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Showing 61 - 80 results of 35,792 for search '(( significant decrease levels ) OR ( significant concern decrease ))*', query time: 0.63s Refine Results
  1. 61
    PM2.5 and wind variations in time in the considered periods in 2019 and 2020.

    PM2.5 and wind variations in time in the considered periods in 2019 and 2020. by Daniele Pala (1524016)

    Published 2022
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  2. 62
    Scatterplots describing the correlation between wind speed, temperature, humidity, precipitations, solar radiation and PM concentration.

    Scatterplots describing the correlation between wind speed, temperature, humidity, precipitations, solar radiation and PM concentration. by Daniele Pala (1524016)

    Published 2022
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  3. 63
    Heatmaps showing adjusted mean variations in terms of PM<sub>2.5</sub> between the 2019 and 2020 study periods by sensor and daily hour intervals.

    Heatmaps showing adjusted mean variations in terms of PM<sub>2.5</sub> between the 2019 and 2020 study periods by sensor and daily hour intervals. by Daniele Pala (1524016)

    Published 2022
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  4. 64
    Range of the PM10 values measured by the seven co-located sensors.

    Range of the PM10 values measured by the seven co-located sensors. by Daniele Pala (1524016)

    Published 2022
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  5. 65
    PM10 and temperature variations in time in the considered periods in 2019 and 2020.

    PM10 and temperature variations in time in the considered periods in 2019 and 2020. by Daniele Pala (1524016)

    Published 2022
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  6. 66
    PM10 variations by daily hour interval.

    PM10 variations by daily hour interval. by Daniele Pala (1524016)

    Published 2022
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  7. 67
    PM2.5 and PM10 distribution during 2019 and 2020.

    PM2.5 and PM10 distribution during 2019 and 2020. by Daniele Pala (1524016)

    Published 2022
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  8. 68
    PM<sub>2.5</sub> variations by daily hour interval.

    PM<sub>2.5</sub> variations by daily hour interval. by Daniele Pala (1524016)

    Published 2022
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  9. 69
    PM2.5 concentration and temperature in the two considered periods in 2019 (upper plot) and 2020 (lower plot).

    PM2.5 concentration and temperature in the two considered periods in 2019 (upper plot) and 2020 (lower plot). by Daniele Pala (1524016)

    Published 2022
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  10. 70
    PM<sub>10</sub> concentration and wind speed in the two considered periods in 2019 (upper plot) and 2020 (lower plot).

    PM<sub>10</sub> concentration and wind speed in the two considered periods in 2019 (upper plot) and 2020 (lower plot). by Daniele Pala (1524016)

    Published 2022
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  11. 71
    PM10 correlation matrix.

    PM10 correlation matrix. by Daniele Pala (1524016)

    Published 2022
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  12. 72
    Results of the Wilcoxon Mann Whitney test on ARPA data.

    Results of the Wilcoxon Mann Whitney test on ARPA data. by Daniele Pala (1524016)

    Published 2022
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  13. 73
    PM<sub>10</sub> daily trends during 2019 and 2020 study periods measured by the two ARPA monitoring stations.

    PM<sub>10</sub> daily trends during 2019 and 2020 study periods measured by the two ARPA monitoring stations. by Daniele Pala (1524016)

    Published 2022
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  14. 74
    Correlation between variations in terms PM2.5 and PM10 between year 2019 and 2020.

    Correlation between variations in terms PM2.5 and PM10 between year 2019 and 2020. by Daniele Pala (1524016)

    Published 2022
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  15. 75
    Range of the PM2.5 values measured by the seven co-located sensors.

    Range of the PM2.5 values measured by the seven co-located sensors. by Daniele Pala (1524016)

    Published 2022
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  16. 76
    PM2.5 correlation matrix.

    PM2.5 correlation matrix. by Daniele Pala (1524016)

    Published 2022
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  17. 77
    Correlation between PM2.5 and PM10 during years 2019 and 2020.

    Correlation between PM2.5 and PM10 during years 2019 and 2020. by Daniele Pala (1524016)

    Published 2022
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  18. 78
    Multivariate linear mixed effects model regression: Variation in terms of PM2.5 and PM10 between 2019 and 2020 accounting for confounders.

    Multivariate linear mixed effects model regression: Variation in terms of PM2.5 and PM10 between 2019 and 2020 accounting for confounders. by Daniele Pala (1524016)

    Published 2022
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  19. 79
    Heatmaps showing the median difference between observed and LMM—predicted PM2.5 and PM10 during 2020 by sensor and daily hour intervals.

    Heatmaps showing the median difference between observed and LMM—predicted PM2.5 and PM10 during 2020 by sensor and daily hour intervals. by Daniele Pala (1524016)

    Published 2022
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  20. 80
    Mapping Blood Lead Levels in China during 1980–2040 with Machine Learning

    Mapping Blood Lead Levels in China during 1980–2040 with Machine Learning by Yanni Zhang (347305)

    Published 2024
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