期刊论文详细信息
Atmosphere
A Spatio-Temporal Visualization Approach of PM10 Concentration Data in Metropolitan Lima
PauloCanas Rodrigues1  Rodrigo Salas2  AlexandraAbigail Encalada-Malca3  JavierDavid Cochachi-Bustamante3  JavierLinkolk López-Gonzales3 
[1] Departament of Statistics, Federal University of Bahia, Salvador 40170-110, Brazil;Escuela de Ingeniería C. Biomédica, Universidad de Valparaíso, Valparaíso 2362905, Chile;Facultad de Ingeniería y Arquitectura, Universidad Peruana Unión, Lima 15, Peru;
关键词: air quality;    PM10;    spatio-temporal visualization;    particulate matter;    dynamic time warping;   
DOI  :  10.3390/atmos12050609
来源: DOAJ
【 摘 要 】

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 PM10 concentration in Metropolitan Lima, where the spatial behavior, at different time scales, of hourly concentrations of PM10 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 PM10 was the HCH station. The highest PM10 concentrations were registered in 2018, during the summer, highlighting the month of March with daily averages that reached 435 μμg/m3. 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 PM10 concentrations. Furthermore, it was concluded that the meteorological variables do not indicate a causal relationship with respect to PM10 levels, but rather that the concentrations of particulate material are related to the urban characteristics of each district.

【 授权许可】

Unknown   

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