| Literature DB >> 36141529 |
Bingyan Jin1, Jinling Wang1, Wei Lou1, Liren Wang1, Jinlong Xu1, Yanfang Pan1,2, Jianbiao Peng3, Dexin Liu1,2,4.
Abstract
Rivers in urban environments are significant components of their ecosystems but remain under threat of pollution from unchecked discharges of industrial sewage and domestic wastewater. Such river pollution, particularly over the longer term involving heavy metals, is an issue of worldwide concern regarding risks to the ecological environment and human health. In this study, we investigate the long-term pollution characteristics of the Huafei River, an important urban river in Kaifeng, China. River sedimentary samples were analyzed, assessing the degree and ecological risk of heavy metal pollution using the geo-accumulation index and potential ecological risk index methods, whilst Pearson's correlation, principal component and cluster analyses were used to identify the sources of pollution. The results show that heavy metal concentrations are significantly higher than their corresponding fluvo-aquic soil background values in China, and the geo-accumulation indexes indicate that of the eight heavy metals identified, Hg is most prevalent, followed in sequence by Cd > Zn > Cu > Pb > Ni > As > Cr. The potential ecological risk index of the Huafei River is very high, with the potential ecological risk intensity highest in the midstream and downstream sections, where it is recommended that pollution control is carried out, especially concerning Hg and Cd. Long-term sequence analysis indicates that Cu and Pb dropped sharply from 1998 to 2017, but rebounded in 2019, and that Zn shows a continuous decreasing trend. Four main sources for the heavy metal contaminants were identified: Cr, Cu, Ni, Pb, Zn and Hg derived mainly from industrial activities, traffic sources and natural sources; Cd originated mainly from industrial and agricultural activities; whilst As was mainly associated with industrial activities. Thus, special attention should be paid to Hg and Cd, and measures must be taken to prevent further anthropogenic influence on heavy metal pollution.Entities:
Keywords: ecological risk; heavy metal; pollution characteristics; river sediments; sources identification
Mesh:
Substances:
Year: 2022 PMID: 36141529 PMCID: PMC9517487 DOI: 10.3390/ijerph191811259
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Figure 1Sampling location map of the study area.
The geo-accumulation index classification standard.
| The Geo-Accumulation Index ( | Class | Pollution Level |
|---|---|---|
| 0 | Unpolluted | |
| 0 < | 1 | From unpolluted to moderately polluted |
| 1 < | 2 | Moderately polluted |
| 2 < | 3 | From moderately to strongly polluted |
| 3 < | 4 | Strongly polluted |
| 4 < | 5 | From strongly to extremely polluted |
| 6 | Extremely polluted |
The adjusted and RI classification standards.
|
| Ecological Risk Levels of a Single Metal | Ecological Risk Levels to the Environment | |
|---|---|---|---|
| <40 | Low ecological risk | <110 | Low ecological risk |
| 40~80 | Moderate ecological risk | 110~220 | Moderate ecological risk |
| 80~160 | Considerable ecological risk | 220~440 | Considerable ecological risk |
| 160~320 | High ecological risk | ≥440 | Very high ecological risk |
| ≥320 | Very high ecological risk |
Descriptive statistics of physical and chemical properties of the surface sediments from the Huafei River.
| pH | TN (mg·kg−1) | TP (mg·kg−1) | OM (mg·kg−1) | |
|---|---|---|---|---|
| Average | 7.73 | 2089.76 | 786.58 | 5932.59 |
| Maximum | 8.23 | 5401.84 | 1496.07 | 13,122.10 |
| Minimum | 7.31 | 587.65 | 344.81 | 472.63 |
Descriptive statistics of heavy metal concentrations (mg·kg−1).
| As | Cd | Cr | Cu | Hg | Ni | Pb | Zn | |
|---|---|---|---|---|---|---|---|---|
| Average | 26.62 | 50.76 | 97.08 | 292.37 | 10.01 | 50.13 | 238.59 | 1335.12 |
| Median | 9.55 | 11.72 | 102.05 | 137.23 | 3.20 | 43.61 | 95.32 | 523.95 |
| Maximum | 100.04 | 371.47 | 160.97 | 866.90 | 56.92 | 101.35 | 745.76 | 4206.97 |
| Minimum | 4.91 | 0.15 | 23.13 | 7.70 | 0.40 | 11.33 | 2.80 | 50.00 |
| SD | 30.18 | 89.11 | 31.23 | 275.65 | 13.68 | 21.51 | 262.88 | 1394.02 |
| CV(%) | 113 | 176 | 32 | 94 | 137 | 43 | 110 | 104 |
| Background of Chinese fluvo-aquic soil | 9.30 | 0.09 | 64.81 | 22.90 | 0.032 | 28.10 | 20.60 | 67.80 |
Figure 2The concentrations of heavy metals in the sediments from the Huafei River.
Figure 3Geo-accumulation indexes level distribution of heavy metals in sediments from the Huafei River. Note: 0: Unpolluted. 1: From unpolluted to moderately polluted. 2: Moderately polluted. 3: From moderately to strongly polluted. 4: Strongly polluted. 5: From strongly to extremely polluted. 6: Extremely polluted.
The potential ecological risk indexes of heavy metals in sediments from the Huafei River.
| Samping Points | Cd | Cr | Cu | Ni | Pb | Zn | Hg | As |
| |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 83.42 | 1.22 | 4.31 | 3.81 | 2.02 | 2.24 | 652.60 | 9.72 | 759.34 | Very high |
| 2 | 163.88 | 0.71 | 1.68 | 2.02 | 0.68 | 0.74 | 1060.19 | 5.73 | 1235.63 | Very high |
| 3 | 50.47 | 2.36 | 7.34 | 7.41 | 2.49 | 2.46 | 698.61 | 5.66 | 776.81 | Very high |
| 4 | 150.05 | 2.20 | 4.46 | 7.05 | 2.41 | 2.38 | 541.47 | 5.29 | 715.30 | Very high |
| 5 | 123,823.82 | 2.96 | 99.71 | 8.50 | 79.91 | 25.53 | 9290.63 | 7.34 | 133,338.38 | Very high |
| 6 | 26,556.22 | 3.11 | 98.52 | 10.63 | 97.04 | 29.96 | 12,124.13 | 5.69 | 38,925.30 | Very high |
| 7 | 87,100.00 | 3.19 | 132.64 | 10.52 | 122.45 | 31.24 | 12,199.62 | 20.86 | 99,620.51 | Very high |
| 8 | 1545.36 | 1.42 | 13.61 | 4.91 | 10.53 | 4.21 | 1485.98 | 18.67 | 3084.70 | Very high |
| 9 | 22,482.55 | 3.72 | 130.39 | 13.08 | 150.52 | 49.50 | 28,908.59 | 5.65 | 51,744.02 | Very high |
| 10 | 28,851.26 | 4.11 | 155.27 | 14.34 | 178.78 | 61.56 | 71,146.54 | 5.28 | 100,417.14 | Very high |
| 11 | 27,645.11 | 3.91 | 124.38 | 13.47 | 158.43 | 62.05 | 33,870.61 | 5.69 | 61,883.64 | Very high |
| 12 | 3213.45 | 2.88 | 19.91 | 7.96 | 21.12 | 8.46 | 4638.47 | 7.33 | 7919.60 | Very high |
| 13 | 4395.60 | 3.36 | 11.48 | 6.88 | 18.08 | 7.57 | 7937.35 | 13.04 | 12,393.36 | Very high |
| 14 | 3416.67 | 3.49 | 38.96 | 8.45 | 26.54 | 12.42 | 12,375.63 | 6.17 | 15,888.32 | Very high |
| 15 | 17,298.11 | 3.55 | 172.19 | 15.95 | 134.31 | 42.64 | 31,768.86 | 6.69 | 49,442.29 | Very high |
| 16 | 16,201.86 | 3.65 | 108.95 | 11.33 | 94.01 | 27.67 | 17,757.24 | 10.82 | 34,215.53 | Very high |
| 17 | 27,816.55 | 4.97 | 189.28 | 18.03 | 181.01 | 56.57 | 38,051.43 | 82.91 | 66,400.76 | Very high |
| 18 | 4719.18 | 2.35 | 21.34 | 6.35 | 20.27 | 6.44 | 3356.16 | 107.57 | 8239.66 | Very high |
| 19 | 4427.86 | 2.72 | 28.54 | 6.65 | 25.15 | 7.18 | 2574.30 | 31.76 | 7104.16 | Very high |
| 20 | 3154.05 | 2.61 | 27.52 | 6.92 | 32.49 | 6.98 | 2723.45 | 59.18 | 6013.20 | Very high |
| 21 | 482.37 | 2.69 | 27.43 | 7.29 | 8.65 | 7.68 | 2400.77 | 90.72 | 3027.60 | Very high |
| 22 | 1979.37 | 3.55 | 55.97 | 7.92 | 10.54 | 7.78 | 1875.00 | 76.45 | 4016.58 | Very high |
| 23 | 416.25 | 3.84 | 31.39 | 7.60 | 7.57 | 6.54 | 493.95 | 35.10 | 1002.23 | Very high |
| 24 | 99.60 | 3.33 | 26.77 | 7.00 | 4.87 | 2.80 | 2375.63 | 63.58 | 2583.57 | Very high |
| average | 16,919.71 | 3.00 | 63.84 | 8.92 | 57.91 | 19.69 | 12,512.80 | 28.62 | 29,614.48 | Very high |
The amount of each heavy metal at each ecological level.
| Cd | Cr | Cu | Ni | Pb | Zn | Hg | As | |
|---|---|---|---|---|---|---|---|---|
| Low | 24 | 14 | 24 | 15 | 19 | 18 | ||
| Moderate | 1 | 1 | 1 | 5 | 3 | |||
| Considerable | 3 | 7 | 6 | 3 | ||||
| High | 1 | 2 | 2 | |||||
| Very high | 19 | 24 |
Figure 4Change in heavy metal concentrations in the sediment from the Huafei River from 1998 to 2019.
Figure 5The average concentration of heavy metals over the last 20 years.
The correlation coefficients between heavy metals in sediments of the Huafei River.
| Pearson Correlation | Cd | Cr | Cu | Ni | Pb | Zn | Hg | As |
|---|---|---|---|---|---|---|---|---|
| Cd | 1 | |||||||
| Cr | 0.242 | 1 | ||||||
| Cu | 0.539 ** | 0.719 ** | 1 | |||||
| Ni | 0.332 | 0.837 ** | 0.934 ** | 1 | ||||
| Pb | 0.505 * | 0.670 ** | 0.961 ** | 0.910 ** | 1 | |||
| Zn | 0.446 * | 0.689 ** | 0.933 ** | 0.907 ** | 0.985 ** | 1 | ||
| Hg | 0.267 | 0.627 ** | 0.819 ** | 0.819 ** | 0.883 ** | 0.908 ** | 1 | |
| As | −0.204 | 0.136 | −0.093 | −0.046 | −0.181 | −0.188 | −0.197 | 1 |
Note: * At the 0.05 significance level; ** At the 0.01 significance level.
Rotated component matrix of factor loading.
| Elements | 1 | 2 | 3 |
|---|---|---|---|
| Cd | 0.221 |
| −0.098 |
| Cr |
| 0.062 | 0.294 |
| Cu |
| 0.368 | −0.022 |
| Ni |
| 0.134 | 0.042 |
| Pb |
| 0.313 | −0.140 |
| Zn |
| 0.239 | −0.153 |
| Hg |
| 0.029 | −0.209 |
| As | −0.050 | −0.095 |
|
| Eigenvalue (total) | 5.038 | 1.253 | 1.122 |
| % of total variance | 62.974 | 15.659 | 14.020 |
| % of cumulative | 62.974 | 78.633 | 92.653 |
Figure 6Plot of loading of three principal components in PCA results.
Figure 7Cluster analysis heat map of heavy metals in sediments from the Huafei River.
Heavy metal concentrations in sediment samples from the Huafei River and other selected rivers from the references (mg·kg−1).
| As | Cd | Cr | Cu | Hg | Ni | Pb | Zn | Reference | |
|---|---|---|---|---|---|---|---|---|---|
| Huafei River, China | 26.62 | 50.76 | 97.08 | 292.37 | 10.01 | 50.13 | 238.59 | 1335.12 | This study |
| Wen-Rui Tang River, China | 17.7 | 193 | 310 | 115 | 1362 | Xia et al. [ | |||
| Shiqiao River, China | 2.79 | 133 | 100 | 66 | 96 | 327 | Xiao et al. [ | ||
| Buriganga River, Bangladesh | 19.25 | 7.29 | 1399 | 61.86 | 50.00 | 68.36 | 54.54 | Bhuiyan et al. [ | |
| Kabini River, India | 254,520 | 110,550 | 91,120 | 11,670 | Hejabi et al. [ | ||||
| Huangbian River, China | 7.49 | 0.35 | 46.46 | 30.09 | 22.71 | 24.12 | 90.30 | Yang [ | |
| Majia River, China | 12.58 | 0.33 | 64.85 | 26.21 | 21.10 | 20.69 | 114.05 | Yang [ | |
| Liaohe River, China | 9.88 | 1.20 | 35.06 | 17.82 | 17.73 | 10.57 | 50.24 | Ke et al. [ | |
| Hunza River, Pakistan | 1.11 | 62.3 | 36.4 | 52.6 | 14.9 | 54.3 | Kashif et al. [ | ||
| Brisbane River, Australia | 3.9 | 0.3 | 15 | 29 | 0.4 | 15.3 | 25.6 | 106.6 | Duodu et al. [ |