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Evaluación temporal del material particulado PM2.5 y PM10 en el Distrito Metropolitano de Quito – Ecuador

&nbs= p;

Temporary assessment = of PM2.5 and PM10 particulate matter in the Metropolitan District of Quito – Ecuador

 

 


= 1=

Franz Patricio Verdezoto Mendoza<= /span>

https://orcid.org/0000-0002-0049-005X

 <= /span>

Universidad Estatal de Bolívar (UEB), Facultad de Cienci= as Agropecuarias, Recursos Naturales y del Ambiente, Guaranda-Ecuador

fverdezoto@ueb.edu.ec=

= 2=

Juan Carlos Muyulema Allaica

https://orcid.org/0000-0002-9663-8935

 <= /span>

Universidad Estatal Península de Santa Elena, Centro de Investigación e Innovación de Ingeniería Industrial, La Libertad, Ecuador.

jmuyulema@upse.edu.ec=

= 3=

Héctor Ricardo Cuba Torre

https://orcid.org/0000-0002-9011-0363

 <= /span>

Universidad Nacional del Callao (UNAC), Facultad de Ingeniería Química, Lima, Perú

hrcubat@unac.edu.pe=

= 4=

Anita Karina Serrano Castro

https://orcid.org/0000-0002-0347-1823

 <= /span>

Universidad Estatal de Bolívar, Facultad de Ciencias de la Salud y del Ser Humano, Gu= aranda-Ecuador.

aserrano@ueb= .edu.ec=

 

<= span style=3D'font-family:"Times New Roman",serif;color:#767171;mso-themecolor:b= ackground2; mso-themeshade:128;mso-ansi-language:ES-EC'> 

 

 

Art= ículo de Investigación Científica y Tecnológica

Env= iado: 08/08/2022

Rev= isado: 23/09/2022

Ace= ptado: 24/10/2022

Pub= licado:15/11/2022

DOI: = https://doi.org/10.33262/concienciadigi= tal.v5i4.1.2393  

 

=  

 

Cítese:

 

 

 

Ver= dezoto Mendoza, F. P., Muyulema Allaica, J. C., Cuba Torre, H. R., & Serrano Castro, A. K. (2022). Evaluación temporal del material particulado PM2.5 y PM10 en el Distrito Metropolitano de Quito – Ecuador. ConcienciaDigital, 5(4.1), 21-44. https://doi.org/10.33262/concienciadigi= tal.v5i4.1.2393

 

 

 

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Palabras claves: PM2.5; PM10; Calidad del A= ire, Correlación, Meteorológicas.

 

 

Resumen

Int= roducción. El material particulado se constituye en uno de= los criterios más transcendentales al momento de evaluar la contaminación del aire, debido a la gran diversidad de fuentes que lo pueden producir y a l= os efectos que tiene sobre la salud. Objetivo. El presente estudio tuvo por objetivo evaluar el material particulado PM<= sub>2.5 y PM10, en la temporalidad horario, mensual, estacional y anua= l y la correlación con las variables meteorológicas en la zona del Distrito Metropolitano de Quito-Ecuador, en el periodo 2013-2020. Metodología. La base de datos y variables meteorológicas se obtuvieron de dos estaciones de monitoreo, Belisario y Carapungo, que est= án distribuidas en la zona de estudio. Se realizó un análisis exploratorio y correlación simple para 65718 datos de PM2.5 en Belisario, 661= 91 datos para PM2.5 en Carapungo y 61152 datos de PM10= en Carapungo. Resultados.  Los resultados evidencian que la esta= ción de Carapungo presenta mayor concentración de material particulado respect= o a la estación Belisario. La relación PM2.5/PM10 de la estación Carapungo es de 0.41 de material fino anisotrópico, que comparad= os con algunas ciudades como Perú, Colombia, México y Chile es similar. Resp= ecto a las correlaciones el PM2.5 y PM10 presentan una correlación significativa con la temperatura, humedad relativa, dirección= del viento y precipitación, pero difieren en las dos estaciones. Conclusiones. Se concluye que el material particulado PM2.5 y PM10 en el área analiz= ada no depende de factores climáticos, sino más bien, puede deberse a la topografía especifica de la zona la cual se encuentra caracterizada por e= star rodeada de bosques, volcanes y montañas.

 

 

Keywords:

PM2.5; PM10; A= ir Quality; Correlation; Meteorological.

 

Abstract

Introduction. Particulate matter is one of the most transcendental criteria when evaluating air pollution, due to the great diversity of sources that can produce it and the effects it has on health= . Objective. The objective of this study was to evaluate PM2.5 and PM10 particulate ma= tter in the hourly, monthly, seasonal, and annual time periods and the correla= tion with meteorological variables in the area of the Metropolitan District of Quito-Ecuador, in the period 2013-2020. Methodology. The database and meteorological variables were obtained from two monitori= ng stations, Belisario and Carapungo, which are distributed in the study are= a. An exploratory analysis and simple correlation were performed for 65718 P= M2.5 data at Belisario, 66191 data for PM2.5 at Carapungo and 61152= PM10 data at Carapungo. Results. = The results show that the Carapungo station has a higher concentration of particulate matter than the Belisario station. The PM2.5/PM10 ratio of the Carapungo station is 0.41 of anisotropic fine material, which compared to some cities such as Peru, Colombia, Mexico and Chile is simil= ar. Regarding correlations, PM2.5 and PM10 present a significant correlation with temperature, relative humidity, wind directi= on and precipitation, but they differ in the two stations. Conclusions. It is concluded that PM2.5 and PM10 particulate matter in the area analyzed does not depend on climatic facto= rs, but rather, it may be due to the specific topography of the area, which is characterized by being surrounded by forests, volcanoes, and mountains.

 

 

 

 

Introducción

El término material particulado (PM, del inglés Particulate Matter), se refiere a partículas discretas (gotas de líquido o sólido), la= contaminación por partículas incluye dos grupos principales: PM10 (fracción inhalable o gruesa) las cuales tienen un tamaño mayor a 2.5 y menor a 10 micrómetros (μm) y PM2.5 (fracción torácica o fina) que son partículas de diámetro menor o igual a 2.5 μm (Lega= rreta et al., 2015; Ryu et al., 2021).

El material particulado que contiene el aire urban= o es una mezcla compleja de componentes químicos y biológicos de múltiples fuent= es, que incluyen el hollín, metales pesados y de transición, hidrocarburos aromáticos policíclicos (HAPs), polen y componentes bacterianos (He e= t al., 2022). Var= ios estudios han demostrado que la composición de las partículas y sus efectos toxicológicos sobre la salud varían según el tiempo, la ubicación, el tamañ= o de partícula y el origen de las partículas (Rönk= kö et al., 2020; Veld et al., 2022; Wu et al., 2022).

Según la Organización Mundial de la Salud (OMS), el 92% de las personas en todo el mundo vive en lugares con mala calidad del a= ire exterior, donde los principales factores de riesgo para desarrollar enfermedades respiratorias crónicas (ERC) están relacionados con el clima y= el medio ambiente (Barr= y & Annesi-Maesano, 2017). Conjuntamente, reportó para el 2016, un valor de 4,2 millones de muertes que fueron causadas por la contaminación ambiental del aire en todo el mundo. Se estima que causa aproximadamente el 29% de las muertes por cáncer de pulmón= , el 24% de las muertes por accidente cerebrovascular, el 25% de las muertes por enfermedades cardíacas y el 43% de otras enfermedades pulmonares. Además, la contaminación del aire se ha atribuido al 26% de las muertes por infecciones respiratorias, el 25% de las muertes por enfermedad pulmonar obstructiva crónica (EPOC) y aproximadamente el 17% de las enfermedades cardíacas isquémicas y los accidentes cerebrovasculares (Khom= si et al., 2021). En Ecuador la exposición a la contaminación atmosférica representa un estimado= de 2700 muertes prematuras en el año 2018 y un costo de 1000 millones de dólar= es para ese mismo año (Alva= rez-Mendoza et al., 2020; Cornejo-Vásconez et al., 2022).

Referente al material particulado, este contaminan= te presenta los mayores factores de riesgo para la salud humana mundial y se asocia con una mayor morbilidad y mortalidad debido a un conjunto diverso de efectos perjudiciales para la salud que incluyen enfermedades cardiovascula= res, accidente cerebrovascular, Alzheimer y asma (Rönk= kö et al., 2020).

La calidad del aire de un área determinada depende= de las fuentes de emisiones de los contaminantes y de las condiciones meteorológicas regionales (Vale= ncia et al., 2020), est= os últimos pueden afectar los procesos físicos y las reacciones químicas de los contaminantes, por ejemplo, la velocidad y dirección del viento pueden afec= tar la difusión y transmisión de contaminantes mientras que la temperatura y la humedad pueden afectar los procesos de reacción de contaminantes ADDIN CSL_CITAT= ION {"citationItems":[{"id":"ITEM-1","itemDa= ta":{"DOI":"10.1016/j.envres.2021.110879","au= thor":[{"dropping-particle":"","family":= "Jiaxin","given":"Chen","non-dropping-pa= rticle":"","parse-names":false,"suffix":= ""},{"dropping-particle":"","family"= ;:"Hui","given":"Hu","non-dropping-parti= cle":"","parse-names":false,"suffix":&qu= ot;"},{"dropping-particle":"","family":&= quot;Feifei","given":"Wang","non-dropping-par= ticle":"","parse-names":false,"suffix":&= quot;"},{"dropping-particle":"","family"= :"Mi","given":"Zhang","non-dropping-part= icle":"","parse-names":false,"suffix":&q= uot;"},{"dropping-particle":"","family":= "Ting","given":"Zhou","non-dropping-part= icle":"","parse-names":false,"suffix":&q= uot;"},{"dropping-particle":"","family":= "Shicheng","given":"Yuan","non-dropping-= particle":"","parse-names":false,"suffix"= ;:""},{"dropping-particle":"","family&qu= ot;:"Ruoqiao","given":"Bai","non-droppin= g-particle":"","parse-names":false,"suffix&qu= ot;:""},{"dropping-particle":"","family&= quot;:"Nan","given":"Chen","non-dropping= -particle":"","parse-names":false,"suffix&quo= t;:""},{"dropping-particle":"","family&q= uot;:"Ke","given":"Xu","non-dropping-par= ticle":"","parse-names":false,"suffix":&= quot;"},{"dropping-particle":"","family"= :"Hao","given":"Huang","non-dropping-par= ticle":"","parse-names":false,"suffix":&= quot;"}],"container-title":"Environmental Research","id":"ITEM-1","issue":"Fe= bruary","issued":{"date-parts":[["2021"]= ]},"title":"Air quality characteristics in Wuhan ( China ) during the 2020 COVID-19 pandemic","type":"article-journal","volume&qu= ot;:"195"},"uris":["http://www.mendeley.com/docume= nts/?uuid=3D76855158-a8da-4771-829c-fb7df8ff3afb","http://www.men= deley.com/documents/?uuid=3D62f44548-5a37-4fbb-b0b7-a8f5a9f8d163"]}],&= quot;mendeley":{"formattedCitation":"(Jiaxin et al., 2021)","plainTextFormattedCitation":"(Jiaxin et al., 2021)","previouslyFormattedCitation":"(12)"},"= ;properties":{"noteIndex":0},"schema":"https:= //github.com/citation-style-language/schema/raw/master/csl-citation.json&qu= ot;}(Jiax= in et al., 2021).

Según reporte del informe emitido por la Secretarí= a de Ambiente del Distrito Metropolitano de Quito (DMQ) para el año 2018, el material particulado PM10 sobrepasa la Norma Ecuatoriana de Cali= dad de Aire (NECA) en la mayoría de las estaciones de monitoreo y el PM2.5= sobrepasa en todas las estaciones monitoreadas (Rodr= íguez-Guerra & Cuvi, 2019).

Tomando en consideración que el material particula= do es una variable muy importante por sus niveles de concentración y efectos e= n la salud de la población del DMQ, el presente estudio tiene como objetivo principal, evaluar la variación temporal del PM10 y PM2.5 y su relación con las variables meteorológicas en la Zona del Distrito Metropolitano de Quito – Ecuador durante los años 2013-2020.

Materiales y Métodos

El estudio se realizó entre 2013 y 2020 en el DMQ, provincia de Pichincha, Ecuador, ubicada geográficamente en la Latitud 0° 1= 3’ 07” S y Longitud 78°30’35” O a 2800 msnm. Quito presenta una topografía compleja con temperatura y humedad relativa media de 13.5°C y 82%, respectivamente.

La calidad del aire del DMQ, es monitoreado por La= Red Metropolitana de Monitoreo Atmosférico de Quito (REMMAQ), cuya localización= de las estaciones cumplen con las recomendaciones de la Agencia de Protección Ambiental de los Estados Unidos (US-EPA) (EPA. 40CFR58, Apéndice E) y de la Organización Meteorológica Mundial (OMM, No. 8), además cuenta con informac= ión validada mediante respaldo procedimental y documental, desde enero de 2004 = (IAMQ, 2018).

Los datos del material particulado PM2.5 y PM10 y las variables meteorológicas se obtuvieron de dos estacio= nes de monitoreo, Belisario y Carapungo que están distribuidos en el DMQ se incorporan en la y su ubicación  REF _Ref63331032 \h  \* MERGEFORMAT =

Tabla 1, las cuales forman parte de la Red Automática (RAUTO) del subsistema de la REMMA= Q de la secretaria de Ambiente del Ecuador.

Figura 1=

Ubica= ción espacial de las estaciones de calidad de aire de Carapungo y Belisario=

 <= /a>

Tabla= = 1=

Carac= terísticas generales de las estaciones de Carapungo y Belisario=

Estaciones

Código

Altura (msnm)

Ubicación

Sitio*

Belisario

BEL

2835

Terraza del Edificio Administrativo del Colegio San Gabriel (Av. A= mérica 3541)

UB-R

Carapungo

CAR

2660

Super manzana B, el Verjel S/N, edificio Andinatel.

UB-C

*Categoría del sitio: UB-Urbano, C- Comerc= ial, R-Residencial.  <= /p>

Los métodos y equipos con la cual se registraron l= as concentraciones de PM10, PM2.5 y datos meteorológicos= se muestra en la Tabla= 2, los cuales son parte de la Red Metropolitana de Monitoreo Atmosférico de Quito (REMMAQ) del subsistema Red Automática (RAUTO) de la Secretaría del Ambiente del Ecuador.

Tabla 2=

Características de los parámetros evaluados en Carapungo y Belisario

Estacione= s

PM10= y PM2.5

PM10=

PM2.= 5

Temperatura Humedad

Precipita= ción

Dirección del viento

Método de medida

Marca y Modelo

……………

Equipo

…………….

Belisario=

y

Carapungo

Atenuación de rayos beta (Método equivalente para PM10 EPA No. EQPM-1102-150)

Thermo Scientific/FH62

C14

Thermo Andersen/ FH62

C14

Sensor Pt100 y sensor capacitivo para HR / Clase II

Báscula oscilante / Clase II

Veleta y potenciómetro con señal de voltaje proporcional a la dirección de viento / Clase II.

=  

Resultados y Discusión

Evaluación de los datos<= /p>

Se realizó un análisis exploratorio para 65718 datos de PM2.5 en Belisario, 66191 datos para PM2.5 en Carapungo y 61152 da= tos de PM10 en Carapungo. La Figura 2 presenta el diagrama de cajas para material particulado de las dos estaciones analizadas en las que= se puede observar de datos fuera de lugar o valores atípicos, razón por la cual sus desviaciones estándar respecto a la media son valores altos, con valores 10,07 para PM2.5 en la estación Belisario, 13.72 para PM2.5 en la estación Carapung= o y 34,42 para PM10 de la estación Carapungo. La mayor cantidad de valores están muy cerca de la media representado por la anchura de la caja entre el primer y tercer cuartil. Los bigotes presentan una mayor variabili= dad de los datos en el cuartil superior para todos los conjuntos de datos, con máximos de 447,11 µg/cm3 para PM2.5 de la estación Belisario, 648,38 µg/cm3 para PM2.5 de la estación Carapung= o y 1061,75 µg/cm3 para PM10 de la estación Carapungo, que puede deberse a eventos extraordinarios durante el periodo evaluado.

Figura 2<= !--[if supportFields]>

Diagrama de cajas para = los datos de las estaciones de Calidad del Aire Belisario y Carapungo en PM2.5 y PM10

Variación hora= ria de PM2.5 para Belisario y Carapungo

En la Figura 3<= /b> se observa el comportamiento del promedio horario multianual del PM= 2.5. Se evidencia comportamientos semejantes de las concentraciones durante las = 24 horas, registrándose valores máximos de 32.1 (06:00 horas) y 24.73 μg/= m3 (8:00 horas) y mínimas de 14.14 μg/m3 (23:00 horas) y 11.78 (23:00 horas) para las estaciones de Belisario y Carapungo respectiva= mente, ambos asociados a las emisiones del parque automotor y las actividades antropogénicas. Estos resultados son coherentes con los estudios realizados= por De Jesús et al. (2019) y Pacsi (20= 16), del mismo modo se verifica que la estación de Carapungo presento mayor concentración, superando a los valores obtenidos en Belisario durante las 24 horas este comportamiento puede estar determinado por fuentes locales de combustión, el mismo que es coherente con los encontrados por De Jesús.

Comparando los valores medidos con lo que establec= e la Guía de la OMS Diario para PM2.5 (25 µg/m3), se observa que la estación de Belisario no supera la concentración establecida= por dicha norma durante las 24 horas, a diferencia de la estación de Carapungo = que supera este valor desde las 6:00 hasta las 7:00 horas. Sin embargo, al comp= arar con la NECA Diario para PM2.5 (50 μg/m3) = se evidencia durante las 24 horas que dichos valores no superan la concentraci= ón establecida para ambas estaciones.

Figura 3= <= /o:p>

Variación horaria multianual de PM2.= 5 entre Belisario y Carapungo

= =  

 =

 =

Variación diaria de PM2.5 para Belisar= io y Carapungo

En la Figura 4 <= /i>se muestra la variación promedia diaria para el periodo 2013-2020. Se puede apreciar que la estación de Carapungo presenta = una mayor concentración de contaminantes durante todos los días de la semana en comparación con la estación de Belisario. Por otro lado, los días de mayor concentración con características similares se registró el martes miércoles= y jueves, cuyas concentraciones fueron bajando paulatinamente lunes y sábado hasta llegar a las concentraciones mínimas registradas el domingo, comportamientos semejantes para las 2 estaciones.

Para ambas estaciones los mínimos valores se regis= tran el domingo, y los máximos miércoles y jueves, estando estrechamente relacio= nado con los hábitos de la población, donde los domingos disminuyen las activida= des antropogénicas y el flujo del transporte vehicular. Similares resultados fu= eron obtenidos por estudios realizados por Pacsi.

Figura 4<= /p>

Variac= ión diaria multianual de PM2.5 entre Belisario y Carapungo

= =  

Variación mensual de PM2.5 para Belisar= io y Carapungo

En la

Figura 5 se puede observar que en los meses de enero, febrero, marzo, abril y mayo las dos estaciones no presentaron diferencias respectos a las concentraciones registradas, a partir de este mes las concentraciones se incrementaron en la estación de  Carapungo hasta llegar a sus valores máximos en el mes de setiembre = de 23.03 μg/m3, sin embargo la estación de Belisario presento = un comportamiento opuesto cuyos valores disminuyeron hasta concentraciones mín= imas de 11.23 μg/m3 en el mes de julio, para que a partir de all= í se incrementara hasta valores picos en el mes de noviembre de 19.45 μg/m<= sup>3.

 

Figura 5

Variación mensual multianual de PM2.5 entre Belisario y Carapungo

 

En tal sentido Pacsi (2016), sostiene en sus estud= ios que el comportamiento de las concentraciones estaría asociado a las características urbanísticas y meteorológicas de la zona, del mismo modo IA= CAQ (2019), en su informe anual indica que la disminución se debe a la limitada presencia del tráfico vehicular debido a las vacaciones = de las escuelas y colegios (julio y agosto), así como al efecto meteorológico = de la época de verano que presenta fuertes vientos y alta radiación solar (IAMQ, 2018).

Variación<= span style=3D'font-family:"Times New Roman",serif;mso-ansi-language:ES-EC;mso-bi= di-font-weight: bold'> anual de PM2.5 para Belisario y Carapungo

En la 

 

 

 =

 =

Figura 6 se puede observar que la estación de Carapungo registro las más alt= as concentraciones a diferencia de Belisario durante los años evaluados. Cuyas concentraciones máximas se registraron, en el 2015 y 2016 respectivamente p= ara Carapungo y Belisario.

 En dicha = figura se puede evidenciar que los valores del PM2.5, superaron significativamente los valores límites de la OMS para PM2.5 (10 μg/m3) en todos los años evaluados para las dos estaciones, sin embargo, al comparar con la NECA anual para PM2.5 (15 μg/m3) los valores del año 2020 no superaron a dicha no= rma.

 =

 =

 =

 =

 =

Figura 6

Variación anual de PM2.5 entre Belisario y Carapungo

3D"Cuadro3D"Cuadro

 

Los valores bajos registrados en año 2020 en las d= os estaciones , estaría directamente relacionado con la limitada circulación y desactivación de actividades comerciales que se produjo debido al Decreto Ejecutivo No. 1017, quien declaro estado de excepción por calamidad pública= en todo el territorio nacional debido al impacto del coronavirus COVID-19, que rigió a partir del 17 de marzo 2020, en dicho decreto en el artículo 4 establece la limitación del derecho a la libertar del tránsito en Ecuador, siendo este una de las principales fuentes de generación de PM2.5.<= o:p>

Variación estacional de PM2.= 5 para Belisario y Carapungo

La Figura 7 <= /i>se muestra la variación estacional del PM10 <= /sub>paras las estaciones de Belisario y Carapungo para el periodo 2013-2020. Se obser= va en todas las estaciones del año los valores registrados en Carapungo fueron mayores en comparación a los obtenidos en Belisario. Del mismo modo se evidencia que los máximos valores se presentaron en la época de primavera p= ara las dos estaciones y los mínimos en otoño e invierno para Belisario y Carap= ungo respectivamente. Las bajas concentraciones de PM2.5 = en invierno puede estar asociada a las condiciones de humedad ambiental y fuer= tes precipitaciones (IAMQ, 2018). Mientras que las altas concentraciones pueden es= tar asociados a la cercanía de vías de alto tránsito vehicular, las calles sin pavimentar y las condiciones meteorológicas de la zona (Pacsi, 2016).

Figura 7

Variación estacional multianual de PM2.= 5 entre Belisario y Carapungo

 

Variación horaria de PM10 para Carapun= go

En la =

 =

 =

 

Figura 8 se observa la variación promedia horaria mensual del= PM10 para la estación de Carapungo durante el periodo 2013-2020. Esta variación = se caracteriza por presentar dos picos máximos durante el día para todos los m= eses evaluados, cuyas concentraciones de incremento se presentó entre las 06:00 y 07:00 horas, así como a la 13:00 y 14:00 horas. Dicho incremento están asociados a las emisiones del parque automotor y las actividades antropogén= icas del lugar, debido a que esta estación de monitoreo está ubicado a 76 metros= de la Av. Giovanni Calle (IAMQ, 2018) .

Así mismo las máximas concentraciones se registrar= on en el mes de setiembre a las 06:00 horas y 14:00 horas. con valores de concentración de 92.69 μg/m3 y 103.86 μg/m3 respectivamente. Los valores mínimos se registraron a las 03:00 horas (21.79 μg/m3) en el mes de mayo y 09:00 horas (22.93 μg/m3) en el mes abril. Por su parte Pacsi (2016), indica que la disminución de la concentración tiene probable relación a la disminución de las emisiones de = las fuentes móviles.

 

 

 

 

Figura 8<= /p>

Variación horaria multianual = de PM10 para Carapungo

 

Comparando los valores medidos con lo que establec= e la Guía de la OMS Diario (50 µg/m3), se observa que el mes de marzo= de 06:00 a 07:00 horas la concentración de PM10 no supera lo establecido por dicha norma a diferencias del resto de meses que,= si superan, del mismo modo se supera la norma en mención para todos los meses = en el horario de 1:00 a 3:00 pm. Sin embargo, al comparar la NECA Diario para = PM10 (100 μg/m3) se evidencia que solo en el mes de setiembre se sobrepasa esta concentración en las horas de 14:00 a 15:00 horas.

Variación diaria de PM10 para Carapungo

En la  Figura 9 se muestra la variación promedia diaria mensual para periodo 2013-2= 020. Se observa que el máximo valor de concentración de PM10 e= n promedio se presentó el jueves y el mínimo para el domingo, este comportamiento puede estar asociados a los patrones de usos y costumbres de la población. Además, los valores de los meses de julio, agosto, septiembre y octubre superaron al promedio para todos los días.

En todos los meses los mínimos valores se registra= n el domingo, y los máximos miércoles y jueves, estando estrechamente relacionado con los hábitos de la población, donde los domingos disminuyen las activida= des antropogénicas y el flujo del transporte vehicular. Similares resultados fu= eron registrados por estudios realizados por Pacsi.

 

 

Figura = 9

Variación diaria multianual d= e PM10 para Carapungo

=  

Variación mensual de PM10 para Carapun= go

En la Figura 10 se muestra las variaciones promedio mensual por año del PM1= 0 para la estación de Carapungo durante el periodo de 2013-2020. Se observa q= ue los mayores valores de concentración de PM10, se presentó= en los meses de agosto y setiembre, presentando valores entre 46.81 – 78.58 μg/m3. Por su parte IACAQ (IACAQ, 2019) en su reporte anual sostiene que este comportamie= nto se debe a las bajas precipitaciones y fuertes vientos de la época, sumados = a la falta de recubrimiento vegetal de terrenos, canteras de extracción de mater= ial pétreo y la circulación de vehículos, mismos que resuspenden el contaminant= e.

Figura = 10

Variación mensual multianual = de PM10 para Carapungo

Por otro lado, los mínimos valores según el promed= io mensual se registran durante los meses de marzo abril y mayo. En tal sentido Pacsi (2016), sostiene en sus estudios que este comportamiento estaría asoc= iado a las características urbanísticas y meteorológicas de la zona, del mismo m= odo IACAQ (IACAQ, 2019) en su informe anual indica que esta disminución se debe a las mayores precipitaciones evitando la resuspensión de material particulado.

Del mismo modo los valores más bajos de concentrac= ión se registraron en el año 2020 en los meses de marzo, abril, mayo los cuales están relacionado con la limitada circulación y desactivación de actividades comerciales que se produjo debido al Decreto Ejecutivo No. 1017, quien decl= aro estado de excepción por calamidad pública en todo el territorio nacional de= bido al impacto del coronavirus COVID -19, que rigió a partir del 17 de marzo 20= 20, en dicho decreto en el artículo 4 establece la limitación del derecho a la libertar del tránsito en Ecuador, siendo este una de las principales fuente= s de generación de PM10.

Variación anual de PM10 para Carapun= go

La

Figura 11 se observa la variación promedio diario anual del PM10 p= ara la estación de Carapungo durante el periodo 2013-2020. Evaluando el comportamiento de la concentración para cada año se puede observar que los máximos valores promedios de concentraciones se presentaron en el año 2015 = que oscila entre 46.50 y 59.58 μg/m3 y los mínimos valores fuer= on registrados en el año 2020 con valores comprendidos entre 31.75 y 37.91 μg/m3 para todos los días evaluados.

Por ot= ro lado, se observa que los valores del PM10, superaron significativamente los valores límites del NECA anual para PM10 (50 μg/m3) y las guías de la OMS para PM10 (20 μg/m3) para todos los años evaluados.

Figura = 11

Variación anual multianual de= PM10 para Carapungo

=  

Del mismo modo se observa que el año 2020 presento= una reducción significativa de la concentración del material particulado PM<= sub>10, siendo alrededor del 23% respecto al promedio diario de todos los años y un= 17 % respecto al año 2017 quien también se presentó como uno de los años con m= ás bajas concentraciones durante el periodo de evaluación 2013 – 2020. Este al= to porcentaje de reducción de PM10 se debe a la limitada circulación y desactivación de actividades comerciales que se produjo debid= o al Decreto Ejecutivo No. 1017, quien declaro estado de excepción por calamidad pública en todo el territorio nacional debido al impacto del coronavirus COVID-19, que rigió a partir del 17 de marzo 2020, en dicho decreto en el artículo 4 establece la limitación del derecho a la libertar del tránsito en Ecuador, siendo este una de las principales fuentes de generación de PM<= sub>10.

Variación estacional de = PM10 para Carapun= go

En la Figura 12¡Error! No se encuentra el origen de la referencia. se muestra la variación estacional del PM2.5= para la estación de Carapungo para el periodo 2013-2020. Se evidencia que los máximos valores se presentaron en la época de primavera y los mínimos en invierno. Las bajas concentraciones de PM2.5 en invierno puede estar asociada a las condiciones de humedad ambiental y fuer= tes precipitaciones (IAMQ, 2018). Mientras que las altas concentraciones pueden es= tar asociados a la cercanía de vías de alto tránsito vehicular, las calles sin pavimentar y las condiciones meteorológicas de la zona (Pacsi, 2016).

Figura = 12

Variación estacional multianual de PM10 para Carapungo

 

 

 

Análisis de correlación Horaria d= e PM2.5/PM10 de Carapungo

En la siguiente

Tabla = 3 <= /i>se tiene el análisis del ratio PM2.5/PM10 de 0.41 para la estación de Carapungo y con respecto a otras Ciudades, Perú, Colombia, México y Chile presenta un menor= ratio. Si bien las fracciones de PM2.5/PM10 obtenidos del análisis estadístico presenta un menor valor y si lo comparam= os con los establecido por las Guías de Calidad del Aire de la (OMS, 2006) est= án entre 0.5 - 0.8 para ambientes urbanos, y guardan correlación con los ratios utilizados por Larsen (PM2.5/PM10 =3D 0= .6) para AMVA en el año 2004 (Aguiar-Gil et al., 2020).

Tabla = 3

Relación de PM2.5/PM10 para Carapungo y otras Ciudades

País

Ciudad /zona

Estación

PM2.= 5/PM10

 

Ecuador

 

Perú*

 

 

 

 

 

Colombia**

México **

Chile **

Inglaterra **

España **

            =                                                      =                         

 

Quito

&nbs= p;

Carapungo=

&nbs= p;

0,41=

Lima norte

Lima Sur

Lima Este

Lima Centro

Callao

Santa Luzmila

María Auxiliadora

Hipólito Unanue

Conaco

Callao

Promedio Lima

0,50=

0,60=

0,66=

0,75=

0,72=

0,65=

Bogotá

México DF

Santiago

Birmingham

Barcelona

 

0,60=

0,50 – 0,= 70

0,40 – 0,= 60

0,50 – 0,= 80

0,60=

Fuente:= * Pacsi (2016),  ** Galvis = & Rojas (2006), Pandey et al. (2012), Rojas & Galvis (2005)

Correlaciones de PM2.5 multivariante para la estación Belisario

La ¡Error! No se encuentra el origen de la referencia., presenta las correlaciones del Material Particul= ado PM2.5 con la temperatura es de -0.88 y la dirección del viento es -0.75 indicando una relación significativa inversa, es decir que cuando aumentan estos factores meteorológicos el PM2.5 di= sminuye. La humedad

relativa con un valor de 0.82 y la precipitación c= on un valor de 0.73 tienen una relación significativa directa, es decir, cuando aumenta el porcentaje de humedad relativa y la precipitación, puede aumenta= r el material particulado PM2.5. El estudio de Yang et al. (2021), que evalúa los efectos meteorológicos en varias ciudades de China, observó que la velocidad del viento, la temperatura y las precipitaciones son los principales factores meteorológicos que influyen en= la concentración de PM2.5, esto afirma que en la ciudad de Q= uito también existe influencia de los factores meteorológicos en el PM2.= 5.

La fuerza de la correlación del PM2.5 bien sea negativa o positiva depende también de otros factores como topogra= fía, localización por lo cual puede existir variabilidad de la correlación entre diferentes zonas y no necesariamente debe ser igual en todas las localizaci= ones geográficas tal como lo deduce el estudio de la variación del PM2.5= realizado por Yang et al. (2017), en China. La topografía de la zona en que se ubi= ca la ciudad de  Quito presenta la for= ma de una cuenca que tiene en las elevaciones pertenecientes al ramal occidental = de la cordillera de Los Andes, el macizo del Guagua y el Ruco Pichincha, crean= do una especie de barrera natural que limita la libre circulación del viento y consecuentemente, la capacidad de la atmósfera de dispersar los contaminant= es es bajo, este es un fenómeno común de las ciudades que están en valles; es decir su baja ventilación, hace que Quito, salvo los meses muy secos de mediados del año, tenga vientos promedio de entre uno y dos metros por segu= ndo, bastante más bajos que los que experimentan poblaciones localizadas en ampl= ias sabanas como Bogotá (Páez, 2012).

Figura 13

Correlación del P= M10 y PM2.5 con los factores meteorológicos en la estación Belisario=

Correlaciones de PM multivariante para la estación Carapungo

La ¡Error! No se encuentra el origen de la referencia., presenta correlaciones insignificantes del PM= 2.5 en la estación Carapungo con la temperatura (-0.10) la humedad relativa (-0.23) y la precipitación (0.04). La correlación del PM2.= 5 con la dirección del viento es de -0.51 indicando una correlación significativa= del tipo inversa. Podemos notar entre las dos estaciones de medición de PM2.5 que no hay una relación y pueden deberse a varias condiciones topográficas de la ciudad ya que la estación Belisario se encuentra en el centro financiero de la ciudad el cual tiene las características de estar rodeada por montañas y la estación Carapungo se encuentra en una zona aleda= ña en la que no interviene tanto la zona montañosa, este se corrobora en la Figura = 1.

La fuerza de la correlación del PM2.5 bien sea negativa o positiva depende también de otros factores como topografía, localización por lo cual puede existir variabilidad de la correlación entre diferentes zonas y no necesariamente debe ser igual en todas las localizaci= ones geográficas tal como lo deduce el estudio de la variación del PM2.5= realizado por Yang et al. (2017), en China. La topografía de la zona en que se ubi= ca la ciudad de  Quito presenta la for= ma de una cuenca que tiene en las elevaciones pertenecientes al ramal occidental = de la cordillera de Los Andes, el macizo del Guagua y el Ruco Pichincha, crean= do una especie de barrera natural que limita la libre circulación del viento y consecuentemente, la capacidad de la atmósfera de dispersar los contaminant= es es bajo, este es un fenómeno común de las ciudades que están en valles; es decir su baja ventilación, hace que Quito, salvo los meses muy secos de mediados del año, tenga vientos promedio de entre uno y dos metros por segu= ndo, bastante más bajos que los que experimentan poblaciones localizadas en ampl= ias sabanas como Bogotá (Páez, 2012).

Figura 14

Correlación del P= M10 y PM2.5 con los factores meteorológicos en la estación Carapungo

El PM10 tiene una correlación de 0.54 con la temperatura indicando una relación significativa de tipo direct= a, es decir, que al aumentar la temperatura también aumenta el PM10. Los valores de correlación con la dirección del viento (-0.78), porcentaje = de humedad (-0.86) y la precipitación (-0.69), indican una relación significat= iva del tipo inversa de estos factores meteorológicos con el PM10= , es decir, al disminuir los valores de estos factores meteorológicos, aument= a el PM10.

Conclusiones

·      =    El análisis exploratorio indica que el conjunto de datos de material particulado PM2.5 y PM10 en las estaciones de Belisario y Carapungo cumplen con el criterio de normalidad definido por las medidas de tendencia central pareci= das y el análisis de los gráficos de histogramas y QQ-plot. =

·      =    El diagrama de cajas y bigotes indica que el conjunto de datos presenta valores atípicos e= n su mayoría con concentraciones muy altas respecto a la media, que podría haber= se dado por eventos antropogénicos o naturales.

·      =    Del estudio realizado en las estaciones de Carapungo y Belisario para el PM2.5<= /sub> se obtuvieron que las máximas concentraciones de están entre las 06:00 hora= s y 08:00 horas de 32 µg/m3 promedio para luego dismi= nuir a niveles debajo de 25 µg/m3 recomendados por la OMS.

·&nb= sp;        Los valores de= l PM10 obtenidos para Carapungo superaron significativamente los valores límites d= el NECA anual para PM10 (50 µg/m3) y las guías de la OMS para PM10 (20 µg/m3) para todos los años evaluados.=

·&nb= sp;        En los análisis efectuados para PM10 Carapungo y Belisario se obtuvo resultados = de un alto porcentaje de reducción de PM10 debido a la limitación e= n el tráfico vehicular y la desactivación de actividades comerciales por el Decr= eto Ejecutivo No. 1017-EC, declarando el estado de excepción por calamidad públ= ica en todo el territorio nacional debido al impacto del coronavirus COVID -19.=

·&nb= sp;        El PM2= .5 y PM10 = en los análisis con respecto a las vari= ables meteorológicas para las estaciones Belisario y Carapungo presenta una relac= ión una relación directamente proporcional con respecto a las precipitaciones pluviales como lo evidencia lo ocurrido en el 2017 (Fenómeno del Nino).

·&nb= sp;        Los factores climáticos analizados, precipitación, temperatura, dirección del viento y humedad relativa fueron evaluados respecto al PM2.5 y PM10 de las dos estaciones, mediante el método de Spearman, el cual entrega valores= muy bajos reflejando que el material particulado PM2.5= y PM10 en la ciudad de Quito, el área analiza= da no depende de estos factores climáticos, que puede deberse a la topografía especifica de la ciudad la cual se encuentra rodeada de montañas.

·&nb= sp;        El modelamiento desarrollado para las estaciones de Belisario y Carapungo del material particulado PM2.5, los resultados evidencian que ex= iste una correlación estadísticamente significativa.

 

Conflicto de Intereses

Los aut= ores declaran que no existe conflicto de intereses para la publicación del prese= nte artículo científico.

Financiamiento

Los aut= ores declaran que no recibieron financiamiento

Agradecimiento

Los aut= ores reflejan su agradecimiento a cada= una de las Instituciones de Educación Superior que representan. Ejemplo del desarrollo de investigaciones multidisciplinares e interdisciplinares, bajo colaboración binacional Ecuador-Perú entre la Universidad Estatal de Bolívar (UEB), Guaranda, Ecuador; Universidad Estatal Península de Santa Elena (UPS= E), La Libertad, Ecuador, y la Universidad Nacional del Callao (UNAC), Lima, Pe= rú, mismas que aportaron al desarrollo del presente artículo científico.<= /p>

 

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