LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Predicting Fine-Scale Daily NO2 for 2005-2016 Incorporating OMI Satellite Data Across Switzerland.

Photo by calum_mac from unsplash

Nitrogen dioxide (NO2) remains an important traffic-related pollutant associated with both short- and long-term health effects. We aim to model daily average NO2 concentrations in Switzerland in a multistage framework… Click to show full abstract

Nitrogen dioxide (NO2) remains an important traffic-related pollutant associated with both short- and long-term health effects. We aim to model daily average NO2 concentrations in Switzerland in a multistage framework with mixed-effect and random forest models to respectively downscale satellite measurements and incorporate local sources. Spatial and temporal predictor variables include data from the Ozone Monitoring Instrument, Copernicus Atmosphere Monitoring Service, land use, and meteorological variables. We derived robust models explaining ∼58% (R2 range, 0.56-0.64) of the variation in measured NO2 concentrations using mixed-effect models at a 1 × 1 km resolution. The random forest models explained ∼73% (R2 range, 0.70-0.75) of the overall variation in the residuals at a 100 × 100 m resolution. This is one of the first studies showing the potential of using earth observation data to develop robust models with fine-scale spatial (100 × 100 m) and temporal (daily) variation of NO2 across Switzerland from 2005 to 2016. The novelty of this study is in demonstrating that methods originally developed for particulate matter can also successfully be applied to NO2. The predicted NO2 concentrations will be made available to facilitate health research in Switzerland.

Keywords: no2; 2005 2016; fine scale; switzerland; across switzerland; no2 concentrations

Journal Title: Environmental science & technology
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.