Performance of fine particulate matter data on air quality in an epidemiological study in Salvador, Brazil
ABSTRACT Objective: To evaluate the performance of satellite-derived PM2.5 concentrations against ground-based measurements in the municipality of Salvador (state of Bahia, Brazil) and the implications of these estimations for the associations of PM2.5 with daily non-accidental mortality. Methods:...
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| Language: | English |
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Associação Brasileira de Pós-Graduação em Saúde Coletiva
2024-12-01
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| Series: | Revista Brasileira de Epidemiologia |
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| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2024000100462&lng=en&tlng=en |
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| author | Ludmilla Viana Jacobson Sandra Hacon Vanúcia Schumacher Clarcson Plácido Conceição Dos Santos Nelzair Vianna |
| author_facet | Ludmilla Viana Jacobson Sandra Hacon Vanúcia Schumacher Clarcson Plácido Conceição Dos Santos Nelzair Vianna |
| author_sort | Ludmilla Viana Jacobson |
| collection | DOAJ |
| description | ABSTRACT Objective: To evaluate the performance of satellite-derived PM2.5 concentrations against ground-based measurements in the municipality of Salvador (state of Bahia, Brazil) and the implications of these estimations for the associations of PM2.5 with daily non-accidental mortality. Methods: This is a daily time series study covering the period from 2011 to 2016. A correction factor to improve the alignment between the two data sources was proposed. Effects of PM2.5 were estimated in Poisson generalized additive models, combined with a distributed lag approach. Results: According to the results, satellite data underestimated the PM2.5 levels compared to ground measurements. However, the application of a correction factor improved the alignment between satellite and ground-based data. We found no significant differences between the estimated relative risks based on the corrected satellite data and those based on ground measurements. Conclusion: In this study we highlight the importance of validating satellite-modeled PM2.5 data to assess and understand health impacts. The development of models using remote sensing to estimate PM2.5 allows the quantification of health risks arising from the exposure. |
| format | Article |
| id | doaj-art-31b220cf1b954282a31417283bfdec9f |
| institution | OA Journals |
| issn | 1980-5497 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Associação Brasileira de Pós-Graduação em Saúde Coletiva |
| record_format | Article |
| series | Revista Brasileira de Epidemiologia |
| spelling | doaj-art-31b220cf1b954282a31417283bfdec9f2025-08-20T02:36:53ZengAssociação Brasileira de Pós-Graduação em Saúde ColetivaRevista Brasileira de Epidemiologia1980-54972024-12-012710.1590/1980-549720240068Performance of fine particulate matter data on air quality in an epidemiological study in Salvador, BrazilLudmilla Viana Jacobsonhttps://orcid.org/0000-0002-6698-4431Sandra Haconhttps://orcid.org/0000-0002-8222-0992Vanúcia Schumacherhttps://orcid.org/0000-0003-1753-567XClarcson Plácido Conceição Dos Santoshttps://orcid.org/0000-0001-7598-3775Nelzair Viannahttps://orcid.org/0000-0002-5183-6671ABSTRACT Objective: To evaluate the performance of satellite-derived PM2.5 concentrations against ground-based measurements in the municipality of Salvador (state of Bahia, Brazil) and the implications of these estimations for the associations of PM2.5 with daily non-accidental mortality. Methods: This is a daily time series study covering the period from 2011 to 2016. A correction factor to improve the alignment between the two data sources was proposed. Effects of PM2.5 were estimated in Poisson generalized additive models, combined with a distributed lag approach. Results: According to the results, satellite data underestimated the PM2.5 levels compared to ground measurements. However, the application of a correction factor improved the alignment between satellite and ground-based data. We found no significant differences between the estimated relative risks based on the corrected satellite data and those based on ground measurements. Conclusion: In this study we highlight the importance of validating satellite-modeled PM2.5 data to assess and understand health impacts. The development of models using remote sensing to estimate PM2.5 allows the quantification of health risks arising from the exposure.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2024000100462&lng=en&tlng=enAir pollutionPublic healthTime seriesInformation systems |
| spellingShingle | Ludmilla Viana Jacobson Sandra Hacon Vanúcia Schumacher Clarcson Plácido Conceição Dos Santos Nelzair Vianna Performance of fine particulate matter data on air quality in an epidemiological study in Salvador, Brazil Revista Brasileira de Epidemiologia Air pollution Public health Time series Information systems |
| title | Performance of fine particulate matter data on air quality in an epidemiological study in Salvador, Brazil |
| title_full | Performance of fine particulate matter data on air quality in an epidemiological study in Salvador, Brazil |
| title_fullStr | Performance of fine particulate matter data on air quality in an epidemiological study in Salvador, Brazil |
| title_full_unstemmed | Performance of fine particulate matter data on air quality in an epidemiological study in Salvador, Brazil |
| title_short | Performance of fine particulate matter data on air quality in an epidemiological study in Salvador, Brazil |
| title_sort | performance of fine particulate matter data on air quality in an epidemiological study in salvador brazil |
| topic | Air pollution Public health Time series Information systems |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2024000100462&lng=en&tlng=en |
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