Copper ecological risk assessment using DGT technique and PNEC: A case study in the Brazilian coast

Umbría-Salinas, Karelys; Valero, Astolfo; Martins, Samantha Eslava; Wallner-Kersanach, Mônica

doi:10.1016/j.jhazmat.2020.123918

Cited by 20 publications

(6 citation statements)

References 56 publications

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“…39 Cu and Pb are primarily found in the steel structure manufacturing workshop, ship hull block workshop, and container stacking area. These activities, such as steel structure manufacturing, grinding, and painting, generate abundant metal oxides and welding dust, 3 and the HMs, like Cu, Pb, Cr and Ni, in the antifouling paint 4,7 further enrich HMs in the surrounding soil. 40 Hence, source 1 likely represents the Cu and Pb pollution coming from the steel structure manufacturing and ship hull block preinstallation at the site.…”

Section: Analysis Of Soil Heavy Metal Pollution Sources Via the Recep...mentioning

confidence: 99%

“…The shipyard, characterized as a resource-intensive and material-intensive industry, involves long production cycles and complex processes . The dispersion and leakage of antifouling paint from ship surfaces, along with metal dust generated during surface treatment and steel processing, − frequently result in severe heavy metal (HM) pollution in the nearby environment. − Nonetheless, extant research on environmental pollution around shipyards predominantly concentrates on pollution in offshore areas or volatile organic compounds produced by paintwork, − with less attention paid to the environmental pollution within shipyards. The complex production flow within the shipyard exposes the soil environment to a variety of production activities, which potentially impedes the sustainable development of the site, while posing threats to the health of the worker and the ecological security of the surrounding environment.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative Analysis of Heavy Metal Pollution Sources, Influencing Factors, and Delineation of Pollution Risk Areas in Industrial Soil: A Combined Application of Receptor Models and GeoDetector

Lin,

Liu,

Deng

et al. 2023

ACS EST Eng.

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The identification of factors influencing heavy metals (HMs) pollution distribution in industrial sites and delineation of risk areas are critical for preventing soil pollution during production processes. This study introduced a methodology that integrates receptor models and Geodetector, which aim to quantitatively analyze the contribution of the influencing factors of the spatial distribution of HMs in soil and accurately delineate the pollution risk areas within industrial sites. This methodology was applied at a shipyard site. Through the employment of receptor models and Geodetector, we assessed the influence of various factors, such as the distribution of production workshops, offices, and material stacking yard, hydrogeological conditions, and soil physicochemical properties, on the spatial distribution of HMs in the soil. The findings indicate that the sources of HMs are closely associated with specific production processes. By further applying the interaction detector and risk detector of Geodetector and considering the multifactor influences, we delineated primary pollution areas, high-risk pollution areas, and potential pollution areas of HMs within the shipyard site. This provides an indication of severely contaminated areas and the pollution diffusion trend of HMs within the sites, thereby offering scientific guidance for the prevention and mitigation of soil HMs pollution in industrial sites.

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Section: Analysis Of Soil Heavy Metal Pollution Sources Via the Recep...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of Heavy Metal Pollution Sources, Influencing Factors, and Delineation of Pollution Risk Areas in Industrial Soil: A Combined Application of Receptor Models and GeoDetector

Lin,

Liu,

Deng

et al. 2023

ACS EST Eng.

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“…where RCR represents as the risk characterization ratio of NPs; EC represents as the environmental concentration of NPs in seawater (mg/L); and PNEC represents as predicted no-effect concentration of NPs for marine species (mg/L). If the RCR ≤ 0.1, a low risk is expected for marine species at particular environmental concentrations of NPs; if the 0.1< RCR< 1.0, a moderate risk is expected; if the RCR ≥ 1.0, a high risk is expected (Umbrıá-Salinas et al, 2021).…”

Section: Risk Assessmentmentioning

confidence: 99%

Ecological risk assessment of metallic nanoparticles on the marine environments: Species sensitivity distributions analysis

et al. 2022

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Metallic nanoparticles (NPs) are increasingly being used and inevitably entering the marine environment. Therefore, the adverse effects of NPs on individual marine species have attracted increasing attentions. However, to date, the ecological risks of NPs on the marine ecosystem remain poorly understood. In this study, species sensitivity distributions (SSDs) were constructed for Ag, ZnO, CuO, and TiO2 NPs to understand their ecotoxicity to the marine ecosystem and the contribution of size effect and ion effect to the nanotoxicity. Furthermore, a case study on the assessment of marine ecological risk and marine environment carrying capacity of metallic NPs was performed in Jiaozhou Bay, China. The results showed the toxicity of metallic NPs to marine species following the order of Ag > ZnO > CuO > TiO2. Both size effect and ion effect contributed to the toxicity of NPs. Environmental concentrations of Ag, ZnO, CuO, and TiO2 NPs are much lower than the predicted no-effect concentrations, indicating that these metallic NPs have not yet posed risks to the marine ecosystem based on currently limited measured environmental concentrations of metallic NPs in seawater. And the marine environment carrying capacity of Ag, ZnO, CuO, and TiO2 NPs in Jiaozhou Bay seawater were determined to be 5.03, 8.72, 93.06, and 629.79 t, respectively. The results help us understand the ecological risk of NPs in marine environments and provide a scientific basis for the sustainable development of nanotechnology.

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“…Diffusive gradients in thin films (DGT) is a passive sampling technique that has been applied to evaluate labile metal concentrations in waters, soils, and sediments since 1994 [13][14][15][16], and has recently been used to predict the toxicity and bioavailability of metals to benthic organisms [3,17,18]. Yet, the DGT technique has rarely been used for environmental toxicology purposes to determinate the concentrations of an integrated pool of labile metals present in water and in weakened form in waters associated with sediments [3].…”

Section: Introductionmentioning

confidence: 99%

“…At present, only one paper reported availability and ecotoxicological risk of one metal copper in coastal environment [16]. Therefore, to our knowledge, the bioavailability and ecotoxicological risk of metals based on DGT technique are currently scarce.…”

Section: Introductionmentioning

confidence: 99%

Risk assessment of eight metals and their mixtures to aquatic biota in sediments with diffusive gradients in thin films (DGT): a case study in Pearl River intertidal zone

2021

Environ Sci Eur

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Background The ecotoxicological risk posed by metals and their mixtures in sediments depends on their bioavailability. Many methods for evaluating the bioavailability of metals in sediments/soils are time-consuming and expensive, and frequently result in equivocal outcomes. The diffusive gradients in thin films (DGT) technique is a good measure of bioavailability for metals that can avoid the above drawbacks. Therefore, more effective approaches to this method should be developed that focus on metal bioavailability. No studies have been conducted using DGT to assess metal mixtures to aquatic biota in sediments. This study is therefore the first attempt to assess sediment toxicity of metals and their mixtures to aquatic biota based on the DGT technique. The intertidal zone of the Pearl River Estuary is selected as a case study. Results The bioavailable (DGT-labile) concentrations of metals range as follows (μg/L): Cd, 0.34–3.62; Pb, 1.35–1.92; Ni, 0.67–92.83; Cu, 0.74–10.30; Zn, 28.60–296.94; Co, 0.03–58.85; Fe, 7.23–4539.36; and Mn, 19.40–6626.83. The risk quotient (RQ), which is the ratio between the measured metal concentrations in the environment (MEC) and the predicted no-effect concentration (PNEC), is conducted to evaluate the single metal risk. The RQ based on summing up the MEC/PNEC ratios (RQMEC/PNEC) and the RQ based on sum of toxic units (RQSTU) are used to assess risk of metal mixture. TheRQ values of Cd, Pb, Ni, Cu, Zn, Fe, and Mn significantly exceed 1, indicating that the adverse effects of the metals are not negligible. Regarding the toxicity of metal mixtures, the values of RQMEC/PNEC and RQSTU are both between 62.45 and 743.48, revealing that the possible risk has already occurred in the study area. Conclusions The two methods of RQMEC/PNEC and RQSTU based on DGT-labile metal concentrations are effective and suitable to estimate the toxicity of metal mixtures in sediments.

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Copper ecological risk assessment using DGT technique and PNEC: A case study in the Brazilian coast

Cited by 20 publications

References 56 publications

Quantitative Analysis of Heavy Metal Pollution Sources, Influencing Factors, and Delineation of Pollution Risk Areas in Industrial Soil: A Combined Application of Receptor Models and GeoDetector

Quantitative Analysis of Heavy Metal Pollution Sources, Influencing Factors, and Delineation of Pollution Risk Areas in Industrial Soil: A Combined Application of Receptor Models and GeoDetector

Ecological risk assessment of metallic nanoparticles on the marine environments: Species sensitivity distributions analysis

Risk assessment of eight metals and their mixtures to aquatic biota in sediments with diffusive gradients in thin films (DGT): a case study in Pearl River intertidal zone

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