Environmental and Earth Sciences

Abstract: This study aimed to evaluate the distribution of lead (Pb), cadmium (Cd), chromium (Cr), and arsenic (As) in Andean dairy production systems located within areas affected by volcanic ash deposition, and to analyse their implications for milk safety. To this end, samples from 15 georeferenced dairy production units were analysed to determine heavy metals and physicochemical characteristics in soil, forage, feed, drinking water, and raw milk. Soil and forage were considered the main environmental matrices within the soil–forage–milk pathway, whereas feed and drinking water were interpreted as external exposure matrices. The data were analysed using descriptive statistics, box plots, principal component analysis, and Spearman correlation analysis. The findings indicated that heavy metal behaviour was metal-specific and did not follow a strictly linear pattern. Pb and As exhibited marked attenuation before reaching milk, suggesting limited final transfer to the consumable product. Cd exhibited greater biological mobility, with detectable concentrations in milk and stronger relevance from a chronic exposure perspective. Cr persisted at relatively high levels in forage and feed but decreased substantially in milk. Correlation analysis demonstrated that Pb, Cr, and As were mainly associated with the solid fraction of milk, whereas Cd demonstrated an inverse relationship with corrected density, protein, lactose, and total solids. Overall, the results indicate that milk safety in volcanic-influenced Andean dairy systems should be assessed through an integrated chemical and physicochemical approach, considering environmental availability, external dietary inputs, and milk compositional quality.

Abstract: Air pollution is a public health threat that requires urgent action. This study conducted a bibliometric analysis of air pollution and human health in Indian cities to examine trends and the geography of the scientific literature, the evolution of research, and co-occurrence patterns of pollution sources, types, and health impacts. Furthermore, a narrative review of air pollution mitigation strategies was conducted using scholarly articles, policy documents, and reports. Relevant publications from the Web of Science (WoS) and Scopus databases were downloaded. The search identified 3307 articles published between 1987 and 2024, of which 172 met the inclusion criteria. The bibliometric analysis was conducted using VOSviewer and R software. The results indicate a steady rise in studies on air pollution and health issues in India. Initially, research concentrated on various sources and types of pollution, subsequently transitioning to the evaluation of exposure risks, risk assessment, and health implications, ultimately narrowing its focus to risk assessment concerning human health. Over the course of forty years, there has been a growing emphasis on the influence of indoor air quality, including ‘PM2.5’, ‘PM10’, dust, chemical pollutants, heavy metals, and exhaust dust, on human health. Research on pollution-related health effects has moved from examining general impacts to focusing on long-term, chronic consequences of pollutant exposure. Notably, most studies are centred in large metropolitan areas, whereas medium and small towns are underrepresented. Urban areas face severe air-quality challenges, requiring strategies such as monitoring pollution, promoting renewable energy, reusing materials, installing green walls or buffers in pollution zones, improving transport infrastructure, and reducing dust with grass covers. This study underscores the importance of implementing effective air pollution control measures across various geographic regions and integrating air pollution mitigation strategies into comprehensive urban development and planning frameworks.

Abstract: Rapid urbanization and inadequate sanitation infrastructure threaten water security in many sub-Saharan African cities. This study presents the first integrated assessment of groundwater, surface water, and wastewater quality in Bangui, Central African Repub-lic, using physicochemical, trace metal, and microbiological indicators. A total of 28 sampling sites were analyzed using standardized methods, including ion chromatog-raphy, ICP-OES, ICP-MS, and membrane filtration. Results revealed a clear contamina-tion gradient. Wastewater showed the highest electrical conductivity, turbidity, chlo-ride concentrations, and microbial loads, reaching 2.41 × 10⁶ CFU/100 mL for total coli-forms and 1.93 × 10⁶ CFU/100 mL for fecal coliforms. Groundwater exhibited high ni-trite levels and low dissolved oxygen, indicating vulnerability to sewage infiltration. Surface waters were characterized by high turbidity and widespread fecal contamina-tion despite relatively good oxygenation. In contrast, trace metal concentrations gener-ally remained below World Health Organization guideline values. Geochemical anal-yses identified distinct elemental signatures for each water type. Microbial contamina-tion emerged as the dominant factor affecting water quality. High fecal coliform/fecal streptococci ratios (13.08-22.16) indicated predominantly human-derived pollution linked to untreated wastewater and inadequate sanitation systems. The association between elevated nitrite concentrations and fecal indicators suggests active contami-nation pathways connecting wastewater, surface water, and shallow aquifers. These findings highlight the urgent need for improved wastewater management, groundwa-ter protection, and long-term monitoring to ensure sustainable urban water security in Bangui.

Abstract: Accumulation of radionuclides in crops products can pose public health risks. Parameters of 137Cs root uptake by maize were investigated at 4 growth stages from leaf development to ripening (June-September) in the post-Chernobyl area of the Plavsk radioactive hotspot (Tula region of Russia). It has been established that chernozem of the agrosystem still contains about 180 kBq 137Cs m-2. Seasonal trends of 137Cs activity concentrations in above- and belowground parts of maize differ appreciably. In aerial parts, 137Cs accumulation rate increases as vegetative organs develop from June to July, then they drop when generative organs appear in August. In the belowground biomass, the 137Cs content increases with the growth of fine roots, which, due to their rhizofiltration capacity, have maximal radionuclide concentration. However, at all stages of growth radionuclide transfer to maize occurs with low intensity and does not directly depend on changes in biomass, dry matter content, 40K content; and only slightly relates to the ash content. The transfer factor is estimated to be 6.2 x 10-3 for cob kernels (grain) and 3.8 x 10-2 for stems and leaves, which corresponds to the IAEA recommended values and ensures acceptable levels of 137Cs accumulation in crop products produced on the territory.

Abstract: Potentially toxic elements (PTEs) are persistent contaminants that can bioaccumulate and transfer through food webs, making wildlife valuable sentinels of ecosystem health. This study provides the first characterization of metal and metalloid concentrations in whole blood from free-ranging Iberian lynxes (Lynx pardinus) and evaluates biological and environmental factors influencing their variability, including comparisons with captive individuals. A total of 229 blood samples collected from Iberian lynxes in Extremadura (SW Spain) between 2018 and 2024 were analyzed for Cr, Mn, Cu, Zn, As, Se, Cd, Hg, Fe, and Pb. Concentrations were generally within physiological ranges reported for other mammals, and no clinically detectable adverse effects were observed during routine health examinations. Significant correlations were detected among several elements, particularly between Zn and Fe, with moderate associations between Mn and Zn and between Fe and Cu, suggesting shared environmental sources and interconnected physiological regulation mechanisms. Element concentrations were significantly influenced by endogenous factors (age and sex) and exogenous variables (geographical area and sampling period), especially for As, Zn, and Se, reflecting differences in bioaccumulation, metabolism, and environmental exposure. Principal Component Analysis revealed a largely common multielemental profile across individuals, with no clear segregation among populations or biological groups, indicating relatively homogeneous exposure patterns despite subtle spatial and individual variability. These results establish the first reference values for inorganic contaminant biomonitoring in Iberian lynx whole blood and provide a baseline for ecotoxicological assessment and conservation management of this endangered felid.

Abstract: Petroleum, also known as crude oil, is a natural, non-renewable, and essential energy resource. Its extraction and transportation require specific precautions/recommendations to prevent or mitigate potential emergency scenarios, and pollution of soil, air, and water resources. One of the safest ways of transporting crude oil is through pipelines. However, they are subject to corrosion that may lead to leaks that cause severe environmental and water pollution. In this paper, we investigate the migration of petroleum in a scenario mimicking a pipeline leakage (with the pipeline included in the numerical simulation) and the consequent spread of the contaminant in the environment. We use the numerical code CactusHydro, which accurately resolves the sharp discontinuities and temporal dynamics of three-phase fluid flow and thereby accurately tracks contaminant migration in space and time through a variably saturated zone with variable permeability and porosity. We analyze various scenarios encompassing different climatic conditions, including rainfall-induced water saturation, in the variable-saturation porous medium zone and different porosity values, for a total of sixteen transient numerical simulations. Hydraulic conductivity is linked to saturation and provides information on the type of porous soil that facilitates contaminant migration. Also, the porosity can vehicle more or less rapidly its vertical movement in the unsaturated zone. The numerical results show that the vertical migration of the petroleum is primarily driven by the high pressure within the pipeline, since the contaminant has a very limited mobility. Moreover, hydraulic conductivity and porosity play important roles in petroleum migration. Our results suggest that, for crude oil, the distribution of leaked oil may not extend below 2 meters in elevation within 10 days. Our conclusions show that certain types of soil are more adaptable at preventing possible spill migration and can be helpful in constructing pipeline paths that avoid or reduce pollution.

Abstract: The concentration of olive tree pollen in the atmosphere is likely to vary from one region to another, owing to the fluctuations in meteorological and climatic factors. Furthermore, particulate matter (PM) has been shown to interact with olive tree pollen, as airborne particles can adhere to pollen grains, altering their allergenicity and enhancing their ability to trigger respiratory pathologies. This interaction between PM and olive pollen may intensify the health impact on sensitive populations, particularly in areas with high levels of both air pollution and olive tree cultivation. The town of sig (located between mascara and oran) in Algeria is representative of this phenomenon, due to the vast fields of olive trees that surround the town. Significant correlations were recorded between the prevalence of olive tree pollen allergy and meteorological data as well as fine particle air pollution estimated from Sentinel5P satellite images during the years 2018 and 2019. The application of SVR, RFR and MLR Machine Learning methods made it possible to create models that could explain the prevalence of olive pollen allergy. The best result was obtained with the SVR algorithm, whose performance is expressed by R2=0.92, RMSE=2.27 and MAE=0.66. The model developed in this study could therefore contribute to the elaboration of more effective strategies aimed at minimizing the adverse effects of olive pollen allergens within the investigated region.

Abstract: Mycotoxin research has traditionally focused on cultivated crops, whereas far less attention has been paid to wild plants growing in semi-natural vegetation adjacent to agricultural fields. We investigated the occurrence, seasonal dynamics, organ-specific distribution, and growth-form differences of three major mycotoxins—aflatoxin B1 (AFB1), deoxynivalenol (DON), and zearalenone (ZEN)—in wild plant species collected in an agricultural region of the Hungarian Plain. A total of 134 samples were collected during the vegetation period (July, August, and October) and analyzed for mycotoxin contamination. All three mycotoxins were frequently detected, and only 13% of samples contained none of the investigated mycotoxins. Mycotoxin profiles changed seasonally: multi-toxin co-occurrence was most common in July, ZEN predominated in August, and DON became most frequent in October, while AFB1 declined toward the end of the season. Growth form was a major determinant of contamination patterns, with AFB1 and DON occurring predominantly in woody species and ZEN in grasses. Plant organs had a weaker effect, although leaves were the most frequently contaminated tissues. Most concentrations were low, but occasional extreme values exceeded European Union guidance values, particularly for AFB1 and, in one case, DON. These findings show that semi-natural vegetation can act as a reservoir of multiple mycotoxins and highlight the importance of seasonal dynamics together with plant growth forms when assessing environmental mycotoxin exposure in agricultural landscapes.

Abstract: Low-cost air quality sensors can expand PM₂.₅ monitoring networks but require calibration against regulatory-grade monitors to correct systematic bias. Although interest in predictive uncertainty for air quality estimation has increased, uncertainty reliability under spatial sparsity and wildfire-induced distribution shift remains poorly understood. This study develops a transformer-based PM₂.₅ calibration model and evaluates two uncertainty quantification methods, GeoConformal Prediction (GCP) and Monte Carlo Dropout (MCD), using sensor pairs in California and the Northeast United States. The calibration model achieved strong performance at short spatial distances, with test R² values of 0.89 and 0.91 at the 1 km threshold in California and the Northeast, respectively, with accuracy declining as sensor separation increased. GCP generally produced calibration curves closer to the ideal diagonal, while MCD generated tighter prediction intervals under normal conditions. During wildfire events, uncertainty performance depended on sensor separation. At short distances, MCD expanded its uncertainty intervals and captured PM₂.₅ spikes more effectively than GCP (71% vs. 61% coverage). At larger separations, MCD captured only 44% of elevated observations, whereas GCP widened its intervals and achieved 83% coverage. These results demonstrate that uncertainty reliability is strongly influenced by spatial separation and environmental conditions, highlighting the need for uncertainty-aware calibration of low-cost PM₂.₅ sensors.

Abstract: Accurate estimation of carbon dioxide (CO₂) emissions, both per capita and per GDP, is essential for effective environmental policy and sustainable development. This study proposes a data-driven framework based on machine learning techniques to improve the prediction of CO₂ emissions per capita and per unit of Gross Domestic Product (GDP) in France. Artificial Neural Networks (ANN), Decision Trees (DT), and a mathematical interpolation approach were developed and evaluated using datasets incorporating energy consumption, industrial activity, and transportation indicators. Model performance was assessed using MAE, MSE, RMSE, and R² metrics. The results indicate that the interpolation method provides the highest accuracy for predicting CO₂ emissions per capita (R² = 0.996), while DT and ANN achieve superior performance for emissions per unit of GDP (R² = 0.999), with DT offering greater overall stability. The findings demonstrate the effectiveness of machine learning approaches over conventional methods, highlighting interpolation as suitable for population-based predictions and DT as a robust tool for economy-based emission forecasting. These models offer valuable support for environmental monitoring and long-term sustainability planning.

Abstract: Little is known about the vertical distribution of microplastics (MPs) in deep stratified lakes. This study investigates the MPs in the large and deep Lake Trichonis during the thermal stratification period, using two nets of different porosity (50 μm and 200 μm) in three depth strata. Fibers dominated upon fragments having an average abundance of 10.63 ± 1.00 items/m³ and 3.10 ± 0.52 items/m³ respectively in the samples of the 50 μm net in the entire water column, while the respective values for the 200 μm net were 1.4 and 7.4 times greater. Fibers had highest abundance within the thermocline, and most of them were blue having length 12 mm. There were only abundance differences between the two nets and no qualitative disparities concerning color, size, shape and polymer types. There was strong positive correlation between the abundance of fibers and the adults of the dominant copepod Eudiaptomus drieschi, which accumulated also within the thermocline. Considering that the adults of E. drieschi are among the preferred prey of Atherina boyeri, the most important commercial fish, certain issues arise concerning possible fibers’ bioaccumulation on the food web. The study highlights the importance of investigating MPs in connection with biotic elements.

Abstract: Tropospheric ozone (O³) is a phytotoxic air pollutant that can impair visible foliar injury (O³ VFI) and reduces photosynthesis in sensitive forest species. Viburnum lantana L. has been widely used as an in situ bioindicator of O³ pollution in mountainous areas of Europe; however, field-observed O³-induced VFI as well as critical levels (CLs) established to protect forests, have not been validated. This study validated field-observed O³ effects in V. lantana through experiments carried out in a Free-air O³ eXposure infrastructure (FO₃X) and determined which O³ metric (exposure-based—AOT40 or flux-based—POD₁) best explains O³ effect on leaf physiology and VFI. V. lantana saplings were subjected to ambient air (AA) conditions and elevated O³ levels at 1.5× and 2.0× AA. Throughout the experimental period (T1: 2-month and T2: 3.5-month O³ exposure) measurements were taken for the Plant Injury Index (PII), light-saturated net photosynthetic rate (A_sat), stomatal conductance (g_s), leaf color index (SPAD), and the maximum photochemical efficiency of photosystem II (Fv/Fm). O³ VFI was first observed in 2.0× after 16 days. As a result, O³ treatment influenced PII, which was significantly higher in the 2.0× (9.06 ± 3.24) than in the 1.5× and AA treatments (1.31 ± 0.62 and 1.29 ± 0.71) at T2. The A_sat, SPAD, and Fv/Fm were significantly affected by O³ treatments; no significant difference in g_s was found. POD1 better explained variability in O³ VFI and physiological parameters, with CLs proposed for V. lantana of 1.61 mmol m^–2 and 1.22 mmol m^–2 for a 4% reduction of A^sat and g_s, and a CL of 7.82 mmol m^–2 for the onset of O³ VFI.

Abstract: Particle pollution has been recognized as a major part of environmental pollution. More specifically, the inhalation of very small (ultrafine) airborne particulate matter (PM) that is emitted from the burning of fossil fuels poses the most serious threat to human health. High-efficiency retention of these particles is one of the most challenging environmental problems, since conventional techniques like electrostatic precipitators, bag filters or cyclones have low collection efficiency in the respirable range (0.1 μm–1.0 μm). Acoustically induced agglomeration of ultrafine particles is a promising technique to increase the size of small particles before they enter a conventional filter. During this process, high-intensity acoustic fields are applied to the flue gas stream, inducing interaction effects among suspended particles that give rise to collisions and agglomeration. The preconditioned aerosol can then be filtered within conventional filters with higher collection efficiency. The present work reports the results of a numerical investigation of the effect of ultrasound preconditioning on the particle size distribution as a function of parameters related to the ultrasound system design, such as the acoustic frequency and intensity, and the initial mass loading. Particle agglomeration is modeled via the solution of the population balance equation (PBE) with the Multi-Monte Carlo (MMC) method. Results show that acoustic agglomeration can shift particle size distribution towards larger values of diameters and reduce the total number concentration of particles, thus leading to increased capture efficiency of conventional filters.

Abstract: The accelerating accumulation of atmospheric carbon dioxide (CO₂) from fossil fuel combustion represents one of the foremost environmental challenges of the twenty-first century. This paper presents the design, theoretical basis, and experimental framework of a novel artificial photosynthesis system capable of capturing CO₂ from combustion flue gases and converting it into oxygen (O₂) and energy-rich compounds, directly mimicking the biochemical process performed by trees. The proposed system integrates a sodium carbonate (Na₂CO₃) absorption tower for CO₂ capture, a thermal desorption unit for solvent regeneration, and a cobalt oxide-catalyzed photosynthetic reactor for CO₂-to-O₂ conversion. System performance is quantified using non-dispersive infrared (NDIR) sensors for CO₂ measurement and electrochemical oxygen sensors for O₂ detection. Stoichiometric analysis indicates that 1 kg of captured CO₂ yields approximately 0.73 kg of O₂, and national-scale deployment projections suggest energy savings of approximately $200 billion per year by 2030 alongside a potential reduction of 302,600 million metric tons of CO₂ emissions. Comparative analysis with existing decarbonization approaches—including carbon capture and storage (CCS), hydrogen production, and enhanced oil recovery (EOR)—demonstrates that artificial photosynthesis offers a fundamentally superior outcome by permanently transforming CO₂ into life-sustaining O₂ rather than merely sequestering or displacing it. This work establishes a laboratory-scale proof of concept and a systematic experimental roadmap for scaling the technology to industrial application.

Abstract: The increasing presence of microplastics (MPs) in freshwater ecosystems poses significant threats to aquatic biota; yet, species-level information on the presence of MPs in Indian riverine ecosystems is scarce. This study assessed 220 fish samples from twelve species and various trophic levels for MP ingestion, organ-level accumulation, polymer type, and ecological risk at four locations along the River Yamuna in India. MPs were detected in all the studied species and organs, indicating their widespread distribution across various ecological habitats and trophic levels. A total of 1,678 MPs were quantified, which were significantly higher in fish from urban Delhi compared to upstream regions. The gastrointestinal tract had the highest MP concentrations (751), followed by gills (605) and muscle tissues (322), thus confirming ingestion as the primary route of MP uptake and their subsequent translocation into internal organs. Fibers dominated the MP community (>78%), with transparent (44%) and blue (19.5%) particles being the most abundant. ATR-FTIR analysis revealed the presence of ten different polymers, with polyethylene (≈24%) and polypropylene (≈21%) contributing to approximately 45% of MPs. Significant organ-level correlations (r/ρ = 0.635-0.958) and spatial variability (Kruskal-Wallis, H = 11.03, p = 0.011) indicated coordinated MP accumulation influenced by urban pollution. The Polymer Hazard Index analysis revealed a high PHI value (Category IV), mainly contributed by the widespread distribution of highly toxic polymers such as polycarbonate and polyimide.

Abstract: A three-year (January 2020–December 2022) daily dataset of 16 polycyclic aromatic hydrocarbons (PAHs) co-sampled with PM2.5 and a suite of meteorological variables at a Mediterranean coastal urban site in southern Italy (Pomigliano d’Arco, Campania) is presented and analysed. Raw PAH time series were decomposed into a long-term trend component (LT), a seasonal component (ST), and a residual component (RT) using an iterative missing-value-robust Kolmogorov–Zurbenko (KZ) moving-average filter. Spearman rank correlations between PAH concentrations and four meteorological predictors (mean temperature, relative humidity, mean wind speed, and maximum wind speed) were computed for each congener. Diagnostic molecular ratios — Fluoranthene/(Fluoranthene+Pyrene), BaP/BghiP, Indeno[1,2,3-cd]pyrene/(IcdP+BghiP), and Benz[a]anthracene/(BaA+Chrysene) — were evaluated seasonally and subjected to an information-theoretic Bayesian mixture modelling procedure (SNOB/MML) to estimate the number and nature of prevailing emission source classes. Total PAH concentrations (sum of 16 congeners) ranged from <1 ng m−3 in summer to 46 ng m−3 during winter high-pollution episodes, with BaP peaking at ≈6.7 ng m−3. Pronounced seasonal variability was driven primarily by residential heating emissions, and the incremental lifetime cancer risk (ILCR) for inhalation exposure reached 1.03×10−4 (95% CI: 0.88−1.20×10−4) during the heating season, exceeding standard regulatory thresholds. An anomalous near-background PAH signal during spring 2020 is attributed to the COVID-19 national lockdown, which reduced total PAH concentrations by approximately 85% relative to the seasonal component predicted by the iterative moving-average filter for the same calendar window. Source apportionment via diagnostic ratios identifies residential/biomass combustion as the dominant cold-season source and vehicular emissions as the prevailing warm-season source. These results provide a novel characterisation of PAH pollution dynamics in the undersampled southern Mediterranean and offer insights for targeted abatement policies.

Abstract: Urban noise pollution disproportionately affects Latin American cities, where rapid urbanization, weak governance and limited monitoring networks coexist with diverse economic activities. This study compares the spatial and temporal dynamics of environmental noise between two Colombian municipalities with contrasting urban typologies: Soledad (Atlántico), a metropolitan city dominated by traffic and aircraft noise, and Montelíbano (Córdoba, ~86,647 inhabitants), a mid-sized municipality whose acoustic environment is conditioned by ferronickel mining (Cerro Matoso), heavy-duty transport and small-scale aviation. A two-tier methodology was applied: (i) field monitoring under Colombian Resolution 627 of 2006 (LAeq) at 80 points in Soledad and 30 points in Montelíbano, covering daytime and night-time periods including replicates; and (ii) noise dispersion modelling in SoundPLAN Essential v5.1/6.0 using the ISO 9613-2 propagation method, calibrated with field measurements through an iterative residual-minimization process. Results show that Soledad exhibits a strong day–night gradient (mean LAeq diurnal = 67.7 dB(A); nocturnal = 61.7 dB(A); 96.2% non-compliance at night) with linear-corridor acoustic patterns driven by arterial roads and the Ernesto Cortissoz airport, while Montelíbano displays a near-flat day–night profile (diurnal = 67.1 dB(A); nocturnal = 67.0 dB(A)) consistent with continuous mining-industrial operations. The modelled maps reproduce the measured patterns with mean residuals of −2.72 dB(A) (day) and −2.92 dB(A) (night) in Montelíbano (75% within ±5 dB(A), consistent with international SoundPLAN benchmarks), and mean residuals of +5.78 dB(A) (day) and +1.43 dB(A) (night) in Soledad, the latter reflecting the greater acoustic heterogeneity of a larger urban environment. These findings demonstrate that urban typology shapes acoustic patterns in fundamentally different ways, with implications for sustainable land-use planning, public health and the design of differentiated noise-mitigation policies.

Abstract: Sandy beaches in the Central Region of Veracruz (RCV) face constant anthropogenic pressure from port and urban activities. This study aimed to evaluate total hydrocar-bon (TH) concentrations in the intertidal interstitial water of five beaches in the RCV, analyzing their variability by depth (15 and 30 cm) and seasonality (northerly winds, dry, and rainy seasons). TH determination was performed using gas chromatography (GC-FID), following the NMX-AA-117-SCFI-2001 and NOM-138-SEMARNAT/SSA1-2012 standards. Results showed concentrations ranging from 0.86 to 6.53 µg L⁻¹. Significant spatial differences were identified (p < 0.05); An-tepuerto beach presented the highest levels due to its proximity to the port, while Far-allón showed the lowest concentrations, confirming its role as a reference site. No sig-nificant variations were detected by depth or season (p > 0.05), indicating temporal stability associated with continuous anthropogenic inputs. Although levels comply with Mexican regulations, the continuous presence of TH represents a potential risk to benthic biota and the integrity of the Veracruz Reef System (SAV). This study pro-vides a critical baseline for strengthening coastal ecosystem management strategies in the Gulf of Mexico.

Abstract: Microplastic contamination in coral reef environments is increasingly recognized as a global concern; however, the extent to which polymer composition can resolve contamination sources and transport processes remains poorly understood. In this study, we assessed the abundance, composition, and diversity of microplastics (< 300 µm) across multiple reef systems in the Cuban archipelago using high-resolution spectroscopic analysis. Microplastic abundance varied substantially among sites, with a median concentration of 66 particles L⁻¹ (IQR: 45–115 particles L⁻¹), ranging from 8 to 218 particles L⁻¹. A total of 11 polymer types were identified, with polyethylene (PE), polypropylene (PP), and polyamide (PA) dominating the assemblages and accounting for approximately 77% of detected particles. While these polymers were consistently observed across all sites, indicating a pervasive regional background signal, highly impacted reefs exhibited more complex polymer profiles, including the enrichment of polyurethane (PU), polytetrafluoroethylene (PTFE), and polyvinyl chloride (PVC), reflecting localized anthropogenic inputs. Multivariate analysis revealed distinct compositional groupings associated with different contamination regimes. Notably, some sites exhibited elevated microplastic abundances while remaining dominated by common polymers, indicating a decoupling between contamination levels and source-specific signatures. This pattern suggests that regional transport and mixing processes, including circulation through the Caribbean basin and the Yucatán Channel, play a major role in shaping microplastic distributions in reef environments. These findings demonstrate that polymer composition provides critical information beyond abundance alone, enabling the differentiation between source-driven contamination and transport-driven accumulation. The integration of polymer-specific analysis with abundance and diversity metrics offers a robust framework for improving source apportionment and informing monitoring and management strategies in coral reef systems.

Abstract: Microplastics are particles derived from polymer degradation, and their occurrence and abundance have been assessed across various environments and compartments. The method commonly used for their evaluation and quantification in sediments involves a marine salt solution for decantation. However, due to the high incidence of plastics in marine environments, this salt may already contain a considerable concentration of microplastics and must be carefully filtered to minimize interference during laboratory processing. To assess the importance of this procedure, sediment samples from an estuarine environment, in which the salt used for laboratory sorting was not filtered, were compared with samples from semiarid reservoirs, in which the salt underwent filtration before decantation. All other procedures were identical, performed by the same team under controlled airborne contamination conditions. The Mann–Whitney test applied to samples with and without NaCl filtration revealed a significantly lower incidence of microplastics in samples whose salt had been filtered. Based on these findings, a filtration protocol for NaCl used in sediment decantation was developed, emphasizing an accessible, low-cost product widely applied in natural environmental quality assessments. Only through the standardization of methodologies and sampling units will it be possible to compare environments in terms of actual anthropogenic impact, generating outcomes that provide scientific support for conservation actions and impact mitigation.