Andrew Beddows

Andrew Beddows is a researcher specializing in environmental epidemiology and air quality modeling. His work focuses on the intersection of air pollution exposure and health outcomes, particularly mental health and psychopathology in adolescents. He has contributed to studies analyzing PM2.5 concentrations, measurement error impacts in pollution data, and the use of machine learning for environmental monitoring.

• Key Affiliation: Collaborator with the European Space Agency (ESA) on air quality projects
• Research Themes: Air pollution health effects, multi-level modeling, machine learning applications

His recent publications include quantitative analyses of childhood air pollution exposure and depression risk in UK adolescents, simulation studies on measurement error in particulate matter data, and PM2.5 concentration prediction models using machine learning techniques in London-based case studies.

He has participated in two ESA-funded projects: the Satellite Air Quality Modelling (SAQM) Demonstration Project (2019-2021) and an earlier SAQM project (2018-2018), serving as a Co-Investigator in both. His methodological expertise spans generalized additive models, multi-level statistical frameworks, and exposure assessment validation.