Zinc Smelter Research Articles

Physicochemical Properties and Leaching Toxicity Assessment of Jarosite Residue

The safe disposal of hazardous waste from zinc hydrometallurgy, such as jarosite residue, is crucial for the sustainable development of the industry. The chemical, structural and morphological properties of jarosite residue from zinc smelting were studied by a combination of various characterizations, and environmental stability was evaluated using the toxicity characteristic leaching procedure (TCLP), Chinese standard leaching tests (CSLT) and long-term leaching experiments (LTLE). Phase composition analysis revealed that zinc ferrite and sodium jarosite were the main phases present in the jarosite residue. TCLP and CSLT analyses indicated that the Zn and Pb contents exceeded their respective toxicity identification standards by more than 30 times and 8 times, respectively, exceeding the threshold values of the standard. The LTLE results demonstrated that Pb concentrations continued to exceed the standard limits, even after long contact times. This study has paramount significance in the prediction of jarosite residue stability and the evaluation of its potential for secondary environmental pollution.

Spatial Distribution and Associated Risk Assessment of Heavy Metal Pollution in Farmland Soil Surrounding the Ganhe Industrial Park in Qinghai Province, China

The farmland around the industrial areas in the Upper Yellow River is crucial for agricultural production but is vulnerable to contamination from the surrounding industries. This research focused on analyzing the spatial distribution and environmental risks of heavy metal pollution in the farmland around the Ganhe Industrial Park in the Qinghai–Tibet Plateau. A total of 138 surface soil samples were collected, and the concentration of seven heavy metals (Cd, As, Pb, Cr, Cu, Ni, and Zn) was analyzed using the random forest (RF) model. Pollution indicators, including the pollution index and Nemero index, were used to evaluate the pollution levels of soil heavy metals. The human health and ecological risks were estimated using the hazard index (HI) and the potential ecological risk index (RI). Cd and Zn were identified as the primary soil pollutants in the study area, with Cd being more concentrated than other heavy metals. Heavy metal contamination was most severe in the central–eastern region of the study area, with a ring-shaped distribution, which correlated with the presence of zinc smelting and chemical plants. Furthermore, the study revealed that soil heavy metal contamination posed a health threat to the local population, with children being particularly vulnerable to non-carcinogenic risks when the HI was 1.21 and to potential carcinogenic risks when the CR was 2.27 × 10−5. Additionally, heavy metal pollution caused a moderate to high ecological risk in 56.4% of the samples. The results highlighted the severe impact of soil heavy metal pollution on the delicate ecosystem of the Upper Yellow River and Qinghai–Tibet Plateau. The government should take action to improve soil environment management and prevent heavy metal pollution to protect the health of the local population and the ecological environment.

Geochemical fractionation and potential release behaviour of heavy metals in lead‒zinc smelting soils

The lack of understanding of heavy metal speciation and solubility control mechanisms in smelting soils limits the effective pollution control. In this study smelting soils were investigated by an advanced mineralogical analysis (AMICS), leaching tests and thermodynamic modelling. The aims were to identify the partitioning and release behaviour of Pb, Zn, Cd and As. The integration of multiple techniques was necessary and displayed coherent results. In addition to the residual fraction, Pb and Zn were predominantly associated with reducible fractions, and As primarily existed as the crystalline iron oxide-bound fractions. AMICS quantitative analysis further confirmed that Fe oxyhydroxides were the common dominant phase for As, Cd, Pb and Zn. In addition, a metal arsenate (paulmooreite) was an important mineral host for Pb and As. The pH-stat leaching indicted that the release of Pb, Zn and Cd increased towards low pH values while release of As increased towards high pH values. The separate leaching schemes were associated with the geochemical behaviour under the control of minerals and were confirmed by thermodynamic modelling. PHREEQC calculations suggested that the formation of arsenate minerals (schultenite, mimetite and koritnigite) and the binding to Fe oxyhydroxides synchronously controlled the release of Pb, Zn, Cd and As. Our results emphasized the governing role of Fe oxyhydroxides and secondary insoluble minerals in natural attenuation of heavy metals, which provides a novelty strategy for the stabilization of multi-metals in smelting sites.

Cadmium-treatment efficiency and membrane fouling during electrodialysis of wastewater discharged from zinc smelting

Zinc smelting wastewater contains high concentrations of Cd. Here, the treatment efficiency of Cd using electrodialysis was evaluated. In addition, scale accumulation of ion-exchange membrane (IEM) was analyzed, and fouling control was studied. The results showed that spacers effectively improved the limiting current density but accelerated foulant accumulation. The Cd-treatment efficiency improved to 85.4% without a spacer. Dissolved organic carbon (DOC) and hydrophobic DOC levels in diluted water decreased by 0.65 mg L−1 and 2.1 mg L−1, respectively; in contrast, hydrophilic DOC level increased by 1.45 mg L−1. Some of the hydrophobic DOC in the diluted water was converted to hydrophilic DOC and subsequently to low-molecular-weight (LMW) DOC. DOC level in the concentrated water did not change substantially, but the LMW fraction of the hydrophilic DOC increased. In the cation-exchange membrane, a material composed of calcium sulfate accumulated in the bottom layer, and hydroxides of divalent and trivalent ions accumulated on top of it. In contrast, the anion-exchange membrane was fouled by humic substances. In terms of fouling control, physical and acid cleaning of IEMs was more effective than the reversal operation.

Spatial Distribution and Risk Assessment of Heavy Metal(oid)s Contamination in Topsoil around a Lead and Zinc Smelter in Henan Province, Central China.

A total of 137 farmland soil samples were collected around a lead/zinc smelter within 64 km2. The concentration, spatial distribution, and potential source of nine heavy metal(oid)s (As, Cd, Co, Cr, Cu, Ni, Pb, V, and Zn) in soils and their potential ecological risk were investigated in detail. The results showed that the average concentrations of Cd, Pb, Cr and Zn in these soils were higher than their background value in Henan Province, and the average content of Cd was 2.83 times of the risk screening values in the national standard of China (GB 15618-2018). According to the distribution of different heavy metal(oid)s in soils, Cd and Pb in soil decrease gradually with the increase of distance from the smelter to the surrounding area. This indicates that the Pb and Cd originate from smelters via airborne practices according to the typical air pollution diffusion model. The distribution of Zn, Cu, and As were similar to Cd and Pb. However, Ni, V, Cr, and Co were mainly affected by soil parent materials. The potential ecological risk of Cd was higher than those of other elements, and the risk grade of the other eight elements was mainly low. The polluted soils with significantly high and high potential ecological risk covered 93.84% of all the studied regions. This should be of serious concern to government. The results of a principal component analysis (PCA) and cluster analysis (CA) show that Pb, Cd, Zn, Cu, and As were the elements mainly stemmed from smelter and other types of plants, with a contribution rate of 60.08%, while Co, Cr, Ni, and V are mainly caused by nature, with a contribution rate of 26.26%.

A Systematic Procurement Supply Chain Optimization Technique Based on Industrial Internet of Things and Application

Smart manufacturing has become mainstream in the development of manufacturing industry, where Industrial Internet of Thing plays a critical role. In this paper, a systematic intelligent technique for procurement supply chain optimization is proposed. In this technique, an integrated approach based on variational mode decomposition and long short-term memory network is used to predict the market price. Considering the factors such as production plan and market fluctuation, a multi-period dynamic purchasing model is built. A stacked autoencoder under bootstrap aggregation is then trained to evaluate suppliers automatically end-to-end based on various data. Finally, a multi-objective order allocation model is established considering the procurement costs and supplier scores, and solved by particle swarm optimization. The extensive experiments are performed using a realistic industrial application in a zinc smelter company. The experimental results demonstrate that the proposed technique greatly reduces labor costs, improves the efficiency of procurement supply chain, and reduces the procurement costs of the company.

Vertical distribution of nutrients, enzyme activities, microbial properties, and heavy metals in zinc smelting slag site revegetated with two herb species: Implications for direct revegetation

Direct revegetation is an important measure to immobilize heavy metals and improve the microecological properties of metal smelting slag sites. However, the vertical distribution of nutrients, microecological properties, and heavy metals at a directly revegetated metal smelting slag site remains unclear. Here, the distribution characteristics of nutrients, enzyme activities, microbial properties, and heavy metals in the vertical profile at a zinc smelting slag site directly revegetated with two herb species (Lolium perenne and Trifolium repens) for 5 years were investigated. The results showed that the nutrient contents, enzyme activities, and microbial properties decreased with increasing slag depth after revegetation with the two herb species. The nutrient contents, enzyme activities, and microbial properties of the surface slag revegetated with Trifolium repens were better than those in the surface slag revegetated with Lolium perenne. The higher root activity in the surface slag (0–30 cm) resulted in relatively higher contents of pseudo-total and available heavy metals in the surface slag. Moreover, the contents of pseudo-total heavy metals (except for Zn) and available heavy metals in the slag revegetated with Trifolium repens were lower than those in the slag revegetated with Lolium perenne at most slag depths. Overall, the greater phytoremediation efficiency of the two herb species occurred mainly in the surface slag (0–30 cm), and the phytoremediation efficiency of Trifolium repens was higher than that of Lolium perenne. The findings are beneficial for understanding the phytoremediation efficiency of direct revegetation strategies for metal smelting slag sites.

Trace mercury migration and human exposure in typical mercury-emission areas by compound-specific stable isotope analysis

Anthropogenic mercury (Hg) emissions have increased significantly since the Industrial Revolution, resulting in severe health impacts to humans. The consumptions of fish and rice were primary human methylmercury (MeHg) exposure pathways in Asia. However, the lifecycle from anthropogenic Hg emissions to human MeHg exposure is not fully understood. In this study, a recently developed approach, termed MeHg Compound-Specific Isotope Analysis (CSIA), was employed to track lifecycle of Hg in four typical Hg-emission areas. Distinct Δ199Hg of MeHg and inorganic Hg (IHg) were observed among rice, fish and hair. The Δ199Hg of MeHg averaged at 0.07 ± 0.15 ‰, 0.80 ± 0.55 ‰ and 0.43 ± 0.29 ‰ in rice, fish and hair, respectively, while those of IHg averaged at − 0.08 ± 0.24 ‰, 0.85 ± 0.43 ‰ and − 0.28 ± 0.68 ‰. In paddy ecosystem, Δ199Hg of MeHg in rice showed slightly positive shifts (∼0.2 ‰) from those of IHg, and comparable Δ199Hg of IHg between rice grain and raw/processed materials (coal, Hg ore, gold ore and sphalerite) were observed. Simultaneously, it was proved that IHg in fish muscle was partially derived from in vivo demethylation of MeHg. By a binary model, we estimated the relative contributions of rice consumption to human MeHg exposure to be 84 ± 14 %, 58 ± 26 %, 52 ± 20 % and 34 ± 15 % on average in Hg mining area, gold mining area, zinc smelting area and coal-fired power plant area, respectively, and positive shifts of δ202HgMeHg from fish/rice to human hair occurred during human metabolic processes. Therefore, the CSIA approach can be an effective tool for tracking Hg biogeochemical cycle and human exposure, from which new scientific knowledge can be generated to support Hg pollution control policies and to protect human health.

Study on the Removal of Chloride Ions in an Acidic Solution of Zinc Smelting by Green Method

In the process of zinc smelting, when the chloride ion concentration exceeds 100 mg/L, it continuously corrodes the electrode plate and affects the stability of the electrodeposition process. Therefore, the chloride concentration must be reduced below 100 mg/L. Compared with other methods used to control the reactions of Cu(II), the use of the copper slag produced in zinc smelting without other additives does not cause reverse dissolution; to reduce the cost, turn the waste into treasure, and protect the environment, research was carried out on chloride removal by the copper slag via a synergistic valence control process. In this study, the influencing factors, such as the amount of copper slag, the reaction time, and reaction temperature, were systematically investigated. The results showed that the optimum dechlorination conditions were as follows: the copper: copper(II): chloride molar ratio was 6:5:1, the reaction time was 60 min, and the reaction temperature was 20 °C. The chloride ion concentration was decreased from 1.6 g/L to 0.05 g/L, the dechlorination efficiency was 96.875%, and the residual chloride ion concentration was less than 100 mg/L, which provides a basis for industrial use.

Digital twin for zinc roaster furnace based on knowledge-guided variable-mass thermodynamics: Modeling and application

Roaster furnace is a large-scale equipment in zinc smelting process, which plays an significant role in safety production and enviromental protection. An accurate digital twin of roaster furnace can help to explore the influence of control parameters and serve as a test platform to verify the effectiveness of control strategies. However, the traditional thermodynamics cannot be used for dynamic modeling, and inability to measure key data greatly affects the accuracy of kinetic modeling. Therefore, this paper establishes a novel digital twin of zinc roaster furnace based on knowledge-guided variable-mass thermodynamics. First, based on the integration of mechanism analysis for mass balance and energy balance, a dynamic modeling method is proposed. Then, particle swarm optimization (PSO) algorithm is introduced to optimize the parameters of conversion rates guided by knowledge. Finally, by connecting the dynamic model with distributed control system (DCS) through OPC communication protocol, a digital twin of roaster furnace is constructed. Extensive experiments show that the simulation results of the digital twin roughly agree with the actual industrial data under steady and dynamic working conditions, and the application of the digital twin on the performance analysis of control parameters and testing of control strategies can provide guidance for the optimal control of roaster furnace.

Source apportionment and quantitative risk assessment of heavy metals at an abandoned zinc smelting site based on GIS and PMF models

The abandoned smelters have caused serious hazards to the surrounding environment and residents. Taking an abandoned zinc smelter in southern China as an example, a total of 245 soil samples were collected to study spatial heterogeneity, source apportionment, and source-derived risk assessment of heavy metal(loid)s (HMs) in the region. The results showed that the mean values of all HMs concentrations were higher than the local background values, with Zn, Cd, Pb, and As contamination being the most serious and their plume penetrating to the bottom layer. Four sources were identified by principal component analysis and positive matrix factorization, with their contributions to the HMs contents ranked as: surface runoff (F2, 63.2%) > surface solid waste (F1, 22.2%) > atmospheric deposition (F3, 8.5%) > parent material (F4, 6.1%). Among these, F1 was a determinant source of human health risk with a contribution rate of 60%. Therefore, F1 was considered to be the priority control factor, but it only accounted for 22.2% of HMs contents contribution. Hg dominated the ecological risk with a contribution of 91.1%. Pb (25.7%) and As (32.9%) accounted for the non-carcinogenic risk, while As (95%) dominated the carcinogenic effect. The spatial characteristics of human health risk values derived from F1 indicated that high-risk areas were mainly distributed in the casting finished products area, electrolysis area, leaching-concentration area, and fluidization roasting area. The findings highlight the significance of priority control factors (including HMs, pollution sources and functional areas) for consideration in the integrated management of this region, thus saving costs for effective soil remediation.

Fixing sulfur dioxide by feeding calcine oxide into the rotary volatilization kiln in zinc smelting plant.

Sulfur dioxide (SO2) is a toxic pollutant and its fixation is a high cost but imperative task for sulfide metallurgy industry. Although being a mature technology for on-line fixation of SO2 by limestone injection in coal-fired boilers, its application is rarely investigated in the sulfide metallurgy plant. Extending this technology to the metallurgy industry is highly plausible, but with the feasibility and practicability waiting to be uncovered. Herein, feeding CaO into the rotary volatilization kiln as SO2-fixation agent is demonstrated to be an efficient in-furnace desulfurization strategy for zinc smelting plant. The sulfur distribution within the entire smelting process is systematically analyzed, determining that the critical procedure for pressuring the desulfurization system is the rotary volatilization kiln. The thermodynamics analysis shows that addition of CaO is feasible for SO2 fixation by forming CaS or restraining the reductive decomposition of SO42-. The industrial tests, including the online monitoring of kiln flue gas and kiln slag analysis, validate the thermodynamics analysis, realizing a 24.6% reduction of SO2 in the flue gas by converting gaseous SO2 to solid CaS via feeding 20% CaO. The present study highlights an effective strategy for on-line fixing the SO2, being a potential way for relieving the desulfurization pressures in zinc sulfide metallurgy plant.

Extending Ag Nanoparticles as Colorimetric Sensor to Industrial Zinc Electrolyte for Cobalt Ion Detection

The direct and rapid determination of trace cobalt ion (Co2+) in the electrolyte of zinc smelting plants is urgently needed but is impeded by the severe interference of extremely high-concentration zinc ions in the solution. Herein, colorimetric detection of Co2+ by the polyvinylpyrrolidone functionalized silver nanoparticles (PVP-AgNPs) is realized in solutions with the Zn/Co ratio being high, up to (0.8-5) × 104, which is located within the ratio range in industrial solution. The high concentration of Zn2+ induces a strong attenuation of Co2+-related signals in ultraviolet-visible (UV-vis) extinction spectra; nevertheless, a good linear range for detecting 1-6 mg/L Co2+ in 50 g/L Zn2+ solution is still acquired. The strong anti-interference toward other metal ions and the mechanism understanding for trace Co2+ detection in such a high-concentration Zn2+ solution are also revealed by systematic analysis techniques. The results extend the AgNPs as colorimetric sensors to industrial solutions, providing a new strategy for detecting trace-metal ions in industrial plants.

The Phytoremediation Potential of Local Wild Grass Versus Cultivated Grass Species for Zinc-Contaminated Soil

The aim of the study was to compare the phytoremediation potential of cultivated grasses with local wild grass for soil contaminated with zinc. Two pot experiments were carried out on soil artificially contaminated with Zn. Four species of cultivated grasses were used as test plants: Poa pratensis, Lolium perenne, Festuca rubra, Festuca pratensis, and one wild, native grass: Deschampsia caespitosa. Wild grass seeds were collected from soil contaminated with heavy metals near a zinc smelter. The phytoremediation potential of grasses was determined on the basis of the tolerance index (TI), bioaccumulation (BF), and translocation (TF) factors. Differences were found between the species in the reduction in the shoot and root biomass with increasing soil contamination with Zn. The tolerance of the studied grasses to excess Zn in the soil was in the following order: D. caespitosa > L. perenne > F. rubra > F. pratensis > P. pratensis. In addition, there were differences in the accumulation and distribution of Zn between the roots and shoots, which is related to the different defense mechanisms of the studied grasses against Zn phytotoxicity. Of the five grasses tested, the highest phytoremediation potential was shown by D. caespitosa. This grass had a significantly higher tolerance to Zn and a lower transfer of Zn from the roots to shoots than the other cultivated grasses tested. All four cultivated grasses can be useful for phytostabilization because they accumulated Zn mainly in the roots and limited its translocation to the shoots. Unlike wild grass seeds, cultivated grass seeds are readily available commercially and can be used for the phytoremediation of HM-contaminated sites.

Zinc ore supplier evaluation and recommendation method based on nonlinear adaptive online transfer learning

<p style='text-indent:20px;'>Purchasing decisions determine the purchasing cost, which is the largest section of the production cost of zinc smelting enterprise(ZSE). An excellent supplier recommendation is significant for ZSE to reduce the cost. However, during the supplier recommendation process, the nonlinear demand feature of purchasing department varies with the production environment, and there are wrong samples that can affect the supplier recommendation effect. To handle these problems, the recommendation strategy based on a multiple-layer perceptron adaptive online transfer learning algorithm(AOTLMLP) are proposed. In this method, the original prediction function is modified based on MLP nonlinear projective function and adaptive loss function, which enables the AOTLMLP algorithm to tackle the nonlinear classification problems and efficiently follow the demand change of purchasing department, thereby improving the result of the recommendation. The performance of the AOTLMO algorithm is evaluated through a common dataset and a purchasing dataset from a zinc smelter that generated by a supplier evaluation model. It can be assumed that AOTLMLP can ignore the influence of wrong samples and provide an effective recommendation confronting the characteristic of zinc ore purchasing.</p>

A Systematic Review on Concentration of Heavy Metal in the Ambient Air of Different Industries and the Health Risk Assessment

Heavy metals are a group of pollutants that are found in ambient air of the industries. The metals can lead to cancerous and non-cancerous diseases in the exposed persons. In this systematic review, the concentration of heavy metals in the ambient air of industries and the related health risks were studied. In general, heavy metals with different average concentrations were found in various industries. Given the results, Zinc (539.96 µg/m³ ), Iron (216.04 µg/m³), Mercury (19.37 µg/m³), Lead (19.24 µg/m³), Arsenic (17/51 µg/m3), Chromium (12/18 µg/m³), Titanium (10/63 µg/m³ ), Nickel (9/09 µg/m³), Copper (8/11 µg/m³), Cadmium (6/7 µg/m³), Antimony (3/2 µg/m³), Manganese (2.99 µg/m³), Cobalt (1.32 µg/m³ ) were found in the air of the industries. For the zinc smelting, atomic energy, steel, roofing, printing, tape production, and cement, the highest concentration was for zinc (2518 µg/m³), lead (41/35 µg/m³), lead (45 µg/m³), lead (1/38 µg/m³), copper (20/20 µg/m³) and iron (216/04 µg/m³), respectively. All of the concentration in this research is reported in µg/m³. The average carcinogenic risk for the metals were 1.78×10-2, 3.32×10-3, 3.6×10-2, and 1.79×10-3 respectively for arsenic, cadmium, chromium, and nickel. The average non-carcinogenic risk of chromium, manganese, and mercury were 8.06×104 , 77×10-4, and 1.22×10-2, respectively. According to the results, the variety of heavy metals in cement industry is more than in other industries, while the concentration of heavy metals in zinc smelting and atomic energy industries was more than remain. Zinc showed the highest average concentration and chromium showed the highest expected risk of carcinogenicity for occupational exposure.

Removal of Cd2+ from zinc smelter wastewater using graphene oxide foam cross-linked with epichlorohydrin: comprehensive optimization, isotherms, kinetics, and real water column studies

Removal of Cd2+ from zinc smelter wastewater using epichlorohydrin-cross-linked chitosan-GO (EPCSGO).

Heavy Metals Pollution in Soil Around the Lead-zinc Smelting Plant in guanzhong Plain

[Objective] T To analyze and determine the content of eight heavy metals Cd, Cr, Cu, Pb, Hg, Zn, As, and Ni in 40 soil samples collected around a lead-zinc smelting plant in Guanzhong through experimental analysis, and to preliminarily grasp the content of heavy metals in the soil around the smelting plant, and to conduct pollution research and evaluation.. [Method] In mid to late April 2020, 40 soil samples (with a sampling depth of 0-30 cm) were collected from the vicinity of a lead zinc smelter in Guanzhong. The heavy metal content was determined through transcoding, natural air drying, and grinding processes.. [Results] The average contents of Cd, Cr, Cu, Pb, Hg, Zn, As, and Ni in the soil around a lead zinc smelter in Guanzhong were 0.40, 85, 26.0, 48, 0.078, 108, 12.5, and 26 mg. kg-1, respectively. Except for Ni, the average contents of Cd, Cr, Cu, Pb, Hg, Zn, and As were higher than the background values of soil elements in China and Shaanxi Province, especially Cd, Hg, and Pb, The content is 4.26, 2.60, and 2.28 times the background values of soil elements in Shaanxi Province, and 4.12, 1.2, and 1.85 times the background values of soil elements in China. By calculating the standard deviation and coefficient of variation, it was found that the standard deviation and coefficient of variation of Cd, Pb, and Zn in the soil around the smelter were relatively large, indicating that these three heavy metal elements accumulated significantly in the soil.. [Conclusion] The soil around a lead-zinc smelter in Guanzhong is mainly contaminated by multiple heavy metal complexes, mainly Cd pollution. The atmospheric sedimentation around the smelter and dust from mining sites may be the main sources of pollution..

Closed-Loop Dynamic Blending Optimization Based on Variational Bayesian and its Application in Industry

There exist uncertainties in raw material components and distribution parameters in blending process. Considering the dynamic uncertainty of distribution parameters and the dynamic change of raw material inventory, a general closed-loop dynamic blending optimization (CDBO) is proposed. The proposed method consists of both data-driven system and model-based system. In the data-driven system, the feedback optimization problem is reconstructed into a linear regression problem, and the variational Bayesian is proposed to obtain the mean and variance of the distribution. Then, according to the incoming raw materials, the mean value of each distribution parameter is adjusted by expert rules. Last, in the model-based system, blending ratio is obtained by chance-constrained programming. To verify the effectiveness of CDBO, a detailed derivation process of variable Bayesian, expert rule and chance-constrained programming are established for zinc smelting process. Numerical studies and an industrial application for zinc smelting process are presented to demonstrate the advantages of the proposed method. Compared with the manual blending, the volatility index of chemical tests data is greatly reduced and the compliance rates of zinc and lead is increased by 6.7% and 3.3%, respectively.

Mercury Contamination of Water and the Removal of Mercury from Water

Mercury is a common element in nature. Mercury that is in compound form does not severely harm the environment and human being. However, when the mercury element is by itself, that is when its oxidation state is zero, it easily gets into the air or the water. And because the mercury is not in any compound form, nothing restricts its toxicity, it affects the environment and people’s health. Both anthropogenic reasons and natural factors lead to the mercury contamination in water. Coal combustion, zinc smelting, gold rushing, and mercury mining are the major anthropogenic reasons. And since mercury naturally exists in the nature, natural soil would release mercury, which then goes into water as rainwater or flows pass by. Removing mercury from water has been a focus in many places like Guizhou, China and Peru. Ion exchange resins adsorption and multifunctional chitosan non-woven fabrics modified with carbon dots (CDs) can be used. Ion exchange resins adsorption includes a wide variety of substrate. And with these binding agents, mercury, along with many other heavy metal ions, can be easily adsorbed. CDs are carbon nanoparticles that exhibit high sensitivity and good ability to fluoresce, With the modification with CDs, fabrics can change into a cheap and easy tool to remove mercury from water. Studying the removal of mercury contamination from water helps reduce gradual damage to the environment and to human bodies.