Modelling the effects of meteorological variables on ozone concentration—a quantile regression approach

By Dirk G. Baur, Michaela Saisana, Niels Schulze. 2004

111 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Environmental Engineering, Health, Toxicology and Mutagenesis

View Paper: https://www.semanticscholar.org/paper/da30d26c86fd65ca106a08a1231f4e54843f8da9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Said Munir
2. Alex J. Cannon
3. Turki M. Habeebullah
4. Arwa S. Sayegh

In Environmental Engineering

1. Said Munir
2. Alex J. Cannon
3. Turki M. Habeebullah
4. Arwa S. Sayegh
5. José Manuel Benítez
6. Christoph Bergmeir

In Health, Toxicology and Mutagenesis

1. Said Munir
2. Alex J. Cannon
3. Turki M. Habeebullah
4. J. Sillmann
5. Arwa S. Sayegh

Citations in the corpus

• Comparing the Performance of Statistical Models for Predicting PM10 Concentrations (2014, methodology): “To estimate global metrics for QRM, this study adopts the Amalgamated Quantile Regression Model (AQRM) technique suggested by Baur et al. (2004).”
• Synoptic and meteorological drivers of extreme ozone concentrations over Europe (2016, background): “…et al 2007, Demuzere et al 2009), relative humidity (Dueñas et al 2002, Sousa et al 2008), total cloud cover (Bloomfield et al 1996), solar radiation fluxes (Chaloulakou et al 2003, Baur et al 2004), geopotential height (Camalier et al 2007, Porter et al 2015) and wind speed (Dueñas et al 2002).”
• Quantile regression neural networks: Implementation in R and application to precipitation downscaling (2011, methodology): “…models have been applied in the environmental sciences to climate trend detection (Koenker and Schorfheide, 1994), ozone pollution modelling (Baur et al., 2004), wind power forecasting (Bremnes, 2004b), ecological modelling (Cade and Noon, 2003), and precipitation downscaling (Bremnes,…”