistry and Physics (ACP), Vol: 25, Pages: 16411-16433, ISSN: 1680-7316Contrails are ice clouds formed along aircraft flight tracks, responsible for much of aviation's climate warming impact. Ice-supersaturated regions (ISSRs) provide conditions where contrail ice crystals can persist, but meteorological models often mispredict their occurrence, limiting contrail modelling. This deficiency is often treated by applying local humidity corrections. However, model performance is also affected by synoptic conditions (such as extratropical depressions).Here, composites of ERA5 reanalysis data around North Atlantic extratropical depressions enable a link between their structure and ISSR modelling. ISSRs are structured by these systems: at flight levels, ISSRs occur less frequently in the dry intrusion – descending upper-tropospheric air – than above warm conveyors – where air is lifted. Both ERA5 reanalysis and in situ aircraft observations show this contrast, demonstrating that the model reproduces the fundamental relationship. Individual-ISSR modelling performance (quantified using interpretable metrics) is also structured. Of the rare ISSRs diagnosed in the location associated with the dry intrusion, fewer are confirmed by in situ observations (20 %–25 % precision drop compared to the warm conveyor) and fewer of those observed were diagnosed (13 %–19 % recall drop). Scaling humidity beyond the occurrence rate bias dramatically increases the recall at low precision cost, demonstrating the potential value of scaling approaches designed with different intentions. However, the failure of scaling to improve precision, or the performance in the dry intrusion, implies that there is a need to account for the synoptic weather situation and structure in order to improve ISSR forecasts in support of mitigating aviation's climate impact.
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Journal articleXu H, Chen Y, Cao R, et al., 2025,
Generative discovery of partial differential equations by learning from math handbooks
, Nature Communications, Vol: 16, ISSN: 2041-1723Data-driven discovery of partial differential equations (PDEs) is a promising approach for uncovering the underlying laws governing complex systems. However, purely data-driven techniques face the dilemma of balancing search space with optimization efficiency. This study introduces a knowledge-guided approach that incorporates existing PDEs documented in a mathematical handbook to facilitate the discovery process. These PDEs are encoded as sentence-like structures composed of operators and basic terms, and used to train a generative model, called EqGPT, which enables the generation of free-form PDEs. A loop of “generation–evaluation–optimization” is constructed to autonomously identify the most suitable PDE. Experimental results demonstrate that this framework can recover a variety of PDE forms with high accuracy and computational efficiency, particularly in cases involving complex temporal derivatives or intricate spatial terms, which are often beyond the reach of conventional methods. The approach also exhibits generalizability to irregular spatial domains and higher dimensional settings. Notably, it succeeds in discovering a previously unreported PDE governing strongly nonlinear surface gravity waves propagating toward breaking, based on real-world experimental data, highlighting its applicability to practical scenarios and its potential to support scientific discovery.
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Journal articlePugsley G, Gryspeerdt E, Nair V, 2025,
Cloud fraction response to aerosol driven by nighttime processes
, Proceedings of the National Academy of Sciences of USA, ISSN: 0027-8424 -
Journal articleBjørnestad M, Halsne T, Malila M, et al., 2025,
Whitecaps, bubbles and advection: insights from concurrent measurements in the open ocean
, Geophysical Research Letters, Vol: 52, ISSN: 0094-8276Field measurements of breaking waves and bubble depths were obtained using a stereo video system collocated with a submerged acoustic Doppler current profiler (ADCP) in the central North Sea. We discriminate between two bubble depths that define an active near-surface layer and a deeper layer. The active layer intermittently sees short-lived injected bubble depths from breakers whereas the deeper layer is dominated by persistent passive bubble plumes that remain visible for more than 50 mean wave periods. We augment traditional single-beam bubble detection methods by utilizing all five beams of the ADCP to achieve broader spatial coverage of bubble plume measurements. The combined wave and bubble observations reveal that deep bubble plumes often occur offset spatially from surface whitecaps, suggesting that Langmuir-type circulation plays a role in the formation and persistence of deep bubble plumes through vertical and horizontal advection.
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Journal articleChen J, Kang Y, Toumi R, et al., 2025,
Increasing Temporal Variability of Global Tropical Cyclone Near-Storm Rainfall Under Global Warming: Insights From CMIP6 HighResMIP Simulations
, JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, Vol: 130, ISSN: 2169-897X -
Journal articleTalepour N, Birgani YT, Kelly FJ, et al., 2025,
Ambient PM2.5: health policy implications and management in Khuzestan, Iran
, Science of the Total Environment, Vol: 1004, ISSN: 0048-9697Ambient fine particulate matter (PM2.5) is a major environmental risk for premature mortality worldwide. This study quantifies the health and economic impacts of PM2.5 exposure in Khuzestan Province of Iran. This study quantifies the health and economic impacts of PM2.5 exposure in Khuzestan Province, Iran. Validated daily PM2.5 data from eight monitoring stations in 2021 were preprocessed, including outlier removal and gap-filling using a PM10-to-PM2.5 conversion factor of 0.45. Population data were projected from the 2016 census. The U.S. EPA's BenMAP-CE tool was used to estimate avoidable premature deaths under two PM2.5 reduction scenarios (10 and 5 μg/m3). This study assessed mortality for five outcomes: acute lower respiratory infections (ALRI), ischemic heart disease (IHD), chronic obstructive pulmonary disease (COPD), lung cancer (LC), stroke, and all-cause mortality. Economic valuation employed the value of statistical life (VSL), adjusted for Iran's GDP. PM2.5 concentrations (30–55 μg/m3) surpassed WHO limits by 6–11 times, especially in Ahvaz and Omidiyeh. A total of 3174 avoidable deaths per 100,000 were estimated annually under the WHO's 5 μg/m3 guidelines. Among diseases, ischemic heart disease (IHD) accounted for the largest share of avoidable deaths (≈38 %), followed by stroke (≈23 %) and all-cause mortality (≈18 %). The annual economic benefits of reducing PM2.5 under the 5 μg/m3 scenario were estimated at USD 46–236.4 million. The greatest health and economic benefits from improved air quality are expected in Ahvaz (central Khuzestan) and Dezful (north), followed by Abadan and Bandar-e-Mahshahr (southwest). This study highlights the high PM2.5 burden in Khuzestan's urban and industrial centers. Targeted air quality policies in these areas could bring significant health and economic benefits. The results provide a solid basis for targeted policies, including stricter emission controls in high-burden re
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