High resolution mapping of nitrogen dioxide and particulate matter in Great Britain (2003–2021) with multi-stage data reconstruction and ensemble machine learning methods

This publication has 53 references indexed in Scilit:

• Predicting fine-scale daily NO2 over Mexico city using an ensemble modeling approach
  Atmospheric Pollution Research, 2023
• A comparison of statistical and machine-learning approaches for spatiotemporal modeling of nitrogen dioxide across Switzerland
  Atmospheric Pollution Research, 2022
• Predicting daily concentrations of nitrogen dioxide, particulate matter and ozone at fine spatial scale in Great Britain
  Atmospheric Pollution Research, 2022
• The ERA5 global reanalysis
  Quarterly Journal of the Royal Meteorological Society, 2020
• Particle concentrations, dispersion modelling and evaluation in southern Sweden
  SN Applied Sciences, 2020
• Comparative Evaluation of Air Quality Dispersion Models for PM2.5 at Air Quality Control Regions in Indian and UK Cities
  MAPAN, 2015
• Examination of geostatistical and machine-learning techniques as interpolators in anisotropic atmospheric environments
  Atmospheric Environment, 2015
• A review of land-use regression models to assess spatial variation of outdoor air pollution
  Atmospheric Environment, 2008
• A review of dispersion modelling and its application to the dispersion of particles: An overview of different dispersion models available
  Atmospheric Environment, 2006
• Stacked regressions
  Machine Learning, 1996