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Forestry Studies
Volume 78 (2023): Issue 1 (November 2023)
Open Access
Air pollution monitoring with
Tradescantia
hybrid and optical sensors in Curitiba and Araucária, Brazil
Leatrice Talita Rodrigues
Leatrice Talita Rodrigues
,
Emílio Graciliano Ferreira Mercuri
Emílio Graciliano Ferreira Mercuri
and
Steffen Manfred Noe
Steffen Manfred Noe
| Nov 09, 2023
Forestry Studies
Volume 78 (2023): Issue 1 (November 2023)
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Article Category:
Research paper
Published Online:
Nov 09, 2023
Page range:
57 - 71
Received:
Mar 31, 2023
Accepted:
May 30, 2023
DOI:
https://doi.org/10.2478/fsmu-2023-0005
© 2023 Leatrice Talita Rodrigues et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Figure 1.
Location of cities and points studied.
Figure 2.
Tradescantia sp. clone 4430 and its main parts, adapted from Small (1922).
Figure 3.
Illustration of the Backward Sliding Window (BSW) Method for detecting possible exposure window size and lag time before inflorescence sampling.
Figure 4.
Stamen hair mutations by the Trad-SHM bioassay, indicated by arrows.
Figure 5.
Boxplots of (a) daily mean PM2.5 concentration, (b) daily mean PM10 concentration and (c) mutation frequencies in stamen hair for the sample points. The number of sampling days (n) is indicated for each station, averages are indicated as white circles.
Figure 6.
Time series of PM10 and PM2.5 average daily concentration and Tradescantia sp. clone 4430 mutations per 1000 stamen hair according to the sampling day. SD is the standard deviation considering all sampling points, except the control.
Figure 7.
Daily variation of (a) PM10 and (b) PM2.5 in sampling points, except the control point. Hourly means are depicted with 5 times the standard error (SE) colored shaded area.
Figure 8.
BSW Method correlation analysis between PM and mutations for detecting lag time and window size of exposition (a) PM2.5 and (b) PM10.
Figure 9.
Results of the BSW Method, showing the size of the exposure window and the lag time adopted for PM2.5 and PM10.
Figure 10.
Pearson’s correlation between PM10 and PM2.5 × mutations per 1000 stamen hairs of Tradescantia sp. clone 4430 for selected stations.