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Uncertainty assessment of PM(2.5) contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data
Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environ...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4828716/ https://www.ncbi.nlm.nih.gov/pubmed/27067017 http://dx.doi.org/10.1038/srep24335 |