PROCEEDINGS of the23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Sound absorption by tree barkMengmeng LI1; Timothy Van Renterghem2; Jian KANG1,3; Dick Botteldooren2
1

School of Architecture, Harbin Institute of Technology; Heilongjiang Cold Region Architectural Science Key

2

Laboratory, China
Ghent University, Faculty of Engineering and Architecture, Department of Information Technology, WAVES
research group, Belgium
3
UCL Institute for Environmental Design and Engineering, The Bartlett, University College London, UKABSTRACT
Scattering of sound waves by trunks is part of the noise reducing potential of tree belts, and it has been shown
before that the absorbing properties of the trunks are relevant in this respect. Detailed information on barkabsorption is currently very limited. Therefore, laboratory experiments were conducted with an impedance
tube to measure the bark sound absorption of various species, including variations in bark thickness, tree age,density, and trunk diameter. Preliminary measurements were made to define the relevant part of the trunk for
its acoustic absorption and to come to a reproducible sample handling procedure. The measurements showthat the absorption (at normal incidence) is generally below 0.1 for the deciduous species considered, andthat there is a small variation in between them.
Keywords: Sound absorption, Tree bark, Impedance tube

1. INTRODUCTION
Scattering of sound waves by trunks contributes largely to the noise reduction of tree belts, and it
has been shown before that also the absorbing properties of the trunks are relevant in this respect.
While absorption by plants did receive quite some attention before (1, 2, 7), research on barkabsorption is very limited.
In his pioneering work, Reethof (3) measured the absorption coefficient of a few tree bark samples
in the impedance tube. His main conclusions were that the absorption i s rather frequency independent
in the range of frequencies covered. Some species gave significant higher absorption values.
However, these were only exploratory measurements, and no further analysis was made to reveal
what parameters could potentially predict tree stem absorption. Since this study dates already fromthe 70’s, and no further attention has been paid to acoustically charac terize tree bark, more extensiveand systematic work is needed as will be initiated in this paper.
Although the absorption of bark might be rather low, full-wave numerical simulations reported in
Van Renterghem’s research (4) shows that even small variations can be relevant e.g. when looking at
sound propagation through tree belts. Knowledge of the variation in bark absorption between species
and their influencing parameters are therefore of interest to optimize sound attenuation by tree belt.
There are two main methods for measuring the sound absorption coefficient of a material : one isthe reverberation chamber method, and the other one is the impedance tube method. Both have beenused before to acoustically characterize plant material. Horoshenkov (1) used an impedance tube totest the sound absorption coefficient of five different types of low growing plants with and without
soil. It was found that the absorption coefficient of plants is mainly influenced by the density of theleaf area and the leaf main orientation angle. He also showed that there is an interaction between
plants and the soil: for heavy-density clay base soil, the absorption in combination with plants
significantly increased compared to bare soil. For low-density substratum soil, this interaction is muchless pronounced. Yang (2) carried out measurements in a reverberation chamber to test random1limmeng@stu.hit.edu.cn

2 timothy.vanrenterghem@ugent.be582

incidence absorption of plants. In the mid frequencies, the absorption coefficient of top soil increased
approximately with 0.2 in case of plant cover. Near 2000 Hz, there was no obvious relationshipbetween absorption and plant cover, and the absorption decreased by about 0.1 when the vegetation
cover increased at higher frequency.
In the current work, the impedance tube technique has been used to measure the absorption of barksamples, similar to Reethof. In contrast to the reverberation chamber method, the absorption at normal
incidence is then measured.

2. METHODOLOGY

Absorption coefficient

2.1 Experimental Setting
The diameter of the impedance tube was 100 mm, yielding a maximum frequency of 1.5 kHz at
which absorption can be measured. A two microphone technique was used, and phase errors wereminimized by microphone swapping. The benefits of this specific procedure were shown before in
Chung’s research (5, 6).
The effect of the necessary thickness of the sample was first tested. We started off with a thicknessof the wood sample of about 5 cm, while the bark itself is about 1cm. The wood behind the bark has
been cut from 4 cm to 2 cm in different steps. Above 2cm there was no statistically significant effecton the absorption. To prevent the circumferential gap problem, it has been ensured that each sam ple was well sealedby the use of plasticine. Each sample was put several times in place (and re-sealed) to check thereproducibility of this rather uncommon sample handling (see Fig.1). Variance analysis shows that therepetitions are not significantly different. Before and after each measurement, the absorption of theempty tube was measured to ensure correct measurements in this low absorption range.
In this study, from each trunk cross section, four cylindrical samples from different orientation
along its circumference were made including about 2cm of wood behind the bark.
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
00100200

Repeat1
Repeat5300

400500600700Repeat2
Repeat6800

900 1000 1100 1200 1300 1400

Repeat4 Frequency
Repeat8

Repeat3
Repeat7

Fig.1 The results for repeat measurements
2.2 Plant Selection
In this study, six species were selected. Table 1 shows the basic characteristics of these species.
For the bark classification, Bertrand’s (7) research shows a method used to recognize species basedon visual bark texture criteria. The tree bark samples can be divided into seven types namely “smooth”,“lenticels”, “furrows”, “ridges”, “cracks”, “scales” and “strips”.
Table 1 Characteristics of 6 plant species
PhotosThickness of bark
Diameter ofSpecies
TypeAgetrunk(cm)12341234
Acacia ARidges

34

20.50

1.50 1.20 1.90 1.50

Walnut B

Furrows

20

22.40

1.30 1.10 1.10 1.05

Cherry C

Lenticels

30

25.00

1.50 1.20 1.40 1.60

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BirchDCracks

32

24.40

1.30 1.40 1.35 1.60

Poplar E

Lenticels

26

22.90

1.40 1.50 1.40 1.20

Willow F

Furrows

14

24.60

1.30 1.10 1.10 1.00

2.3 Data Extraction
Given the impedance tube diameter and the distance between the microphones, the result can beused in the frequency range of 150 Hz to 1500 Hz. The data was processed to one-third octave bandaveraged absorption values. In this study, for each trunk, the reported value is the average from theabsorption coefficient of four cylindrical samples cut along the circumference of the trunk. In addition,
each bark sample was measured four times including repositioning and resealing in the impedance
tube.

3. Results
3.1 Absorption of barkThe results show that the tree barks considered in this work have a rather low absorption and only
small differences can be found in between the different species. As Fig.2 shows, the absorption of treebarks are near 0.02-0.04, while there is no clear frequency dependence.

Absorption Coefficient

0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0.00
0100

BarkA

200

300

BarkB

400

500

600

BarkC

700

800

BarkD

900

1000

1100

BarkE

1200

BarkF

1300

1400

Frequency
Empty

Fig.2 Absorption Coefficient for 6 plants
A three-way ANOVA analysis showed that the plant species and taking different bark samples atother parts along the trunk circumference are statistically significant effects, while the repeatedrepositioning of the same sample had no significant effect on the measurement results. Plant species
had statistically significant effect on bark absorption coefficient for all one-third octave band in thefrequency range of 150 Hz to 1500 Hz. Figure 3 shows the differences between the four samples ofeach trunk cross section. Note that the bark thicknesses can be different.
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
00.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
00300600

900

1200

1500

Frequency

584

0300

600

900

1200

1500

Frequency

BarkA

BarkB

0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
00.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
00300

600

900

120001500

300

BarkC

300

600

900

900

1200

1500

900

1200

1500

Frequency

BarkD

0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
00600

Frequency

1200

1500

Frequency

0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
00

BarkE

300

600

Frequency

BarkF

Fig. 3 The absorption coefficient of 4 bark samples taken at different positions along the trunk
circumference, for the 6 species considered.
3.2 Factors influencing absorption
There are potentially multiple factors that can influence the sound absorption by tree bark. It could
be of practical use to predict this absorption based on common characteristics like e.g. thickness ofthe bark, age, trunk diameter or bark roughness. The shape index (8, 9) was used to characterize theroughness of the bark; the closer this value is to 1, the better the bark cross section approaches a circle.
Fig. 4 shows the bark roughness of the six trees considered.

Fig. 4 The roughness of barks
Table 2 shows the correlation between a number of selected bark properties and the averagedabsorption. Significant factors are the thickness of bark, tree age, diameter of the trunk and barkroughness. Except for the diameter of the trunk, these factors are positively correlated with the(averaged) absorption coefficient. Tree age is the best predictor for the absorption coefficient. Note,however, that these factors are not independent.
Table 2 Correlation between bark properties and absorption
Thickness of bark,

Age,

Diameter of trunk,

Bark roughness,

Ti(cm)Ai

Di(cm)

Ri-0.395*

0.521**

Absorption coefficient
0.533*
0.671**** Significantly correlated at the 0.01 level (both sides)* Significantly correlated at the 0.05 level (both sides)

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Multiple linear regression showed that the averaged absorption coefficient ߙ݅ in the frequency
range 500-1600Hz for a bark can be predicted from the following expression:
αi= 0.029255 Ri -0.0026156 Di+ 0.057638, (R2=0.486, F-statistics p=0.009)(1)
with ܴ݅ the bark roughness and‫ ݅ܦ‬the diameter of trunk. The absorption coefficient reduces withtrunk diameter and increases with bark roughness. The effect of diameter could be caused by adeficiency in the way of measuring – smaller trunk diameters could have lead to a larger absorbing
surface in the tube since it deviates more from a fully flat surface.
3.3 Moss-grown samples
The surface of barks are easily grown in forest stands. A sample has been tested where a part ofthe bark was grown with moss. As Fig. 5 shows, Bark1is the sample with moss on the surface, whichhas higher absorption than the other parts of the trunk circumference. This increased absorption ismainly found in the lower frequency range. Although the absorption of bark with moss increases,
values stay below 0.1.
0.1

Absorption Coefficient

0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
00100

200

300

400

500

600

700

800

900

Bark1˄with moss˅
bark3˄without moss˅

1000

1100

1200

1300

1400

bark2˄without moss˅ Frequency
bark4˄without moss˅

Fig. 5 The difference of absorption between bark with moss and without moss

Absorption Coefficient

3.4 Sample ageDuring the first 30 days after sample collection in the field, bark F was sealed in plastic to prevent
water loss. Afterwards, the sample was allowed to dry in the air. Figure 6 shows the absorption
coefficient of bark F at different moments. It can be seen that there is not much difference in absorption
after 5 and 20 days. Afterwards, the absorption decreased slightly, which is most likely to be related
to the reduction in bark thickness.
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
00100

200

BarkF(5days)

300

400

500

600

700

BarkF(20days)

8009001000 1100 1200 1300 1400

BarkF(71days)

Frequency
BarkF(78days)

Fig. 6 The influence of sample age on bark F’s absorption

4. CONCLUSIONS AND FURTHER WORK
Although the absorption of these six species is less than 0.1, statistically significant differences586

can be found in between species. Bark thickness, tree age, trunk diameter and bark roughness can becorrelated with the absorption. Based on a multiple linear regression, bark roughness is the factor thatwas retained, together with trunk diameter. The latter is potentially a deficiency by measuring in theimpedance tube.
In this study, all six species come from deciduous trees. Future work should include coniferous
trees. In addition, other characteristics of the bark should be included to analyze the influencing
factors.

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