Assessment of environmetntal pollution levels and forecast of changes in some heavy metals and grease in sediment of Nam Cau Trang Port cluster - Quang Ninh Province
| Meeting | VIWC2026 |
| Topic | OS3: Water Environment and Mining |
| Author | Phuong Nguyen | Cuc Thi Nguyen | Lan Anh Thi Vu | Dong Phuong Nguyen | Hoang Hai Yen |
| Organization | General Association of Geology of Vietnam | Ha Noi University of Mining and Geology, Viet Nam | Ha Noi University of Mining and Geology, Viet Nam | Ha Noi University of Mining and Geology, Viet Nam | Mining and Geology Construction and Technology Deployment Consulting Company |
| ID | 2022.1672454426 |
Content
- Introduction
Population growth and industrial, urban, and tourism growth have significantly increased pollution emissions, causing direct pressure on the natural environment and a significant impact on biodiversity and porcelain, healthy community, including NCT Port Cluster area.
Therefore, the assessing the current situation and forecasting environmental changes; The focus is on heavy metal and oil elements in seawater and coastal sediments in Quang Ninh province in general and NCT Port Cluster area in particular, is necessary and important in the orientation of economic - society, ensuring sustainable development goals.
The article introduces several research results on the assessment of the current state and forecasts of environmental changes in the sediments of NCT Port Cluster on the basis of the combined application of statistical models and key factor analysis methods; thereby proposing solutions to prevent and minimize negative impacts from human activities on the environment and measures to improve the efficiency of environmental state management in the NCT Port Cluster, Quang Ninh Province.
- Materials and methods
NCT Port Cluster is located in Hong Ha Ward. Its topography is mainly hilly, limestone mountains (Nui Dam), and earth hills in the North of the ward. The region\'s topography is high in the north and lowers in the south. Due to socio-economic development requirements, a part of the wetlands and tidal flats in the south of the ward have gradually been converted to use purposes into new urban areas.
Population growth and industrial development (including mining activities), and urbanization have been putting direct and increasing pressure on the coastal water and sediment environments. Quang Ninh province in general, NCT port cluster in particular.
The risk of pollution of the quality of seawater and coastal sediments is also due to the operation of fishing villages on the sea as well as wastewater and domestic waste from coastal residential areas that have not been thoroughly controlled.
Pollutants discharged into the study area are often in two main ways, due to the washing of the pollution sources on the mainland through the river, stream, creek system, tide to the bay and directly from the domestic wastewater, coastal residents, tourists, aquaculture, water transport activities, etc.
2.2. Research Methods
2.2.1. Outdoor method
Field survey, collecting documents on the current state of water, soil and air environment at some points in the area of the NCT port cluster in Quang Ninh. The locations of samples collected in sediments NCT Port Cluster, Quang Ninh Province with the analysis results of heavy metals and grease used in the paper are shown in Figure 1.
Figure 1. Sampling location
2.2.2. Collection and synthesis of documents
Collecting and synthesizing documents collected from previous works [2,4]; selecting documents to ensure reliability to handle in order to improve the effectiveness of the assessment of the current environmental situation and forecast the sediment environment fluctuations.
2.2.3. Document handling
a. Statistical method
- One-way statistical method: One-dimensional statistical model allows to describe of the statistical distribution law of certain environmental parameters (indicators).
- Two-dimensional statistical method: The content of heavy metals and grease in sediments often varies greatly by location, possibly close to the natural content or thousands of times higher, depending on the location taken sample and source of pollution. The concentration of heavy metals tends to decrease gradually from shore to sea, from inside the channel to the waterway transport route.
Correlation coefficient reflects the relationship between two environmental parameters (criteria) x, y, denoted by Rxy and is determined by the formula:
(1) In which: xi; yi is the value of parameter x and y in the ith sample (monitoring point); n is the number of samples (points) studied. For highly reliable prediction, the correlation coefficient needs to be large (Rxy ≥ 0.7).
b. Main ingredient analysis method
Assuming each research object (soil, water, air), we only need to consider two main components Y and Z, characteristic of some pollution level out of the m indicator, is enough, i.e. The original document match (Tn´m) only needs two columns and n rows corresponding to n objects (sampling point). Then, if we represent the object on the correlation field with X and Y axis, we can imagine the uniformity level of the object of study. To evaluate the uniformity of the sample set and search for the most important indicators among the m indicators, people often use the analysis of main factors [Nguyen Phuong, Nguyen Quoc Phi (2018)].
Assuming the base matrix T has m columns, that is, there are m symbols x1, x2,... xm and are all centered with a covariance matrix [Sij]mxm, then we find a new variable Y is a linear combination of m initial variables x1, x2,..., xn in the form of the following general equation: (2)
The requirement is to determine the bi coefficients such that variable Y contains the most initial information. In addition, for the variable Y to be unique, the following conditions must be met: (3)
If the symbol p is a vector with components (b1, b2,..., bm), then the vector to be found is called the eigenvector corresponding to the maximum p value of the covariance matrix [Sij]mxm, determined by the equation: (S- ll)p = 0 (4)
Similarly, we consider adding a new variable Z which is a linear combination of the original variables in the form of an equation: (5)
Equation 5 must satisfy the following conditions: It contains many parameters about the original data and satisfies the condition that is the only variable: (6)
The component variable Z must satisfy the orthogonal condition with component Y. Let g be the eigenvectors of the components (c1, c2,..., cm), then the vector is also the eigenvector corresponding to the second eigenvalue of the covariance matrix [Sij]mxm, i.e. was: (S- ll)g = 0 (7)
In general, if the random variable X has m dimensional, the expectation is 0, then the covariance matrix [Sij]mxm has an orthogonal transformation: U = p’X (8)
Such that the variance matrix of U is diagonal with the molecules li is the solution of Equation 8. The Uk= pk’X component is orthogonal and is called the main factor. In addition, the random variable U received through the orthogonal transformation will preserve the variance, that is: s2y + s2z = s2x + s2y = const (9)
Thus, the determinant of the corresponding covariance matrix U is also |S|.
- Results and discussion
The results of the treatment of the statistical characteristics of the content of heavy metals and oil elements in the sediments of NCT port cluster are summarized in Table 1. Table 1. The statistical characteristic parameters of the content of heavy metal elements and oil and grease in the sediments of the NCT port cluster
| Element | Content (mg.kg-1) | Variance (s2) | Coefficient of variation (V%) | QCVN 43:2017 /BTNMT | ||
| Min | Max | Average | ||||
| As | 16.8 | 39.6 | 25.8 | 89.38 | 36.6 | 41.60 |
| Hg | 1.3 | 2.7 | 1.9 | 0.24 | 26.1 | 0.70 |
| Pb | 113.5 | 289.2 | 169.9 | 3612.9 | 35.4 | 112.00 |
| Cd | 0.06 | 0.26 | 0.15 | 0.0058 | 54.6 | 4.20 |
| Grease | 65 | 461 | 205.9 | 17141.7 | 63.6 | - |
| Table 2. Results of calculation of rated component (t) of elements | Table 3. Results of Z value calculation for the Main ingredient | |||||||||
| N0 | As | Hg | Pb | Cd | Grease | As | Hg | Pb | Cd | Grease |
| t1 | t2 | t3 | t4 | t5 | t1 | t2 | t3 | t4 | t5 | |
| 1 | 0.909 | 0.393 | 2.027 | 1.433 | 0.498 | 2.301 | 1.382 | 0.352 | -0.266 | 0.036 |
| 2 | 0.640 | 1.128 | 2.120 | 1.298 | 0.527 | 2.499 | 1.329 | -0.123 | 0.356 | -0.009 |
| 3 | -0.872 | -1.075 | -0.762 | -0.721 | -0.690 | -1.845 | -0.008 | 0.248 | -0.127 | -0.137 |
| 4 | -0.914 | -0.708 | -0.790 | -0.856 | -0.617 | -1.738 | -0.155 | 0.025 | 0.151 | -0.079 |
| 5 | 1.427 | 1.311 | 0.533 | 0.894 | 0.936 | 2.311 | -0.434 | -0.339 | -0.148 | 0.233 |
| 6 | 1.230 | 1.495 | 0.409 | 1.164 | 0.805 | 2.323 | -0.418 | -0.549 | -0.102 | -0.129 |
| 7 | -0.872 | -0.892 | -0.706 | -0.991 | -0.741 | -1.887 | -0.024 | 0.079 | 0.056 | 0.080 |
| 8 | -0.810 | -1.075 | -0.681 | -0.856 | -0.719 | -1.860 | 0.033 | 0.230 | -0.111 | 0.026 |
| 9 | -0.769 | -0.525 | -0.639 | -0.721 | -0.814 | -1.550 | 0.014 | -0.222 | 0.061 | -0.062 |
| 10 | -0.644 | -0.708 | -0.566 | -0.856 | -0.836 | -1.620 | 0.069 | -0.109 | -0.054 | 0.141 |
| 11 | 1.220 | 1.128 | 0.141 | 1.029 | 1.752 | 2.397 | -1.027 | 0.296 | 0.055 | -0.098 |
| 12 | 1.137 | 0.944 | 0.288 | 0.760 | 1.716 | 2.191 | -0.882 | 0.425 | 0.138 | 0.116 |
| 13 | -0.872 | -0.892 | -0.722 | -0.721 | -0.887 | -1.832 | 0.079 | -0.009 | -0.099 | -0.132 |
| 14 | -0.810 | -0.525 | -0.651 | -0.856 | -0.931 | -1.689 | -0.549 | -0.559 | -1.658 | 1.493 |
| | 4.423 | 0.455 | 0.084 | 0.025 | 0.012 | |||||
Figure 2. Position of sampling points on the new coordinate system identified by 2 main components (main indicator) As and Hg In Figure 2, sampling points are divided into 2 Areas (2 groups) (Figure 1):
- The content of the elements As, Hg, Pb, Cd and grease in area 1 (group 01 - along the waterway) is 1.6 (Pb) to 3.8 times higher (grease). Compared with the average content of samples in area 2 (group 2) and the average content of elements Hg, Pb and grease all exceed the National Technical Regulation on Sediment Quality Standards (QCVN 43:2017/BTNMT) from 1.8 to 3.5 times.
- The average content of As, Hg, Pb, Cd and grease in area 2 (group 2) is lower than group 1, but the average content of Hg and Pb also exceeds the Sediment Quality Standards (QCVN43:2017/BTNMT).
3.3. Solutions to prevent and minimize environmental impacts
To ensure sustainability in the operation of the NCT Port cluster, Quang Ninh Province, according to the author, some solutions should be concentrated as follows:
- Strengthen periodic environmental monitoring, analysis and research and export batch; for indicators of grease and heavy metals, the monitoring frequency should be once a month.
- Constructing works to prevent surface washout, landslide of landfill sites in mineral exploitation areas, coal export ports. Enterprises are required to invest in the installation of advanced waste treatment systems, in order to limit the load and ensure the concentration of waste must be below the permitted level before being discharged into the environment.
- Conclusion
The pollution of heavy metals and grease in the bottom sediments of NCT port cluster at the time of the study is tending to increase and is complicated by the emission sources have not been thoroughly controlled. At the time of assessment, the average content of Hg, Pb and grease in NCT port cluster sediments all exceeded the permitted norms (QCVN 43:2017/BTNMT).
The results of grouping based on the analysis of the main components of the study area are divided into 2 areas with specific characteristics.
NCT port cluster area is adjacent to Ha Long Bay; at the time of research, the bottom sediments have been and are being polluted with mineral oil and some heavy metals content (As, Hg, Pb). To ensure sustainable development, in the short term, it is necessary to focus on a number of overall solutions on environmental policies and management, combining solutions to socialize environmental protection with instrumental solutions, providing economic support to harmonize benefits between mineral exploitation, water transport with other activities that are effective and sustainable development.
References
