In this paper, we propose a real-time prediction model that can respond to particulate matters (PM) in the air, which are an indication of poor air quality. The model applies interpolation to air quality and weather data and then uses a Convolutional Neural Network (CNN) to predict PM concentrations. The interpolation transforms the irregular spatial data into an equally spaced grid, which the model requires. This combination creates the interpolated CNN (ICNN) model that we use to predict PM10 and PM2.5 concentrations. The PM10 and PM2.5 evaluation results show an effective prediction performance with an R-squared higher than 0.97 and a root mean square error (RMSE) of approximately 16% of the standard deviation. Furthermore, both PM10 and PM2.5 prediction models forecast high concentrations with high reliability, with a probability of detection higher than 0.90 and a critical success index exceeding 0.85. The proposed ICNN prediction model achieves a high prediction performance using spatio-temporal information and presents a new direction in the prediction field.
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http://dx.doi.org/10.1038/s41598-021-91253-9 | DOI Listing |
Med Sci Monit
May 2024
Department of Maternal Health Care, Maternal and Child Health Hospital of Tongling, Tongling, Anhui, China (mainland).
BACKGROUND Exposure to air pollution (AP) during pregnancy is associated with pre-labor rupture of membranes (PROM). However, there is limited research on this topic, and the sensitive exposure windows remain unclear. The present study assessed the association between AP exposure and the risk of PROM, as well as seeking to identify the sensitive time windows.
View Article and Find Full Text PDFPathog Glob Health
September 2023
Center for Evidence-Based Health Care, Department of Medical Research, Taipei Medical University Shuang Ho Hospital, New Taipei, Taiwan.
Air pollution may be involved in spreading dengue fever (DF) besides rainfalls and warmer temperatures. While particulate matter (PM), especially those with diameter of 10 μm (PM10) or 2.5 μm or less (PM25), and NO2 increase the risk of coronavirus 2 infection, their roles in triggering DF remain unclear.
View Article and Find Full Text PDFEnviron Res
November 2022
School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China. Electronic address:
Previous studies have attempted to clarify the relationship between the occurrence of pulmonary tuberculosis (PTB) and exposure to air pollutants. However, evidence from multi-centres, particularly at the national level, is scarce, and no study has examined the modifying effect of greenness on air pollution-TB associations. In this study, we examined the association between long-term exposure to ambient air pollutants (PM p.
View Article and Find Full Text PDFJ Clean Prod
July 2021
Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
Air quality changes during the coronavirus disease 2019 (COVID-19) pandemic in China has attracted increasing attention. However, more details in the changes, future air quality trends, and related death benefits on a national scale are still unclear. In this study, a total of 352 Chinese cities were included.
View Article and Find Full Text PDFRev Chil Pediatr
April 2019
Instituto de Ciencias Biomédicas, Facultad de Medicina, Universidad de Chile, Chile.
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