NDLI: A Spatio-Temporal Visualization Approach of $PM_{10}$ Concentration Data in Metropolitan Lima

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A Spatio-Temporal Visualization Approach of $PM_{10}$ Concentration Data in Metropolitan Lima

Content Provider	MDPI
Author	Javier, López-Gonzales Encalada-Malca, Alexandra Cochachi-Bustamante, Javier Rodrigues, Paulo Salas, Rodrigo
Copyright Year	2021
Abstract	Lima is considered one of the cities with the highest air pollution in Latin America. Institutions such as DIGESA, PROTRANSPORTE and SENAMHI are in charge of permanently monitoring air quality; therefore, the air quality visualization system must manage large amounts of data of different concentrations. In this study, a spatio-temporal visualization approach was developed for the exploration of data of the PM $_{10}$ concentration in Metropolitan Lima, where the spatial behavior, at different time scales, of hourly concentrations of PM $_{10}$ are analyzed using basic and specialized charts. The results show that the stations located to the east side of the metropolitan area had the highest concentrations, in contrast to the stations located in the center and north that reported better air quality. According to the temporal variation, the station with the highest average of biannual and annual PM $_{10}$ was the HCH station. The highest PM $_{10}$ concentrations were registered in 2018, during the summer, highlighting the month of March with daily averages that reached 435 μ $μ$ g/m $^{3}$ . During the study period, the CRB was the station that recorded the lowest concentrations and the only one that met the Environmental Quality Standard for air quality. The proposed approach exposes a sequence of steps for the elaboration of charts with increasingly specific time periods according to their relevance, and a statistical analysis, such as the dynamic temporal correlation, that allows to obtain a detailed visualization of the spatio-temporal variations of PM $_{10}$ concentrations. Furthermore, it was concluded that the meteorological variables do not indicate a causal relationship with respect to PM $_{10}$ levels, but rather that the concentrations of particulate material are related to the urban characteristics of each district.
Starting Page	609
e-ISSN	20734433
DOI	10.3390/atmos12050609
Journal	Atmosphere
Issue Number	5
Volume Number	12
Language	English
Publisher	MDPI
Publisher Date	2021-05-07
Access Restriction	Open
Subject Keyword	Atmosphere Air Quality Pm10 Spatio-temporal Visualization Particulate Matter Dynamic Time Warping
Content Type	Text
Resource Type	Article

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