Risk Assessments of Plant Leaf and Soil Mercury Pollution in Different Functional Areas of Changchun City
Abstract
:1. Introduction
- (1)
- To examine the characteristics of mercury emissions in the leaves of broad-leaved forested areas in industrial cities (taking Changchun as an example), and to further explore the total content of mercury emissions in plants across one year through the mechanism of deciduous leaves, while exploring the differences in the mercury emission characteristics of different tree species.
- (2)
- To investigate and analyze the factors affecting the enrichment of leaf mercury and the sources of environmental mercury pollution, providing a scientific basis for the prevention and control of urban mercury pollution.
- (3)
- To assess the ecological risks of the mercury pollution levels in each region.
2. Materials and Methods
2.1. Study Area
2.2. Sample Collection
2.2.1. Sample Point Settings and Types of Sample Points
2.2.2. Collection of Deciduous Tree Samples and Soil Samples
2.2.3. Sample Pretreatments
2.3. Sample Analysis
2.4. Ecological Risk Assessment Processes
2.4.1. Geo-Accumulation Index (Igeo)
2.4.2. Potential Ecological Risk Index (Er)
3. Results
3.1. Concentration Levels of Mercury in Fallen Leaves
3.1.1. Concentration Levels of Mercury among the Different Land-Use Types
3.1.2. Mercury Concentrations in the Fallen Leaves of the Different Tree Species
3.2. Mercury Concentrations in the Soil
3.2.1. Mercury Concentrations in the Soil
3.2.2. Values of the pH and Soil Organic Matter
3.2.3. Soil Mercury Concentrations in the Different Functional Regions
3.3. Ecological Risk Assessment of Soil Mercury Pollution
4. Discussion
4.1. Factors Influencing Mercury Concentration Levels in Leaves
4.1.1. Effects of the Different Land-Use Types on Leaf Mercury Concentrations
4.1.2. Effects of Different Plant Types on Deciduous Mercury Concentrations
4.2. Factors Influencing the Soil Mercury Content Levels
Effects of the Different Land-Use Types on Soil Mercury Concentrations
4.3. Relationships between the Deciduous Mercury, Soil Mercury, and Atmospheric Mercury
4.4. Risk Assessments
4.4.1. Evaluation of Soil Mercury Pollution Levels in Changchun City through the Geo-Accumulation Index (Igeo)
4.4.2. Evaluation of Soil Mercury Pollution Levels in Changchun City Using the Potential Ecological Risk Index (Er)
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Er | <40 | 40 to 80 | 80 to 160 | 160 to 320 | >320 |
---|---|---|---|---|---|
Potential ecological risk index | Slight | Medium | Strong | Very strong | Extremely strong |
Land-Use Type | Number of Effective Cases | Maximum | Minimum | Average | Standard Deviation |
---|---|---|---|---|---|
W | 2 | 0.0283 | 0.0277 | 0.028 | 0.0004 |
B | 15 | 0.075 | 0.0241 | 0.0388 | 0.0117 |
R | 51 | 0.0906 | 0.0189 | 0.0409 | 0.0136 |
G | 114 | 0.0906 | 0.0155 | 0.041 | 0.0156 |
A | 53 | 0.1945 | 0.0133 | 0.0463 | 0.0298 |
S | 15 | 0.0868 | 0.0245 | 0.0487 | 0.0177 |
M | 5 | 0.0822 | 0.0215 | 0.0504 | 0.025 |
Plant Type | Number of Effective Cases | Maximum | Minimum | Average | Standard Deviation |
---|---|---|---|---|---|
Populus alba | 6 | 0.0359 | 0.0261 | 0.0312 | 0.004 |
Quercus mongolica Fisch. ex Ledeb. | 7 | 0.0413 | 0.0279 | 0.0342 | 0.0052 |
Populus tomentosa | 28 | 0.1494 | 0.0201 | 0.0347 | 0.0233 |
Salix babylonica | 1 | 0.0349 | 0.0349 | 0.0349 | 0 |
Populus pseudo-simonii Kitag. | 32 | 0.062 | 0.0162 | 0.0353 | 0.0112 |
Salix matsudana | 3 | 0.0433 | 0.0316 | 0.0357 | 0.0066 |
canadensis Moench | 37 | 0.1945 | 0.0133 | 0.0363 | 0.0285 |
willow | 41 | 0.0585 | 0.0197 | 0.0382 | 0.0092 |
Acer pictum Thunb. ex Murray | 10 | 0.0594 | 0.02 | 0.0392 | 0.0128 |
Acer ginnala Maxim. | 4 | 0.0663 | 0.0315 | 0.0429 | 0.016 |
Toxicodendronsuccedaneum (L.) O. Kuntze | 9 | 0.056 | 0.033 | 0.044 | 0.0092 |
Prunus salicina Lindl. | 4 | 0.0504 | 0.0427 | 0.0463 | 0.0037 |
Ulmus pumila L. | 23 | 0.0868 | 0.0275 | 0.048 | 0.0145 |
Armeniaca vulgaris Lam. | 7 | 0.0628 | 0.033 | 0.0499 | 0.0124 |
Catalpa ovata G. Don | 3 | 0.0641 | 0.0436 | 0.0558 | 0.0108 |
Armeniaca mandshurica (Maxim.) Skv. | 4 | 0.0637 | 0.0462 | 0.0567 | 0.0085 |
Malus baccata | 12 | 0.0765 | 0.0267 | 0.0567 | 0.0129 |
Padus virginiana ‘Canada Red’ | 6 | 0.0842 | 0.0436 | 0.0591 | 0.0165 |
Fraxinus mandshurica Rupr. | 7 | 0.0906 | 0.0415 | 0.0645 | 0.0181 |
Padus racemosa (Lam.) Gilib. | 6 | 0.0906 | 0.0478 | 0.0666 | 0.0156 |
Pyrus ussuriensis Maxim. | 5 | 0.0896 | 0.0393 | 0.0755 | 0.0213 |
Maximum | Minimum | Average | Median | Max/Min | Background |
---|---|---|---|---|---|
4.2967 | 0.0183 | 0.1732 | 0.074 | 236.082 | 0.0400 |
City | Range | Average | Background | References |
---|---|---|---|---|
Chongqing | 0.060–3.881 | 0.319 | 0.040 | [41] |
Beijing | 0.010–0.966 | 0.278 | 0.058 | [42] |
Guangzhou | 0.013–12.231 | 0.614 | 0.157 | [43] |
Taiyuan | 0.040–0.297 | 0.105 | 0.098 | [44] |
Tibet | Unknown–0.056 | 0.026 | 0.021 | [45,46] |
Urumqi | 0.012–0.176 | 0.062 | 0.055 | [47] |
Nanjing | 0.041–8.090 | 0.043 | 0.025 | [48] |
Ningbo | 0.010–0.565 | 0.103 | 0.143 | [49] |
Guiyang | 0.010–7.030 | 0.222 | - | [50] |
Guilin | 0.136–1.873 | 0.557 | 0.150 | [51] |
Lanzhou | Unknown–0.117 | -- | 0.150 | [52] |
Zhaoyuan | 0.002–0.815 | 0.149 | 0.019 | [53] |
Qingdao | 0.004–0.259 | 0.081 | - | [54] |
Land-Use Type | Number of Effective Cases | Maximum | Minimum | Average | Standard Deviation |
---|---|---|---|---|---|
A | 18 | 0.5707 | 0.0217 | 0.0971 | 0.13463 |
B | 7 | 0.1467 | 0.0190 | 0.0782 | 0.05154 |
G | 38 | 0.2610 | 0.0183 | 0.0874 | 0.54540 |
M | 2 | 4.2967 | 0.0713 | 2.1840 | 2.32117 |
R | 17 | 2.0733 | 0.0310 | 0.2767 | 0.54144 |
S | 5 | 0.1257 | 0.0537 | 0.0850 | 0.02750 |
W | 1 | - | - | 0.0643 | 0.00723 |
Land-Use Type (I) | Land-Use Type (J) | Mean Difference (I–J) | Std. Error | Sig. | 95% Confidence Interval | |
---|---|---|---|---|---|---|
Lower Bound | Upper Bound | |||||
A | B | 0.0189 | 0.11285 | 0.867 | −0.2034 | 0.1210 |
G | 0.0097 | 06934.0 | 0.889 | −0.1268 | 0.1463 | |
M | −2.0869 * | 017765 | 0.000 | −2.4368 | −1.7370 | |
R | −0.1796 * | 0.08277 | 0.031 | −0.3426 | −0.0165 | |
S | 0.0121 | 0.12090 | 0.920 | −0.2260 | 0.2502 | |
W | 0.0328 | 0.24453 | 0.894 | −0.4489 | 0.5144 | |
B | A | −0.0189 | 0.11285 | 0.867 | −0.2411 | 0.2034 |
G | −0.0091 | 0.10439 | 0.930 | −0.2148 | 0.1965 | |
M | −2.1058 * | 0.19403 | 0.000 | −2.4879 | −1.7236 | |
R | −0.1984 | 0.11376 | 0.082 | −0.4225 | 0.0256 | |
S | −0.0068 | 0.14390 | 0.962 | −0.2902 | 0.2766 | |
W | 0.0139 | 0.25668 | 0.957 | −0.4917 | 0.5194 | |
G | A | −0.0097 | 0.05934 | 0.889 | −0.1463 | 0.1268 |
B | 0.0091 | 0.10439 | 0.930 | −0.1965 | 0.2148 | |
M | −2.0966 * | 0.17240 | 0.000 | −2.4362 | −1.7571 | |
R | −0.1893 * | 0.09082 | 0.008 | −0.3288 | −0.0498 | |
S | 0.0024 | 0.11305 | 0.983 | −0.2203 | 0.2250 | |
W | 0.0230 | 0.24075 | 0.924 | −0.4511 | 0.4972 | |
M | A | 2.0869 * | 0.17765 | 0.000 | 1.7270 | 2.4368 |
B | 2.1058 * | 0.19403 | 0.000 | 1.7236 | 2.4879 | |
G | 2.0966 * | 0.17240 | 0.000 | 1.7571 | 2.4362 | |
R | 1.9073 * | 0.17823 | 0.000 | 1.5563 | 2.2584 | |
S | 2.0090 * | 0.19882 | 0.000 | 1.7074 | 2.4906 | |
W | 2.1197 * | 0.19105 | 0.000 | 1.5464 | 2.6929 | |
R | A | 0.1796 * | 0.08277 | 0.031 | 0.0165 | 0.3426 |
B | 0.1984 | 0.11376 | 0.082 | −0.0256 | 0.4225 | |
G | 0.1893 * | 0.07082 | 0.008 | 0.0498 | 0.3288 | |
M | −1.9073 * | 0.17823 | 0.000 | −2.2584 | −1.5563 | |
S | 0.1917 | 0.12175 | 0.117 | −0.0481 | 0.4315 | |
W | 0.2123 | 0.24495 | 0.387 | −0.2701 | 0.6948 | |
S | A | −0.121 | 0.12090 | 0.920 | −0.2502 | 0.2260 |
B | 0.0068 | 0.14390 | 0.962 | −0.2766 | 0.2902 | |
G | −0.0024 | 0.11305 | 0.983 | −0.2250 | 0.2203 | |
M | −2.0990 * | 0.19882 | 0.000 | −2.4906 | −1.7074 | |
R | −0.1917 | 0.12175 | 0.117 | −0.4315 | 0.0481 | |
W | 0.0207 | 0.26032 | 0.937 | −0.4921 | 0.5334 | |
W | A | −0.0328 | 0.24453 | 0.894 | −0.5114 | 0.4489 |
B | −0.0139 | 0.25668 | 0.957 | −0.5194 | 0.4917 | |
G | −0.0230 | 0.24075 | 0.924 | −0.4972 | 0.4511 | |
M | −2.1197 * | 0.29105 | 0.000 | −2.6929 | −1.5464 | |
R | −0.2123 | 0.24495 | 0.387 | −0.6948 | 0.2701 | |
S | −0.0207 | 0.26032 | 0.937 | −0.5334 | 0.4921 |
Land-Use Type | Number of Effective Cases | Pearson Correlation | Sig (2-Tailed) |
---|---|---|---|
A | 51 | 0.339 * | 0.015 |
B | 18 | 0.124 | 0.624 |
G | 114 | 0.235 * | 0.012 |
M | 6 | −0.997 ** | 0.000 |
R | 48 | −0.118 | 0.426 |
S | 15 | 0.643 ** | 0.010 |
W | 3 | c |
Land-Use Type | No Pollution | Light Pollution | Near Moderate Pollution | Moderate Pollution | Near Heavy Pollution | Heavy Pollution | Serious Pollution |
---|---|---|---|---|---|---|---|
A | 4 | 4 | 7 | 0 | 1 | 1 | 0 |
G | 3 | 6 | 20 | 6 | 2 | 0 | 0 |
R | 0 | 6 | 6 | 3 | 0 | 0 | 2 |
W | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
S | 0 | 1 | 3 | 1 | 0 | 0 | 0 |
B | 1 | 2 | 1 | 2 | 0 | 0 | 0 |
M | 0 | 0 | 1 | 0 | 0 | 0 | 1 |
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Pan, J.; Chen, M.; Zhang, Z.; Zhang, H.; Zong, J.; Wang, Z.; Zhang, G. Risk Assessments of Plant Leaf and Soil Mercury Pollution in Different Functional Areas of Changchun City. Forests 2023, 14, 1108. https://doi.org/10.3390/f14061108
Pan J, Chen M, Zhang Z, Zhang H, Zong J, Wang Z, Zhang G. Risk Assessments of Plant Leaf and Soil Mercury Pollution in Different Functional Areas of Changchun City. Forests. 2023; 14(6):1108. https://doi.org/10.3390/f14061108
Chicago/Turabian StylePan, Jiafang, Ming Chen, Zhe Zhang, Hongjie Zhang, Jing Zong, Zhaojun Wang, and Gang Zhang. 2023. "Risk Assessments of Plant Leaf and Soil Mercury Pollution in Different Functional Areas of Changchun City" Forests 14, no. 6: 1108. https://doi.org/10.3390/f14061108
APA StylePan, J., Chen, M., Zhang, Z., Zhang, H., Zong, J., Wang, Z., & Zhang, G. (2023). Risk Assessments of Plant Leaf and Soil Mercury Pollution in Different Functional Areas of Changchun City. Forests, 14(6), 1108. https://doi.org/10.3390/f14061108