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http://repositorio.utfpr.edu.br/jspui/handle/1/30152
Título: | Predição de ozônio troposférico no monitoramento da qualidade do ar |
Título(s) alternativo(s): | Prediction of tropospheric ozone in air quality monitoring |
Autor(es): | Menezes, Ana Paula Fernandes Lucio Daniel, Bruna Henemann Armani, Fernando Augusto Silveira Lopes, Yuri Kaszubowski |
Palavras-chave: | Ozônio Ar - Controle de qualidade Banco de dados Ozone Ar quality management Data bases |
Data do documento: | 6-Nov-2021 |
Câmpus: | Dois Vizinhos |
Citação: | MENEZES, Ana Paula Fernandes Lucio; DANIEL, Bruna Henemann; ARMANI, Fernando Augusto Silveira; LOPES, Yuri Kaszubowski. Prediction of tropospheric ozone in air quality monitoring. In: CONGRESSO DE CIÊNCIA E TECNOLOGIA DA UTFPR-DV, 6. 2021, On-line. Anais... Dois Vizinhos: UTFPR, 2021. On-line. disponível em: <http://portal.utfpr.edu.br/estrutura/pesquisa-e-pos-graduacao/dirppg/dois-vizinhos>. |
Abstract: | Resulting of the chemical reaction between primary pollutants, tropospheric ozone (O3) causes extensive damage to human health, vegetation and animals due to its high oxidative power. Sensors for accurately measuring O3 are expensive, difficult to handle, and require regular maintenance, which renders its availability at air quality stations difficult, unlike those used to measure the elements that compose O3. In this paper, we use a forecasting time series method developed by the Facebook - Prophet model. The approach is to apply this model to real data collected during the period of 2018 to 2020 from an air quality station in Parana, Brazil, to predict O3 from meteorological variables combined with as few sensors of primary pollutants as possible but aiming for accurate results. |
URI: | http://repositorio.utfpr.edu.br/jspui/handle/1/30152 |
Aparece nas coleções: | DV - Ciência de Dados |
Arquivos associados a este item:
Arquivo | Descrição | Tamanho | Formato | |
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predicaoozonioqualidadear.pdf | 745,44 kB | Adobe PDF | Visualizar/Abrir |
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