Network analysis: a novel approach to identify PM2.5 hotspots and their spatio-temporal impact on air quality in Santiago de Chile
Author:
Funder
CONICYT
Publisher
Springer Science and Business Media LLC
Subject
Health, Toxicology and Mutagenesis,Management, Monitoring, Policy and Law,Atmospheric Science,Pollution
Link
https://link.springer.com/content/pdf/10.1007/s11869-020-00862-2.pdf
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3. Díaz-Robles L, Ortega J, Fu J, Reed G, Chow J, Watson J, Moncada J (2008) A hybrid ARIMA and artificial neural networks model to forecast particulate matter in urban areas: The case of temuco, Chile. Atmos. Environ. 42(35):8331–8340. https://doi.org/10.1016/j.atmosenv.2008.07.020
4. Diebold F, Yilmaz K (2014) On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics 182:119–134.
5. Feng X, Li Q, Zhu Y, Hou J, Jin L, Wang J (2015) Artificial neural networks forecasting of PM 2.5 pollution using air mass trajectory based geographic model and wavelet transformation. Atmos. Environ. 107:118–128. https://doi.org/10.1016/j.atmosenv.2015.02.030
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