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Article

Submicron Particles and Micrometeorology in Highly Densified Urban Environments: Heavy-Tailed Probability Study

by
Patricio Pacheco Hernández
1,2,*,
Eduardo Mera Garrido
1,2,
Gustavo Navarro Ahumada
3,
Javier Wachter Chamblas
1,2 and
Steicy Polo Pizan
2
1
Departamento de Física, Facultad de Ciencias Naturales, Matemáticas y Medio Ambiente, Universidad Tecnológica Metropolitana, Las Palmeras 3360, Ñuñoa, Santiago 7750000, Chile
2
Research Laboratory in Environment and Learning, RLEL, Universidad Tecnológica Metropolitana, Underground Building M1, J. P. Alessandri 1242, Ñuñoa, Santiago 7750000, Chile
3
Departamento de Ciencias Exactas, Facultad de Ingeniería, Arquitectura y Diseño, Universidad de San Sebastián, Bellavista 7, Recoleta, Santiago 8420000, Chile
*
Author to whom correspondence should be addressed.
Atmosphere 2025, 16(9), 1044; https://doi.org/10.3390/atmos16091044
Submission received: 1 August 2025 / Revised: 23 August 2025 / Accepted: 29 August 2025 / Published: 2 September 2025
(This article belongs to the Section Air Quality and Health)

Abstract

Submicron particles (SPs), with diameters less than 1.0 μm, are a serious health risk, and urban meteorology variables (MVs), impacted by human activity, can support their sustainability. This study, in a city immersed in a basin geomorphology, is carried out during the summer period of high temperatures and variable relative humidity. An area of high urban density was selected, with the presence of high-rise buildings, urban canyons that favor heat islands, low forestation, intense vehicular traffic, and extreme conditions for MVs. Hourly measurements, in the form of time series, record the number of SPs (for diameters of 0.3, 0.5, and 1.0 μm) along with MVs (temperature (T), relative humidity (RH), and wind speed magnitude (WS)). The objective is to verify whether MVs (RH, T) promote the sustainability of SPs. For this purpose, Spearman’s analysis and a heavy-tailed probability function were used. The central tendency probability, a Gaussian distribution, was discarded since its probability does not discriminate extreme events. Spearman’s analysis yielded significant p-values and correlations between PM10, PM5.0, PM2.5, and SPs. However, this was not the case between MVs and SPs. By applying a heavy-tailed probability analysis to extreme events, the results show that MVs such as T and RH act in ways that can favor the accumulation and persistence of SP concentrations. This tendency could have been exacerbated during the measurement period by heat waves and a geographical environment under the influence of a prolonged drought resulting from climate change and global warming.
Keywords: time series; submicron particles; urban micrometeorology; Kolmogorov entropy; Spearman correlation; heavy-tailed probability; sustainability time series; submicron particles; urban micrometeorology; Kolmogorov entropy; Spearman correlation; heavy-tailed probability; sustainability
Graphical Abstract

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MDPI and ACS Style

Hernández, P.P.; Garrido, E.M.; Ahumada, G.N.; Chamblas, J.W.; Pizan, S.P. Submicron Particles and Micrometeorology in Highly Densified Urban Environments: Heavy-Tailed Probability Study. Atmosphere 2025, 16, 1044. https://doi.org/10.3390/atmos16091044

AMA Style

Hernández PP, Garrido EM, Ahumada GN, Chamblas JW, Pizan SP. Submicron Particles and Micrometeorology in Highly Densified Urban Environments: Heavy-Tailed Probability Study. Atmosphere. 2025; 16(9):1044. https://doi.org/10.3390/atmos16091044

Chicago/Turabian Style

Hernández, Patricio Pacheco, Eduardo Mera Garrido, Gustavo Navarro Ahumada, Javier Wachter Chamblas, and Steicy Polo Pizan. 2025. "Submicron Particles and Micrometeorology in Highly Densified Urban Environments: Heavy-Tailed Probability Study" Atmosphere 16, no. 9: 1044. https://doi.org/10.3390/atmos16091044

APA Style

Hernández, P. P., Garrido, E. M., Ahumada, G. N., Chamblas, J. W., & Pizan, S. P. (2025). Submicron Particles and Micrometeorology in Highly Densified Urban Environments: Heavy-Tailed Probability Study. Atmosphere, 16(9), 1044. https://doi.org/10.3390/atmos16091044

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