Spatial patterns and temporal variations of pollutants at 56 air quality monitoring stations in the state of São Paulo, Brazil

Author:

Godoy Angela Rosa LocateliORCID,da Silva Ana Estela Antunes

Publisher

Springer Science and Business Media LLC

Subject

Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine

Reference95 articles.

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2. Aggarwal, C. C., & Reddy, C. K. (2013). Data Clustering: Algorithms and applications. CRC Press, (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series).

3. Aghabozorgi, S., Shirkhorshidi, A. S., Wah, T. Y., Soltanian, H., & Herawan, T. (2015) Spatial and temporal clustering of air pollution in Malaysia: A review. International Conference on Agriculture, Environment and Biological Sciences. Antalya, Turkey, 213 – 219.

4. Agrawal, R., & Srikant, R. (1994). Fast Algorithms for mining association rules in large databases. In: International conference on very large data bases, 20. VLDB, Santiago de Chile, 12–15, 487–499.

5. Araújo, J., & Rosário, N. (2020). Poluição atmosférica associada ao material particulado no estado de São Paulo: Análise baseada em dados de satélite. Revista Brasileira De Ciências Ambientais (online), 55(1), 32–47. https://doi.org/10.5327/Z2176-947820200552

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