Publications

Search or filter publications

Search publications Search

Filter by type:

Filter by publication type

• Book
• Book chapter
• Conference paper
• Journal article
• Other
• Patent
• Poster
• Report
• Scholarly edition
• Software
• Thesis dissertation
• Working paper

Filter by year:

Filter from 202620252024202320222021202020192018201720162015201420132012201120102009200820072006200520042003200220012000199919981997199619951994199319921991199019891988198719861985198419831982198119801979197819771976197519741973197219711970 to Filter to 202620252024202320222021202020192018201720162015201420132012201120102009200820072006200520042003200220012000199919981997199619951994199319921991199019891988198719861985198419831982198119801979197819771976197519741973197219711970

---

Search results

• Other
  Hvidtfeldt UA, Chen J, Rodopoulou S, Strak M, de Hoogh K, Andersen ZJ, Bellander T, Brandt J, Fecht D, Forastiere F, Gulliver J, Hertel O, Hoffmann BH, Katsouyanni K, Ketzel M, Brynedal B, Leander K, Ljungman PLS, Magnusson PKE, Nagel G, Pershagen G, Rizzuto D, Boutron-Ruault M-C, Samoli E, So R, Stafoggia M, Tjønneland A, Vermeulen R, Verschuren WMM, Weinmayr G, Wolf K, Zhang J, Zitt E, Brunekreef B, Hoek G, Raaschou-Nielsen Oet al., 2025,

  Figure S3 from Breast Cancer Incidence in Relation to Long-Term Low-Level Exposure to Air Pollution in the ELAPSE Pooled Cohort

  <jats:p>&lt;p&gt;Supplementary Figure S3 shows the results from single- and multi-pollutant models and the cumulative risk index for breast cancer&lt;/p&gt;</jats:p>

  • Abstract
  • Publisher Web Link
  • Cite
• Other
  Hvidtfeldt UA, Chen J, Rodopoulou S, Strak M, de Hoogh K, Andersen ZJ, Bellander T, Brandt J, Fecht D, Forastiere F, Gulliver J, Hertel O, Hoffmann BH, Katsouyanni K, Ketzel M, Brynedal B, Leander K, Ljungman PLS, Magnusson PKE, Nagel G, Pershagen G, Rizzuto D, Boutron-Ruault M-C, Samoli E, So R, Stafoggia M, Tjønneland A, Vermeulen R, Verschuren WMM, Weinmayr G, Wolf K, Zhang J, Zitt E, Brunekreef B, Hoek G, Raaschou-Nielsen Oet al., 2025,

  Figure S4 from Breast Cancer Incidence in Relation to Long-Term Low-Level Exposure to Air Pollution in the ELAPSE Pooled Cohort

  <jats:p>&lt;p&gt;Supplementary Figure S4 shows the natural cubic splines for air pollutants and breast cancer incidence&lt;/p&gt;</jats:p>

  • Abstract
  • Publisher Web Link
  • Cite
• Journal article
  Christen P, Michalow J, Naidoo T, Topazian H, van Elsland SL, Arif AM, Baguelin M, Clunie G, Essilfie-Quaye S, Fecht D, Garske T, Hassounah S, Husbands J, Kwok W, Leuba S, McCormack C, Mitchell KM, Pianella M, Pickles M, Ruybal S-P, Schmit N, Udeh-Momoh C, Cori A, Blake I, Okell LCet al., 2025,

  Examining gender and ethnic disparities in scientific authorship to promote a culture of equity, diversity and inclusion at a university school of public health

  , Proceedings of the Royal Society of London. Biological Sciences, Vol: 292, ISSN: 0962-8452

  In public health research, diverse perspectives are vital to identify biases that homogenous teams might miss. Since publication metrics influence career progression, we investigated publication rate disparities within a School of Public Health. We analysed 18 322 peer-reviewed publications by 513 affiliated researchers between 2014 and 2023 using multivariable regression models and network analysis to assess the impact of gender, ethnicity, job level and centrality in the School’s research network on publication rates. We found a persistent gender gap in publication rates across job levels and ethnicities, with men publishing more than women (incidence rate ratio 1.30, 95% confidence interval (CI): 1.15–1.46). This disparity was present from early career levels and amplified in senior roles, where men were over-represented (71.2% of men at Professor level). Unadjusted analyses indicated higher publication rates for white researchers (median of one publication more per person per year). The COVID-19 pandemic led to increased publication rates for both genders, but the gender gap persisted, with men publishing 1.27 (95% CI: 1.10–1.46) times more than women in 2020/2021. This study underscores the need to identify and address root causes of these disparities to foster an inclusive research environment where diverse contributions are recognized and valued.

  • Abstract
  • Publisher Web Link
  • Cite
• Other
  Hvidtfeldt UA, Chen J, Rodopoulou S, Strak M, de Hoogh K, Andersen ZJ, Bellander T, Brandt J, Fecht D, Forastiere F, Gulliver J, Hertel O, Hoffmann BH, Katsouyanni K, Ketzel M, Brynedal B, Leander K, Ljungman PLS, Magnusson PKE, Nagel G, Pershagen G, Rizzuto D, Boutron-Ruault M-C, Samoli E, So R, Stafoggia M, Tjønneland A, Vermeulen R, Verschuren WMM, Weinmayr G, Wolf K, Zhang J, Zitt E, Brunekreef B, Hoek G, Raaschou-Nielsen Oet al., 2025,

  Table S1 from Breast Cancer Incidence in Relation to Long-Term Low-Level Exposure to Air Pollution in the ELAPSE Pooled Cohort

  <jats:p>&lt;p&gt;Supplementary Table S1 shows Spearman correlations per (sub) cohort between NO2, PM2.5, BC, and O3 (warm season) among participants with full information in the main model&lt;/p&gt;</jats:p>

  • Abstract
  • Publisher Web Link
  • Cite
• Other
  Hvidtfeldt UA, Chen J, Rodopoulou S, Strak M, de Hoogh K, Andersen ZJ, Bellander T, Brandt J, Fecht D, Forastiere F, Gulliver J, Hertel O, Hoffmann BH, Katsouyanni K, Ketzel M, Brynedal B, Leander K, Ljungman PLS, Magnusson PKE, Nagel G, Pershagen G, Rizzuto D, Boutron-Ruault M-C, Samoli E, So R, Stafoggia M, Tjønneland A, Vermeulen R, Verschuren WMM, Weinmayr G, Wolf K, Zhang J, Zitt E, Brunekreef B, Hoek G, Raaschou-Nielsen Oet al., 2025,

  Figure S1 from Breast Cancer Incidence in Relation to Long-Term Low-Level Exposure to Air Pollution in the ELAPSE Pooled Cohort

  <jats:p>&lt;p&gt;Supplementary Figure S1 shows box plots of exposures by individual (sub-) cohort study.&lt;/p&gt;</jats:p>

  • Abstract
  • Publisher Web Link
  • Cite
• Other
  Hvidtfeldt UA, Chen J, Rodopoulou S, Strak M, de Hoogh K, Andersen ZJ, Bellander T, Brandt J, Fecht D, Forastiere F, Gulliver J, Hertel O, Hoffmann BH, Katsouyanni K, Ketzel M, Brynedal B, Leander K, Ljungman PLS, Magnusson PKE, Nagel G, Pershagen G, Rizzuto D, Boutron-Ruault M-C, Samoli E, So R, Stafoggia M, Tjønneland A, Vermeulen R, Verschuren WMM, Weinmayr G, Wolf K, Zhang J, Zitt E, Brunekreef B, Hoek G, Raaschou-Nielsen Oet 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>&lt;div&gt;AbstractBackground:&lt;p&gt;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.&lt;/p&gt;Methods:&lt;p&gt;We conducted a pooled analysis among six European cohorts (&lt;i&gt;n&lt;/i&gt; = 199,719) on the association between long-term residential levels of ambient nitrogen dioxide (NO&lt;sub&gt;2&lt;/sub&gt;), fine particles (PM&lt;sub&gt;2.5&lt;/sub&gt;), black carbon (BC), and ozone in the warm season (O&lt;sub&gt;3&lt;/sub&gt;) 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.&lt;/p&gt;Results:&lt;p&gt;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&lt;sub&gt;2&lt;/sub&gt;, 1.06 (1.01–1.11) per 5 μg/m³ PM&lt;sub&gt;2.5&lt;/sub&gt;, 1.03 (0.99–1.06) per 0.5 10&lt;sup&gt;−5&lt;/sup&gt; m&lt;sup&gt;−1&lt;/sup&gt; BC, and 0.98 (0.94–1.01) per 10 μg/m³ O&lt;sub&gt;3&lt;/sub&gt;. The effect estimates were most pronounced in the group of middle-aged women (50–54 years) and among never smokers.&lt;/p&gt;Conclusions:&lt;p&gt;The resu

  • Abstract
  • Publisher Web Link
  • Cite
• Other
  Hvidtfeldt UA, Chen J, Rodopoulou S, Strak M, de Hoogh K, Andersen ZJ, Bellander T, Brandt J, Fecht D, Forastiere F, Gulliver J, Hertel O, Hoffmann BH, Katsouyanni K, Ketzel M, Brynedal B, Leander K, Ljungman PLS, Magnusson PKE, Nagel G, Pershagen G, Rizzuto D, Boutron-Ruault M-C, Samoli E, So R, Stafoggia M, Tjønneland A, Vermeulen R, Verschuren WMM, Weinmayr G, Wolf K, Zhang J, Zitt E, Brunekreef B, Hoek G, Raaschou-Nielsen Oet 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>&lt;p&gt;Supplementary Figure S2 shows the results of the two-pollutant models of single and co-pollutants and breast cancer&lt;/p&gt;</jats:p>

  • Abstract
  • Publisher Web Link
  • Cite
• Conference paper
  Lin 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 Recognition

  Obtaining 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/.

  • Abstract
  • Cite
• Journal article
  Williams RG, Goodwin P, Ceppi P, Jones CD, MacDougall AHet al., 2025,

  A normalised framework for the Zero Emissions Commitment

  , BIOGEOSCIENCES, Vol: 22, Pages: 7167-7186, ISSN: 1726-4170
  • Cite
• Journal article
  Driver 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: 1680-7316

  Contrails 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.

  • Abstract
  • Publisher Web Link
  • Cite

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.