Variation of Ba concentration in some plants grown in industrial zone in Türkiye

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Variation of Ba concentration in some plants
grown in industrial zone in Türkiye
Ayşe Öztürk Pulatoğlu
To cite this article: Ayşe Öztürk Pulatoğlu (08 Dec 2023): Variation of Ba concentration
in some plants grown in industrial zone in Türkiye, Forest Science and Technology, DOI:
10.1080/21580103.2023.2290500
To link to this article: https://doi.org/10.1080/21580103.2023.2290500
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UK Limited, trading as Taylor & Francis
Group.
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ARTICLE
Variation of Ba concentration in some plants grown in industrial zone in
T€
urkiye
Ays¸e €
Ozt€
urk Pulato
glu
Faculty of Forestry, Department of Forest Engineering, Kastamonu University, Kastamonu, Turkey
ABSTRACT
This study was carried out on Fagus orientalis Lipsky (Oriental beech), Carpinus orientalis
(Oriental hornbeam), and Quercus petraea (Matt.) Liebl. (Sessile oak) species that naturally
spread out in the C¸aycuma district of Zonguldak province, an industrial area in the north-
western T€
urkiye. The study aimed to determine the annual changes in barium (Ba) concen-
trations in the annual rings of the wood of the species. Moreover, Ba concentrations in the
inner and outer bark were compared with the concentration in the wood, and changes in
Ba concentration were determined by years and directions. As a result, the lowest mean Ba
concentrations were found in hornbeam for all organs, whereas the highest values in the
inner bark (944134 ppb) and wood (46996 ppb) were found in beech. The highest values in
the outer bark were found in oak with 927482 ppb. For the three species, the values
obtained on the outer side of the outer bark were higher. The study showed that all three
species are useful in monitoring the changes in concentrations and the pollution of Ba in
the air and can be used for this purpose. However, the most suitable species that can be
used to reduce Ba concentration is Fagus orientalis, which has the highest Ba storage ability
in the wood part.
ARTICLE HISTORY
Received 27 July 2023
Revised 6 December 2023
Accepted 29 November 2023
KEYWORDS
Air pollution; air quality;
barium; biomonitoring;
heavy metal
Introduction
Together with the growing global population, urban-
ization, and industrialization, the pressure on the
environment also increases and the resulting pollution
negatively affects human health. Industrial activities
and heavy traffic have long-term negative effects on
nature and, therefore, environmental pollution and air
pollution are two of the most important problems
(Kilicoglu et al. 2020; Isinkaralar 2022).
Considering environmental pollution components,
air pollution and particularly heavy metal pollution,
which increases remarkably with industrial operations,
are significantly important. It was reported that there
is a constant increase in the levels of heavy metal con-
centrations in the air, water, and soil due to mining
operations and the use of underground mineral resour-
ces as raw materials (Kumar and Khan 2021; Natasha
et al. 2022). Besides deteriorating the air quality, this
increase also poses a significant threat to all organisms,
especially humans and ecosystems (Br
azov
a et al.
2021). Heavy metals do not easily decompose in nature
(Farzin et al. 2017). They tend to accumulate in the
cells of organisms, and some heavy metals have car-
cinogenic or toxic effects even at low concentrations
(Turkyılmaz et al. 2020; DołeRgowska et al. 2021;
Kumar and Dwivedi 2021). Atmospheric heavy metals
are transferred to the soil by precipitation, and air pol-
lutants lead to diseases among humans when inhaled.
This effect increases to much higher levels in urban
areas because of the increasing concentration of the
population (Aricak et al. 2020; Kilicoglu et al. 2021).
Therefore, it is very important to determine the risk
levels and risky areas of heavy metals that can remain
in nature for a long time without degradation
(Turkyılmaz et al. 2020; Ucun Ozel et al. 2020). The
uptake of heavy metals from the soil to the roots and
their accumulation in the above-ground parts of plants
make them good bioindicators. Various plant organs
have been used for a long time in determining the
concentrations of heavy metals (Sawidis et al. 2011;
Shahid et al. 2017; Turkyilmaz et al. 2018a, b).
Many studies reported that trees can accumulate
pollutants in their annual rings (Perone et al. 2018).
Using the annual rings as a pollution indicator, it is
possible to gather important information about the
chronology and distribution of elements that cause
pollution in the area, where the tree has grown
(Beramendi-Orosco et al. 2013; Yigit 2019; Sevik et al.
2020; Koc 2021).
Monitoring the changes in heavy metal concentra-
tions in the air is crucial to detecting the effects of air
pollution on living organisms and natural ecosystems
and taking measures to improve air quality. Using this
CONTACT Ays¸e €
Ozt€
urk Pulato
glu ayseozturk@kastamonu.edu.tr Faculty of Forestry, Department of Forest Engineering, Kastamonu University,
Kastamonu, Turkey
� 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/),
which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this
article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
FOREST SCIENCE AND TECHNOLOGY
https://doi.org/10.1080/21580103.2023.2290500

method, it is possible to track backward changes in
heavy metal concentrations, particularly in industrial
areas or in areas with increasing traffic-related pollu-
tion (Yayla et al. 2022; Cobanoglu et al. 2023).
However, the number of studies examining the tree
species fitting to this purpose is not enough.
Therefore, it is important to carry out more studies on
different species and regions.
Barium (Ba) is a metal that naturally exists in ample
amounts in nature. However, in studies conducted to
date, Ba has generally been neglected and a very lim-
ited number of studies have been conducted to moni-
tor the change in Ba concentration in the air. It is
industrially used in the production of many different
products (Khan et al. 2022). Ba, its isotopes, com-
pounds, and alloys are used in the production of Zn,
Pb, Ag, rubber, paint, medicine, rat poison, ink, brake
pads, machine oil, radio vacuum tubes and bulbs,
adhesives, candles, photographic paper, bricks, optical
glass, batteries, detergents, drilling applications, the
petroleum industry, plastic and textile products, paper
coatings, oil paint production, special glass production,
ceramic materials, fireworks, and ceramic glazes
(Dibello et al. 2000; Johnson et al. 2017; Lima et al.
2023). However, Ba is one of the most dangerous
heavy metals, and all its compounds have toxic effects
(Cetin and Jawed 2022; Khan et al. 2022). Ba is an
extremely active element and often occurs in nature as
a form of barite (BaSO
4
) and witherite (BaCO
3
)
(B€
ottcher et al. 2018; Peana et al. 2021). According to
Bowen (1966), the average Ba content in soil is 500 mg
kg
−1
. The reported range for Ba soil on a world scale
is 19 to 2368 mg kg
−1
(Madej
on et al. 2013). Schroeder
(1970) reported that Ba in soil was present in concen-
trations ranging from 100 to 3000mg kg
−1
.
People are exposed to Ba through ingestion and
inhalation (Khan et al. 2022), which poses a direct and
indirect potential risk to human health (Lima et al.
2023). The health effects and toxicity of Ba are related
to its solubility. US EPA puts the risk level for oral
intake of Ba as 0.2 mg/kg/day for adults (IRIS 2005;
ATSDR 2013; Kravchenko et al. 2014). Ba compounds
dissolved in water can cause harmful health effects
such as difficulty in breathing, facial numbness, stom-
ach irritation, vomiting, diarrhea, increased blood pres-
sure, brain swelling, arrhythmia, muscle weakness, and
damage to the kidneys, liver, spleen, and heart, and
can lead to death if left untreated (US EPA 1984, 1987;
Aziz et al. 2017; Companhia Ambiental do Estado de
S~
ao Paulo (CETESB) 2017). Approximate acute and
lethal (single) toxic oral doses of BaCl
2
are 0.5 g and 3-
4 g, respectively, for a 70-kg person (Reeves 1979; HSE
1984).
Most Ba exists in low-solubility forms. It is spar-
ingly soluble due to its low absorption in the gastro-
intestinal tract. For this reason, the risk of Ba toxicity
is thought to be very low (Llugany et al. 2000; Menzie
et al. 2008). On the other hand, Ba in the ionic form is
thought to be toxic to humans, animals, and plants at
moderate concentrations (Chaudhry et al. 1997). Pais
and Jones (1998) found that a Ba content of 200 mg
kg
−1
could be moderately toxic and more than 500 mg
kg
−1
could be considered toxic to plants.
The decrease in plant yield and phytotoxic effects
are associated with Ba suppression of K uptake
(Llugany et al. 2000). Llugany et al. (2000) studied
Phaseolus vulgaris in an experiment using a culture
solution containing different doses of Ba. It was found
that Ba interferes with both SO
4 2-
transport from
roots to shoots and Ca transfer to leaves (Llugany
et al. 2000). Similar results were previously found by
Wang (1988) and Wallace and Romney (1971).
Carried out on beech, oak, and hornbeam species
that naturally spread out in the C¸aycuma district of
Zonguldak province, which is an industrial zone in
northwestern T€urkiye, this study aims to determine the
annual changes in Ba concentrations in the annual
rings of beech, oak, and hornbeam trees located in the
industrial zone near C¸aycuma district of Zonguldak
province. In addition, Ba concentrations in the inner
and outer bark were compared to those in the wood.
Moreover, the changes in Ba concentrations were
determined on a yearly and directional basis.
Differences in Ba accumulation in the outer bark,
inner bark, and wood, how those differences change in
different directions, and if this change can be effect-
ively used in monitoring the yearly changes in Ba con-
centration and its changes were evaluated by
interpreting the data obtained.
Material and method
Zonguldak province is among the cities having the
most polluted air in T€
urkiye in terms of particulate
matter pollution and air pollution is the most signifi-
cant environmental problem in the province (URL-1
2019). The main pollutants that cause air pollution in
Zonguldak are generally related to industrialization,
domestic heating in cold weather, and traffic. Located
in the Western Black Sea region, where industrializa-
tion is quite intense, Zonguldak province has a
remarkable share in the coal mining, energy, and
metallurgy industry (Yıldırım et al. 2011; C¸elik and
Arıcı 2021). The log samples used in this study were
obtained from the trunks of naturally grown beech,
oak, and hornbeam trees in the C¸aycuma district of
Zonguldak province (425899.83E, 4586845.06N) in
February 2022 (Figure 1). Log samples were taken at a
thickness of 10 cm from a height of approximately
50 cm above the ground. Attention was paid to ensur-
ing that the logs showed almost identical growing con-
ditions and soil properties. In addition, individuals of
similar age were preferred. When taking log samples
belonging to these species, the directions (North,
South) were indicated on the logs, and the coordinates
were noted and preserved.
The species selected for the study are Fagus orienta-
lis Lipsky (Oriental beech) (Fagaceae), Carpinus orien-
talis (Oriental hornbeam) (Corylaceae), and Quercus
petraea (Matt.) Liebl. (Sessile oak) (Fagaceae). The sec-
tions taken from the trunk logs were first sanded in
the laboratory to smooth the upper surface so that the
2 A. ÖZTÜRK PULATOĞLU E-ISSN 2158-0715

annual rings could be more clearly visible. Although it
is possible to determine in which year the annual rings
formed, it is not possible to take samples from each
annual ring since they are narrow. For this reason, the
annual rings were clustered by considering their width
and the age of the tree. Previous studies grouped the
20-year-old trees into two-year periods (Turkyilmaz
et al. 2019), 55-year-old trees were grouped into five-
year periods (Yigit et al. 2019), and 30-year-old
(Isinkaralar et al. 2022a) and 33-year-old trees were
grouped into three-year periods (Koc 2021; Savas et al.
2021). The trees examined in this study were found to
be 60 years old. Considering the annual ring widths,
the wood surface was divided into groups ranging
from 1 to 12, with five-year periods inwardly. After
dividing the wood surface into groups and determining
the age intervals, samples were taken from the outer
bark, inner bark, and wood of each age interval using
a stainless-steel drill and placed in glass Petri dishes.
This procedure was carried out in two directions,
toward and away from the industrial area. This
method has been used in previous studies carried out
on the accumulation and transportation of elements in
wood due to pollution sources (Sevik et al. 2020; Cesur
et al. 2021; Isinkaralar et al. 2022). The wood samples
were then fragmented into wood chips by not using
any tools made of the metals, that are examined in this
research, during this process.
After putting them in glass containers without
closing the lids, the samples were kept in the labora-
tory for 15 days until they were completely dry and
turned into room-dried samples. The room-dried
samples were taken to the laboratory oven (N€
ukleon
brand) and dried at 45 C for two weeks. Then, 0.5
grams of the dried samples were taken and placed in
a microwave oven by adding 6ml of 65% HNO
3
and
2 ml of 30% H
2
O
2
. The microwave oven was set to
reach 200 C for 15 min and remain at 200 C for
15 min.
After combusting the samples, the resultant solu-
tions were transferred to balloons and filled to 50 ml
by using ultrapure water for heavy metal analysis of Ba
with an ICP-OES device. Since the samples were
diluted 100 times, the results were multiplied by 100.
If the analysis results did not fall within the calibration
graph, new calibration graphs were created at ppm or
ppb levels in accordance with the analysis results. For
each species, 14 wood and bark samples, including (12
age range þouter bark þinner bark) 2 directions ¼
28 wood and bark samples, were analyzed. Therefore,
3 species 28 wood and bark samples ¼84 wood and
bark samples were studied. All measurements within
the scope of the study were repeated three times. Thus,
a total of 252 samples were analyzed.
The data obtained were analyzed by using SPSS
21.0 package program, and ANOVA analysis was con-
ducted. Duncan’s test was performed for the factors
that were found to have statistically significant differ-
ences with a confidence level of at least 95% (p<0.05)
according to the ANOVA results. Given the Duncan
test results, the concentrations of heavy metals for Ba
were analyzed separately for the following parameters:
a. On a tree basis for each organ (outer bark, inner
bark, and wood).
b. On an organ basis for each tree.
c. On a directional basis for the annual rings of each
tree.
Figure 1. The study area.
E-ISSN 2158-0715 FOREST SCIENCE AND TECHNOLOGY 3

d. On an age range basis for the annual rings of each
tree (this analysis also demonstrates the changes
in airborne Ba concentrations over time).
Results and discussion
As a result of this study, annual changes in the Ba
concentrations in the annual rings were determined. In
addition to comparing the Ba concentrations in the
inner and outer bark to those found in the wood, and
the changes in Ba concentration by years and direc-
tions were also determined. The changes in Ba concen-
tration by species and organ are given in Table 1.
As can be seen in Table 1, a statistically significant
difference (p<0.05) by species and organs was found
in the change of Ba concentration in all organs and all
species, respectively. The highest concentrations were
observed in the outer bark of oak and hornbeam and
in the inner bark of beech, whereas the lowest ones
were found in the wood of all species. Considering the
species, the lowest values were found in hornbeam for
all organs, while the highest values were determined in
the wood and inner bark of beech and in the outer
bark of oak. The changes in Ba concentration in the
wood by species and season are presented in Table 2.
As can be seen, there were statistically significant
changes in the mean Ba concentration in woods by
species and seasons in all season and species, respect-
ively (p<0.05). The lowest concentration was found in
oak, and the highest concentration in beech.
Considering the seasons, it can be seen that the mean
values obtained in the period 2017–2021 were remark-
ably high. The changes in Ba concentration in oak by
direction and organ are presented in Table 3.
The change in Ba concentration by direction in oak
wood was not statistically significant. In both
directions, the highest level of change was found in the
outer bark, followed by the inner bark and wood. It
was determined that the Ba concentration was in the
outer bark was higher than that in the inner part. Ba
concentration changes in oak by directions and periods
are shown in Table 4.
Ba concentration in oak was higher in the inner
part until the period 1992–1996, but it was higher in
the outer part after this period. In general, Ba concen-
tration significantly increased in the period 2017–2021.
The changes in Ba concentration by direction and
organ in hornbeam are presented in Table 5.
Table 1. Changes in Ba (ppb) concentration by species and organ.
Organ Quercus petraea Carpinus orientalis Fagus orientalis F value Mean
Wood 4485.9 Ba 1548.3 Aa 4699.6 Ca 23.4 3635.9 a
Inner bark 70718.4 Bb 18175.7 Ab 94413.4 Cc 135.9 61102.5 b
Outer bark 92748.2 Cc 30578.4 Ac 54961.4 Bb 99.9 59429.3 b
F value 865.9 2357.7 3109.1 350.0
Mean 15521.2 B 5060.5 A 14697.8 B 5.1
According to statistical analysis, values followed by the different letters mean they are different at p0.05. Lowercase letters
(a, b) show vertical directions, while uppercase letters (A, B) show horizontal directions. p0.05; p0.01; p0.001;
ns ¼not significant.
Table 2. Changes in Ba (ppb) concentration in wood by species and season.
Years Quercus petraea Carpinus orientalis Fagus orientalis F value Mean
2017–2021 14898.5 Cc 2212.0 Ac 10710.3 Bb 5.29273.6 b
2012–2016 3894.9 Bab 659.0 Aa 4506.9 Ca 26.0 3492.5 a
2007–2011 3365.9 Bab 1062.9 Aab 3427.8 Ba 8.5 2618.9 a
2002–2006 2846.1 Bab 2218.3 Ac 4204.8 Ca 50.7 3264.0 a
1997–2001 2237.2 Ba 1290.4 Aabc 4425.2 Ca 89.9 2651.0 a
1992–1996 3316.0 Bab 1695.5 Abc 4090.3 Ca 14.2 3033.9 a
1987–1991 2599.6 Ba 2125.2 Ac 4140.7 Ca 51.5 2955.1 a
1982–1986 2467.0 Ba 1345.9 Aabc 4292.8 Ca 200.4 2701.9 a
1977–1981 2694.5 Ba 1373.3 Aabc 3765.3 Ca 45.4 2611.0 a
1972–1976 4705.2 Cab 1378.2 Aabc 3636.2 Ba 62.6 3239.9 a
1967–1971 4033.8 Bab 1695.3 Abc 4110.4 a 50.1 3279.8 a
1962–1966 6771.8 Cb 1414.5 Aabc 5084.1 Ba 62.7 4423.5 a
F value 8.3 2.45.8 7.6
Mean 4485.9 B 1548.3 A 4699.6 B 23.4
Table 3. Changes in Ba (ppb) concentration by direction and organ
in oak.
Outer Inner F value Mean
Wood 5299.4 a 3672.3 a 2.5 ns 4485.9 a
Inner bark 82212.6 Bb 59224.2 Ab 814.9 70718.4 b
Outer bark 104257.7 Bc 81238.8 Ac 685.0 92748.2 c
F672.3 3553.2 865.9
Mean 17861.6 13180.8 0.5 ns
Table 4. Changes in Ba (ppb) concentration by direction and period
in oak.
Years Outer Inner F value Mean
2017–2021 23837.0 Bı5960.0 Ah 6270.4 14898.5 c
2012–2016 4846.8 Bfg 2943.1 Ae 9418.9 3894.9 ab
2007–2011 5088.2 Bg 1643.7 Aa 542.1 3365.9 ab
2002–2006 2750.1 c 2942.0 e 1.9 ns 2846.1 ab
1997–2001 2232.9 a 2241.6 bc 0.0 ns 2237.2 a
1992–1996 4544.0 Bf 2088.0 Ab 1027.2 3316.0 ab
1987–1991 2610.8 bc 2588.4 d 0.1 ns 2599.6 a
1982–1986 2509.0 abc 2424.9 cd 0.9 ns 2467.0 a
1977–1981 2396.6 Aab 2992.4 Be 44.2 2694.5 a
1972–1976 4035.5 Ae 5374.8 Bg 37.6 4705.2 ab
1967–1971 3295.3 Ad 4772.2 Bf 2436 4033.8 ab
1962–1966 5446.7 Ah 8097.0 Bı14147 6771.8 b
F3242.5 733.6 8.3
Mean 5299.4 3672.3 2.5 ns
4 A. ÖZTÜRK PULATOĞLU E-ISSN 2158-0715

In hornbeam wood, the changes in Ba concentra-
tion by periods and organs were found to be signifi-
cant in all organs and periods, respectively (p<0.05).
In both directions, the highest change in Ba concentra-
tion was found in the outer bark, followed by the inner
bark and wood. It was revealed that the Ba concentra-
tion in the outer bark and wood was higher than in
the inner bark. The changes in Ba concentration in
hornbeam by direction and period are shown in
Table 6.
Ba concentration in hornbeam remained below the
detectable limits in the outer bark during the periods
of 2002–2006 and 2012–2016. While the concentration
of Ba in beech was higher in the inner bark until the
period of 1992–1996, it was higher in the outer bark
after this period. Furthermore, during the period
2017–2021, the Ba concentration in the outer bark was
found to be more than five times higher than in the
inner bark. The changes in Ba concentration by direc-
tion and organ in beech are shown in Table 7.
The changes in Ba concentration in beech woods by
direction were not statistically significant. The highest
change in Ba concentration in both directions was
found to be in the inner bark, followed by the outer
bark and wood, whereas it was determined that the Ba
concentration in the outer bark was higher than that
in the inner bark. The changes in Ba concentration by
direction and period in beech are given in Table 8.
The changes in Ba concentration in beech by period
were statistically significant in both directions.
However, the changes by direction were not statistic-
ally significant in the periods of 1967–1971 and 1992–
1996. It was found that the Ba concentration in beech
fluctuated and the changes in both period and direc-
tion were unstable.
Plants contribute to cleaning the environment by
accumulating heavy metals in the air, water, and soil
in their organs (Turkyilmaz et al. 2020; Kuzmina et al.
2022). Plants are one of the most important factors
affecting heavy metal accumulation. Numerous studies
revealed that the level of heavy metal accumulation
varies depending on the species (Sevik et al. 2019a, b;
Turkyilmaz et al. 2019; Karacocuk et al. 2022). The
anatomical structure and genetic structure of plants
shape the plant-heavy metal interaction. A previous
study examining the changes in Ba concentration in 5
different species in Pakistan reported that the Ba con-
centration in Conocarpus erectus was 1162 ppb in the
region with heavy traffic, whereas the average concen-
tration in Azadirechta indica was found to be 3982 ppb
(Cetin and Jawed 2022).
In studies conducted to determine the Ba concen-
tration in the air, the concentrations measured in rural
areas were the lowest (0.2–2.6 ng m
−3
), while in indus-
trial areas it was found to be 35.7 ngm
−3
(Centre for
Ecology and Hydrology 2012). Harrison et al. (2012)
observed Ba averages as 20.7–30.9 ng m
−3
in urban
traffic areas in London. On the other hand, in another
study in the UK, average Ba concentrations (ng m
−3
)
were determined as 24.3 in Urban traffic (n¼2), 5.56
in Urban background (n¼6), 5.91 in Urban industrial
(n¼7), 1.13 in Rural background (n¼8), 18.8 in
Traffic increment, 4.43 in Urban increment (Goddard
et al. 2019).
Ba is taken up by plants from the air and soil. Since
plants are at the bottom of the food chain, Ba is trans-
ferred throughout the food chain. Ba is usually reduced
biologically during transfer (Schroeder et al. 1972; Elias
et al. 1977; Reeves 1979). Davis et al. (2009) report
that Ba is consistently associated with natural resources
in urban and rural areas. In the study conducted in
Virginia, it was concluded that although Ba appears to
have bioconcentration and bioaccumulation ability in
terrestrial and aquatic environments, its bioaccumula-
tion factors are low (Hope et al. 1996). In the study,
Table 5. Changes in Ba (ppb) concentration in hornbeam by direction
and organ.
Outer Inner F value Mean
Wood 1741.3 Ba 1387.6 Aa 4.21548.3 a
Inner bark 15971.1 Ab 20380.4 Bb 1046.1 18175.7 b
Outer bark 32761.0 Bc 28395.8 Ac 218.0 30578.4 c
F2519.9 4509.2 2357.7
Mean 5512.1 4673.3 0.1ns
Table 6. Changes in Ba (ppb) concentration by direction and period in
hornbeam.
Years Outer Inner F value Mean
2017–2021 3775.2 Bg 648.8 Aa 1170.2 2212.0 c
2012–2016 LA 659.0 a – 659.0 a
2007–2011 980.9 b 1144.9 ab 2.3 ns 1062.9 ab
2002–2006 LA 2218.3 d – 2218.3 c
1997–2001 695.5 Aa 1885.4 Bcd 407.9 1290.4 abc
1992–1996 1499.1 Acd 1892.0 Bcd 9.21695.5 bc
1987–1991 2248.9 f 2001.5 cd 0.2 ns 2125.2 c
1982–1986 1662.2 Bde 1029.6 Aa 155.1 1345.9 abc
1977–1981 1787.1 Be 959.6 Aa 38.5 1373.3 abc
1972–1976 1793.4 Be 963.1 Aa 47.3 1378.2 abc
1967–1971 1654.2 d 1736.5 cd 2.7ns 1695.3 bc
1962–1966 1316.6 c 1512.3 bc 3.0 ns 1414.5 abc
F113.2 12.6 2.4
Mean 1741.3 B 1387.6 A 4.2
LA: under limit.
Table 7. Changes in Ba (ppb) concentration by direction and organ in
beech.
Outer Inner F value Mean
Wood 4185.0 a 5214.1 a 2.8 ns 4699.6 a
Inner bark 99883.4 Bc 88943.4 Ac 257.9 94413.4 c
Outer bark 57937.5 Bb 51985.3 Ab 131.9 54961.4 b
F56429.1 1027.2 3109.1
Mean 14860.1 14535.6 0.0 ns
Table 8. Changes in Ba (ppb) concentration by direction and period in
beech.
Years Outer Inner F-value Mean
2017–2021 4584.6 Ag 16836.0 Bh 18310.2 10710.3 b
2012–2016 3967.1 Acd 5046.7 Bg 859.0 4506.9 a
2007–2011 3868.4 Bc 2987.3 Aa 863.4 3427.8 a
2002–2006 4599.0 Bg 3810.7 Abc 155.2 4204.8 a
1997–2001 4643.7 Bg 4206.7 Ae 14.54425.2 a
1992–1996 4100.2 e 4080.4 de 0.0 ns 4090.3 a
1987–1991 4346.8 Bf 3934.5 Acd 74.7 4140.7 a
1982–1986 4072.6 Ad 4513.0 Bf 38.8 4292.8 a
1977–1981 3334.3 Aa 4196.3 Be 265.7 3765.3 a
1972–1976 3553.4 Ab 3719.1 Bb 22.33636.2 a
1967–1971 4149.3 e 4071.5 de 1.4 ns 4110.4 a
1962–1966 5000.6 Ah 5167.7 Bg 8.55084.1 a
F126.7 5575.8 5.8
Mean 4185.0 5214.1 2.8 ns
E-ISSN 2158-0715 FOREST SCIENCE AND TECHNOLOGY 5

the average Ba content in the soil was determined as
105 mg kg
−1
. The analyzed vegetation showed an aver-
age Ba concentration of 30mg kg
−1
, the average con-
centration in terrestrial invertebrates was 16 mg kg
−1
,
and the Ba content in the small mammals analyzed
was around 2 mg kg
−1
.
Bowen and Dyamon (1950) found that Ba contents
of plants from normal soils vary from 0.5 to 40 mg
kg
−1
with a mean value of 10 mg kg
−1
. In plants on a
barite-rich soil (760 mg kg
−1
Ba in aqua regia extract)
shoot Ba concentrations ranged from 21 mg kg
−1
in
grass species to 320 mg kg
−1
in Rubia peregrine (Wild
Madder) (Lledo et al. 1998). The highest concentra-
tions (10000 mg kg
−1
) have been found in Brazil nut
trees (Bertholletia excelsa), a Ba-accumulating species
(Smith 1971). Crum and Franzmeier (1980) reported
normal Ba values in plants from 10 to 150 mg kg
−1
. In
another study, while apple leaves contained 49ppm Ba,
it was found to be 63 ppm in tomatoes (Padilla and
Anderson 2002). Pais and Jones (1998) found that Ba
contents of 200 mg kg
−1
could be moderately toxic,
and an excess of 500 mg kg
−1
could be considered
toxic for plants.
Previous studies also revealed that the concentration
of heavy metals in different organs of the same plant
might vary significantly (Sevik et al. 2019a, b;
Karacocuk et al. 2022). Cetin and Jawed (2022) deter-
mined the changes in Ba concentration in the leaves
and branches of Ficus bengalensis, Ziziphus mauritiana,
Conocarpus erectus, and Azadrechta indica species in
relation to traffic density. Azadrechta indica leaves
were determined to be the most suitable organs. The
heavy metal concentrations in different organs of
plants grown in the same environment vary by factors
including organ structure, morphology, surface area,
surface texture, and size (Isinkaralar et al. 2022). In
this study, the lowest mean Ba concentrations were
found in hornbeam in all organs, which is related to
the anatomical structure of the species. The Ba element
in oak, hornbeam, and beech woods are 4485.9,
1548.3, and 4699.6, respectively. Therefore, the most
suitable species for reducing Ba pollution was found to
be beech, which was found to have the highest concen-
trations in the wood.
Wood is the largest organ of the plant by mass and,
therefore, it has the highest capacity to accumulate
heavy metal. For this reason, plants that can store
heavy metals in their wood are particularly important.
Previous studies indicated that heavy metal concentra-
tions are high in most species, especially in the outer
bark (Koc 2021; Cobanoglu et al. 2023). Studies carried
out on Ba also showed that the highest concentrations
were generally found in the bark (Ozel et al. 2021).
Cobanoglu et al. (2023) reported that transfers of Cd,
Ni, and Zn elements in cedar wood were limited,
whereas Zhang (2019) found that Zn and Pb concen-
trations in annual rings of Cedrus deodora shifted to a
certain extent, but Cu concentration did not change.
Key et al. (2022) determined that Ni, Co, and Mn
transfers in Corylus colurna wood were very limited.
Cesur et al. (2021, 2022) also reported that Fe, Cd, and
Ni transfers in Cupressus arizonica wood were limited,
but those of Bi, Li, and Cr were higher.
As a result of this study, the highest Ba levels were
found in the inner bark (94413.4 ppb) and wood
(4699.6 ppb) for the beech, and in the outer bark for
the oak (92748.2 ppb). This situation is related to the
entry of heavy metals into the plant structure. The
intake of heavy metals into the plant structure occurs
in three ways; roots, leaves, and stem parts (Cesur
et al. 2021). The transportation of various elements in
the wood is related to the cell structure and cell wall.
The cell wall-plasma membrane represents a flexible
structure related to sensing and signaling the metal/
metalloid stress (Wani et al. 2018). Since the cell wall-
plasma membrane interface accumulates large heavy
metal fractions, it is considered to be the potential
region of HM tolerance (Wu et al. 2010).
The concentrations found in the outer bark of oak
were very high. This is due to the structure of the
outer bark and its interaction with heavy metal-conta-
minated particles. Therefore, the high values found in
the outer bark of oak can be explained by its rough
bark structure, which allows particles to easily adhere.
In all three species, concentrations found in the
outer bark were higher. This can be explained by the
fact that the external side is the source of the contam-
ination agent and by the presence of particulate matter
contaminated with Ba. Particularly the high concentra-
tions found from 2017 to 2021 indicate the role of
industrial activities, which are the source of Ba pollu-
tion, during this period. Previous studies also showed
that industrial activities constitute the most significant
source of heavy metal pollution (Istanbullu et al. 2023;
Isinkaralar 2023). Studies show that heavy metals
formed as a result of industrial activities contaminate
particulate matter and these particulate matter are car-
ried long distances by the wind and cause pollution
(Koc et al. 2023; Sulhan et al. 2023). The significant
increase in Ba concentration in recent years and the
increase in industrial activities in the study area during
this period, as observed in this study, support this
finding.
Conclusion
The present study shows that oak, beech, and horn-
beam species are suitable for monitoring the changes
in Ba concentrations and the Ba pollution in the air.
The highest values were determined in the outer bark
of oak and hornbeam, and in the inner bark of beech.
The lowest values in all species were obtained in wood.
As for the species, the lowest values were obtained in
hornbeam in all organs, while the highest values were
obtained in beech in the wood and inner bark, and in
oak in the outer bark. The most suitable species for
reducing Ba pollution is beech, where the highest con-
centrations are obtained in wood.
The use of annual rings as pollution indicators of
pollution provides important data on the chronology
and distribution of elements, which have caused the
pollution. Using this method, it is possible to monitor
6 A. ÖZTÜRK PULATOĞLU E-ISSN 2158-0715

the changes in heavy metal concentrations, especially
in industrial areas or areas with increasing traffic pol-
lution. The transfer of elements within the wood varies
depending on the plant species. Therefore, it is impor-
tant to separately identify the tree species, which are
suitable for determining the heavy metal pollution, for
each heavy metal. The present study is important since
the study area is located in an organized industrial
zone hosting many industrial facilities. However, there
are not enough studies on which species fit more for
this purpose. Therefore, it is important to carry out
more studies on different regions and species.
Disclosure statement
No potential conflict of interest was reported by the authors.
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