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Bayesian geostatistical modelling of high-resolution [Formula: see text] 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...
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| Publicado no: | Environ Int |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Elsevier Science
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7152800/ https://ncbi.nlm.nih.gov/pubmed/32179313 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.envint.2020.105578 |
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