Bayesian geostatistical modelling of high-resolution NO2 exposure in Europe combining data from monitors, satellites and chemical transport models
Bayesian geostatistical regression (GR) models estimate air pollution exposure at high spatial resolution, quantify the prediction uncertainty and provide probabilistic inference on the exceedance of air quality thresholds. However, due to high computational burden, previous GR models have provided...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-05-01
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| Series: | Environment International |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0160412019324109 |