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dc.contributor.author
Represa, Natacha Soledad
dc.contributor.author
Fernández Sarría, Alfonso
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Porta, Atilio Andrés
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Palomar Vazquez, Jesús
dc.date.available
2022-01-18T14:42:10Z
dc.date.issued
2020-03
dc.identifier.citation
Represa, Natacha Soledad; Fernández Sarría, Alfonso; Porta, Atilio Andrés; Palomar Vazquez, Jesús; Data mining paradigm in the study of air quality; Springer; Environmental Processes; 7; 1; 3-2020; 1-21
dc.identifier.issn
2198-7491
dc.identifier.uri
http://hdl.handle.net/11336/150224
dc.description.abstract
Air pollution is a serious global problem that threatens human life and health, as well as the environment. The most important aspect of a successful air quality management strategy is the measurement analysis, air quality forecasting, and reporting system. A complete insight, an accurate prediction, and a rapid response may provide valuable information for society’s decision-making. The data mining paradigm can assist in the study of air quality by providing a structured work methodology that simplifies data analysis. This study presents a systematic review of the literature from 2014 to 2018 on the use of data mining in the analysis of air pollutant measurements. For this review, a data mining approach to air quality analysis was proposed that was consistent with the 748 articles consulted. The most frequent sources of data have been the measurements of monitoring networks, and other technologies such as remote sensing, low-cost sensors, and social networks which are gaining importance in recent years. Among the topics studied in the literature were the redundancy of the information collected in the monitoring networks, the forecasting of pollutant levels or days of excessive regulation, and the identification of meteorological or land use parameters that have the most substantial impact on air quality. As methods to visualise and present the results, we recovered graphic design, air quality index development, heat mapping, and geographic information systems. We hope that this study will provide anchoring of theoretical-practical development in the field and that it will provide inputs for air quality planning and management.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Springer
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
AIR POLLUTION
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AIR QUALITY
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DATA MINING
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ENVIRONMENTAL MANAGEMENT
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Otras Ciencias de la Tierra y relacionadas con el Medio Ambiente
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Ciencias de la Tierra y relacionadas con el Medio Ambiente
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CIENCIAS NATURALES Y EXACTAS
dc.title
Data mining paradigm in the study of air quality
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2020-12-16T16:08:15Z
dc.identifier.eissn
2198-7505
dc.journal.volume
7
dc.journal.number
1
dc.journal.pagination
1-21
dc.journal.pais
Estados Unidos
dc.description.fil
Fil: Represa, Natacha Soledad. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigaciones del Medio Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones del Medio Ambiente; Argentina. Universidad Politécnica de Valencia; España
dc.description.fil
Fil: Fernández Sarría, Alfonso. Universidad Politécnica de Valencia; España
dc.description.fil
Fil: Porta, Atilio Andrés. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigaciones del Medio Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones del Medio Ambiente; Argentina
dc.description.fil
Fil: Palomar Vazquez, Jesús. Universidad Politécnica de Valencia; España
dc.journal.title
Environmental Processes
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/s40710-019-00407-5
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs40710-019-00407-5
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