Abstract
The objective of this study was to determine suitable tree species to monitor and reduce Sn concentrations in the environment of Düzce province in Türkiye. A further goal was to test the hypothesis that, possibly due to air transport, the uptake of Sn in tree rings would show a significant and consistent dependency on compass direction. The timber samples were from the trunks of Tilia tomentosa (linden), Robinia pseudoacacia (black locust), Cedrus atlantica (cedar), Pseudotsuga menziesii (Douglas fir), and Fraxinus excelsior (European ash), which are commonly used in landscaping in Düzce province. Levels of Sn concentrations in annual rings were determined. Cedrus atlantica and F. excelsior were found to be suitable biomonitors that can be used to monitor changes in annual amounts of Sn contamination. Among the studied tree species, R. pseudoacacia had the highest average values and C. atlantica had the second-highest levels of Sn uptake. However, no consistent dependency on compass direction was found. It follows that rather than depending on the direction of prevailing winds, the uptake of metals to the xylem of trees must be due to direction-independent processes, such as transport via roots and xylem or absorption into leaves and subsequent transport via the phloem.
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Directionality in Tree Ring Accumulation of Tin (Sn) in Three Tree Species
Ayse Ozturk Pulatoglu *
The objective of this study was to determine suitable tree species to monitor and reduce Sn concentrations in the environment of Düzce province in Türkiye. A further goal was to test the hypothesis that, possibly due to air transport, the uptake of Sn in tree rings would show a significant and consistent dependency on compass direction. The timber samples were from the trunks of Tilia tomentosa (linden), Robinia pseudoacacia (black locust), Cedrus atlantica (cedar), Pseudotsuga menziesii (Douglas fir), and Fraxinus excelsior (European ash), which are commonly used in landscaping in Düzce province. Levels of Sn concentrations in annual rings were determined. Cedrus atlantica and F. excelsior were found to be suitable biomonitors that can be used to monitor changes in annual amounts of Sn contamination. Among the studied tree species, R. pseudoacacia had the highest average values and C. atlantica had the second-highest levels of Sn uptake. However, no consistent dependency on compass direction was found. It follows that rather than depending on the direction of prevailing winds, the uptake of metals to the xylem of trees must be due to direction-independent processes, such as transport via roots and xylem or absorption into leaves and subsequent transport via the phloem.
DOI: 10.15376/biores.19.4.8542-8562
Keywords: Air quality; Heavy metal; Biomonitor; Tin pollution; Sn
Contact information: Kastamonu University, Faculty of Forestry, Department of Forest Engineering, 37150, Kastamonu, Türkiye; *Corresponding author: ayseozturk@kastamonu.edu.tr
INTRODUCTION
Air pollution is considered one of the most significant environmental issues. Air pollution and its effects are at a higher level in urban areas because of industrial activities and traffic density. These factors increase the heavy metal concentrations. Elements that are considered as heavy metals have relatively high density, usually higher than 5 g/cm3, and are indestructible or non-degradable; even low levels of heavy metals can be toxic or poisonous (Sulhan et al. 2023). In addition to their ecological effect on natural environments, heavy metals are also a major concern for global public health (Cetin et al. 2022; Isinkaralar et al. 2023). Inhaling high amounts of heavy metal particles in the course of time can increase the metal load in the human body, and it poses a health risk (Gray et al. 2003). Heavy metal pollutants can affect people living near the source through suspended dust or direct contact (Chen et al. 2010). In agricultural lands, these pollutants can also enter the human food chain through edible plants and cause people to be exposed to heavy metals (Sevik et al. 2020). Heavy metals accumulate in the atmosphere and pose harm to ecosystems and organisms. Plant leaves and stems can also absorb heavy metals from atmospheric particles (Karacocuk et al. 2022). Heavy metals can be transported to the soil through atmospheric deposition (Nabuloa et al. 2006). Plant roots uptake heavy metals from soil (Erdem et al. 2023). Some changes are observed in physiological and biochemical processes in plants grown in heavy metal-contaminated soils such as DNA damage, disruptions in biosynthetic pathways, and reduced growth (Taofeek and Tolulope 2012).
Tin (Sn) is one of the most concerning heavy elements. Its tendency to biologically accumulate increases the severity of its toxic effects. It is known that inorganic tin compounds have mutagenic, carcinogenic, and teratogenic potential and that they can damage the cardiovascular system. In addition to symptoms, such as shortness of breath, coughing, and wheezing, inhaling tin can lead to dizziness, balance disorders, headaches, diarrhea, vomiting, abdominal pain, muscle weakness, paralysis, anemia, and severe liver and kidney damage (Cima 2011; Sharma and Kumar 2020). Inhalation, oral intake, or dermal contact with specific Sn compounds was observed to be associated with skin and eye irritation, respiratory distress, gastrointestinal disorders, and neurological problems (Nakanishi 2008). Poisoning related with certain tin compounds can result in permanent neurological problems, and even death (ATSDR 2015).
For a sustainable environment, it is important to assess the risk levels associated with heavy metals that can persist in nature for extended periods without degradation, identify high-risk areas, and monitor the heavy metal levels. Trees in urban areas contribute to the filtration of the surrounding air and the reduction of pollution levels by absorbing heavy metals (Dzierżanowski et al. 2011). By capturing pollutants and reducing the amounts in the air or soil, there is potential to improve urban air or soil quality (Freer-Smith et al. 2005; Tomašević et al. 2005; Chakre 2006; Peachey et al. 2009; Warczyk et al. 2024; Zhao et al. 2024). However, plant capacity for heavy metal translocation and accumulation is highly variable, depending on genotypic and environmental traits (Pietrini et al. 2010; Di Baccio et al. 2014). Popek et al. (2017) investigated the accumulation of particulate matter (PM), including heavy metals and polycyclic aromatic hydrocarbons, on the foliage of small-leaved lime (Tilia cordata Mill.) in five Polish cities. The study showed that there were significantly different PM amounts found in the trees between the cities which related to the different quantities of PM in the atmosphere at these cities. The results of the study suggested that T. cordata improves the air quality in cities. A similar phenomenon was observed in another study, in which the root systems of Salix integra accumulated relatively high concentrations of Zn and Cd in the root and above ground tissues and in Quercus spp. and Salix matsudana, the highest absolute concentrations of Pb, Zn, and Cd were retained in roots. (Shi et al. 2017). Another study states that Lolium multiflorum is suitable for phytoestabilization since it is able to uptake heavy metals such as Pb and Zn and improve the soil properties (Mugica-Alvarez et al. 2015).
The use of urban trees as bioindicators is a sustainable ecological approach to preserve urban living spaces. Therefore, trees can be used as bioindicators to obtain time-dependent information on pollutant levels in cities (Gupta et al. 2011; Ghoma et al. 2023). The use of annual rings as indicators of heavy metal pollution can yield valuable data on the chronology and distribution of elements contributing to pollution (Chen et al. 2021; Savas et al.2021; Key et al. 2023; Cobanoglu et al. 2023). Previous studies documented the usability of tree rings in monitoring heavy metal pollution (Edusei 2021; Isinkaralar 2022, 2024; Cuciurean et al. 2024). It was reported in many studies that there is a relationship between elemental concentrations in annual rings and environmental pollution (Key et al. 2022; Erdem et al. 2024; Ozturk Pulatoglu 2024; Şevik et al. 2024). However, the transfer of elements within wood varies between the plant species. Further studies are necessary to analyze the concentration and long-term level of Sn in the air-soil-plant system for realistic risk assessments. Monitoring urban air quality is important to determine the atmospheric pollution and potential damage. Therefore, it is important to identify tree species suitable for detecting heavy metal pollution separately for each heavy metal. The objective of this study is to determine the most suitable species to monitor and accumulate Sn concentrations, with an assumption that the primary route of contamination is through the air. The main hypothesis of the study is that, because of prevailing winds, the Sn accumulation in the tree rings of the species under study will depend on the compass direction.
MATERIALS AND METHODS
As reported in the 2021 World Air Pollution Report, Düzce province has the fifth-highest pollution level in Europe (IQAir Staff Writers 2021). The topography and meteorological characteristics of Düzce province located in the Western Black Sea region of Türkiye can intensify some air pollution effects. The main pollutants causing air pollution in Düzce province generally originate from industrial facilities, residential fuel use, and vehicular traffic.
The timber samples used in this study were obtained from the trunks of Tilia tomentosa Moench (linden), Robinia pseudoacacia L. (black locust), Cedrus atlantica (Endl.) G. Manetti ex Carrière (Cedar), Pseudotsuga menziesii (Mirb.) Franco (Douglas fir), and Fraxinus excelsior L. (European ash), which are commonly used in landscaping in Düzce province. Trees of similar ages were preferred for this work. The timber samples were collected in the year 2022 and were approximately 10 cm thick, taken from an aboveground height of approximately 50 cm during the non-vegetation season. Because the trees are close to each other, it is thought that they are exposed to similar amounts of soil and airborne pollutants. To date, this method has been used in studies on the accumulation and transmission of elements in wood depending on the pollution source (Sevik et al. 2020; Cesur et al. 2021; Isinkaralar et al. 2022). The area where the trees were taken is on the edge of the city and there is a highway on one side and an agricultural area on the other. To interpret the pollutant source correctly, during the collection of timber samples, directions (east, west, north, and south) were labeled on the logs. Sections taken from the trunk logs were sanded in the laboratory to flatten the upper surface for clearer visibility of annual rings.
Because the annual rings are narrow, samples cannot be taken from the rings formed each year. Rather, the annual rings were grouped by considering their width and the age of the tree. In the studies, it was determined that 20-year-old trees were grouped for two years of annual rings (Turkyilmaz et al. 2019), 55-year-old trees were grouped for 5 years (Ozturk Pulatoglu 2024), 30-year-old trees were grouped for 3 years (Isinkaralar et al. 2022), and 33-year-old trees were grouped for 3 years (Koc 2021; Savas et al. 2021). Annual rings were clustered considering the ring width and the age of the trees. Therefore, trees that were approximately 40 years old were divided into 5-year age groups. Then, the outer bark, inner bark, and wood samples were collected from each age group using stainless steel drills and then placed in glass Petri dishes. These samples were processed into sawdust without using any tools made of the metals examined in this study and they were left in the laboratory, uncovered, for 15 days until completely dry to achieve air-dried specimens. Then, these samples were subjected to one week of drying in an oven set at 45 °C. Following this process, 0.5 g of the dried samples were mixed with 6 mL of 65% HNO3 and 2 mL of 30% H2O2 before placing them in a microwave oven (Key et al. 2023; Erdem et al. 2024; Şevik et al. 2024).
After the combustion, the samples were transferred to measuring bottles, and the final volume was completed to 50 mL by using ultra-pure water. The samples were analyzed by using an ICP-OES (Inductively Coupled Plasma-Optic Emission Spectrometer, GBC Scientific Equipment Pty Ltd., Melbourne, Australia) device, and Sn-concentrations were determined by multiplying the results with the corresponding dilution factor. This method has been commonly used in literature (Işınkaralar et al. 2022; Key et al. 2023).
Variance analysis was conducted by using the SPSS package program. Moreover, the Duncan test was conducted for factors showing statistically significant differences at a minimum of 95% confidence level (P < 0.05). Considering the results achieved from the Duncan test, analyses and interpretations were conducted after tabularizing the results. In each organ (outer bark, inner bark, wood) on a tree basis, in each tree on an organ basis, in each tree’s annual rings on a direction basis, in each tree’s annual rings on an age range basis, and in the process, the changes in heavy metal concentrations in the air were analyzed separately.
RESULTS
The annual variations of Sn concentrations in annual rings were determined in this study. Additionally, changes in Sn concentration by years and directions were calculated by comparing Sn concentrations in the inner bark (IB) and outer bark (OB) to the wood (WD). The statistical analysis results, average values, and the Sn concentration changes by species and directions are shown in Table 1.
Table 1. Sn Concentrations (ppb) by Species and Direction
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; UL: under limit
Changes in Sn concentration were statistically significant in all directions (Table 1), though the trends were not consistent among different species. The changes by direction were found to be statistically significant in all species other than F. excelsior. Tin concentrations in the wood were found to change and there were differences between different directions and periods. In R. pseudoacacia, the change in Sn concentration in the north remained lower than the measurable limits. The highest concentration found in the north (9490 ppb) was measured in C. atlantica, whereas the highest concentrations in the east (15300 ppb), west (14500 ppb), and south (15900 ppb) were measured in R. pseudoacacia. Considering the average values, R. pseudoacacia was found to yield the highest concentration (15300 ppb).
Table 2. Sn Concentrations (ppb) by Periods and Directions
Given the results obtained from variance analysis, the changes in Sn concentration by periods and directions were not determined to be statistically significant (Table 2). Similarly, no significant changes were determined in the average values. Tin concentrations by organs and directions are presented in Table 3.
Table 3. Sn Concentrations (ppb) by Organs and Directions
OD: Outer bark, IB: Inner bark, WD: Wood
The changes in Sn concentration by directions and organs were not statistically significant (Table 3). Examining the average values, the results also confirmed that there was no significant difference by organ and direction. The changes in Sn concentration by periods and species are presented in Table 4.
Table 4. Sn Concentrations (ppb) by Periods and Species
Variance analysis results showed that the changes in Sn concentrations were statistically significant by period in all species (except for C. atlantica and F. excelsior) and by species in all periods. When the changes in Sn concentration on a period basis were examined, it was determined that it ranged between 336 to 521 ppb in T. tomentosa, 14800 to 15700 ppb in R. pseudoacacia, 6690 to 10400 ppb in C. atlantica, 96.9 to 231.3 ppb in P. menziesii, and 130 to 1570 ppb in F. excelsior. The highest value in C. atlantica was obtained in the periods 2013-2017 and 2018-2022. In F. excelsior, however, the highest concentration was obtained in the period 2018-2022. Moreover, the highest average concentration was found in R. pseudoacacia (15238.3 ppb), whereas the lowest ones were found in T. tomentosa (421.8 ppb), P. menziesii (153.8 ppb), and F. excelsior (338.7 ppb).
Table 5. Sn Concentrations (ppb) by Organs and Species
Changes in Sn concentration were statistically significant by species in all organs (except for R. pseudoacacia) and by organ in all species. The lowest concentration was found in wood, followed by inner bark and outer bark, respectively, in T. tomentosa and P. menziesii. In C. atlantica, however, the ranking is outer bark < inner bark < wood. Given the average values, the highest average concentration was found in R. pseudoacacia (15267.2 ppb), followed by C. atlantica (7645.0 ppb).
Table 6. Sn Concentrations (ppb) in Tilia tomentosa by Organs and Directions
The changes in Sn concentration by organs and directions were determined to be statistically significant in T. tomentosa (Table 6). The lowest level of Sn in the north was found in wood (475 ppb), followed by inner bark (699 ppb) and outer bark (1450 ppb). The highest levels in the south and west were found in the outer and inner bark, whereas the highest value in the east was obtained in the outer bark. Further, the highest average Sn levels were observed in the north (560 ppb), south (494 ppb), and west (516 ppb), whereas the ranking by organs is wood (422 ppb) < inner bark (651 ppb) < outer bark (1020 ppb).
Table 7. Sn Concentrations (ppb) in Tilia tomentosa by Periods and Directions
The variance analysis results revealed that there were significant changes in Sn concentration in T. tomentosa by directions and periods. The highest values in the south were found in the period 2018-2022 (650 ppb), whereas the highest values were found in the period 1983-1987 (624 ppb) in the north and in the periods 1988-1992 (648 ppb) in the west. Examining the average Sn concentrations, the highest average levels were found in the west (479 ppb), north (475 ppb), and south (422 ppb).
Table 8. Sn Concentrations (ppb) in Robinia pseudoacacia by Organs and Directions
As shown in Table 8, the changes in Sn concentrations in R. pseudoacacia were statistically significant by direction were significant in organs other than the inner bark. The change in Sn concentration in the north was determined to be lower than the detectable limits in all organs. However, the changes by organs were not statistically significant in directions other than the east. The highest Sn level in the east was measured in the inner bark (14810.4 ppb) and the lowest one in the outer bark (14250.9 ppb) and wood (14546.4 ppb). Considering the average values, the highest average value was measured in the south (15925.4 ppb).
Table 9. Changes in Sn Concentration (ppb) in Robinia pseudoacacia by Periods and Directions
Given the variance analysis results, the changes in Sn concentration in R. pseudoacacia by directions were found to not be statistically significant in periods other than 1963-1967, 1973-1977, 1988-1992, 1993-1997, and 1988-2002. The concentration changes in the north direction remained lower than detectable limits for all periods. Moreover, the only significant change in concentration was found to be in the west. The highest value in this direction was obtained in the periods 2003-2007 (15400 ppb) and 2013-2017 (15500 ppb).
Table 10. Sn Concentrations (ppb) in Cedrus atlantica by Organs and Directions
The changes in Sn concentration in C. atlantica by direction were found to be statistically significant in all organs (Table 10). However, the changes by organs were not statistically significant in directions other than the north. Considering the average values by organs, the highest level was measured in the inner bark (9390 ppb) and the lowest ones in the wood (7540 ppb) and outer bark (7160 ppb). Similarly, regarding the averages by directions, the highest value was found in the north (9490 ppb).
Table 11. Sn Concentrations (ppb) in Cedrus atlantica by Periods and Directions
Considering the results achieved, it was determined that the changes in Sn concentration in C. atlantica by periods and directions were statistically significant. The highest level in the north was measured for the periods 2013-2017 (16465.6 ppb) and 2018-2022 (16260.5 ppb) and the highest one in the east was measured for the period 1963-1967 (7004.2 ppb). The concentration changes in the east were found to be lower than the detectable limits for the period 2013-2017. Given the average values by periods, the highest value was measured for the periods 2013-2017 (10392.6 ppb) and 2018-2022 (9222.6 ppb).
Table 12. Sn Concentrations (ppb) in Pseudotsuga menziesii by Organs and Directions
The changes in Sn concentration in P. menziesii by direction were determined to be statistically significant in all organs (Table 12). The changes in Sn concentration by organs were also statistically significant in the east, west, and south. In the north direction, however, the changes in Sn concentration in both inner bark and wood remained lower than the detectable limits. The values can be ranked as wood (154 ppb) < inner bark (516 ppb) < outer bark (719 ppb) for the east and south directions. The changes in Sn concentration in P. menziesii by period and direction are presented in Table 13.
Table 13. Sn Concentration (ppb) in Pseudotsuga menziesii by Periods and Directions
It was determined that the changes in Sn concentration in P. menziesii by direction were statistically significant in periods other than 1968-1972 and 1988-1992 (Table 13). The changes in Sn concentration were also determined to be statistically significant in all directions other than the north. The changes in Sn concentration in the north remained lower than the detectable limits in all periods. Moreover, the changes in Sn levels were found to be lower than the detectable limits in the south for the periods 2013-2017 and 2018-2022 and in the west direction for the periods other than 1978-1982, 2008-2012, 2013-2017, and 2018-2022. The highest level was measured for the period 1973-1977 in the east (238 ppb), for the period 1968-1972 (167 ppb) in the south, and for the periods 2013-2017 (319 ppb) and 2018-2022 (330 ppb) in the west. Considering the average values, the highest average level was measured in the north (647).
Table 14. Sn Concentrations (ppb) in Fraxinus excelsior by Organs and Directions
Changes in Sn concentration in F. excelsior by directions and organs were found to be statistically significant in both inner and outer bark and in all directions other than the west, respectively. In the north, the changes in Sn levels were found to be lower than the detectable limits in wood for the north and in inner barks for the west. Considering the average values by organs, the highest value was measured in the outer bark (1105.8 ppb). The changes in Sn concentrations in F. excelsior by periods and directions are presented in Table 15.
Table 15. Sn Concentrations (ppb) in Fraxinus excelsior by Periods and Directions
Given the results shown in Table 15, the changes in Sn concentrations in F. excelsior by directions were found to be statistically significant in all periods other than 1968-1972 and 1973-1977. The changes in Sn levels in the north were determined to be lower than detectable limits for all periods. Moreover, the changes in Sn concentration were found to be lower than the detectable limits for the period 2013-2017 in the south and for the periods 1993-1997, 2003-2007, and 2008-2012 in the west. The highest value was obtained for the period 2008-2012 (476.1 ppb) for the east, for the period 2018-2022 (4054.0 ppb) for the west, and for the periods 1963-1967 (348.7 ppb) and 2018-2022 (352.2 ppb) for the south.
When the changes in wood based on period and direction are examined, it is seen that there was no significant difference between neighboring wood groups in T. tomentosa, R. pseudoacacia, P. menziesii, and the values were relatively close to each other. However, there were big differences between neighboring woods in C. atlantica and F. excelsior. For example, in C. atlantica, while it was 16300 ppb in the north direction in the 2018-2022 period, it was determined as 6650 ppb in the south direction in the same period. Again, in C. atlantica, 16500 ppb in the north direction and 7340 ppb in the south direction were determined in the period 2013-2017. In the F. excelsior species, it was determined as 304.3 ppb in the east direction and 4050 ppb in the west direction in the period 2018-2022. According to these results, it can be said that Sn can be transported in the wood of T. tomentosa, R. pseudoacacia, and P. menziesii. The study results indicate that T. tomentosa are not suitable bio-monitors for monitoring the changes in the Sn concentrations and cannot be recommended for the purposes of phytoremediation of Sn-contaminated sites.
DISCUSSION
The main hypothesis of the study is that Sn accumulation in the organs of the species under study varies depending on the compass direction. Although the study results revealed differences between the directions, it can be said that the data on compass directions did not show a consistent trend as a result of the study. Since the data did not match the hypothesis, this situation shows that the entry of metals into tree rings varies depending on other factors. For example, it is well known that water is transmitted from the roots of a tree upwards through the xylem of the last year. Another possible path may be downwards, if the metal is able to pass into the leaves, from which it would be conducted through the phloem tissue and then to some parts of the xylem via ray cells. The mechanism involving passage into leaves does not match the originally proposed hypothesis, because a leaf on the side away from the wind is still expected to be affected by the wind. There is no mechanism that would allow the metal falling on the trunk of a tree to enter the lower xylem on that side of the tree (Shahid et al. 2017; Wani et al. 2018). Based on the present findings, any mechanism that would be expected to have contributed to a consistent directionality does not have empirical support. According to these results, the hypothesis of the study can be rejected.
Heavy metals in the air enter the plant directly by respiration or by adhering to plant organs with the help of particulate matter. Some of them mix into the soil and water due to the effects of rain and gravity. Phytoremediation of soil contaminated with heavy metals involves various steps and processes, which include heavy-metal uptake (phytoextraction), accumulation and translocation of heavy metals (phytoaccumulation), emission to atmosphere (phytovolatilization), and their stabilization in the root zone (phyto-stabilization) (Shah and Daverey 2020). Heavy metals can be taken up by root cells from soil, with subsequent storage in root tissues, long-distance transport upwards via xylem and downwards via phloem (Luo et al. 2016; Cao et al. 2020; Rosa et al. 2022). Heavy Metals are primarily taken up by the plants along with water and nutrients (Shah and Daverey 2020). The roots receive metal either by symplastic transport (via plasma membrane of endodermal cells of roots) or by apoplastic transport (movement via free space between cell wall) (Ling et al. 2017; Thakur et al. 2016). Heavy metals enter through intercellular spaces (apoplast) in apoplastic transport and through specific ion channels or carriers in symplastic transport (Chaudhary et al. 2018). Metals are stored in vacuoles by the non-hyperaccumulator plant, while they are translocated very efficiently from root-to-shoot via xylem in the hyperaccumulator plant. Heavy metals are primarily transported to the aboveground tissues via xylem (Wu et al. 2010). For xylem loading, metal ions have to cross a water impervious barrier Casparian band. As a result, it blocks the apoplastic efflux of metal ions from the root cortex to stele and metals start moving through symplastic transport to pass this barrier and to reach the xylem (Mahmood 2010). The heavy metal is then absorbed, precipitated and accumulated in the aerial parts of the plant (i.e., shoot, leaves, etc.) by the process called phytoaccumulation (Shah and Daverey 2020). According to studies, heavy metals can be efficiently moved through the root symplast and loaded into xylem vessels, where subsequent transport to the above-ground tissues is driven by transpiration stream (Deng et al. 2016; Zeng et al. 2013). Thus, plants contribute to cleaning the environment by absorbing heavy metals from the air, water, and soil in their organs (Shahid et al. 2017; Türkyılmaz et al. 2020; Ghoma et al. 2022; Hlihor et al. 2022).
Many studies have been conducted on the use of plants as biomonitors and to decrease heavy metal pollution (Tufail et al. 2022; Yaashikaa et al. 2022; Kuzmina et al. 2023). Several studies reported the level of heavy metal accumulation to vary depending on the species (Türkyılmaz et al. 2019; Karacocuk et al. 2022). The most critical feature sought in species that can be used to determine heavy metal pollution is the ability of the species to accumulate heavy metals in their bodies (Savas et al., 2021). Çetin et al. (2023) suggested Pinus pinaster and Picea orientalis as suitable species for monitoring Sn pollution, whereas Cupressus arizonica, Cedrus atlantica, and Pseudotsuga menziesii were reported to have the potential to mitigate Sn pollution. However, it was found in the present study that Robinia pseudoacacia and Cedrus atlantica trees yielded the highest average Sn concentrations, which indicates that Robinia pseudoacacia and Cedrus atlantica are the most suitable species for reducing Sn pollution among those studied.
The anatomical and genetic structure of plants plays a critical role in the interaction between plants and heavy metals. Previous studies reported that heavy metal concentrations might exhibit significant variation between different organs of the same plant (Sevik et al. 2019a,b; Sulhan et al. 2023). For instance, Cetin and Jawed (2022) determined that there were traffic density-related changes in Ba concentration in the leaves and branches of Ficus bengalensis, Ziziphus mauritiana, Conocarpus erectus, and Azadirachta indica. Azadirachta indica leaves were found to be the most suitable organ. Plants growing in the same environment have different heavy metal concentrations in different organs depending on factors such as organ structure, morphology, surface area, surface texture, and size (Isinkaralar et al. 2022). Therefore, it is important to identify specific species for each heavy metal to effectively reduce heavy metal pollution (Yayla et al. 2022).
Wood is the largest part of a plant in terms of mass and, therefore, it has the highest heavy metal accumulation capacity. Differing from many other parts, wood remains integrated with the tree for a long period. Thus, plants that can accumulate heavy metals in their wood are of particular importance to prevent air-borne heavy metal pollution (Koc 2021; Key et al. 2023). Considering the average values of species in this study, the lowest average Sn concentration was found in Pseudotsuga menziesii (255 ppb), whereas Robinia pseudoacacia (15300 ppb) was determined to have the highest average concentration, followed by Cedrus atlantica (7640 ppb). Therefore, the most suitable species to reduce Sn pollution was determined to be Robinia pseudoacacia, which has the highest Sn concentration in wood.
Previous studies revealed that heavy metal concentrations were high in many species, especially in the outer bark (Koç 2021; Çobanoğlu et al. 2023). Gueguen et al. (2012) observed V, Ni, Cr, Sb, Sn, and Pb pollutions in the outer bark of plants taken from areas near traffic axes Strasbourg and Kehl in the Rhine Valley, whereas Cr, Mo, and Cd pollutions were found in samples taken from industrial areas. This is because of the structure of the outer bark and its interaction with metal-contaminated particles. In this study, the highest Sn concentrations were found in the outer bark of Tilia tomentosa, Pseudotsuga menziesii, and Fraxinus excelsior species. This result can be explained by the outer surface serving as the source of pollutant material and the presence of Sn-contaminated particles.
The complex transfer of elements within the wood is an important uncertainty in understanding the applicability of biomonitors in examining heavy metal pollution. Although the internal conductivity and transport of substances vary among species, other studies have shown that all of them have more/less transport and accumulation (Turkyilmaz et al. 2020). However, it has been reported that some of them have become widely preferred in mitigation of environmental pollution due to their higher absorption capacity compared to others. Previous studies reported remarkable variations in the transfer of different elements within the wood of different tree species. Çobanoğlu et al. (2023) emphasized that the transfer of Cd, Ni, and Zn in cedar wood is limited, whereas Zhang (2019) reported variations in Zn and Pb concentrations in the annual rings of Cedrus deodara but no change in Cu concentration. Key et al. (2022) determined that the transfer of Ni, Co, and Mn in the wood of Corylus colurna was very limited. Cesur et al. (2021, 2022) reported limited transfers of Fe, Cd, and Ni elements in the wood of Cupressus arizonica but higher levels of transfer for Bi, Li, and Cr. Moreover, it was found that the transfer of Ni in the wood of Cedrus atlantica is quite restricted, whereas Co has more mobility (Koç 2021).
The transfer of various elements within wood varies between species and it is related to cell structure and cell wall. The cell wall-plasma membrane represents a flexible structure involved in the perception and signaling of metal/metalloid stress (Wani et al. 2018). The interface between the cell wall and plasma membrane is considered the potential region for heavy metal tolerance because it accumulates large heavy metal fractions (Wu et al. 2010).
Concentrations obtained in the outer bark and on the sides of the tree where pollution is present are expected to be much higher. Studies show that heavy metals in the air adhere to particulate matter in areas close to the pollution source and contaminate particulate matter with heavy metals, and these particulate matter settles in plant organs and increases heavy metal concentrations in these organs (Sevik et al. 2020; Yayla et al. 2022; Kuzmina et al. 2023). Airborne metals (as ions) can enter a tree is by means of rainfall, which allows the ions to be taken up by the tree’s roots and then be distributed to the leaves and other parts of the plant. Elements uptake by plants is highly dependent on the concentration, amount, and activity of element in the soil solution (Erdem et al. 2024).
In urban-industrial areas exposed to anthropogenic pressures and with high traffic density, proper plantations might contribute to environmental improvements and air pollution reduction. This study showed that selected plants can accumulate heavy metals while growing in polluted environments without compromising their physiological vitality. Thanks to their tolerance to heavy metal pollution, it is recommended to use these species for biological monitoring of air quality in urban environments. These plants can provide a valuable ecosystem service by removing heavy metals from the air. Expanding such studies can provide insights into pollution levels in environments contaminated with heavy metals. Air quality maps can be created in urban areas to obtain information about the effects of air pollution on ecosystems and organisms.
CONCLUSIONS
- To use annual rings to monitor the change of heavy metal pollution in the process, the displacement of the element to be monitored in the wood must be limited. When the changes in wood based on period and direction were examined, it was seen that there was no significant difference between neighboring wood groups in T. tomentosa, R. pseudoacacia, P. menziesii, and the values were relatively close to each other. According to these results, T. tomentosa, R. pseudoacacia, P. menziesii were not suitable biomonitors for monitoring the change of Sn pollution.
- However, there were big differences between neighboring woods in C. atlantica and F. excelsior. Therefore, C. atlantica and F. excelsior were judged to be suitable biomonitors that can be used to monitor the change in air concentrations of Sn.
- The present study revealed that the species examined here have different capacities regarding Sn accumulation. R. pseudoacacia and C. atlantica were found to be the most suitable species for mitigating Sn pollution. Examining the average values by species, P. menziesii was determined to have the lowest average Sn concentration in all organs, whereas R. pseudoacacia had the highest average values and C. atlantica had the second-highest ones. Therefore, R. pseudoacacia, which has the highest wood concentration, was determined to be the most effective species for reducing Sn pollution. Therefore, it is appropriate to use R. pseudoacacia and C. atlantica species to reduce Sn pollution in urban areas where Sn pollution is high.
- Extensive measurements were analyzed in this work to examine a hypothesis regarding the compass orientation of metal uptake – especially with respect to the annual rings of trees. Though the data included various statistically significant differences, when considering individual tree species and specific year spans, none of these correlations showed consistency across different tree species and different time periods, as would have been expected for a mechanism influenced by prevailing winds. On this basis, the hypothesis was rejected. Instead, the present results suggest that metal uptake into the xylem of trees involves mechanisms that are unrelated to prevailing wind directions, sunlight directions, or other such factors that would be expected to have a consistent relationship to compass orientation.
ACKNOWLEDGEMENTS
The authors would like to express their gratitude to Semsettin Kulac and Ismail Koc at Duzce University, Duzce, Türkiye, for providing the materials.
Declaration of İnterest Statement
No potential conflict of interest was reported by the author(s).
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Article submitted: June 5, 2024; Peer review completed: August 17, 2024; Revisions accepted: September 13, 2024; Published: September 23, 2024.
DOI: 10.15376/biores.19.4.8542-8562