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Article

Spatiotemporal Distribution of Mercury in Tree Rings and Soils Within Forests Surrounding Coal-Fired Power Plants

by
Eugene Ha
1,†,
Ikhyun Kim
1,†,
Heemun Chae
2,
Sangsin Lee
3,
Youngsang Ahn
4,* and
Byoungkoo Choi
2,*
1
Department of Forestry and Environmental Systems, Kangwon National University, Chuncheon 24341, Republic of Korea
2
Division of Forest Science, Kangwon National University, Chuncheon 24341, Republic of Korea
3
Climate Change Research Center, ChungNam Institute, Hongseong 32258, Republic of Korea
4
Department of Forest Resources, College of Agriculture and Life Sciences, Chonnam National University, Gwangju 59626, Republic of Korea
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Atmosphere 2024, 15(11), 1287; https://doi.org/10.3390/atmos15111287
Submission received: 25 September 2024 / Revised: 22 October 2024 / Accepted: 24 October 2024 / Published: 27 October 2024
(This article belongs to the Special Issue Industrial Emissions: Characteristics, Impacts and Control)
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Abstract

:
The release of mercury (Hg) from coal-fired power plants (CPPs) into local ecosystems poses substantial environmental and health hazards. This study was conducted in Chungcheong-nam-do, South Korea, a region featuring over half of the country’s coal power facilities, to estimate the impacts of CPPs on Hg distribution in forest ecosystems. By analyzing Hg concentrations in pine tree rings and soil at 21 locations around CPPs and comparing them to control sites and industrial zones, we present a nuanced understanding of the effects of CPPs on Hg concentration. The analysis of Hg concentrations in tree rings showed a significant decrease in Hg levels as the distance from the power plants increased, suggesting that CPPs primarily influence Hg distribution in trees within a 25 km radius. In contrast, soil Hg concentrations did not exhibit a clear trend. This may reflect the limitations of this study in accounting for the physicochemical properties of the soil at each sampling site. Nevertheless, the Potential Ecological Risk Index for soil Hg contamination indicated a higher risk rating within a 1 km radius of the CPPs compared to other locations. Hg concentrations in tree rings have shown a steady decline since the 1970s, suggesting the positive effects of air pollution regulations. This also highlights the value of tree core samples as effective tools for monitoring historical Hg pollution. Furthermore, the higher historical concentrations of Hg in tree rings imply that trees may have acted as sinks for atmospheric Hg in the past.

1. Introduction

Natural phenomena and human activity contribute to the emission of Hg into the environment. Recent studies, including those by Amos et al. and Zhang et al. estimate that human activities have increased current atmospheric Hg concentration by approximately 450% above pre-industrial levels, leading to a total atmospheric Hg mass of 4.4 kt [1,2,3,4]. Of these anthropogenic emissions, coal-fired power plants (CPPs) account for 13.1% of total anthropogenic Hg emissions, the second largest contributor after artisanal and small-scale gold mining, which emits 37.7% [5].
Hg released from CPPs, predominantly in elemental form, is known for its capacity to disperse over long distances beyond the point of emission and infiltrate surrounding ecosystems. Some Hg is associated with fly ash produced during combustion, rapidly accumulating in nearby ecosystems and impacting soil quality. The deposition of total gaseous mercury from the atmosphere into forest soils through both wet and dry deposition has been reported [6]. Although it varies depending on soil characteristics [7], the total mercury (Hg) concentration in soil is influenced by emissions from both natural and anthropogenic sources [8]. Notable accumulation near CPPs has been reported, emphasizing the environmental footprint of these facilities.
Mercury is a highly toxic heavy metal with adverse effects on the nervous, digestive, and immune systems even in small amounts [9]. Its toxicity, sustained persistence in the environment, and ability to accumulate in living organisms make Hg pollution a critical environmental concern, posing substantial risks to both human health and ecosystems [10,11]. The Minamata Convention on Mercury, established in 2013, is a worldwide initiative to safeguard human health and the environment against the harmful effects of Hg. This initiative emphasizes the importance of conducting research, promoting development, and enhancing Hg monitoring efforts.
Chronological analysis is appropriate for understanding past pollution events and assessing the effectiveness of pollution mitigation measures. However, while the reconstruction of historical Hg emission trends using natural archives such as ice cores and lake sediments can provide valuable insights, these methods are often limited in their spatial applicability. In contrast, tree rings, though potentially constrained by the tree’s age, offer fixed, location-specific chronological records, making them effective tools for the temporal analysis of past pollution events [12,13,14,15]. Laboratory experiments have shown that trees primarily absorb atmospheric Hg through their canopies during photosynthesis, storing it in their trunks, which validates the use of tree rings for chronological Hg estimations [14,16,17]. Furthermore, recent advances in core sampling, as opposed to traditional disk sampling through tree felling, have expanded the applicability of tree ring analysis for historical Hg concentration assessments, increasing the utility of trees in understanding past Hg pollution levels [18].
The choice of tree species significantly influences Hg accumulation, with pines being widely distributed among evergreen conifers and exhibiting higher Hg concentrations owing to their large annual biomass increment index. This characteristic renders pine particularly suitable for studying Hg concentrations compared to other species [17,19].
South Korea’s dependence on CPPs for electricity generation is influenced by factors such as low fuel prices, construction costs, and geographical limitations. Chungcheongnam-do, located on the west coast of South Korea, is home to 31 of the country’s 61 CPPs. This unique combination of geographical and industrial factors increases the risk of regional air pollution. In particular, CPPs are major contributors to Hg emissions; however, there is a scarcity of comprehensive studies on the extent and sources of Hg pollution in areas surrounding these facilities in South Korea.
This research evaluated temporal (tree core) and spatial (soil and tree core) distributions of Hg downwind of CPPs along the west coast of South Korea. Through the analysis of the spatial distribution of Hg around the CPPs, we aimed to estimate the range of influence of these power plants and provide a basis for developing localized pollution mitigation strategies. Additionally, by analyzing the annual temporal changes in Hg concentrations in tree rings, we sought to: (1) assess the impact of CPP operations, and (2) present trends in Hg contamination, offering insights to inform future Hg air pollution control measures.

2. Materials and Methods

2.1. Site Description and Experimental Design

Chungcheongnam-do is located in the central-western part of the Korean Peninsula, featuring a terrain that rises in the east and descends in the west around the Charyeong Mountains (Figure 1). The coastline is characterized as a typical ria coast, with significant tidal ranges and developed sea and land breezes due to the thermal differences between land and sea. This coastal region is densely populated with industrial complexes (INDs) and coal-fired power plants that facilitate the import and export of raw materials and products [20].
The region experiences distinct seasons with hot, humid summers and cold, dry winters, encompassing a mid-latitude temperate monsoon climate. Over the past 30 years (1992–2021), the annual average precipitation has been 1252.1 mm, predominantly occurring in summer. The average summer temperature is 24 °C, while the winter average is −0.2 °C (Korea Meteorological Administration). Influenced significantly by its coastal location and the peninsula’s characteristics, the wind direction and strength vary widely across Chungcheongnam-do.
To estimate the spatial distribution of Hg pollution, we conducted a detailed analysis of four coal-fired power plants (CPP1, CPP2, CPP3, and CPP4) by strategically selecting forest sites at distances of 1, 5, 15, 25, and 30 km, respectively. This site selection was informed by the need to assess environmental conditions both prior to and following the establishment of CPPs, prioritizing national and public forests for their accessibility and the suitability of pine forests for dendrochronological studies. A key consideration was the placement of sites southward of the CPPs, aligned with prevailing wind directions, to accurately track Hg dispersion. This rigorous process led to the identification of 21 Coal-fired Power Plant-influenced Areas (CPPAs), where comprehensive tree core and soil sampling were conducted (Figure 1).
Each CPP differs in fuel type, facility capacity, plant equipment number, and the start of operations (Table 1). The first unit of CPP1 was completed in 1999, while that of CPP2 was completed in 1995. CPP3 and CPP4 had their first units completed in 1983, making them the earliest. Except for the older unit in CPP4, all used bituminous coal as fuel (Table 1). The offline timing of a CPP refers to the closure of all units within the power plant and does not include cases where only some units are closed (Table 1).
To estimate the natural background concentrations of Hg and the potential impacts of CPP emissions, we designated Gyeryong Mountain National Park (C1) and Boeun in Chungcheongbuk-do (C2) as control areas. C1 and C2, distanced 74–114 km and 110–140 km from CPPs respectively, were strategically chosen to explore the variability in Hg concentrations due to their locations and the influence of wind patterns. C1 provides an opportunity to study the potential for indirect Hg transport via air currents, offering valuable insights into atmospheric Hg dynamics. C2, situated laterally to the prevailing wind directions, presented a scenario with a lower likelihood of Hg exposure from CPP emissions, which is crucial for estimating natural Hg concentrations in areas with minimal industrial impact. Although soil samples were not collected from C2, comprehensive data derived from tree cores across both control sites offered a robust foundation for analyzing the environmental dynamics of Hg. This approach ensured the integrity of the study and provided valuable insights into the spatial distribution of Hg despite the constraints faced during the research process. Additionally, areas 1 km and 20 km from the Asan National Industrial Complex, Chungcheongnam-do Bugok District, were designated as areas estimated to be influenced by industrial complexes (INDA) to assess the impact of Hg pollution from human activities. The CPPA sites were determined as follows: CPPA1 with five sites (1, 5, 15, 25, and 30 km), CPPA2 with seven sites (5, 5 (2), 15, 15 (2), 25, 25 (2), and 30 km), CPPA3 with five sites (5, 5 (2), 25, 25 (2), and 30 km), and CPPA4 with four sites (5, 15, 25, 30, 30 (2) km). For the INDA, locations 1 km and 20 km away were selected (Figure 1).

2.2. Sampling Methods

2.2.1. Tree Core Sampling

Over the past few decades, numerous studies have demonstrated the potential of woody plants as bioaccumulators or bioindicators of heavy metals in pollution monitoring [21,22,23,24,25]. In December 2022, tree core samples were collected from two individual trees at each selected research site to analyze tree ring Hg concentrations. This study exclusively used the species Pinus densiflora siebold & zucc., commonly known as Korean red pine, to ensure uniformity in the species examined. Traditional dendrochronological sampling involves harvesting tree discs by logging to ensure an adequate sample size for analysis. However, to avoid deforestation caused by logging, this study employed a power-driven increment borer to extract two 5.15 mm diameter core samples from each tree at approximately 30 cm above ground level near the base of the tree. We collected tree core samples from a total of four sides by individual tree, spaced 90 degrees apart from the individual trees to minimize variability, to create one composite sample. While these measures cannot entirely exclude the potential for mercury redistribution within the tree rings, they were implemented to minimize variability within the samples, and by applying the same methodology across all samples, we aimed to reduce uncertainty in the results. Multiple sets of sampling tools were prepared, and each tool was cleaned after a single use to prevent cross-contamination that may occur due to sampling tools during sample collection. The cleaning procedure involved the following steps: (1) rinsing with distilled water, (2) washing with a 10% nitric acid solution, (3) rinsing with deionized water, and (4) drying. The collected samples were stored in polyethylene tubes sealed with tape to prevent contamination.

2.2.2. Soil Sampling

When considering soil heterogeneity, the soil sampling approach was based on ISO18400-104 to ensure representativeness. Although the standards advise collecting samples from one central point and four peripheral points in all directions (totaling five points), this study modified the method because of variations in slope, accessibility, and soil layer thickness at the study sites. Consequently, samples were obtained from three distinct locations situated within a radius of 5 to 10 m around the central point of each target area in May 2023. A soil auger was used to collect approximately 300 g of topsoil (from the 0–15 cm layer) at each location. The soil auger was cleaned using the same procedure as the tree core sampler to prevent cross-contamination.
To enhance sample representativeness, more than six composite samples were collected from each of these points. The collected samples were then securely sealed within polyethylene zipper bags and preserved in iceboxes for transport while maintaining a temperature below 4 °C to prevent degradation. In total, 72 soil samples were successfully collected from 24 designated sites.

2.3. Measuring Total Hg Concentration

2.3.1. Tree Core Samples

The sample analysis was conducted at the Joint Experimental Laboratory of Chonnam National University. Taking into account the volatile and physicochemical properties of Hg, the samples were dried for over 40 days at 40 °C. The tree core samples were sectioned biennially using a microscope and a stainless-steel scalpel blade. The sectioned cores were ground using an MM 400 ball-mill grinder (Retsch GmbH, Haan, Germany), and the ground samples were weighed on an electronic scale. The total Hg concentration was measured using a Milestone DMA-80 Direct Mercury Analyzer (Milestone GmbH, Lenting, Germany). This analyzer processes samples via thermal decomposition and atomic absorption spectrophotometry, enabling direct analysis of the total Hg content. The analyzer has a Hg detection limit of 0.005 ng. The operational conditions for DMA-80 were based on the EPA Method 7473 protocol (US/EPA 2000). Mercury standard solutions from the National Institute of Measurement Standards, Canada, were utilized, with MES-3 (Mercury Standard Solution, certified value = 90 ± 9 ppb HgT) used to establish the calibration curve. The coefficient of determination (R2) exceeded 0.999 with recoveries ranging from 97% to 102%, indicating high accuracy and precision.

2.3.2. Soil Samples

The Hg concentration analysis of the forest soil samples was performed at the Korea Environment & Water Institute. The total Hg concentration was determined using a NIC MA-3000 Direct Mercury Analyzer (NIC, Tokyo, Japan). This device also employs thermal decomposition and atomic absorption spectrophotometry for the direct analysis of total mercury. The operational conditions for the MA-3000 adhered to the Soil Contamination Process Testing Standards (National Institute of Environmental Sciences, No. 2022-38). The test environment was maintained at temperatures ranging from 23 °C to 25 °C, with humidity levels between 28% R.H. and 40% R.H. Mercury standard solutions from Kanto Chemical were employed, specifically 210K9517 (Mercury Standard Solution, certified value = 1002 mg·L−1 HgT) for calibration curve creation. The R2 value exceeded 0.999 with recoveries varying between 92% and 107%, demonstrating the high accuracy and precision of the method.

2.4. Data Analysis

2.4.1. Tree Rings

The Hg concentration in the tree rings (both average and standard error) was determined for each 2-year segment of paired trees at each site. For the spatial and time distribution analysis of Hg concentrations, data were standardized across all tree rings based on the average data spanning from 1971 to 2020.
To analyze the factors influencing the spatiotemporal distribution characteristics of Hg concentrations in tree rings, analysis of covariance (ANCOVA) was conducted. The analysis was performed in two stages. In the first stage, the study sites were categorized into three groups (CPPA, INDA, and control) to examine the effects of pollution sources and year on Hg concentrations in tree rings. The covariate used in this analysis was the sub-classification of the study sites (CPPA1~4, INDA, C1, and C2). In the second stage, the analysis focused on the four CPPA areas, investigating the effects of distance from the CPP, distance from the coastline, year, and CPP operation status on Hg concentrations in tree rings. The covariates for this analysis were the four CPPs influencing the CPPA areas. The year variable used in the ANCOVA was categorized into decades (1970s, 1971~1980; 1980s, 1981~1990; 1990s, 1991~2000; 2000s, 2001~2010; 2010s, 2011~2020). Post-hoc tests cannot be conducted directly with ANCOVA. Therefore, when significant differences were detected in the ANCOVA, additional post-hoc tests were performed using analysis of variance (ANOVA). The Scheffé method was applied for the post-hoc test.
To assess the temporal distribution of Hg concentrations, we analyzed data from each CPPA region, focusing on changes in Hg concentrations relative to the commissioning dates of the respective power plants. Additionally, to evaluate the impact of strengthened air pollution emission standards, Hg concentration changes were compared across the CPPA and control areas (C1, C2, and INDA) at critical points in the regulatory history —1999, 2005, 2010, and 2015—based on the ‘Air Pollutant Emission Limits’ (Annex 5 of the Enforcement Rules of the Clean Air Conservation Act, Articles 15 and 33) of Korea.
All statistical tests were performed using SPSS Statistics 26 (IBM Corp., Armonk, NY, USA) and R software (version 4.1.2).

2.4.2. Soil

The Shapiro–Wilk test was used to assess the normality of soil Hg concentrations, revealing an abnormal distribution (p < 0.05). To understand the impact and extent of coal-fired power plants on soil Hg concentrations, we analyzed data across various locations, CPPAs, and distances from the plants using Kruskal–Wallis analysis (p < 0.05). The significance values, adjusted via the Bonferroni correction, helped delineate the influence range of power plants on tree ring Hg concentrations and verify the significance of soil Hg concentrations by research location, CPPA, and distance from power plants.
To quantify soil contamination, we evaluated the Geoaccumulation Index (Igeo) and Potential Ecological Risk Index (Er). Igeo was used to assess whether soil metal concentrations stem from natural or anthropogenic activities, and Er evaluates the ecological risk posed by Hg.
The Igeo was first introduced by Müller [26] to evaluate heavy metals in sediments of the Rhine River and has been utilized since 2003 to measure soil contamination (Muller, 1969). Igeo is calculated using the following formula:
I g e o = log 2 ⁡ C i 1.5 × B i
where Ci represents the concentration of element i measured in sediments or soil and Bi is the background concentration of element i in uncontaminated sediments or soil, which can be directly measured or obtained from the literature. In this study, we used a natural background concentration of 56 ng/g for mercury, based on data provided by the National Institute of Environmental Research (NIER) from the Soil Monitoring Network operated by the Ministry of Environment of South Korea [27]. A factor of 1.5 was applied to account for variations in background values that could arise from lithological changes.
Er was proposed by Hakanson [28] in Sweden to assess the ecological damage caused by heavy metal contamination. This method combines the ecological, environmental, and toxicological effects of heavy metals. Er is defined as follows:
E r = T r × C r = T r ⁡ ( C C n )
where Tr is the toxic response factor for the element, and Cr is the contamination factor. The contamination factor is the ratio of the measured value of the heavy metal (C) to the reference value (Cn). As proposed in the literature, the toxic response factor for Hg is 40.

3. Results and Discussion

3.1. Hg Concentrations in Tree Rings in the Environs of Coal-Fired Power Plants

According to the results of the ANCOVA analysis, there were significant differences in mercury concentrations in tree rings among the CPPA (10.0 ng/g), INDA (8.7 ng/g), and control (5.0 ng/g) groups (p = 0.000) (Table 2 and Table A1). Additionally, the year was found to have a significant effect on mercury concentrations in tree rings in the Chungcheongnam-do region (p = 0.000). The interaction effect between the pollution source categories (CPPA, INDA, and control) and year also had a significant impact on mercury concentrations in tree rings (p = 0.026) (Table 2).
The Hg concentrations in tree rings from all sampling sites varied widely, ranging from 1.3 to 13.3 ng/g (Figure 2, Table A1). This is compared to a range of 1.3 to 32.5 ng/g for pine tree rings near pollution sources reported in previous studies [7]. Notably, studies on conifers near power plants have shown Hg concentrations in pine tree rings ranging from 1.7 to 51.9 ng/g [29]. Navrátil et al. [30] reported that the Hg concentration in pine tree rings from a national park in the Czech Republic was 3.6~5 ng/g. Separately, Novakova et al. [31] investigating the influence of a chemical plant in Germany; the chosen control site exhibited an average Hg concentration in pine tree rings of 4.6 ng/g. These values are comparable to those found in our study’s C1 location, while the concentrations at C2 were lower than those in previous research (Table A1). All sites within the CPPA had higher concentrations than those in C2 (Figure 2, Table A1). However, caution is advised when comparing our results with those of prior studies, as tree ring Hg concentrations can vary according to environmental conditions, age, climate, and species.
Trees absorb some atmospheric Hg through their roots [32], and a relatively large amount of atmospheric mercury uptake occurs through their leaves and bark [33]. While forests play a crucial role in the biogeochemical cycling of Hg, there is still no consensus on whether forests act as a source or a sink of Hg [34]. Nevertheless, the high Hg concentrations in tree rings observed in the CPPA areas suggest that trees could potentially be used for the absorption and sequestration of Hg. However, it must be acknowledged that trees and soils in forest ecosystems can rerelease or export Hg to the atmosphere and hydrosphere through various pathways [34].
From 1971 to 2020, it is evident that the average Hg concentrations in tree rings were higher in CPPA and INDA compared to the control. However, the temporal patterns of Hg concentration changes in each study site were significantly different at the p < 0.05 level (Table 2, Figure 3). In both CPPA (R2 = 0.79) and control (R2 = 0.76) areas, Hg concentrations in tree rings have steadily declined from the past to recent years. Notably, in the control area, Hg concentrations were similar to those of INDA before 1990, but experienced a sharp decline around 1990, continuing to decrease thereafter (Figure 3). Furthermore, the rate of decline in Hg concentration in the control area was more than three times steeper than in the CPPA (Figure 3). This decrease in Hg concentration in the control area may reflect the global efforts to regulate emissions of atmospheric pollutants. Globally, Europe and North America have observed declining atmospheric Hg concentrations, which is attributed to the strengthening of air quality laws and regulations on air pollutants, resulting in reduced anthropogenic Hg emissions [35,36]. This trend underscores the effectiveness of policy-driven environmental protection measures for mitigating Hg pollution. In contrast, Asian countries have experienced a continuous increase in anthropogenic Hg emissions because of industrialization and reliance on coal-fired power generation, raising global concerns about Hg pollution [35]. This divergence highlights the need for international cooperation and adoption of stringent environmental regulations across all regions to address the global challenge of Hg pollution.

3.2. Hg Concentrations in Forest Soils in the Environs of Coal-Fired Power Plants

The distribution of soil Hg concentrations is markedly influenced by several factors, including pollution sources, underlying bedrock, and prevailing climatic conditions [37]. In addition, because Hg has a high affinity for natural organic carbon, the concentration of Hg can increase with the total organic carbon content in the soil [38]. As a result, even within proximate areas receiving similar levels of atmospheric deposition, soil Hg content can exhibit considerable variability. The results of this study may be limited in their generalizability in that they did not account for the variability of Hg concentrations across soil environments and characteristics. In this study, the total soil Hg concentration at all sampling sites ranged from 40 to 210 ng/g (Table A1). In general, most samples exhibited higher concentrations than C1 (Table A1). Notably, the concentration in C1 was lower than the background soil Hg concentration (56 ng/g) in Chungcheongnam-do, as reported by the Korean Soil Network (2020–2021), making it a suitable control (Table A1). The highest values were recorded at sites 1 km from CPP1 and 1 km from an industrial complex, with concentration ranges of 150 to 210 ng/g and 190 to 200 ng/g, respectively (Table A1). These concentrations were significantly higher than C1 (p < 0.05). These values are lower than the soil Hg concentrations near a coal-fired power plant in Chile (568 ng/g) or near the largest power plant site in Serbia (900–12,000 ng/g), highlighting the diverse impacts of different environmental and anthropogenic factors on soil Hg levels [39,40].
The analysis of average soil Hg concentrations by CPPA showed a sequence of CPPA1 (116.7 ng/g) > CPPA2 (108.1 ng/g) > CPPA4 (87.3 ng/g) > CPPA3 (83.3 ng/g), indicating no correlation with the power output, similar to the patterns seen in pine tree ring Hg concentrations (Table A1). CPPA3, which had the highest Hg concentration in the pine tree rings, had the lowest average soil Hg concentration. This outcome contrasts with the findings of Nóvoa-Muñoz et al. [41] who suggested a relationship between soil Hg content and power generation. To accurately determine the cause of these discrepancies, further analysis of the Hg content in the coal used by these power plants or an increase in the number of samples may be necessary.

3.3. Spatial Extent of the Influence of Coal-Fired Power Plants on Hg Concentrations in Forests

The order of Hg concentrations in CPPA was CPPA3 > CPPA2 > CPPA1 > CPPA4, which did not correlate directly with the power output (CPP2 > CPP1 > CPP3 > CPP4). The high concentrations of CPPA3 can be compared with other tree ring Hg concentrations related to coal-fired power plants or other anthropogenic sources (Table A1 and Table 1). For instance, the average Hg concentration in deciduous tree rings near a chemical plant in Germany reached 90 ng/g, and the average concentration in pine tree rings closest to a chlor-alkali plant in the Czech Republic was 32.7 ng/g [31,42]. Tree ring Hg concentrations in the CPPA areas were found to be significantly influenced by the distance from the CPP (p = 0.000) (Table 3). In all CPPAs, tree ring Hg concentrations in tree rings were lowest at the farthest distance of 30 km from the CPP, and this difference was significant in three of the four CPPA areas, excluding CPPA3 (p < 0.05) (Figure 4).
Our findings revealed a nuanced spatial distribution of Hg, with the average concentrations in pine tree rings decreasing with increasing distance from the plants. Notably, the highest average concentration was found at the 15 km mark (11.0 ng/g), progressively diminishing to the lowest level at 30 km (8.0 ng/g). This trend suggests a discernible relationship between proximity to power plants and Hg concentrations. Interestingly, between 1 km and 15 km, a slight increase in the average Hg concentration was noted, followed by a pronounced decrease beyond 25 km, with a significant drop at a distance of 30 km. This distribution pattern aligns with previous studies that reported a reduction in trace element concentrations as the distance from the pollution sources increased [42,43,44,45].
A comprehensive analysis by Carballeira and Fernández [46] enhances our understanding of these spatial patterns. Their seminal work on Hg concentrations in mosses collected at various distances from a power plant underscored an increase in Hg levels up to 30 km, followed by a decline from 30 to 50 km. Their findings not only support our observations but also offer an additional perspective on Hg dispersion from a point source into the surrounding ecosystems. The correlation between their moss study and our investigation of pine tree rings up to 25 km from coal-fired power plants, along with the notable reduction in Hg concentrations in control areas 30 km away, highlights the consistent environmental response to Hg emissions across diverse biological media.
To estimate the distribution of Hg, control areas C1 and C2 were instrumental in benchmarking the influence of CPP. The significantly lower average Hg concentrations observed at C2 suggested a minimal environmental impact, whereas the similarity in Hg levels between pine tree rings at 30 km and those at C1 emphasized comparable Hg exposure across these distances.
Soil analysis indicated the spatial influence of CPPs, demonstrating that the highest Hg concentration was found 1 km from the CPP (133.33 ng/g). Beyond this point, a 28% decrease in the soil Hg concentration was noted at 5 km, with levels stabilizing up to 30 km, showing no significant differences (p > 0.05). The average soil Hg concentration at 1 km was higher than that at C1 and resembled the average concentration of INDA. This pronounced impact near plants was attributed to the deposition of heavier Hg compounds, which tend to settle in closer proximity, as noted in other studies [29,38,47,48]. Martín and Nanos [48] reported contamination extending up to 20 to 55 km from power plants, with localized enrichment due to emissions. Our results, indicating a high Hg concentration near plants with a more uniform spread across distances, challenge the notion of a localized impact, and underscore the necessity of comprehensive soil monitoring around industrial emission sources.
However, the decrease in Hg concentrations in tree rings with increasing distance from the CPP does not appear to be solely due to the influence of the CPP. This is because the distance from the coastline was also found to have a significant impact on Hg concentrations in tree rings in the CPPA areas (p = 0.000) (Table 3). Each CPP is located along the western coast, so the distance from the CPP to the sampling sites is very similar to the distance from the sea. Research on Hg deposition indicates that coastal areas have higher concentrations of Hg, leading to increased wet deposition [49]. This is likely due to halogens such as bromine and iodine oxides, which oxidize Hg0 to Hg2+ [50,51]. Therefore, the significant variation in Hg concentrations in tree rings based on the distance from the coastline in this study may reflect the influence of Hg2, which is more readily redeposited.
Hg concentrations in tree rings showed no significant differences based on CPP operation status but did exhibit significant differences across different years. However, when interpreting these results, it is important to consider that the varying distances of sampling sites within the CPPA areas from the CPP might result in the absence of significant differences on average (Table 3). Tree ring Hg concentrations were higher before the operation of the CPP in three of the CPPA areas, excluding CPPA4, and in these three areas, Hg concentrations consistently decreased over time regardless of whether the CPP was operational (Figure 5). This further underscores the substantial impact of strengthened global air pollution regulations on Hg concentrations in tree rings.
The slightly higher Hg concentrations in tree rings observed in CPPA4 after 1980, compared to earlier periods, may reflect geographical factors (Figure 5). CPPA4 is located at the lowest latitude among all CPPA areas, and the Chungcheongnam-do region, which encompasses all CPPA areas, experiences relatively strong northwesterly or northeasterly winds (Figure 2). Therefore, the possibility that the operation of CPP1~3 may have influenced Hg concentrations in tree rings within CPPA4 should be considered.

3.4. Risk Assessment of Soil Contamination by Hg

To investigate Hg pollution in soils near coal-fired power plants and control areas, we employed the Igeo and Er. Igeo analysis of soil Hg indicated that the median values at varying distances mostly exceeded zero, indicating prevalent contamination. Notably, locations within 1 km of the plants had Igeo values greater than one, indicating moderate contamination (Figure 6). In contrast, the C1 area, with average and median Igeo values of −0.59, suggested no Hg contamination, presenting a largely unspoiled soil environment (Figure 6). Both the INDA and CPPA demonstrated average and median Igeo values of over 0, indicating a spectrum of conditions ranging from uncontaminated to moderately contaminated (Figure 6). This finding contrasts with Özkul’s [52] findings, where Igeo values ranged significantly higher, from 0.6 to 6.3, denoting areas of more intense contamination than observed in our study.
Regarding the Potential Ecological Risk Index (Er), areas from 5 km to 30 km predominantly fell into the medium potential risk category. However, the vicinity within 1 km was distinguished by median and average Er values exceeding 1, placing it in the medium-high potential risk category (Figure 6). This is in stark contrast to C1, where both the average and median Er values at 40 suggested a lower ecological threat, ranking it between low and medium potential risks (Figure 6). CPPA, with an average Er value of 73, also fell into the medium potential risk category, whereas INDA, with an average Er value of 97 and a median Er value of 109, was categorized as having a medium–high potential risk (Figure 6). Remarkably, this study found certain sites with Er values slightly exceeding those reported by Hu et al. [53] for soils around coal-fired power plants in China, where the risk levels mostly ranged from 29 to 82, typically classified as medium to high potential risk.

3.5. Air Pollution Control Regulation Implications

The observed decrease in Hg concentrations in tree rings within the control area from the late 1900s to recent years, along with the continuous decline in Hg concentrations in the CPPA areas irrespective of the CPP operation period, suggests a positive response to global air pollution regulations. These global regulations also encompass regional measures. In South Korea, air pollution has been regulated through the continuous tightening of the ‘Air Pollutant Emission Standards’ under Article 16 of the ‘Clean Air Conservation Act’. The emission standards for mercury have been strengthened every five years, with revisions made in 1995, 2005, 2010, 2015, and 2020. Regulation of mercury emissions from coal-fired power plants specifically began in 2005.
Comparing the changes in Hg concentrations in pine tree rings in relation to the tightening of air pollutant emission limits in South Korea, it was observed that Hg concentrations in GRMs decreased continuously from 1990 to 2020 after the emission regulations were tightened (Figure 6, Table A1). INDA decreased until 2010, followed by a surge until 2016. Overall, a general decrease in Hg concentrations across the CPPA was noted, with levels stabilizing between 9.3 and 9.6 ng/g from 1999 to 2020 (Figure 6, Table A1). The decrease across all sites, including the resurgence in industrial areas post-2010, aligns with the reduction in Hg emissions due to stringent air pollutant standards, as reported by the National Institute of Environmental Science in 2020. The National Institute of Environmental Science (South Korea) has reported that tighter Hg-related emission standards, as well as tighter allowances for airborne pollutants, such as particulate matter, contribute to reductions in Hg emissions. This demonstrates that CPP pollution control equipment is effective in reducing Hg emissions [54]. Consequently, the continuous decline in Hg concentrations in tree rings, despite the operation of coal-fired power plants, is likely attributable to the effectiveness of both regional and international air pollution regulations.

4. Conclusions

This study estimated the spatial and temporal distribution of Hg concentrations in pine tree rings and forest soils around coal-fired power plants. Our estimates suggest an elevated presence of Hg in these environmental components in proximity to coal-fired power plants compared to cleaner and control areas. This proximity implies the potential influence of Hg emissions from these plants on the surrounding forest ecosystems. Although the estimated concentrations were not an immediate concern, they underscore the importance of ongoing vigilance in managing Hg pollution to support sustainable industrial and environmental health practices.
Spatial analysis revealed a decrease in the Hg concentration in pine tree rings with increasing distance from the coal-fired power plants, indicating a dispersion pattern influenced by proximity. However, the soil Hg concentrations exhibited minimal variability across distances, complicating our ability to draw clear conclusions regarding the scope and impact of contamination. This highlights the complexity of accurately assessing the effects of Hg emissions and underscores the need for more comprehensive and detailed investigations. However, both Igeo and Er were highest within a 1 km radius of the CPP, and in the case of Er, the Hg contamination rating for soil was higher within this radius compared to other locations. This suggests that more targeted soil pollution mitigation strategies may be required for areas in close proximity to CPPs compared to other regions. Additionally, although Hg concentrations in tree rings decreased with increasing distance from the coal-fired power plants, this also corresponded to a decrease in Hg concentrations with increasing distance from the sea. Therefore, the possibility of redeposition of oxidized Hg from the sea cannot be excluded.
Furthermore, temporal analysis revealed a general trend of declining Hg concentrations in the pine tree rings over time, possibly reflecting the beneficial outcomes of the improved emission standards. This trend suggests that regulatory efforts can further reduce Hg emissions and environmental repercussions. Moreover, the observation of higher historical Hg concentrations in tree rings, particularly near the CPPs, may indicate that trees acted as sinks for atmospheric Hg. Although there is still no global consensus on whether forests serve as sources or sinks of Hg, the results of this study suggest the potential for managing trees near pollution sources as a means to address air pollution.
In conclusion, although this study provides initial insights into the impact of coal-fired power plants on Hg levels in adjacent forests, it underscores the importance of diligent environmental stewardship. Advocating a precautionary stance, this study calls for augmented research and policy initiatives to address the potential hazards of Hg pollution. Achieving a balance between industrial development and environmental conservation remains a paramount challenge, necessitating unified efforts in research, regulation, and community involvement to secure a sustainable future.

Author Contributions

Conceptualization, B.C., S.L. and Y.A.; methodology, B.C. and Y.A.; software, E.H., I.K. and Y.A.; validation, Y.A., E.H. and B.C.; formal analysis, E.H., I.K. and Y.A.; investigation E.H. and I.K.; resources, B.C. and H.C.; data curation, B.C., I.K., Y.A. and E.H.; writing—original draft preparation, E.H., I.K. and Y.A.; writing—review and editing, B.C., H.C. and S.L.; visualization, E.H. and I.K.; supervision, B.C.; project administration, B.C., H.C. and S.L.; funding acquisition, B.C., S.L. and H.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.

Acknowledgments

This research was supported by the project titled “Climate impact studies in the vicinity of coal-fired power plants” of the ChungNam Institute funded by Chungcheongnam-do.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Byoungkoo Choi and Young Sang Ahn report financial support provided by Chungcheongnam-do. Byoungkoo Choi and Young Sang Ahn report a relationship with Chungcheongnam-do that includes funding grants. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A

Table A1. Basic information on the study sites near the coal power plants (CPPs) at Chungcheongnam-do according to distance from the plant. Overview of the distribution of tree ring and soil Hg concentration.
Table A1. Basic information on the study sites near the coal power plants (CPPs) at Chungcheongnam-do according to distance from the plant. Overview of the distribution of tree ring and soil Hg concentration.
AreaPoint SourceDistance from Point Source
(km)		Hg Concentration (ng/g)
Tree RingSoil
CPPA1CPP1110.7 ± 0.6183.3 ± 30.6
510.8 ± 0.5116.7 ± 58.6
1510.1 ± 0.473.3 ± 25.2
2510.4 ± 0.583.3 ± 15.3
308.4 ± 0.5126.7 ± 32.1
Average10.1 ± 0.2116.7 ± 50.1
CPPA2CPP2510.5 ± 0.5100 ± 20
59.9 ± 0.570 ± 20
1511.1 ± 0.5120 ± 52.9
1510.1 ± 0.5133.3 ± 5.8
2510.3 ± 0.493.3 ± 45.1
2511.7 ± 0.693.3 ± 57.7
306.9 ± 0.1146.7 ± 11.5
Average10.1 ± 0.2108.1 ± 39.3
CPPA3CPP3511.1 ± 0.6113.3 ± 20.8
511.2 ± 0.580 ± 10
2511.6 ± 0.686.7 ± 40.4
3010.4 ± 0.553.3 ± 15.3
Average11.1 ± 0.383.3 ± 30.6
CPPA4CPP4110 ± 0.583.3 ± 20.8
1513.3 ± 0.373.3 ± 35.1
258.2 ± 0.6123.3 ± 45.1
307.3 ± 0.190 ± 17.3
307 ± 0.266.7 ± 5.8
Average8.9 ± 0.287.3 ± 31.5
INDAAsan National
Industrial complex		110.8 ± 0.5193.3 ± 5.8
206.9 ± 0.273.3 ± 35.1
Average8.7 ± 0.3133.3 ± 69.5
C1--1.3 ± 055 ± 5
C2--7.6 ± 0.2-
Total average9.6 ± 0.1101.3 ± 44.1

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Figure 1. Location map of sampling sites in Chungcheongnam-do. Wind rose pattern represents wind levels in Chungcheongnam-do from 1997–2022. Wind rose pattern represents wind levels in Chungcheongnam-do from 1997–2022 at (a) around the coal-fired power plant 1 (CPP1) and CPP2, (b) around the CPP3, (c) around the CPP4, and (d) around the industrial complexes (IND).
Figure 1. Location map of sampling sites in Chungcheongnam-do. Wind rose pattern represents wind levels in Chungcheongnam-do from 1997–2022. Wind rose pattern represents wind levels in Chungcheongnam-do from 1997–2022 at (a) around the coal-fired power plant 1 (CPP1) and CPP2, (b) around the CPP3, (c) around the CPP4, and (d) around the industrial complexes (IND).
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Figure 2. Tree ring Hg concentrations in the environs of coal-fired power plants (CPP), areas estimated to be affected by industrial complexes, and control (C1 and C2) from 1971 to 2020. Wind rose pattern represents wind levels in Chungcheongnam-do from 1997–2022 at (a) around CPP1 and CPP2, (b) around CPP3, and (c) around CPP4. The exact location of the meteorological station from which the weather data used for the wind rose was obtained can be referenced in Figure 1.
Figure 2. Tree ring Hg concentrations in the environs of coal-fired power plants (CPP), areas estimated to be affected by industrial complexes, and control (C1 and C2) from 1971 to 2020. Wind rose pattern represents wind levels in Chungcheongnam-do from 1997–2022 at (a) around CPP1 and CPP2, (b) around CPP3, and (c) around CPP4. The exact location of the meteorological station from which the weather data used for the wind rose was obtained can be referenced in Figure 1.
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Figure 3. Tree ring Hg concentrations by year from 1971 to 2020 at research sites categorized as CPPA, INDA, and control as a function of year with ordinal variable. CPPA includes all of CPPA1 through 4, and control includes C1 and C2. * represents significant differences of tree ring Hg concentrations among categorized research sites at p ≤ 0.05.
Figure 3. Tree ring Hg concentrations by year from 1971 to 2020 at research sites categorized as CPPA, INDA, and control as a function of year with ordinal variable. CPPA includes all of CPPA1 through 4, and control includes C1 and C2. * represents significant differences of tree ring Hg concentrations among categorized research sites at p ≤ 0.05.
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Figure 4. Tree ring Hg concentrations (from 1971 to 2020) within each coal-fired power plant-influenced area (CPPA) by distance from coastline (#DCL) and distance from coal-fired power plants (DCP#). The color and pattern of the bars are different for each CPPA. Different letters represent significant difference of tree ring Hg concentration within each CPPA at *** p < 0.01.
Figure 4. Tree ring Hg concentrations (from 1971 to 2020) within each coal-fired power plant-influenced area (CPPA) by distance from coastline (#DCL) and distance from coal-fired power plants (DCP#). The color and pattern of the bars are different for each CPPA. Different letters represent significant difference of tree ring Hg concentration within each CPPA at *** p < 0.01.
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Figure 5. Tree ring Hg concentrations from 1971 to 2020, depending on the operating status of the coal-fired power plants (CPPs) involved in each coal-fired power plant-influenced area (CPPA).
Figure 5. Tree ring Hg concentrations from 1971 to 2020, depending on the operating status of the coal-fired power plants (CPPs) involved in each coal-fired power plant-influenced area (CPPA).
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Figure 6. (a) Geoaccumulation Index (Igeo) and (c) Potential Ecological Risk Index (Er) for each research site. (b) Igeo and (d) Er by distance from the CPP at the sampling sites within CPPA.
Figure 6. (a) Geoaccumulation Index (Igeo) and (c) Potential Ecological Risk Index (Er) for each research site. (b) Igeo and (d) Er by distance from the CPP at the sampling sites within CPPA.
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Table 1. Operational and technical details of coal-fired power plants (CPPs).
Table 1. Operational and technical details of coal-fired power plants (CPPs).
Online aOffline bPlant Equipment NumberFacility Capacity (MW)Fuel Type
TotalDetail
CPP11999-106040(500 MW × 8) + (1020 × 2)Bituminous coal
CPP21995-116446.33(500 MW × 8) + (1050 × 2) + (346.33 × 1)Bituminous coal
CPP3 *1983-63050(500 MW × 5) + (550 MW × 1)Bituminous coal
2017-220001000 MW × 2Bituminous coal
CPP4 *19832017220001000 MW × 2Anthracite coal
2021-110181018 MW × 1Bituminous coal
* CPP3 and CPP4 each include both older and newer units. a indicates the initial operational start date of each CPP. b indicates the complete decommissioning date of all plant equipment.
Table 2. Statistical significance probability values for the effect of year and the presence and type of pollution source on tree ring Hg concentrations across the entire research site (from 1971 to 2019) from analysis of covariance (ANCOVA) using general linear models (GLM). The covariate was the detail division of the research site (CPPA1, CPPA2, CPPA3, CPPA4, INDA, C1, C2).
Table 2. Statistical significance probability values for the effect of year and the presence and type of pollution source on tree ring Hg concentrations across the entire research site (from 1971 to 2019) from analysis of covariance (ANCOVA) using general linear models (GLM). The covariate was the detail division of the research site (CPPA1, CPPA2, CPPA3, CPPA4, INDA, C1, C2).
DependentTree Ring Hg Concentration
FPr > |F|
Pollution source (P) a12.0580.000
  Year (Y) b6.2030.000
  P × Y2.1930.026
a The years were categorized into decades, resulting in the following groups: 1970s, 1980s, 1990s, 2000s, and 2010s. b The pollution sources were categorized into three groups: areas influenced by coal power plants (CPPA), areas influenced by industrial complexes (INDA), and background concentration areas (C1 and C2).
Table 3. Statistical significance probability values for the effect of dependent variables on tree ring Hg concentrations at coal-fired power plant-influenced area (CPPA from 1971 to 2020) from analysis of covariance (ANCOVA) using general linear models (GLM). The covariate was the individual coal-fired power plant-influenced area (CPPA1, CPPA2, CPPA3, CPPA4).
Table 3. Statistical significance probability values for the effect of dependent variables on tree ring Hg concentrations at coal-fired power plant-influenced area (CPPA from 1971 to 2020) from analysis of covariance (ANCOVA) using general linear models (GLM). The covariate was the individual coal-fired power plant-influenced area (CPPA1, CPPA2, CPPA3, CPPA4).
DependentTree Ring Hg Concentration
FPr > |F|
CPP online (C) a0.5050.478
  C × DCP0.9530.433
  C × Y0.2300.795
  C × DCP × Y0.7100.400
Distance from CPP (DCP)7.6510.000
  DCP × Y0.7170.779
Distance from coastal line (DCL)7.5490.000
  DCL × C0.6860.561
  DCL × DCP1.6920.167
  DCL × Y1.2510.243
  DCL × C × DCP0.0800.778
  DCL × C × Y0.0170.896
  DCL × DCP × Y0.1610.999
Year (Y) b3.5180.007
a CPP online is categorized into active and inactive based on when the first unit of the coal-fired power plant (CPP) corresponding to when each CPPA was first operationalized. b The years are categorized into decades, resulting in the following groups: 1970s, 1980s, 1990s, 2000s, and 2010s.
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Ha, E.; Kim, I.; Chae, H.; Lee, S.; Ahn, Y.; Choi, B. Spatiotemporal Distribution of Mercury in Tree Rings and Soils Within Forests Surrounding Coal-Fired Power Plants. Atmosphere 2024, 15, 1287. https://doi.org/10.3390/atmos15111287

AMA Style

Ha E, Kim I, Chae H, Lee S, Ahn Y, Choi B. Spatiotemporal Distribution of Mercury in Tree Rings and Soils Within Forests Surrounding Coal-Fired Power Plants. Atmosphere. 2024; 15(11):1287. https://doi.org/10.3390/atmos15111287

Chicago/Turabian Style

Ha, Eugene, Ikhyun Kim, Heemun Chae, Sangsin Lee, Youngsang Ahn, and Byoungkoo Choi. 2024. "Spatiotemporal Distribution of Mercury in Tree Rings and Soils Within Forests Surrounding Coal-Fired Power Plants" Atmosphere 15, no. 11: 1287. https://doi.org/10.3390/atmos15111287

APA Style

Ha, E., Kim, I., Chae, H., Lee, S., Ahn, Y., & Choi, B. (2024). Spatiotemporal Distribution of Mercury in Tree Rings and Soils Within Forests Surrounding Coal-Fired Power Plants. Atmosphere, 15(11), 1287. https://doi.org/10.3390/atmos15111287

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