<?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>1909-3667</journal-id>
<journal-title><![CDATA[Tecciencia]]></journal-title>
<abbrev-journal-title><![CDATA[Tecciencia]]></abbrev-journal-title>
<issn>1909-3667</issn>
<publisher>
<publisher-name><![CDATA[Universidad ECCI]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1909-36672020000100015</article-id>
<article-id pub-id-type="doi">10.18180/tecciencia.28.2</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Air quality trend and proposal of a web application for the atmospheric monitoring network in Tabasco, México.]]></article-title>
<article-title xml:lang="es"><![CDATA[Tendencia de la calidad del aire y propuesta de una aplicación web para la red de monitoreo atmosférico en Tabasco, México.]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Magaña-Villegas]]></surname>
<given-names><![CDATA[Elizabeth]]></given-names>
</name>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Díaz-López]]></surname>
<given-names><![CDATA[Mary C.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ramos-Herrera]]></surname>
<given-names><![CDATA[Sergio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Carrera-Velueta]]></surname>
<given-names><![CDATA[Jesús M.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vilchis-Peralta]]></surname>
<given-names><![CDATA[Osiris J.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Juárez Autónoma de Tabasco División Académica de Ciencias Biológicas ]]></institution>
<addr-line><![CDATA[Tabasco ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2020</year>
</pub-date>
<volume>15</volume>
<numero>28</numero>
<fpage>15</fpage>
<lpage>27</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S1909-36672020000100015&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S1909-36672020000100015&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S1909-36672020000100015&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT Air pollution is an increasingly concerning problem given it constitutes a risk for people's health and the environment. In Mexico, there are some regions where society does not know the conditions of air quality, and in some others this information is not used or analyzed. Hence is important the study of air quality evolution to generate strategies that allow to mitigate adverse effects on population. In this research we analyze the trend of Criteria Air Pollutants (PM 10 and O 3 and CO), considering the distribution of good, regular and bad days for air quality, as well as the trend of hourly, daily, monthly and annual concentrations in the city of Villahermosa, Tabasco between 2011-2017, with information provided by the State government, in order to design an effective communication mechanism. We obtained air quality indicators based on the official Mexican regulation and the temporal behavior of the pollutants. Additionally, we trained artificial neural network models for the prediction of air pollutant concentration. Finally, we propose the design of a web portal for the communication of air quality. According to the weekly behavior, is shown that we are exposed daily to potential health hazards by any of the air pollutants, also that the second trimester of each year shows the worst conditions and that the pollutants that have a greater contribution to air pollution in the city are CO, PM 10 and O 3. Likewise, the tendencies of PM 10 and O 3 indicate a slow decrease of -0.5 ug/m 3-year, -0.0004 ppm-year respectively, which requires a redefinition of government strategies that may potentiate their decrease. In this sense, the web portal is proposed under two main approaches: First, with the purpose of communication, aimed to the society so it can take preventive measures on their exposure to high contamination levels. The second approach is aimed to the academic community and government authorities, with graphic information on the criteria air pollutants' tendencies, providing analytical elements for structuring environmental policies.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La contaminación del aire es un problema cada vez más preocupante debido a que constituye un riesgo para la salud de las personas y el ambiente. En México, existen regiones en las cuales la sociedad desconoce las condiciones de la calidad del aire y en otras no se hace uso y análisis de dicha información, por ello es importante el estudio de la evolución de la calidad del aire para generar estrategias que permitan mitigar los efectos adversos a la población. En esta investigación se analizó la tendencia de contaminantes criterio (PM 10 y O 3 y CO), considerando la distribución de los días buenos, regular y malos de la calidad del aire, así como la tendencia de las concentraciones horarias, diarias, mensuales y anuales en la ciudad de Villahermosa, Tabasco para el periodo 2011-2017 con información proporcionada por el gobierno del Estado para diseñar un mecanismo eficaz de comunicación. Se obtuvieron indicadores de calidad del aire con base en las normas oficiales mexicanas y el comportamiento temporal de los contaminantes. Adicionalmente, se entrenaron modelos de red neuronal artificial para la predicción de la concentración de los contaminantes. Finalmente se propuso el diseño de un portal web para la comunicación de la calidad del aire. De acuerdo con el comportamiento semanal, se mostró que todos los días estamos expuestos a potenciales riesgos a la salud por alguno de los contaminantes, que el segundo trimestre de cada año presenta las peores condiciones y que los contaminantes que mayormente condicionan la mala calidad del aire de la ciudad son CO, PM 10 y O 3 . Así mismo, las tendencias de PM 10 y O 3 indican un decrecimiento lento, -0.5 ug/ m 3-año, -0.0004 ppm-año respectivamente, lo que requiere redefinir estrategias gubernamentales que potencialicen su descenso. En este sentido, el portal web se propone bajo dos enfoques. El primero con la finalidad de comunicación, dirigido a la sociedad para que le permita tomar medidas preventivas sobre su exposición a altos niveles de contaminación. El segundo enfoque orientado a la comunidad académica y autoridades gubernamentales cuenta con información gráfica de la tendencia de los contaminantes criterios, que permita tener elementos analíticos para la estructuración de políticas ambientales.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Air Quality]]></kwd>
<kwd lng="en"><![CDATA[Trend]]></kwd>
<kwd lng="en"><![CDATA[Forecast]]></kwd>
<kwd lng="es"><![CDATA[Calidad del Aire]]></kwd>
<kwd lng="es"><![CDATA[Tendencias]]></kwd>
<kwd lng="es"><![CDATA[Pronósticos]]></kwd>
</kwd-group>
</article-meta>
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