<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2007-0705</journal-id>
<journal-title><![CDATA[Nova scientia]]></journal-title>
<abbrev-journal-title><![CDATA[Nova scientia]]></abbrev-journal-title>
<issn>2007-0705</issn>
<publisher>
<publisher-name><![CDATA[Universidad de La Salle Bajío A. C., Coordinación de Investigación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2007-07052021000200106</article-id>
<article-id pub-id-type="doi">10.21640/ns.v13i27.2804</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Aplicaciones geoestadísticas para la evaluación de la contaminación por ozono en la ciudad de Durango, México]]></article-title>
<article-title xml:lang="en"><![CDATA[Geostatistical applications for ozone pollution assessment in Durango city, México]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Loera-Sánchez]]></surname>
<given-names><![CDATA[José Manuel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ramírez-Aldaba]]></surname>
<given-names><![CDATA[Hugo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Meléndez Soto]]></surname>
<given-names><![CDATA[Arnulfo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[García-Montiel]]></surname>
<given-names><![CDATA[Emily]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[González-Laredo]]></surname>
<given-names><![CDATA[Rubén]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="Aaf"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Juárez del Estado de Durango  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>México</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Tecnológico Nacional de México Instituto Tecnológico de Durango ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>México</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2021</year>
</pub-date>
<volume>13</volume>
<numero>27</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-07052021000200106&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-07052021000200106&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-07052021000200106&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Introducción: La contaminación del aire es un problema ambiental causado por actividades antropogénicas. Uno de los contaminantes con mayor impacto a la salud es el ozono, derivado de los óxidos de nitrógeno (NOx) y compuestos orgánicos volátiles que reaccionan con la radiación solar para formar el ozono troposférico. Estos procesos de oxidación en la química atmosférica se conocen como precursores biogénicos del ozono (Compuestos Orgánicos Volátiles Biogénicos, COVB) afectando al balance global del carbono donde los incendios forestales se consideran emisores de dióxido de carbono y NOx (Radke et al., 1991). Los tejidos de las plantas contienen compuestos orgánicos que, emitidos en cantidades suficientes, pueden influir en la química atmosférica (Main, 2003). Una de las herramientas geoespaciales de la geomática que permite modelar y analizar la distribución de contaminantes en el aire es la aplicación de la geoestadística mediante la interpolación. El objeto de este análisis es representar los patrones espaciales de las concentraciones de O3 por medio de la estimación de valores en áreas no muestreadas.  Método: La interpolación espacial destaca como técnica para la evaluación de la contaminación atmosférica, que posibilita la identificación de zonas expuestas a niveles de riesgo de algún contaminante. Análisis de regresión e interpolación como Kriging, permiten la predicción de ozono en zonas no muestreadas de la Ciudad de Durango. También permite identificar estratos de población en zona urbana y puntos críticos de contaminación, además es posible evaluar el grado de exposición a niveles de ozono.  Resultados: El promedio horario por mes calculado en las tres estaciones permitió determinar el lapso en que la concentración de O3 fue máxima y mínima. Con las interpolaciones realizadas con método Kriging ordinario, y mediante álgebra de mapas, se determinó la zona de influencia del contaminante. Existen mayores concentraciones en la zona poniente de la ciudad; esto coincide con otros estudios que muestran que los niveles de O3 fueron mayores en las periferias que en la zona centro debido a la vegetación, que aporta precursores del O3. La zona de influencia se encuentra distribuida en áreas donde se rebasa el valor promedio de 0.032 ppm de dos hasta 11 veces en 24 horas.  Conclusión: El análisis del ciclo diurno del ozono mostró mayores concentraciones en mayo. El método Kriging ordinario realizó una predicción aceptable, de acuerdo con los errores de predicción presentados en otros trabajos, considerando el número de estaciones para determinar la zona de influencia, donde se rebasó el promedio de concentración de ozono troposférico. El ozono mostró correlación positiva con la variable de temperatura en la zona central y noroeste, mientras que presentó una positiva y menor en la zona poniente. Esta relación indica que los niveles de O3 en la ciudad dependen significativamente de la temperatura.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Introduction: Air pollution is an environmental problem caused by anthropogenic activities. One of the pollutants with the greatest impact on health is ozone, derived from nitrogen oxides (NOx) and volatile organic compounds that react with solar radiation to form tropospheric ozone. These oxidation processes in atmospheric chemistry are known as biogenic ozone precursors (biogenic Volatile Organic Compounds, VOCs) affecting the global carbon balance where forest fires are considered emitters of carbon dioxide and NOx (Radke et al. 1991). Plant tissues contain organic compounds that emitted in sufficient quantities can influence atmospheric chemistry (Main, 2003). One of the geospatial tools of geomatics that allows modeling and analysis of the distribution of pollutants in the air is the application of geostatistics through interpolation. The purpose of this analysis is to represent the spatial patterns of O3 concentrations by estimating values in non-sampled areas.  Methods: Spatial interpolation stands out as a technique for the evaluation of atmospheric pollution, which makes it possible to identify areas exposed to risk levels of some pollutant. Regression and interpolation analysis, such as Kriging, allow the prediction of ozone in non-sampled areas of the city of Durango. It also allows the identification of population strata in urban areas and pollution hotspots, and it is also possible to evaluate the degree of exposure to ozone levels.  Results: The hourly average per month calculated at the three stations allowed determine the period in which the O3 concentration was at its maximum and minimum. With the interpolations performed with the ordinary Kriging method and by means of map algebra, the zone of influence of the pollutant was determined. There are higher concentrations in the western part of the city; this coincides with other studies where O3 levels were higher in the outskirts than in the central area, due to the vegetation, which provides O3 precursors. The zone of influence is distributed in areas where the average value of 0.032 ppm is exceeded from two to 11 times in 24 hours.  Conclusion: The analysis of the diurnal ozone cycle showed higher concentrations in May. The ordinary Kriging method performed an acceptable prediction according to the prediction errors presented in other research, considering the number of stations to determine the zone of influence where the average tropospheric ozone concentration was exceeded. Ozone showed a positive correlation with the temperature variable in the central and northwest zone, while it presented a positive and lower correlation in the west zone. This relationship indicates that O3 levels in the city depend significantly on temperature.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[contaminación atmosférica]]></kwd>
<kwd lng="es"><![CDATA[geomática]]></kwd>
<kwd lng="es"><![CDATA[geoestadística]]></kwd>
<kwd lng="es"><![CDATA[interpolación espacial]]></kwd>
<kwd lng="es"><![CDATA[Kriging]]></kwd>
<kwd lng="es"><![CDATA[ozono]]></kwd>
<kwd lng="es"><![CDATA[temperatura]]></kwd>
<kwd lng="es"><![CDATA[compuestos orgánicos volátiles]]></kwd>
<kwd lng="es"><![CDATA[precursores de ozono]]></kwd>
<kwd lng="es"><![CDATA[distribución espacial]]></kwd>
<kwd lng="es"><![CDATA[química atmosférica]]></kwd>
<kwd lng="en"><![CDATA[atmospheric pollution]]></kwd>
<kwd lng="en"><![CDATA[geomatic]]></kwd>
<kwd lng="en"><![CDATA[geostatistics]]></kwd>
<kwd lng="en"><![CDATA[spatial interpolation]]></kwd>
<kwd lng="en"><![CDATA[Kriging]]></kwd>
<kwd lng="en"><![CDATA[ozone]]></kwd>
<kwd lng="en"><![CDATA[temperature]]></kwd>
<kwd lng="en"><![CDATA[volatile organic compounds]]></kwd>
<kwd lng="en"><![CDATA[ozone precursors]]></kwd>
<kwd lng="en"><![CDATA[spatial distribution]]></kwd>
<kwd lng="en"><![CDATA[atmospheric chemistry]]></kwd>
</kwd-group>
</article-meta>
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