Environmental Reactivity of PET Microplastics as Vectors for Toxic Metals in Aquatic Systems

doi:10.21203/rs.3.rs-7710311/v1

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Environmental Reactivity of PET Microplastics as Vectors for Toxic Metals in Aquatic Systems

https://doi.org/10.21203/rs.3.rs-7710311/v1

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This study investigates the adsorption behaviour of toxic metals (Pb, Cr, Zn, Cu, Cd, Hg) onto polyethylene terephthalate (PET) microplastics under various aquatic conditions. Two PET particle size fractions (<0.63 µm and 0.63–1 mm) were examined in both freshwater and simulated seawater environments. The adsorption mechanisms were assessed using Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich isotherm models. The results indicate that adsorption capacity is significantly affected by particle size and water chemistry, with a higher metal uptake observed in freshwater. Adsorption energies (0.68–2.95 kJ/mol) suggest physical adsorption. FTIR analysis revealed structural changes in PET, including degradation at 1560, 1540, and 1520 cm⁻¹, particularly following the adsorption of Cu, Zn, Cd, and Hg. These findings demonstrate that PET microplastics function as chemically active carriers of heavy metals, enhancing their mobility and bioavailability in aquatic ecosystems. Even weak non-covalent interactions can induce polymer degradation, increasing environmental reactivity and ecological risk.

PET microplastic

toxic metals

adsorption

interaction

degradation

The global production of plastics is increasing, and environmental protection is of great importance and significant concern. Microplastics have been detected in aquatic, terrestrial, and atmospheric environments (the aquatic environment being the most explored), as well as in biota. Plastic consumption and production have followed an exponential growth trend since the 1950s and are projected to reach approximately 1,800 million tons by 2050 (Tirkey et al., 2022). Around 90% of global plastic production consists of PET, HDPE, PVC, LDPE, PP, PS, and PUR (Phuong et al., 2016). For instance, global plastic production was 270 million metric tons in 2010, increased to 348 million metric tons in 2017, and reached 367 million metric tons by 2020 (Shi et al., 2023a). The annual worldwide production of PET is approximately 40 million tonnes and is growing at ca. 7% per year. Of these, approximately 65% are used to make fibers, 5% films, and 30% packaging.

Annually, between 4 and 12 million tons of plastics are released into the oceans, and it is estimated that over 250 Mt of plastics will be accumulated in the oceans by 2025. The rest of the waste, between 22% and 43%, ends up at landfills, and only approximately 20% of this waste is recycled or incinerated. However, most of the plastic waste is non-biodegradable and the decomposition could take up to 500 years (Tourinho et al., 2019). It is estimated that at least 14 million tons of plastic end up in the ocean annually. Plastic debris is the most abundant type of litter in the ocean, constituting approximately 80% of all marine debris (Chassignet et al., 2021). This includes various plastic items, such as bottles, bags, packaging materials, fishing gear, and microplastics, which come from land-based sources, including rivers. The current state-of-the-art prediction is that between 1.15 and 2.41 million tons of plastics flow from the global river system into the oceans each year. Over 90% of the plastic inputs to the oceans come from 103 rivers located in Asia, 8 in Africa, 8 in South and Central America and 1 in Europe. Asia accounts for more than two-thirds (67%) of the global annual input of plastics to the oceans (Zhang et al., 2023). It is estimated that the ocean already contains over 150 million tons of plastic (Eriksen et al., 2014), and this amount is projected to nearly double to 250 million tons by 2025 (Jambeck et al., 2015).

Plastic waste is a major threat due to its accumulation in rivers and subsequently in the seas and oceans (Naqash et al., 2020). The presence of microplastics in the environment is becoming a crucial global and significant environmental and health problem. Plastic waste is usually generated (i) by inhabitants, varying according to their habits, geographic location, and existing infrastructure; (ii) by waste management and treatment; and (iii) by industrial and manufacturing plants. Once microplastics enter the environment, they are transported by wind, washed off from land by rainfall, and subsequently transported in fresh water and seawater. Land-based microplastics are introduced into water bodies through wastewater treatment plant effluents and industrial discharges. Microplastics are found in both natural and human-made water cycles, including municipal sewage and wastewater treatment plants, where they come from various sources, such as domestic washing and personal care products (Omidi and Kakanejadifard, 2018; Omidi and Kakanejadifard, 2018; Lin et al., 2020a).

Microplastics (MPs) pollute aquatic, terrestrial, and atmospheric environments and are interconnected via diverse networks of source-pathway-sink connections that influence the flux and retention of MPs in the environment. Nevertheless, most studies conducted in last decades are aimed at the aquatic pollution(Amelia et al., 2021a; Lacerda et al., 2019; Kukkola et al., 2021). These studies confirm the distribution of microplastics from tropical regions to polar regions. Microplastics have also been found in icy snow samples at the summit of Mount Everest, as well as in the deep sea (Napper et al., 2020; Mishra et al., 2021). These facts confirmed that microplastics could be transported to aquatic and terrestrial environments, as well as to the atmosphere, including the most remote and seemingly undisturbed areas. This is a serious problem that requires further research and effort to combat microplastic pollution and protect our planet.

Based on the size of the plastic part, plastics can be divided into macroplastics (> 25 mm), mesoplastics (5–25 mm), large microplastics (1–5 mm), small microplastics (20 µm − 1 mm) and nanoplastics (< 0.1 µm) (Boyle and Örmeci, 2020). Plastic debris can be divided into four categories: megaplastic (> 50 cm), microplastic (5 − 50 cm), mesoplastic (0.5 − 5 cm) and microplastic (< 0.5 cm) (Boyle and Örmeci, 2020). These particles are often further degraded into smaller particles – nanoplastics (Tang et al., 2020; Zon et al., 2018; Brennecke et al., 2016). The International Organization for Standardization has defined nanoparticles as objects with their external dimensions falling into nanoscale (1 − 100 nm). MPs come in various shapes (pellets, fragments, and fibers) and colors. Polyethylene (PE), polypropylene (PP), and polystyrene (PS) are among the most used polymers. (Amelia et al., 2021b; Holmes et al., 2012; Binda et al., 2021). The size, shape, color, and density of microplastics are important for their bioavailability and degradation. The shape, size, and density of microplastics affect their dispersal through natural currents, with large, dense particles sinking easily, irregular-shaped particles remaining underwater, and spherical-shaped particles remaining on the surface. Most of these micro-fragments can accumulate in the central oceanic regions (termed “gyres” - a system of ocean currents that move in a circular pattern). So-called “Stokes drifts” generate the transport of MPs from the open sea to shallow coastal waters. A phenomenon of biofouling is often observed as organisms colonise the surface of plastic fragments and form biofilms, which results in aggregates forming and the speed of sedimenting increasing rapidly (da Costa et al., 2017a; Amelia et al., 2021b; Binda et al., 2021; Brennecke et al., 2016; Omidi and Kakanejadifard, 2018).

The four main factors that can play a role in MPs degradation are biodegradation, hydrolysis, photodegradation and thermooxidative degradation. Biodegradation has been studied extensively in recent years as a promising method for degrading MPs. It is defined as the breakdown of complex polymers by microorganisms (archaea, bacteria, and fungi) into nontoxic products that are reintroduced into biogeochemical cycles. These mechanisms include biodeterioration, biofragmentation, assimilation, and mineralization.

Plastic degradation in the environment can be influenced by both abiotic and biotic factors simultaneously. Typical abiotic degradation is mechanical due to weather and climate change (e.g., freezing, thawing, pressure changes, water turbulence, abrasion, and mechanical damage activities), and only morphological changes occur without the impact of molecular bonds. The molecular bond breakage is caused by chemical degradation through photooxidation (UV 290–400 nm and VIS 400–700 nm), thermal oxidation (150 to 800°C), hydrolysis and changes of alkalinity and salinity (Shah et al., 2013; Yang et al., 2015; Auta et al., 2018; Auta et al., 2018; Zhang et al., 2020a; Chen et al., 2020; Corcoran, 2021; Enfrin et al., 2020). The negative effects of plastic debris on biota are both of physical and chemical nature, therefore, plastic debris potentially acts as a multiple stressor to organisms. Physical negative effects include ingestion, entanglement and smothering (Bai et al., 2020; Chamas et al., 2020; Dong et al., 2020). The negative chemical effects are a result of the presence of chemicals of two types: (i) additives and polymeric raw materials and (ii) chemicals absorbed from the surrounding ambience (Huang et al., 2021a).

Several studies on aquatic organisms have shown harmful, if not lethal, effects of microplastics at the individual, cellular, and molecular levels. Aquatic organisms and aquatic-dependent wildlife can be selective in the types, forms, colors, and sizes of plastics they ingest, depending on their foraging techniques and diet. The toxicity of microplastics may depend on their size, shape, and surface coating. Unmodified polymers were shown to affect cell viability, inflammatory gene expression, and cell morphology in vitro. The ability to interfere with cell processes is greatly enhanced when charge is introduced to the MNPs particles (Mao et al., 2020; Ta and Babel, 2020; Tunali et al., 2020; da Costa et al., 2017b; da Costa et al., 2016; Guo et al., 2020a; Brennecke et al., 2016) .

It is well-known that a wide range of wild animals (amphipods, copepods, lugworms, barnacles, mussels, decapod crustaceans, seabirds, fish, and turtles) confuse plastic debris for food and ingest it. Low-density (i.e., buoyant) microplastics are ingested by pelagic filter feeders, whereas high-density microplastics tend to be ingested by benthic deposit feeders. In most cases, MPs are excreted rapidly, however, for very small MNPs, translocation from the GIT to the circulatory system was observed. Microplastics transfer throughout the food chain, however, there are no data demonstrating their bioaccumulation or biomagnification (Tunali et al., 2020; Barros and Seena, 2021; Naqash et al., 2020).

Recent studies have confirmed the key role of microplastics as significant contaminant vectors in aquatic and terrestrial ecosystems. MPs function as vectors of pollutants that can transport, distribute, and release various pollutants in the environment including heavy metals, old contaminants (polychlorinated biphenyls, polycyclic aromatic hydrocarbons polybrominated diphenyl ethers) and new pollutants (pharmaceuticals, polyfluoroalkyl substances)(Kumar et al., 2021; Sall et al., 2020; Yu et al., 2019). These contaminants originate from industrial discharge, urban runoff, and other pollution sources (Aghilinasrollahabadi et al., 2021; Zhang et al., 2020b). The coexistence of plastic debris and heavy metal pollutants in the ecosystem is a matter of concern (Liu et al., 2022; Liu et al., 2021). The adsorption of heavy metals onto plastics and their potential desorption play a crucial role in understanding the ecological risks associated with microplastics in the environment.

The adsorption process occurs when hazardous metal ions meet the microplastic surface, and electrostatic interactions or chemical bonding cause them to adhere to plastic particles(Cao et al., 2021a; Zou et al., 2020; Huang et al., 2021b; Guo and Wang, 2019; Zou et al., 2020; Guo et al., 2020b). This adsorption phenomenon can vary (Huang et al., 2021b), depending on the type of plastic (Mao et al., 2020; Santos-Echeandía et al., 2020), crystallinity (Fred-Ahmadu et al., 2020; Torres et al., 2021), size differences (Ta and Babel, 2020; Leiser et al., 2020), the composition of the surrounding environment, and the characteristics of the metal ions. The small size and large surface area of microplastics provides ample opportunities for heavy metals to adsorb onto their surfaces (Cao et al., 2021a; Zou et al., 2020; Xie et al., 2021; Ta and Babel, 2020; Sarkar et al., 2021).

Once heavy metals are adsorbed onto microplastics, they may remain attached or have the potential to desorb back into the surrounding environment. Adsorption and desorption can be influenced by various factors, including changes in environmental conditions, such as pH, temperature, salinity, and the coexistence of other ions (causing more serious composite pollution). It is essential to understand the desorption kinetics and mechanisms to assess the potential release of heavy metals from microplastics back into the ecosystem (Naqash et al., 2020; Zou et al., 2020; Wang et al., 2020; Zou et al., 2020; Lin et al., 2021; Shen et al., 2021; Huang et al., 2021c; Tang et al., 2020).

The presence of heavy metals in microplastics and their potential desorption can pose ecological risks to organisms in the environment. If microplastics with adsorbed heavy metals are ingested by aquatic organisms, the metals may be released into their digestive tracts, potentially causing toxic effects. It has been reported that the combined exposure of MPs and heavy metals has negative effects on aquatic organisms such as microalgae, fish, mussels, and oysters (Tunali et al., 2020; Yang et al., 2020; Lin et al., 2020b; Fernández et al., 2020; Petersen and Hubbart, 2021).

Despite growing awareness of microplastics as pollutant carriers, there is a lack of detailed mechanistic understanding of how PET microplastics interact with heavy metals in different aquatic environments. Specifically, the influence of particle size and ionic strength on adsorption capacity and polymer integrity is underexplored. This knowledge gap limits our ability to assess the long-term environmental risks posed by PET microplastics in freshwater and marine systems.

The aims of this study were to (1) analyse the adsorption mechanism of hazardous metals Pb, Cr, Zn, Cu, and Hg on PET microplastic particles under laboratory conditions, (2) compare the adsorption characteristics of five heavy metals on PET, and (3) apply isotherm models to predict risk assessment. This study is crucial in identifying the environmental risks associated with the concurrent presence of heavy metals and PET in the environment. It also aims to elucidate the mechanisms and roles of microplastics (MPs) in contributing to long-term global pollution. The novelty of this research lies in its comprehensive and mechanistic approach to understanding the interactions between PET microplastics and multiple toxic metals under conditions that are environmentally relevant. To the best of our knowledge, no prior study has concurrently investigated six hazardous metals across two particle size fractions and two water chemistries, while also incorporating adsorption modelling, thermodynamic analysis, and FTIR-based structural assessment.

Materials

The plastic powder of polyethylene terephthalate (PET) was obtained from PETKA CZ, a.s. (Czech Republic) with a density of approximately 1.4 g/cm³ and particle size < 500 µm and stored in a dark glass bottle. In this study, for the characterization of the surface morphology of PET, the powder was examined by a scanning electron microscope (SEM - JOEL JSM-7600F), presented as the PET I with size < 0.63 µm (a) and PET II with large size in the range 0.63 µm to 1.00 mm (b) (Fig. 1.).

Specific functional groups were identified using Fourier Transform Infrared Spectroscopy (FTIR ALPHA II, Bruker Optic Instruments) with an attenuated total reflection (ATR) attachment of the diamond crystal and were applied to collect the infrared (IR) spectra (range: 4000–600 cm^− 1; resolution: 4 cm^− 1). PET was first sieved into two fractions: I (< 0.63 µm (small fraction)) and II (0.63 µm − 1 mm (large fraction)). Both fractions were divided and weighed into plastic containers (approximately 50 mg each) and stored in a cool, dry place for subsequent adsorption experiments. The laboratory seawater was prepared to simulate the conditions in real sea water (simulated seawater – SW), with the following composition: NaCl 24.530 g/L, MgCl₂ 5.200 g/L, Na₂SO₄ 4.090 g/L, CaCl₂ 1.160 g/L, KCl 0.695 g/L, NaHCO₃ 0.201 g/L, and KBr 0.101 g/L.

The certified standard solutions metal ions of Pb, Cr, Zn, Cu, Cd, Hg with concentration of 1 ± 0.002 g/L were purchased as CRM ASTASOL— Pb (ANS041), Cr (ANS079), Zn (ANS069), Cu (ANS015), Hg (ANS024) (AN7010N ) from ANALYTIKA®, spol. s r.o., CZ. Metal ion solutions for adsorption kinetics and isotherm experiments were prepared from standard metal solutions and high-purity Milli-Q water (Millipore purification system) with a resistivity higher than 18 MΩ/cm.

Experimental design

Batch adsorption experiments for Pb, Cr, Zn, Cu, Cd and Hg ions were performed with various concentrations of metals and various fractions in fresh water (FW, deionized water) and salt water (SW, simulated sea water). Approximately 50 mg of PET was weighed in each case, and 40 ml of a heavy metal stock solution, which was prepared from standards, was added to glass vials at laboratory temperature (293 ± 2 K). The solutions with concentrations 0.5–40 mg/L for Pb, 0.5–10 mg/L for Cr, 0.05–20 mg/L for Cu, 1–20 mg/L for Zn, 0. 05–1.5 mg/L for Cd were prepared. For Hg, solutions with concentrations 0.5–20 mg/L were prepared. The mixture was then shaken for 96 h in a glass vial. The solutions were filtered through syringe filters PP with pore size 0.22 µm and then measured using analytical methods described in Section 2.3. Three parallel samples and three blanks for each metal adsorption sample were also prepared.

Chemical analysis

The metal concentrations (Pb, Cr, Zn, Cd and Cu) in the solutions were determined using flame atomic absorption spectrometry (F-AAS) (Solar M6, Thermo Analytic). The burner height and gas flow were optimized for each element. The metals were measured using primary wavelengths – 213.9 nm for Zn, 217.0 nm for Pb, 357.9 nm for Cr, 324.8 nm for Cu and 228.8 nm for Cd. An atomic vapor generator AMA 254 (Advanced Mercury Analyzer) was used to precisely determine the mercury concentrations in all solutions. The standard of mercury solution (check standard) was prepared using 0.5 mL concentrated HNO₃ solution and 0.5 mL concentrated HCl and 0.5 mL K₂Cr₂O₇ (1%) solutions and adding 10 µL of calibrating standard of mercury solution with the concentration of 1 g/L, diluted to 50 mL. Quality and accuracy control was provided using a standard measurement protocol and certified standard. The accuracy of the metal concentrations in solutions determined by F-AAS was ensured through 10 repeated analyses of metal standards, and results in the range ± 5% of the certified values were found. The limits of detection (LOD) and quantification (LOQ) were also calculated. The calculated LOD values were 0.014 mg/L for Pb, 0.007 mg/L for Cr, 0.006 mg/L for Zn, 0.005 mg/L for Cu, 0,003 mg/L for Cd and 0.013 ng/L for Hg, and LOQ values were 0.048 mg/L for Pb, 0.025 mg/L for Cr, 0.021 mg/L for Zn, 0.018 mg/L for Cu, 0.011 mg/L for Cd and 0.045 ng/L for Hg. The correlation coefficients (r) were in the range of 0.98–0.99.

The sorption capacity, q_e (mg/g), which indicates the amount of ions adsorbed per unit mass of PET in the equilibrium state, was calculated using Eq. (1):

$$\:{q}_{m}=\frac{\left({c}_{0}-{c}_{e}\right)\:V}{m}$$

where q_e is the amount of metal adsorbed (mg/g), c₀ is the initial metal ion concentration (mg/L), c_e is the equilibrium metal ion concentration (mg/L), V is the volume of the aqueous phase (L), and m is the amount of adsorbent (PET) used (g).The analysis of PET after the adsorption experiments involved infrared spectrometry with Fourier transform. Both pure PET and PET after adsorption of heavy metal ions (concentration of 10 mg/L) were analysed. IR spectra were measured using an ALPHA II (Bruker Optics Instrument) with an attenuated total reflection (ATR) module. The PET samples were air-dried before analysis to avoid interference from water bands in the central region of infrared radiation.

Adsorption isotherms

Adsorption isotherms are mathematical models that describe the equilibrium relationship between the concentration of the adsorbate (the substance being retained on the surface) in the liquid or gas phase and the amount of adsorbate adsorbed onto the surface of the adsorbent material. Several types of adsorption isotherms have been developed, based on experimental observations and theoretical considerations.

The Langmuir isotherm assumes a monolayer adsorption on a homogeneous surface, where the adsorption sites have equal energies and there is no interaction between adsorbed molecules. The Freundlich isotherm is an empirical model that accounts for multilayer adsorption on heterogeneous surfaces. It is assumed that the adsorption capacity increases exponentially with increasing concentration. The Temkin isotherm considers the adsorbent-adsorbate interactions if the heat of adsorption decreases linearly with coverage. The Dubinin-Radushkevich (D-R) isotherm is a commonly used adsorption isotherm model that considers the porous nature of an adsorbent and assumes that the adsorption process occurs via physical adsorption on a heterogeneous surface. This method is particularly suitable for analysing adsorption on microporous materials. The exponential term in this equation accounts for the energy distribution of adsorption sites within the adsorbent material. The lower the value of β, the higher the adsorption energy, indicating stronger adsorption (Mozaffari Majd et al., 2022; Khan et al., 2019; Rajahmundry et al., 2021; Martinez–Vargas et al., 2018). The isotherm models, corresponding equations, and characteristic parameters are summarized in Table 1.

Table 1

Summary of isotherm model with relation equations, plots and parameters
Isotherm model	Equation	Plot	Characteristic constant
Langmuir	Linear $\:\frac{{c}_{e}}{{q}_{e}}=\frac{{c}_{e}}{{q}_{m}}+\frac{1}{{K}_{L}\:{c}_{e}}$ Nonlinear $\:{q}_{e}=\:\frac{{q}_{m}\:{K}_{L}\:{c}_{e}}{1+\:{K}_{L}\:{c}_{e}}$	$\:\raisebox{1ex}{$1$}\!\left/\:\!\raisebox{-1ex}{${q}_{e}$}\right.$ vs $\:\raisebox{1ex}{$1$}\!\left/\:\!\raisebox{-1ex}{${c}_{e}$}\right.$	K_L (L/mg) $\:{q}_{m}\:$ (mg/g)
Freundlich	Linear $\:\text{log}{q}_{e}=\text{log}{K}_{F}+\:\frac{1}{n}\:\text{log}{c}_{e}$ Nonlinear $\:{q}_{e}=\:{K}_{f}\:{c}_{e}^{\frac{1}{n}}$	log $\:{q}_{e}$ vs log $\:{c}_{e}$	K_F ((mg/g)(L/mg)^1/n) 1/n
Temkin	Linear $\:{q}_{e}=\:\frac{R\:T}{{B}_{T}}\text{ln}{K}_{T}+\:\frac{R\:T}{{B}_{T}}\text{ln}{c}_{e}$ Nonlinear $\:{q}_{e}=\:\frac{R\:T}{{B}_{T}}\text{ln}({A}_{T}\:{c}_{e})$	$\:{q}_{e}$ vs ln $\:{c}_{e}$	$\:{A}_{T}\:$(L/mg) $\:{B}_{T}\:$ (J/mol)
Dubinin Radushkevich (D-R)	Linear $\:\text{ln}{q}_{e}=\text{ln}{q}_{s}\:-\:Kad{\epsilon\:}^{2}$ $\:\epsilon\:=R\:T\text{ln}(1+\:\frac{1}{{c}_{e}})$ Nonlinear $\:{q}_{e}=\:{q}_{s}\:{e}^{\left(-{K}_{ad}\:{\epsilon\:}^{2}\right)}\:\:$	$\:\text{ln}{q}_{e}$vs $\:{\epsilon\:}^{2}$	$\:{K}_{ad}\:$(mol²/kJ²) $\:\epsilon\:$ (kJ/mol) E (kJ/mol)
c_e - equilibrium concentration (mg/L), q_m - maximum capacity of adsorption (mg/g), K_L - Langmuir adsorption constant (L/g), 1/n - the intensity of the adsorption or surface heterogeneity, K_F - constant of Freundlich isotherm ((mg/g)(L/mg)^1/n), A_T - equilibrium binding constant (L/mg), B_T - Temkin heat of adsorption constant (J/mol), R - the universal gas constant, 8.314 Jmol^− 1 K^− 1, T - temperature of the system (K), q_s - D–R constant, K_ad - Dubinin–Radushkevich isotherm constant (mol²/kJ²), ε - the adsorption polanyi potential (kJ/ mol), E – sorption energy $\:{\left(\sqrt{2{K}_{ad}}\:\right)}^{-1}$ (kJ/mol)

Model analysis

Linear regression is one of the most widely used tools for defining the most suitable relationship, quantifying the distribution of adsorbates and evaluating the validity of the theoretical model assumptions (Foo and Hameed, 2010). The accuracy and suitability of the adsorption model in correlation with experimental data are usually evaluated based on the coefficient of determination (R²) or the correlation coefficient (r). Therefore, adsorption and kinetic linear models were applied, with model constants calculated from the slope and intercept of their respective linear regressions. The goodness of fit was assessed using the coefficient of determination (R²) and the adjusted R². In contrast, nonlinear optimization offers a more mathematically rigorous method by estimating parameters directly from the original nonlinear form of the adsorption equation (Martinez–Vargas et al., 2018). The predictive performance of the different models was evaluated using the squared correlation coefficient (R²), adjusted R² (Adj-R²), and root mean square deviation (RMSD). Additionally, reduced chi-square (χ²) statistics were calculated by dividing the variance of the fit by the average variance of the observed data to further assess fit quality (Revellame et al., 2020);.

1.1 Data analysis

The experimental data obtained from the adsorption kinetics and isotherms were analysed and fitted using Origin 2018 software. Statistical data analysis was performed using STATISTICA® software (version 12.5) and Origin 2021 was used for data visualization. The sorption isotherm constants and parameters were calculated using linear regression analysis. Basic data diagnostics to identify outliers were performed at a significant level of α = 0.05 (Grubbs test). Duncan’s test was used to analyse significant differences at p < 0.05.

Adsorption isotherms

Various isotherm equations have been applied to characterize the equilibrium adsorption of Pb, Hg, Zn, Cu, Cr and Cd onto PET in two distinct particle fractions: small (< 0.63 µm) and large (0.63 µm to 1 mm), as well as in freshwater (FW) and simulated seawater (SW). The corresponding mathematical expressions are listed in Table 1. The adsorption isotherm data (qm vs. c_e) analysed in this study are presented in Figs. 2, with the related adsorption parameters listed in Table 2. The Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich (D-R) isotherms, along with their linearized formulas, were used to calculate the adsorption parameters, as shown in Table 2.

Table 2
The result of isotherm analysis of adsorption of Pb, Hg, Zn, Cr, Cu and Cd on the PET with various fractions in freshwater (FW) and salt water (SW)
Element	Isotherms	Parameters	Small fraction (I)		Large fraction (II)
Element	Isotherms	Parameters	Fresh water (FW)	Salt water (SW)	Fresh water (FW)	Salt water (SW)
Pb		q_exper, mg/g	3.128	1.155	3.454	3.120
	Langmuir	q_max, mg/g	3.761	1.142	3.323	2.680
		K_L, L/mg	0.180	0.350	0.240	0.244
	Freundlich	n, mg/g	3.760	1.140	3.320	4.800
		K_F, (L/mg)^1/n	1.980	1.490	2.260	3.240
	Temkin	B_T, J/mol	0.686	0.402	0.819	1.175
	D-R	E, kJ/mol	2.403	1.080	2.510	2.450
Hg		q_exper, mg/g	1.720	1.100	1.100	1.230
	Langmuir	q_max, mg/g	2.020	0.920	1.056	0.744
		K_L, L/mg	0.342	0.326	0.339	0.268
	Freundlich	n, mg/g	2.020	0.921	1.050	0.744
		K_F, (L/mg)^1/n	2.002	1.351	1.430	1.221
	Temkin	B_T, J/mol	0.694	0.301	0.359	0.199
	D-R	E, kJ/mol	0.904	1.230	1.680	1.340
Zn		q_exper, mg/g	3.200	2.010	3.200	2.290
	Langmuir	q_max, mg/g	3.460	2.166	3.092	2.040
		K_L, L/mg	0.511	0.288	0.623	0.480
	Freundlich	n, mg/g	3.460	2.160	3.090	2.040
		K_F, (L/mg)^1/n	5.860	1.860	6.860	2.665
	Temkin	B_T, J/mol	1.760	0.624	1.926	0.981
	D-R	E, kJ/mol	2.410	0.680	2.470	1.990
Cr		q_exper, mg/g	2.390	2.850	3.900	2.200
	Langmuir	q_max, mg/g	2.310	2.490	4.190	2.206
		K_L, L/mg	0.182	0.498	0.591	0.284
	Freundlich	n, mg/g	2.310	2.491	4.190	2.206
		K_F, (L/mg)^1/n	1.520	3.460	1.930	1.870
	Temkin	B_T, J/mol	0.422	1.243	2.470	0.421
	D-R	E, kJ/mol	2.205	2.470	2.760	1.180
Cu		q_exper, mg/g	4.000	3.240	3.610	2.710
	Langmuir	q_max, mg/g	4.250	3.105	3.110	2.726
		K_L, L/mg	0.474	0.421	0.325	0.451
	Freundlich	n, mg/g	4.250	3.105	3.112	2.726
		K_F, (L/mg)^1/n	7.540	3.690	2.750	3.416
	Temkin	B_T, J/mol	2.021	1.305	1.014	0.813
	D-R	E, kJ/mol	2.207	2.370	1.960	2.130
Cd		q_exper, mg/g	4.300	3.670	5.400	2.050
	Langmuir	q_max, mg/g	4.180	2.701	5.700	2.046
		K_L, L/mg	0.385	0.392	0.354	0.349
	Freundlich	n, mg/g	4.181	2.701	5.701	2.045
		K_F, (L/mg)^1/n	5.220	2.887	7.564	2.040
	Temkin	B_T, J/mol	1.654	1.060	2.023	0.716
	D-R	E, kJ/mol	2.950	2.320	2.610	1.910

The linearized forms of these isotherms were used for analysis: the Langmuir linearized isotherm was plotted as 1/q_e vs. 1/c_e, the Freundlich linearized isotherm as log q_e vs. log c_e, the Temkin linearized isotherm as q_e vs. ln c_e, and the D-R isotherm as ln q_e vs. ε². The D-R isotherm also allows for the calculation of adsorption energy. The best-fitting adsorption models were evaluated using the coefficient of determination (R²) and the adjusted R² (R²_adjust), which ranged from 0.71 to 0.98. The most suitable models were as follows: Zn followed the Freundlich adsorption model; Hg and Cd adhered best to the Langmuir adsorption model; and Pb and Cu showed the best fit with the Temkin adsorption model.

The adsorption capacity of heavy metals based on experimental results for adsorbed amounts follows the order: small fraction in freshwater – Cd > Cu > Zn > Pb > Cr > Hg, large fraction in freshwater – Cd > Cr > Cu > Pb > Zn > Hg; small fraction in salt water - Cd > Cu > Cr > Zn > Pb > Hg and large fraction in salt water – Pb > Cu > Zn > Hg > Cr > Cd. Overall, the adsorption conditions, including the environment and PET fraction size, significantly influence the metal sorption process. Heavy metal ions can be adsorbed on the surface of microplastics (MP) through electrostatic interactions with charged or polarized regions, whereas neutral metal-organic complexes are bound to this surface through non-specific interactions (Cao et al., 2021b). This study confirmed that adsorbed concentrations of Hg and Pb were relatively lower than that of other metals in freshwater without considering size fractions. These facts confirmed the effect of the different reactivity and effect of partition coefficient of hazardous metals on the adsorption process (Nazareth et al., 2019; Purwiyanto et al., 2020).

The D-R isotherm allows to calculate the free energy and the adsorption energy. In case of E < 8 kJ/mol, it means physical adsorption is taking place, while 8 < E < 16 kJ/mol points to chemical ion exchange or chemisorption (Zhou et al., 2021). The calculated energy was obtained in the range of 0.68–2.95 kJ/mol, which indicates physical adsorption. Figure 3 presents the two-dimensional energy data for adsorbed hazardous metals on PET with respect to the PET size fraction and the type of water conditions.

The highest adsorption energy was found for Cd (2.95 kJ/mol) for the adsorption conditions on the small fraction and in fresh water and the lowest was found for Zn (0.68 kJ/mol), again in fresh water and for the small size fraction. Table 3 lists the adsorption free energy (kJ/mol) among study metals, fractions and type of water conditions.

Table 3
Comparison of adsorption free energy (kJ/mol) among Pb, Hg, Zn, Cr, Cu, Cd; fractions I and II and type of water conditions (FW-freshwater. SW – salt water)
	FW, I	FW, II	SW, I	SW, II
Pb	2.40	2.51	1.08	2.45
Hg	0.90	1.68	1.23	1.34
Zn	2.41	2.47	0.68	1.99
Cr	2.21	2.76	2.47	1.18
Cu	2.21	1.96	2.37	2.13
Cd	2.95	2.61	2.32	1.91

Influence of fraction on the adsorption

The interaction between microplastics and pollutants depends on various factors such as the type of microplastic, particle size and type of contaminant.

As can be seen in Fig. 4, Pb exhibited a high adsorbed amount onto large fraction II (except for adsorption of smaller fraction in seawater). On the contrary, Hg exhibited the smallest amount of all metals in all tested conditions, while Zn showed medium amount in all cases. The adsorbed amounts of Cu and Cd were high. In all cases, the effect of the higher ionic strength prevails over the effect of larger active surface area, hindering the adsorption process. Considering individual metals, their adsorbed amounts in different conditions ascend as follows: Pb: I in SW (1.15 mg/g) < II in SW (3.12 mg/g) < I in FW (3.13 mg/g) < II in FW (3.45 mg/g); Hg: I in SW ≈ II in FW (1.10 mg/g) < II in SW (1.23 mg/g) < I in FW (1.72 mg/g); Zn: I in SW (2.01 mg/g) < II in SW (2.29 mg/g) < II in SW ≈ I in FW (3.20 mg/g); Cr: II in SW (2.20 mg/g) < I in FW (2.39 mg/g) < I in SW (2.39 mg/g) < II in FW (3.90 mg/g); Cu: II in SW (2.71 mg/g) < I in SW (3.24 mg/g) < II in FW (3.61 mg/g) < I in FW (4.00 mg/g); Cd: II in SW (2.05 mg/g) < I in SW (3.67 mg/g) < I in FW (4.30 mg/g) < II in FW (5.40 mg/g).

The differences between small and large size fractions vary among the metals. Based on PCA analysis (Fig. 5), it can be stated that the adsorption behaviour of hazardous metals is similar between the elements Pb and Hg adsorbed on a small fraction and mercury adsorbed on a large fraction. The adsorption behaviour of Zn element is not significantly affected by the size of the PET fraction; approximately identical interactions can be assumed for the elements Cu and Cr in both fractions. However, Cd probably has a different behaviour with respect to the size of the fraction. The adsorption of Hg on PET is approximately the same in both fractions. Adsorption behavior for Cd, Pb, and Cr was more strongly influenced by particle size compared to Zn and Hg. This finding, derived from PCA analysis, highlights the suitability of PCA as a tool for evaluating the interactions of hazardous elements with PET. That shows clear influences of size fraction on the adsorption mechanism. The hypothesis was that the amount of metal adsorbed on smaller fraction would be much more significant compared to the bigger fraction due to a larger active surface area per unit mass and as a result, increased number of active sites available for interaction with the metal ions. However, the results of the experiments indicate other factors, which likely include surface chemistry and solution chemistry, also played a significant role.

Influence of water environment

In this study, conventional PET with fractions of different sizes adsorbed heavy metals under different water conditions, specifically in freshwater (FW) and model seawater (SW), see Fig. 6. All metals show considerably higher adsorbed amounts in fresh water than in sea water. This is likely due to differences in interaction of various ions in freshwater and salt water. Seawater has a higher ionic strength due to dissolved salts, and the adsorption process is therefore affected by competition with hazardous metal ions on the PET surface. The adsorption equilibrium and the mechanism of metal ion adsorption onto microplastics (MPs) are significantly influenced by the ionic strength of the surrounding water, due to the formation of competitive adsorption sites. Given that MPs typically carry a negative surface charge, their adsorption behavior is largely governed by electrostatic interactions. (Dimassi et al., 2023; Jian et al., 2022).

The ions Na⁺ and Cl⁻, which are present in waters in different concentrations and especially in higher concentrations in seawater, have a significant effect on the sorption processes of inorganic ions and organic compounds. The presence of NaCl in the solution also partially neutralizes the negative charge at the adsorption site on the surface of MPs(Vilar et al., 2005; Tang et al., 2021). In seawater, electrostatic repulsion may also be of great importance and complexes (such as MeCl⁺, MeCl⁰₂, MeCl⁻ ₃ and Me(OH)Cl⁰) are also likely to form further reducing the adsorption rate. The salt water can contribute to the formation of electrostatic shielding among positively charged metals and negative charged MPs surfaces, and the salt ions can compete for the limited adsorption sites on MPs surfaces (Shi et al., 2023a). With the increase of water ionic strength in the case of adsorption experiment in salt water, the adsorption of hazardous metals onto PET increased in order: in the case of small fraction (I) Hg < Pb < Zn < Cr < Cu < Cd and in the case of large fraction (II) Hg < Cr < Zn < Cu < Cd < Pb.

The influence of type of water (freshwater and salt water) was also analysed using PCA. The results of PCA are presented graphically in Fig. 7. PCA analysis again confirmed the influence of different water environments on the adsorption process of metal ions onto PET. From Fig. 7 it is evident that for all metal ions there was a change in adsorption in fresh and salt water, which was reflected in the inclusion of the same elements in different environmental conditions in different quadrants. The most striking differences in the influence of water type and therefore also ionic strength were observed for Pb and Cd ions.

FTIR analysis

The FTIR analysis of PET microplastics revealed several distinct bands with characteristic peak wavenumbers in cm^− 1. These bands provide important information about the chemical structure and properties of PET microplastics (Fig. 8).

The FTIR spectra of PET microplastics showed the following characteristic bands: 2918.51 cm^− 1 corresponded to CH stretching; 1710 cm^− 1 indicated the carbonyl group (C = O) of esters, which is a key functional group in the PET molecule; 1407.25 cm^− 1 indicated the presence of the benzyl ring; 1240 cm^− 1, which is associated with C-O-C bonds in ester groups and is ascribed to the elongation of the ester; 1090 cm^− 1, which corresponds to vibrations of the ester group; 1016.02 cm^− 1, which can be attributed to benzene’s in-plane vibration; 720 cm^− 1, which is associated with vibrations of aromatic ring (to the swaying of glycol and the out-of-plane benzene group) and 493.97 cm^− 1, which indicated the out-of-plane vibration of = C-H in the benzene group (Shi et al., 2023b).

The identification of these bands confirms the presence of key functional groups in PET microplastics. Carbonyl groups (C = O) and ester bonds (C-O-C) are characteristic of the PET structure. Aromatic rings are also an important part of the PET structure, contributing to its chemical stability and resistance to degradation (Chen et al., 2024). FTIR spectra of smaller fraction displayed a significantly stronger signal. This is likely due to higher surface area to volume ratio of small fraction, leading to more efficient absorption and scattering of incident IR radiation. PET particles with adsorbed hazardous metals from freshwater adsorption experiments (both fractions) were subsequently measured. Figure 9 demonstrates the PET degradation after sorption of hazardous metals. The degradation was evident in the case of Hg, Cu, and Cd. The characteristic regions of degradation were founded at several peaks, mainly peaks 1560, 1540 and 1520 cm^− 1 and double peak at 2350 cm^− 1 with region of C = O vibrations. The range 1520–1560 cm^− 1 indicates the presence of double bond, such as – CH = CH₂, which could be a site of fragmentation during the degradation of polyethylene terephthalate (PET). PET degradation could be result of the formation of various smaller molecules and fragments via the breakdown of the polymer chains.

This study presents a comprehensive analysis of the adsorption behavior of hazardous metals, specifically Pb, Cr, Zn, Cu, Cd and Hg, onto polyethylene terephthalate (PET) microplastics under varying environmental conditions. The research employed several isotherm models, namely Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich (D-R), to assess the adsorption capacity and mechanisms. The adsorption behavior differed among the metals, with Pb demonstrating high adsorption on larger fractions, whereas Hg exhibited the lowest adsorption across all tested conditions. The adsorption capacity was generally higher in freshwater compared to seawater, primarily due to differences in ionic strength and competition from other ions. The study confirmed that the adsorption energy ranged from 0.68 kJ/mol to 2.95 kJ/mol, indicating physical adsorption. Principal Component Analysis (PCA) demonstrated that the adsorption behavior of metal ions is influenced by the size of the PET fraction and the type of water conditions. The adsorption behavior of Pb and Hg was similar in small fractions, while Zn's adsorption was not significantly affected by fraction size. The adsorption of Cu and Cr exhibited similar interactions in both fractions, meanwhile Cd displayed different behavior with respect to fraction size.

Fourier Transform Infrared (FTIR) spectroscopy confirmed the presence of key functional groups in PET microplastics and identified the degradation of PET material due to the adsorption process in two regions: 2350 and 1520–1560 cm^− 1.

The findings underscore the previously underestimated role of polyethylene terephthalate (PET) microplastics as vectors for heavy metal pollutants in aquatic environments. Through weak physical interactions—primarily electrostatic attraction, ion–dipole forces, and coordination bonding—PET surfaces adsorb toxic metal ions such as Pb²⁺, Cr³⁺, Zn²⁺, Cu²⁺, and Hg²⁺. FTIR spectral shifts confirm the structural degradation of PET upon metal binding, particularly in smaller particles with higher surface reactivity.

The novelty of this work lies in demonstrating that even low-energy, non-covalent interactions can significantly alter PET’s chemical structure and enhance its environmental reactivity. The adsorption behavior is strongly influenced by water chemistry: freshwater systems promote metal uptake due to low ionic strength, while seawater conditions inhibit adsorption through ion competition and metal complexation. This comprehensive study highlights PET's active role in contaminant dynamics, particularly in freshwater systems where adsorption is most pronounced.

From an environmental risk perspective, PET microplastics not only accumulate heavy metals but also facilitate their desorption in the digestive tracts of aquatic organisms, increasing bioavailability and toxicity. This dual role—as both pollutant and carrier—raises concerns about bioaccumulation, trophic transfer, and ecosystem-level impacts, especially in freshwater habitats where adsorption is more efficient.

Future research should consider factors such as environmental conditions, the presence of other contaminants, microorganisms, and organic matter. The results underscore the importance of considering microplastic size and water chemistry in assessing the environmental impact of heavy metal pollution.

Acknowledgements

This research has been financially supported by the project FCH-S-25-8807 of Ministry of Education, Youth and Sports of the Czech Republic.

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Isotherm model	Equation	Plot	Characteristic constant
Langmuir	Linear \(\:\frac{{c}_{e}}{{q}_{e}}=\frac{{c}_{e}}{{q}_{m}}+\frac{1}{{K}_{L}\:{c}_{e}}\) Nonlinear \(\:{q}_{e}=\:\frac{{q}_{m}\:{K}_{L}\:{c}_{e}}{1+\:{K}_{L}\:{c}_{e}}\)	\(\:\raisebox{1ex}{$1$}\!\left/\:\!\raisebox{-1ex}{${q}_{e}$}\right.\) vs \(\:\raisebox{1ex}{$1$}\!\left/\:\!\raisebox{-1ex}{${c}_{e}$}\right.\)	K_L (L/mg) \(\:{q}_{m}\:\) (mg/g)
Freundlich	Linear \(\:\text{log}{q}_{e}=\text{log}{K}_{F}+\:\frac{1}{n}\:\text{log}{c}_{e}\) Nonlinear \(\:{q}_{e}=\:{K}_{f}\:{c}_{e}^{\frac{1}{n}}\)	log \(\:{q}_{e}\) vs log \(\:{c}_{e}\)	K_F ((mg/g)(L/mg)^1/n) 1/n
Temkin	Linear \(\:{q}_{e}=\:\frac{R\:T}{{B}_{T}}\text{ln}{K}_{T}+\:\frac{R\:T}{{B}_{T}}\text{ln}{c}_{e}\) Nonlinear \(\:{q}_{e}=\:\frac{R\:T}{{B}_{T}}\text{ln}({A}_{T}\:{c}_{e})\)	\(\:{q}_{e}\) vs ln \(\:{c}_{e}\)	\(\:{A}_{T}\:\)(L/mg) \(\:{B}_{T}\:\) (J/mol)
Dubinin Radushkevich (D-R)	Linear \(\:\text{ln}{q}_{e}=\text{ln}{q}_{s}\:-\:Kad{\epsilon\:}^{2}\) \(\:\epsilon\:=R\:T\text{ln}(1+\:\frac{1}{{c}_{e}})\) Nonlinear \(\:{q}_{e}=\:{q}_{s}\:{e}^{\left(-{K}_{ad}\:{\epsilon\:}^{2}\right)}\:\:\)	\(\:\text{ln}{q}_{e}\)vs \(\:{\epsilon\:}^{2}\)	\(\:{K}_{ad}\:\)(mol²/kJ²) \(\:\epsilon\:\) (kJ/mol) E (kJ/mol)
c_e - equilibrium concentration (mg/L), q_m - maximum capacity of adsorption (mg/g), K_L - Langmuir adsorption constant (L/g), 1/n - the intensity of the adsorption or surface heterogeneity, K_F - constant of Freundlich isotherm ((mg/g)(L/mg)^1/n), A_T - equilibrium binding constant (L/mg), B_T - Temkin heat of adsorption constant (J/mol), R - the universal gas constant, 8.314 Jmol^− 1 K^− 1, T - temperature of the system (K), q_s - D–R constant, K_ad - Dubinin–Radushkevich isotherm constant (mol²/kJ²), ε - the adsorption polanyi potential (kJ/ mol), E – sorption energy \(\:{\left(\sqrt{2{K}_{ad}}\:\right)}^{-1}\) (kJ/mol)

Environmental Reactivity of PET Microplastics as Vectors for Toxic Metals in Aquatic Systems

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Abstract

Figures

Introduction

Experimental

Materials

Experimental design

Chemical analysis

Adsorption isotherms

Model analysis

Results and discussion

Adsorption isotherms

Influence of fraction on the adsorption

Influence of water environment

FTIR analysis

Conclusion

Declarations

Acknowledgements

References

Supplementary Files

Status:

Version 1