An Overview of Heavy Metal Contamination in Water from Agriculture: Origins, Monitoring, Risks, and Control Measures
Abstract
1. Introduction
2. Prospects of HMs Resulting from Agriculture
2.1. Agricultural Inputs as Sources of HMs
2.2. HMs Transport Pathways from Agricultural Fields to Water Bodies
3. Methods Used for Detection of HMs in Water Samples
3.1. Laboratory Techniques for the Detection of HMs in Water Samples
Detection Method | Target Metals | Sample Preparation/Concentration | Detection Range | Advantages (A) and Limitations (L) | Ref. |
---|---|---|---|---|---|
AAS | Cd, Co, Cr, Cu, Ni, Pb, Zn | - preservation of water samples was ensured with ultrapure HNO3 - prior to analysis, water samples were filtered | mg L−1-μg L−1 | A: high precision, very low detection limits L: expensive equipment, relatively longer analysis times | [82,83] |
Cd, Cr, Co, Cu, Mn, Ni, Pb, Zn | - water samples were concentrated before quantification (excepting Fe, Zn) | [84] | |||
Cr, Fe, Mn, Ni, Pb | - microwave digestion was performed of water samples with an acid mixture (67% HNO3: 98%H2SO4: 37%HCl: 40%HF = 2:1:1:1) | [62] | |||
Cd, Co, Cr, Ni, Pb | - 10 mL water sample was treated with 2 mL 8-hydroxyquinoline and 0.2 mL Cu(II) solution (coprecipitation procedure) - then, centrifugation was performed, and the resulting precipitate was dissolved in 1 mL HNO3 | [60] | |||
Cd, Cr, Mn, Ni, Pb | - water samples were filtered (0.45 μm pore size) and the pH adjusted to 9 - we coprecipitated targeted ions with the aid of Cu(II)-dibenzyldithiocarbamate precipitate, which was then dissolved in 0.5 mL concentrated HNO3 | [61] | |||
GFAAS | Hg | - a 2% solution of KMnO4 was added to the water sample to convert mercury from organo-mercuric compounds into its ionic form and help prevent evaporation and loss of metals - measurements were conducted 24 h later, after adding a 20% solution of SnCl2 to the sample | μg L−1 | A: high sensitivity for trace metals; small sample volumes required; L: expensive, use of matrix modifiers; useful for detection of Pb and Hg, in particular | [84] |
Cd | - microwave digestion was performed of water samples with an acid mixture (67% HNO3: 98%H2SO4: 37%HCl: 40%HF = 2:1:1:1) | [63] | |||
Pb | - water samples were filtered (filter membrane with 0.45 μm pore size) - continuous-flow microextraction was conducted with the addition of chelation reagent 1-phenyl-3-methyl-4-benzoyl-5-pyrazolone | [67] | |||
Cd, Cr, Cu, Fe, Mn, Ni, Pb, Zn | - 3 L of water sample was concentrated at 80 °C till reaching a final volume of 50 mL - 4 mL 98% H2SO4 was added and digested by a Digesdahl apparatus (3 min) - 10 mL 30% H2O2 was added and heated until oxidation was finished - the resulting mixture was filtered and diluted to 50 mL with deionized water | [63] | |||
As, Cd, Cr, Pb | - water samples were filtered (0.45 μm pore size) and we adjusted the pH to lower than 2 - 50 mL acidified sample was treated with 5 mL HNO3 and boiled at 130 °C till the volume was 25–30 mL | [64] | |||
CVAAS | Hg | - water samples spiked with Hg+2 ions were mineralized in a photoreactor thermostatted at 25 °C with a luminous intensity of 3.81 mW cm−2 in the presence of 100 mgTiO2 and 0.01 mol L−1 potassium persulfate - we used a preconcentration system composed of a mini-column packed with 100 mg of 2-aminothiazol-modified silica gel - we carried out elution with 100 μL 2 mol L−1 HCl | ng L−1 | A: highly sensitive for mercury detection L: limited to mercury; possible interferences | [68] |
Hg | - 500 mL water was treated in a separatory funnel with 2.5 mL 20 N H2SO4 and 1.5 mL 0.5% KMnO4 - the mixture was neutralized with 5 mL 10N NaOH and 1.5 mL 10% NH2OH∙HCl and then allowed to rest for 20 min - chelating agent was added (1.5 mL 10% EDTA) - mercury extraction was performed with 10 mL 0.01% dithizone-toluene - toluene was evaporated from the dithizone-toluene phase, leaving behind mercury for further analysis - samples resulting after evaporation were digested (2 mL of HNO3:HClO4 = 1:1 and 5 mL of H2SO4) - finally, 1 mL SnCl2 solution was added as a reductant | [69] | |||
ICP-MS | Cd, Cr, Cu, Pb, Zn | - after sampling, a drop of 50% HNO3 was added to maintain a pH < 2 - 5 mL aqua regia (1:1) was added to 20 mL water sample | μg L−1-ng L−1 | A: extremely sensitive; multielement analysis; speciation analysis (able to distinguish between different oxidation states); low detection limits L: expensive technique; trained personnel; expensive maintenance for apparatus | [78] |
As, Cd, Co, Mn, Ni, Pb, Zn | - water samples were stabilized with ultrapure 0.5% HNO3 | [71] | |||
As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Zn | - water samples were filtered (filter membrane with 0.45 μm pore size) - HNO3 was added to acidify the samples for preservation at pH < 2 to prevent oxidation and bacterial growth | [85] | |||
Cd, Co, Cr, Cu, Mn, Ni, Pb, Zn | - 90 mL water samples were digested with 10 mL concentrated HNO3 at 100 °C - the resulting digestate was filtered and diluted with 0.01 N HNO3 | [72] | |||
ICP-OES | As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Zn | - water samples were pre-acidified with HNO3 (5 mL L−1) - a 10 mL aliquot was subjected to digestion (0.2 mL concentrated HNO3 and 0.5 mL concentrated HCl) - the mixture was heated at 90–95 °C until the final volume was reduced to 3–5 mL - the digested sample was then diluted to a final volume of 10 mL with deionized water | μg L−1 | A: multielement analysis; fast analysis L: less sensitive than ICP-MS | [74] |
As, Cd, Cr, Cu, Mn, Ni, Pb, Zn | - water samples were acidified with 65% HNO3 until reaching pH 1–2 in order to prevent precipitation and retention on the walls of the vessels | [75] | |||
Cd, Co, Cr, Cu, Mn, Ni, Pb, Zn | - 100 mL water samples were acidified with HNO3:HCl = 3:1 - the acidified sample was heated until the final volume was 25 mL - the samples were filtered and diluted to 100 mL final volume | [76] | |||
As, Cd, Hg, Pb | - prior to analysis, water samples were filtered using a 100 mm Whatman filter | [86] | |||
AFS | As, Hg | - after sampling, a drop of 50% HNO3 was added to maintain a pH < 2 - 5 mL aqua regia (1:1) was added to a 20 mL water sample | μg L−1-ng L−1 | A: high sensitivity for Hg, As; selective detection L: limited element range; need to train personnel | [78] |
NAA | Cr, Cu, Fe, Mn, Zn | - 1 L of water sample was evaporated to 20 mL - 0.5 mL was stored in a polyethylene vial - measurement of γ-ray was carried out with a high-purity germanium detector | μg L−1-ng L−1 | A: non-destructive; highly sensitive; used for a wide range of samples; not affected by the errors typically associated with sample preparation L: expensive; requires access to a neutron source or nuclear reactor | [79] |
3.2. Techniques for In Situ and On-Site Measurement of HMs
3.3. Integration of Artificial Intelligence and Internet of Things in HM Detection
4. Regulatory Standards and Legislative Measures for HMs in Water
4.1. Regulations and Legislation Related to HM Levels in Water
4.2. Challenges in Enforcement
5. Impact of HMs on Water Quality and Aquatic Organisms
5.1. Impact of HMs on Water Quality
- (a)
- Heavy metal contamination load (CL) can be calculated using the following equation [118]: CL = HC x Q x 86.4, where CL = heavy metal contamination load (kg day−1), HC = heavy metal content in contaminated water (mg L−1), and Q = flow rate (m3 s−1);
- (b)
- (c)
- Pollution index (PI) is calculated on the basis of individual metal concentration. The calculation for this parameter and water classification according to PI values are reported by Goher et al. [128];
- (d)
5.2. Impact of HMs on Aquatic Organisms
6. Approaches to Mitigate HM Contamination Resulting from Agriculture
6.1. Best Agricultural Practices
6.2. Supplementary Metal Pollution Control Strategies
6.3. Public Awareness and Community Involvement
7. Conclusions and Future Perspectives
- -
- Development of high-sensitivity and high-selectivity sensors, along with other smart monitoring tools, for accurate and real-time field measurements;
- -
- Integration of smart technologies (IoT-enabled systems, remote sensing) into environmental monitoring to enhance detection and early warning capabilities;
- -
- Development of precise, field-ready, and affordable methods for heavy metal monitoring to ensure widespread accessibility, real-time risk assessment, and effective pollution management;
- -
- Incorporation of digital tools and AI-powered systems into precision agriculture to enable smarter input management and improved environmental monitoring;
- -
- Advancement of bioremediation and phytoremediation strategies to enhance their efficiency, flexibility, and affordability in removing heavy metals from the environment;
- -
- Design of multifunctional soil amendments (e.g., biochar, organic amendments) that simultaneously improve soil fertility and immobilize heavy metal contaminants to prevent their leaching into water bodies.
- -
- Enforce stricter quality standards for agricultural inputs to limit heavy metal content;
- -
- Reinforce regulatory frameworks to ensure compliance with environmental protection measures;
- -
- Expand farmer education programs focused on input management and sustainable agricultural practices to prevent environmental pollution.
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Sample | Cd | Cr | Cu | Ni | Pb | Zn |
---|---|---|---|---|---|---|
WW, mg L−1 | 0.8 | 0.87 | 0.4 | 0.38 | 0.36 | 0.28 |
0.64 | 0.82 | 0.37 | 0.31 | 0.33 | 0.23 | |
0.07 | 0.11 | 0.18 | 0.16 | 0.09 | 0.08 | |
SS, mg kg−1 | 3.20 | 63 | 35.40 | 78 | 74.50 | 31.50 |
3.35 | 56 | 38 | 85.50 | 70.75 | 33 | |
1.25 | 34.25 | 16.75 | 36.50 | 46.25 | 15.75 | |
VS, mg kg−1 | 4.53 | 21.15 | 19 | 28.4 | 20.5 | 14.9 |
5.69 | 22.24 | 17.35 | 31.87 | 22.70 | 12.27 | |
2.35 | 15.89 | 11.38 | 17.15 | 7.33 | 8.64 |
Pollutant | EQS (Surface Water) [107] | Drinking Water | ||||
---|---|---|---|---|---|---|
AA-EQS Inland Surface Waters | AA-EQS Other Surface Waters | MAC-EQS Inland Surface Waters | EU Legislation [107] | WHO [113] | USEPA [114] | |
Arsenic (As) | - | - | - | - | 10 | 10 |
Cadmium (Cd) * | ≤0.08 (Class 1) 0.08 (Class 2) 0.09 (Class 3) 0.15 (Class 4) 0.25 (Class 5) | 0.2 | ≤0.45 (Class 1) 0.45 (Class 2) 0.6 (Class 3) 0.9 (Class 4) 1.5 (Class 5) | 5 | 3 | 5 |
Copper (Cu) | - | - | - | 2000 | 2000 | 1300 |
Chromium (Cr) | - | - | - | 25 | 50 | 100 |
Lead (Pb) | 7.2 | 7.2 | NA | 5 | 10 | 15 |
Mercury (Hg) | - | - | - | 1 | 6 | 2 |
Nickel (Ni) | 20 | 20 | NA | 20 | 70 | 100 |
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Madjar, R.M.; Vasile Scăețeanu, G. An Overview of Heavy Metal Contamination in Water from Agriculture: Origins, Monitoring, Risks, and Control Measures. Sustainability 2025, 17, 7368. https://doi.org/10.3390/su17167368
Madjar RM, Vasile Scăețeanu G. An Overview of Heavy Metal Contamination in Water from Agriculture: Origins, Monitoring, Risks, and Control Measures. Sustainability. 2025; 17(16):7368. https://doi.org/10.3390/su17167368
Chicago/Turabian StyleMadjar, Roxana Maria, and Gina Vasile Scăețeanu. 2025. "An Overview of Heavy Metal Contamination in Water from Agriculture: Origins, Monitoring, Risks, and Control Measures" Sustainability 17, no. 16: 7368. https://doi.org/10.3390/su17167368
APA StyleMadjar, R. M., & Vasile Scăețeanu, G. (2025). An Overview of Heavy Metal Contamination in Water from Agriculture: Origins, Monitoring, Risks, and Control Measures. Sustainability, 17(16), 7368. https://doi.org/10.3390/su17167368