Tootfinder

Modelling laminar flow in V-shaped filters integrated with catalyst technologies for atmospheric pollutant removal
Samuel D. Tomlinson, Aliki M. Tsopelakou, Tzia M. Onn, Steven R. H. Barrett, Adam M. Boies, Shaun D. Fitzgerald
https://arxiv.org/abs/2506.00603

Modelling laminar flow in V-shaped filters integrated with catalyst technologies for atmospheric pollutant removal
Atmospheric pollution from particulate matter, volatile organic compounds and greenhouse gases is a critical environmental and public health issue, leading to respiratory diseases and climate change. A potential mitigation strategy involves utilising ventilation systems, which process large volumes of indoor and outdoor air and remove particulate pollutants through filtration. However, the integration of catalytic technologies with filters in ventilation systems remains underexplored, despite t…

Unexpected good news on the grant funding front...
Means I can stop worrying about how we're going to pay the best polar regional climate modelling team in the world™️ for the next 3 years and focus on doing some actually really good, cool science™️.
To be continued...
#AcademicChatter #climate

Joint space-time modelling for upper daily maximum and minimum temperature record-breaking
Jorge Castillo-Mateo (University of Zaragoza), Zeus Gracia-Tabuenca (University of Zaragoza), Jes\'us As\'in (University of Zaragoza), Ana C. Cebri\'an (University of Zaragoza), Alan E. Gelfand (Duke University)
https://arxiv.o…

Joint space-time modelling for upper daily maximum and minimum temperature record-breaking
Record-breaking temperature events are now frequently in the news, proffered as evidence of climate change, and often bring significant economic and human impacts. Our previous work undertook the first substantial spatial modelling investigation of temperature record-breaking across years for any given day within the year, employing a dataset consisting of over sixty years of daily maximum temperatures across peninsular Spain. That dataset also supplies daily minimum temperatures (which, in fac…

Linking climate and dengue in the Philippines using a two-stage Bayesian spatio-temporal model
Stephen Jun Villejo, Sara Martino, Janine Illian
https://arxiv.org/abs/2506.22334

Linking climate and dengue in the Philippines using a two-stage Bayesian spatio-temporal model
Dengue is an infectious disease which poses significant socioeconomic and disease burden in many tropical and subtropical regions of the world. This work aims to provide additional insight into the association between dengue and climate in the Philippines. We employ a two-stage modelling framework: the first stage fits climate models, while the second stage fits a health model that uses the climate predictions from the first stage as inputs. We postulate a Bayesian spatio-temporal model and use…

Low-EFFourth: A computational framework for generating and studying multilevel model ensembles in low-dimensional systems
Francisco de Melo Vir\'issimo
https://arxiv.org/abs/2506.03313

Low-EFFourth: A computational framework for generating and studying multilevel model ensembles in low-dimensional systems
This paper introduces Low-EFFourth (LEF4), a MATLAB-based computational framework designed for generating and studying multilevel model ensembles in continuous dynamical systems. Initially developed to address questions in climate modelling, LEF4 can also be used in other disciplines such as epidemiology, economics, and engineering, with minimal modifications to the code. The framework provides an efficient and flexible approach for investigating uncertainties arising from initial conditions, m…

A Bayesian Spatio-Temporal Model of Temperature- and Humidity-Related Mortality Using High-Resolution Climate Data
Corinna Perchtold, Julia Eisenberg, Philipp Otto
https://arxiv.org/abs/2507.12643

A Bayesian Spatio-Temporal Model of Temperature- and Humidity-Related Mortality Using High-Resolution Climate Data
In this study, we introduce a novel and comprehensive extension of a Bayesian spatio-temporal disease mapping model that explicitly accounts for gender-specific effects of meteorological exposures. Leveraging fine-scale weekly mortality and high-resolution climate data from Austria (2002 to 2019), we assess how interactions between temperature, humidity, age, and gender influence mortality patterns. Our approach goes beyond conventional modelling by capturing complex dependencies through struct…