Title
Analyzing PM<inf>10</inf> concentrations and their trace elements in southern Lima, Peru: a case study from March 06<sup>th</sup> to 13<sup>th</sup>, 2020<sup>•</sup>
Other title
Análisis de las concentraciones de PM10 y sus elementos traza en Sur de Lima, Perú: estudio de caso de 6 al 13 de marzo de 2020
Date Issued
01 April 2022
Access level
open access
Resource Type
journal article
Publisher(s)
Universidad Nacional de Colombia
Abstract
In this research, PM10 concentrations were measured at the Universidad Nacional Tecnológica de Lima Sur (UNTELS), located in southern Lima, from March 06 to 13, 2020. To examine the aerosol-PM10 concentrations and their metals, two techniques were applied. These were: the PM10 air-mass-backward trajectory prediction and the trace metals cluster analysis in order to detect the transport of aerosol-PM10 from remote places to southern Lima, and to find the local sources of elements-particles, respectively. This was done for the first time in southern Lima. The air-mass-backward estimation trajectory of PM10 at UNTELS has shown that high values of the PM10 concentrations are associated with air masses originating and entering from the NW of Lima. However, the low values of PM10 particles are linked with the high humidity of air masses originating from the SSE coming from the Pacific Ocean.
Start page
18
End page
23
Volume
89
Issue
221
Language
English
OCDE Knowledge area
Ética relacionada con la biotecnología ambiental Meteorología y ciencias atmosféricas Ingeniería ambiental y geológica
Scopus EID
2-s2.0-85137328987
Source
DYNA (Colombia)
ISSN of the container
00127353
Sponsor(s)
This research was partially supported by the Universidad Nacional Tecnológica de Lima Sur according to Grant RCO N0 032-2019-UNTELS regarding the research project named “Análisis Morfológico, Metales y Origen de las Partículas Respirables en la Zona Sur de Lima” of the Universidad Nacional Tecnológica de Lima Sur-UNTELS. We thank Jocelyn Gallardo and Jesus Garriazo Gonzales for helping with the PM10 sampling. In addition, we thank the NOAA for giving us the HYPLIST model results. We thank Angela Huachua-Paucarpura, Koral Bravo-Zavala, and Kelly Condori-Condori for their help in writing the proposal project for a research grant at UNTELS. The authors are infinitely grateful to the anonymous reviewers who helped with their valuable suggestions for improving this article.
Sources of information: Directorio de Producción Científica Scopus