Microplastics identification by infrared spectroscopy - Evaluation of identification criteria and uncertainty by the Bootstrap method

Impact of leachate from boiled-water-treated plastic products on male reproductive health: Insights from transcriptomic and metabolomic profiling

Given the extensive use of plastic materials in modern society, there is an escalating concern about the potential risks associated with exposure to plastic products. This study investigated the impact of plastic leachates from boiled-water-treated cups, including polypropylene (PP), high-density polyethylene (HDPE), low-density polyethylene (LDPE), polystyrene (PS), and polyethylene terephthalate (PET), on male reproductive health. Experimental mice were administered daily doses of the plastic leachates for 180 consecutive days. Histological analysis of the testes and epididymis was conducted, revealing vacuolization and absence of sperms in the seminiferous tubules of mice treated with PP, HDPE, LDPE, and PS, while PET exhibited lower reproductive toxicity. Furthermore, transcriptomic and metabolomic profiling were employed to identify key genes and metabolites related to plastic exposure. Transcriptome analysis showed significant changes in genes associated with spermatogenesis following exposure to leachates, while metabolome analysis indicated an impact on the lipid metabolism pathway. Overall, the study provides evidence that oral exposure to leachates from boiled-water-treated plastic cups could negatively affect spermatogenesis and lipid metabolism, thereby posing risks to male reproductive health. These findings offer crucial insights into the potential risks associated with plastic consumption and may advocate for the selection of relatively safe plastic cups for everyday use.

Enhancing Confidence in Microplastic Spectral Identification via Conformal Prediction

Microplastics are an emerging pollutant of concern, with environmental observations recorded across the world. Identifying the type of microplastic is challenging due to spectral similarities among the most common polymers, necessitating methods that can confidently distinguish plastic identities. In practice, a researcher chooses the reference vibrational spectrum that is most like the unknown spectrum, where the likeness between the two spectra is expressed numerically as the hit quality index (HQI). Despite the widespread use of HQI thresholds in the literature, acceptance of a spectral label often lacks any associated confidence. To address this gap, we apply a machine-learning framework called conformal prediction to output a set of possible labels that contain the true identity of the unknown spectrum with a user-defined probability (e.g., 90%). Microplastic reference libraries of environmentally aged and pristine polymeric materials, as well as unknown environmental plastic spectra, were employed to illustrate the benefits of this approach when used with two similarity metrics to compute HQI. We present an adaptable workflow using our open-access code to ensure spectral matching confidence for the microplastic community, reducing manual inspection of spectral matches and enhancing the robustness of quantification in the field.

Levels and Classification of Microplastics and Their Impact on the Wellbeing of Selected Commercially Important Fish Species in Kisumu Bay, Lake Victoria

Microplastics (MPs) are emerging pollutants of concern in aquatic ecosystems. Fish ingest MPs accidentally during normal feeding because they resemble prey or by ingesting prey that previously consumed them. Despite severe plastic pollution in Africa, some countries, including Kenya have implemented laws to curb this pollution menace. MPs have scantly been studied in African freshwaters. This study provides empirical data and describes the levels of MPs in four commercially important fish species in Lake Victoria. A total of 95 fish samples were collected from four sampling sites (inshore-offshore waters) between March and May 2022. Microscopy and Attenuated Total Reflectance Fourier Transformed Infrared (ATR-FTIR) spectroscopy methods were used to identify MPs. In this study, 62 out of 95 (65.26%) of the gastrointestinal tracts of the sampled fish contained MPs. The four species showed different proportions of detected MPs among the sampled individuals: 75.00% (Clarias gariepinus), 75.00% (Synodontis victoriae), 71.43% (Lates niloticus), and 59.26% (Oreochromis niloticus). Polystyrene (PS) and poly (perfluorobutadiene) were the main plastic polymers in the fish samples. The condition factors estimated for O. niloticus, S. victoriae, and L. niloticus were > 1 and < 1 for C. gariepinus, respectively. Positive correlations were observed between microplastic numbers and fish length and microplastic numbers and fish weight. However, the low R2 values obtained implied no strong relationship exists between these parameters. These findings provide evidence of microplastic contamination in fish in Kisumu Bay.

Characterization of microplastics in soil, leachate and groundwater at a municipal landfill in Rayong Province, Thailand

Recent years have witnessed a dramatic increase in global plastic production, leading to heightened concerns over microplastics (MPs) contamination as a significant environmental challenge. MP particles are ubiquitously distributed across both continental and marine ecosystems. Given the paucity of research on MPs in Thailand, particularly regarding MPs contamination in terrestrial environments, this study focused on investigating the distribution and characteristics of MPs in a landfill area. We collected 15 soil samples, 2 leachate samples, and 7 groundwater samples from both inside and outside a municipal landfill situated in the urbanized coastal region of Rayong Province. Our findings revealed variability in MPs concentration across different sample types. In soil, the MP count ranged from 240 to 26,100 pieces per kg of dry soil, 58.71 % of all sample sizes are lower than 0.5 mm. Similarly, the size found in the leachate sample, and the average MP in the leachate samples was 139 pieces per liter of MPs. The groundwater samples showed a fluctuation in MPs count from 18 to 94 pieces per liter, and the size of MPs ranged mostly from 0.5 to 1 mm. The predominant forms of MPs identified were sheets, followed by fragments, fibers, and granules. According to μ-FTIR analysis, the majority of the MPs were composed of polyethylene and polypropylene, commonly used in plastic packaging and ropes. The observed high concentrations and extensive distribution of MP contamination underscore the urgency for further studies and effective management strategies to mitigate the adverse impacts of this pollution on various organisms and ecosystems.

Random forest microplastic classification using spectral subsamples of FT-IR hyperspectral images

In this work, a random decision forest model is built for fast identification of Fourier-transform infrared spectra of the eleven most common types of microplastics in the environment. The random decision forest input data is reduced to a combination of highly discriminative single wavenumbers selected using a machine learning classifier. This dimension reduction allows input from systems with individual wavenumber measurements, and decreases prediction time. The training and testing spectra are extracted from Fourier-transform infrared hyperspectral images of pure-type microplastic samples, automatizing the process with reference spectra and a fast background correction and identification algorithm. Random decision forest classification results are validated using procedurally generated ground truth. The classification accuracy achieved on said ground truths are not expected to carry over to environmental samples as those usually contain a broader variety of materials.

Determination of microplastic contamination levels and trends in vast oceanic sediment areas with uncertainty

Small plastic particles, designated as microplastics, are known vehicles of several contaminants desorbed from their surface after being ingested by marine organisms. The monitoring of the levels and trends of microplastics in oceanic areas is essential to identify relevant threats and respective sources whose management should be improved to protect the environmental resources. However, the assessment of contamination trends in large oceanic areas is affected by contamination heterogeneity, sampling representativeness, and the uncertainty of collected sample analyses. Only contamination variations not justifiable by system heterogeneity and their characterisation uncertainty are meaningful and should be taken seriously by the authorities. This work describes a novel methodology for the objective identification of meaningful variation of microplastic contamination in vast oceanic areas by the Monte Carlo simulation of all uncertainty components. This tool was successfully applied to the monitoring of the levels and trends of microplastic contamination in sediments from a 700 km² oceanic area from 3 km to 20 km offshore Sesimbra and Sines (Portugal). This work allowed concluding that contamination has not varied between 2018 and 2019 (difference of mean total microplastic contamination between -40 kg^-1 and 34 kg^-1) but that microparticles made of PET are the major type of studied microplastics (in 2019, mean contamination is between 36 kg^-1 and 85 kg^-1). All assessments were performed for a 99 % confidence level.

Insights into the characteristics, adsorption and desorption behaviors of microplastics aged with or without fulvic acid

Many aging experiments on microplastics (MPs) have been carried out using UV radiation or strong oxidants. Little attention has been paid to the role of water environmental factors such as dissolved organic matter (DOM). In this study, the role of fulvic acid (FA), the main component of DOM, in the UV-aging process of MPs was explored. MPs aged under UV, and UV along with 0.5 mg/L and 2 mg/L FA, were selected as subjects. The results showed that (1) FA accelerated the aging process of polyethylene (PE). PE aged with FA had a larger specific area (S_BET), with more holes and cracks on the surface. (2) FA enhanced the adsorption capacity of PE. The TC adsorption quantities of 0, 0.5, and 2 mg/L FA-aged PE were 1.100, 1.447, and 1.812 mg/L, respectively. (3) The quantity of TC desorbed by PE increased, whereas the desorption rate decreased as the FA concentration increased. The desorption rates of TC at 0, 0.5, and 2 mg/L FA-aged PE were 25.16%, 22.05%, and 19.52% in water, and 72.10%, 70.36%, and 59.51% in simulated intestinal fluid. This study explored the role of FA in the aging process of MPs. Moreover, research on the aging mechanism of MPs is enriched.

Bottom-Up Evaluation of the Uncertainty of the Quantification of Microplastics Contamination in Sediment Samples

The quantification and comparison of microplastic contamination of sediments are affected by sample heterogeneity and the systematic and random effects affecting sample analysis. The quantification and combination of these components in the measurement uncertainty allows the objective interpretation of analysis results. This work presents the first detailed evaluation of the uncertainty of microplastic contamination quantification in sediments. The random and systematic effects affecting microplastic counts are modeled by the Poisson-lognormal distribution with inputs estimated from duplicate sediment analysis and the analysis of sediments spiked with microparticles. The uncertainty from particle counting was combined with the uncertainty from the determination of the dry mass of the analytical portion by the Monte Carlo method. The developed methodology was implemented in a user-friendly spreadsheet made available as the Supporting Information. The contamination of sediment samples collected in various inland Portuguese waters was determined, ranging from [0; 160] to [361; 2932] kg^-1 for a 99% confidence level, and compared by assessing if the difference between contamination levels is equivalent to zero for the same confidence level. Several samples proved to have metrologically different microplastic contamination. This work represents a contribution to the objectivity of the assessment of environmental contamination with microplastics.

Microplastics contamination in sediments from Portuguese inland waters: Physical-chemical characterisation and distribution

Plastics are the major constituent of waste accumulated in inland waters and subsequently transferred to the ocean. The smaller plastic particles, typically obtained from the fragmentation of larger pieces, are vehicles for food chain accumulation of plastic components and contaminants sorbed to these particles through their ingestion by small organisms. The monitoring of the level and trends of the contamination by microplastics is essential to determine the relevance and potential sources of this contamination necessary to define strategies to reduce this threat. This work presents microplastic contamination levels and trends of sediments of four Portuguese inland waters, namely Ria de Aveiro, Ria Formosa, Mira river, and Mondego river, between 02/2019 and 09/2020. The contamination is classified considering the type of polymer and size, shape, and colour of particles. Polymers are identified by micro-ATR-FTIR with true and false identification rates larger and lower than 95% and 5%, respectively. Duplicate analysis results are used to quantify contamination heterogeneity subsequently applied to assess if a specific contamination trend is not meaningful for a 99% confidence level. The analytical procedure is described in detail to clarify the scope of the analysis. Tests' quality is controlled by following strict quality control measures. Results from sixty-three sediment samples proved the ubiquitous presence of microplastic (MP) in these inland waters with contamination levels ranging between 20 MP kg^-1 and 1090 MP kg^-1, excluding six samples not contaminated with these particles. Overall, more than 86% of the microplastics were fragments lower than 1000 μm, and 33% were identified as polyethylene or polypropylene. A large diversity of microplastic colours was observed. For the Mondego River and Ria de Aveiro locations monitored for consecutive years, no significant variations of microplastic contamination were observed for a 99% confidence level.

Groundwater antibiotics and microplastics in a drinking-water source area, northern China: Occurrence, spatial distribution, risk assessment, and correlation

In recent years, antibiotics and microplastics have both received increasing attention. However, the contamination and correlation between the two pollutants in the groundwater of drinking-water source areas has not yet been considered. In this study, eight antibiotics were detected in 81 groundwater samples from a drinking-water source area. These were trimethoprim (TMP), sulfadimidine (SDD), sulfadiazine (SDZ), sulfamethoxazole (SMX), sulfachloropyridazine (SCP), norfloxacin (NOR), ciprofloxacin (CIP) and enrofloxacin (ENRO). Detection rates ranged from 1.23% to 95.06% and the maximum concentration ranged from 0.44 ng/L to 45.40 ng/L. Antibiotics in the groundwater pose no threat to human health, while only ENRO, CIP, NOR, SMX, and SDZ posed medium to low risks to the aquatic ecosystem. In contrast, the detection rate of microplastics was 100% with abundance values ranging from 4 n/L to 72 n/L, with an average of 29 n/L. Microplastic polymers were identified as polyamide, polyethylene, polypropylene, polyvinyl chloride and polystyrene. These also occurred in surface water but the particle sizes in groundwater were lower than those in the surface water. Through correlation analysis, it was found that NOR, ENRO and total antibiotic concentrations were significantly correlated with microplastic abundances. This study revealed the contamination and potential risks of antibiotics and microplastics in the groundwater of a drinking-water source area and found a correlation between them, indicating that risk management of antibiotics and microplastics in groundwater should be highly concerned.

Validated spreadsheet for the identification of PE, PET, PP and PS microplastics by micro-ATR-FTIR spectra with known uncertainty

The monitoring of microplastics in the environment is crucial to determine the relevance and trends of this contamination necessary to plan environmental protection policies. Monitoring data reliability is essential for this purpose. This work describes a methodology for the reliable identification of the most abundant polymer types in aquatic sediments (polyethylene, PE, polypropylene, PP, polyethylene terephthalate, PET, and polystyrene, PS) by micro-ATR-FTIR. Identifications with true and false result rates greater than 95% and lower than 5% are performed, respectively. The analysis is based on defining spectra requirements regarding characteristic and interfering bands intensity and selecting optimal assessed wavenumber range, signal processing, and algorithm to quantify the match/agreement between particle and reference spectra. It is also defined the minimum match value, P5»P, for reliable identifications. Examinations are performed in two stages where in the first stage PE and PP, PE&PP, are distinguished from other microplastics by taking the [4000-500] cm^-1 spectra and various Match Methods and P5»P depending on the polymer type. PE and PP are distinguished by quantifying weighted or unweighted Pearson correlation coefficients against a reference spectrum in the [3000-2800] cm^-1 range. The defined P5»P are above the 0.6 value considered in many references that do not quantify identification uncertainty. The MS-Excel files used in method development and validation are made available as Supplementary Material being applicable to other spectral techniques and analytical fields.