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

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 Çaycuma district of Zonguldak province, an industrial area in the northwestern Türkiye. The study aimed to determine the annual changes in barium (Ba) concentrations 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.

Keywords:

• Air pollution
• air quality
• barium
• biomonitoring
• heavy metal

Introduction

Together with the growing global population, urbanization, 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 concentrations in the air, water, and soil due to mining operations and the use of underground mineral resources 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 (Brázová 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 carcinogenic or toxic effects even at low concentrations (Turkyılmaz et al. 2020; Dołęgowska et al. 2021; Kumar and Dwivedi 2021). Atmospheric heavy metals are transferred to the soil by precipitation, and air pollutants 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 concentrations 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 method, it is possible to track backward changes in heavy metal concentrations, particularly in industrial areas or in areas with increasing traffic-related pollution (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 limited number of studies have been conducted to monitor 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, compounds, 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 (BaSO₄) and witherite (BaCO₃) (Böttcher 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 (Madejón et al. 2013). Schroeder (1970) reported that Ba in soil was present in concentrations ranging from 100 to 3000 mg 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, stomach irritation, vomiting, diarrhea, increased blood pressure, 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 São Paulo (CETESB) 2017). Approximate acute and lethal (single) toxic oral doses of BaCl₂ 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 sparingly soluble due to its low absorption in the gastrointestinal 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 SO₄ ^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 Çaycuma district of Zonguldak province, which is an industrial zone in northwestern Türkiye, 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 Çaycuma 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 effectively used in monitoring the yearly changes in Ba concentration 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 Türkiye in terms of particulate matter pollution and air pollution is the most significant 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 industrialization is quite intense, Zonguldak province has a remarkable share in the coal mining, energy, and metallurgy industry (Yıldırım et al. 2011; Çelik 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 Çaycuma district of Zonguldak province (425899.83E, 4586845.06 N) 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 ensuring that the logs showed almost identical growing conditions 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.

Figure 1. The study area.

The species selected for the study are Fagus orientalis Lipsky (Oriental beech) (Fagaceae), Carpinus orientalis (Oriental hornbeam) (Corylaceae), and Quercus petraea (Matt.) Liebl. (Sessile oak) (Fagaceae). The sections taken from the trunk logs were first sanded in the laboratory to smooth the upper surface so that the 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 laboratory for 15 days until they were completely dry and turned into room-dried samples. The room-dried samples were taken to the laboratory oven (Nükleon 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 6 ml of 65% HNO₃ and 2 ml of 30% H₂O₂. 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 solutions 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 + outer bark + inner bark) * 2 directions = 28 wood and bark samples, were analyzed. Therefore, 3 species * 28 wood and bark samples = 84 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 conducted. Duncan’s test was performed for the factors that were found to have statistically significant differences 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:

1. On a tree basis for each organ (outer bark, inner bark, and wood).

2. On an organ basis for each tree.

3. On a directional basis for the annual rings of each tree.

4. 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 directions were also determined. The changes in Ba concentration by species and organ are given in Table 1.

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 = not significant.

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.

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***

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, respectively (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 remarkably high. The changes in Ba concentration in oak by direction and organ are presented in Table 3.

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
F	672.3***	3553.2***		865.9***
Mean	17861.6	13180.8	0.5 ns

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.

Table 4. Changes in Ba (ppb) concentration by direction and period in oak.

Years	Outer	Inner	F value	Mean
2017–2021	23837.0 Bı	5960.0 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 Bı	14147***	6771.8 b
F	3242.5***	733.6***		8.3***
Mean	5299.4	3672.3	2.5 ns

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 concentration significantly increased in the period 2017–2021. The changes in Ba concentration by direction and organ in hornbeam are presented in Table 5.

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
F	2519.9***	4509.2***		2357.7***
Mean	5512.1	4673.3	0.1 ns

In hornbeam wood, the changes in Ba concentration by periods and organs were found to be significant in all organs and periods, respectively (p < 0.05). In both directions, the highest change in Ba concentration was found in the outer bark, followed by the inner bark and wood. It was revealed that the Ba concentration 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.

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	2.7 ns	1695.3 bc
1962–1966	1316.6 c	1512.3 bc	3.0 ns	1414.5 abc
F	113.2***	12.6***		2.4*
Mean	1741.3 B	1387.6 A	4.2*

LA: under limit.

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 direction and organ in beech are shown in Table 7.

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
F	56429.1***	1027.2***		3109.1***
Mean	14860.1	14535.6	0.0 ns

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.

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
F	126.7***	5575.8***		5.8***
Mean	4185.0	5214.1	2.8 ns

The changes in Ba concentration in beech by period were statistically significant in both directions. However, the changes by direction were not statistically 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 direction 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 concentration in Conocarpus erectus was 1162 ppb in the region with heavy traffic, whereas the average concentration in Azadirechta indica was found to be 3982 ppb (Cetin and Jawed 2022).

In studies conducted to determine the Ba concentration in the air, the concentrations measured in rural areas were the lowest (0.2–2.6 ng m⁻³), while in industrial 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 (n = 2), 5.56 in Urban background (n = 6), 5.91 in Urban industrial (n = 7), 1.13 in Rural background (n = 8), 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 transferred 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 bioaccumulation factors are low (Hope et al. 1996). In the study, the average Ba content in the soil was determined as 105 mg kg⁻¹. The analyzed vegetation showed an average Ba concentration of 30 mg kg⁻¹, the average concentration 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 concentrations (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 49 ppm 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) determined 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 concentrations 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 concentrations 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 concentrations 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-contaminated 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 contamination agent and by the presence of particulate matter contaminated with Ba. Particularly the high concentrations found from 2017 to 2021 indicate the role of industrial activities, which are the source of Ba pollution, 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 carried 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 hornbeam 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 concentrations 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 the changes in heavy metal concentrations, especially in industrial areas or areas with increasing traffic pollution. The transfer of elements within the wood varies depending on the plant species. Therefore, it is important 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.