Particle Size Distribution Research Articles

Determination of ultrafine particle number emission factors from building materials in standardized conditions

Abstract When comparing the particle emissivity for different materials and/or mechanical activities, a serious methodological issue emerges due to the dynamic nature of solid aerosols. Particle size distribution and concentration depend on initial particle emission that constantly evolves due to aerodynamic collisions. In this context, we propose a methodological approach and an experimental setup that enables to assess the release of fine/ultra-fine particles maintaining a steady-state inhalable mass concentration, here chosen at the Swiss occupational exposure level value for biopersistent granular particles (OEL: 10 mg/m3) in a controlled ventilation chamber. As a case study, this methodological protocol was tested in the occupational exposure scenario in which a series of insulating materials based on silica aerogel and conventional mortar and concrete were subjected to handling or sawing. Once the OEL was reached, the particle size distribution and morphology of the aerosols were characterized using direct reading instruments (scanning mobility sizer, aerosol photometer) and electron microscopy (SEM and TEM) analyses. As a main result, the presence of silica aerogel in the mortar did not modify the emission profile for submicronic particles during sawing in comparison to the bulk mortar. Emission factors for ultra-fine particles were found to be 88 × 106 and 81 × 106 particles/µg of inhalable dust for the aerogel mortar and bulk mortar, respectively. For concrete sawing, the number concentration of submicronic particles at the OEL is one order of magnitude greater. The aerogel-glass-wool handling generated similar particle number concentration at the OEL with ultra-fine particle emission factors of 647 × 106 particles/µg of inhalable dust, in comparison to 758 × 106 particles/µg of inhalable dust during dry concrete sawing. In conclusion, the methodology introduced in this work provides standardized particle emission factors for comparing materials and activities, while establishing a link between particle number emissions and occupational exposure limits.

Investigation of particle size distribution and ultrafiltration of digestates from short-fibre residues in paper mills

ABSTRACT Industrial digestates from short-fibre residues, generated in paper recycling mills, are driving interest in resource recovery. This study aims to explore their potential for water recovery. Understanding particle dynamics aids in optimizing dewatering for digestate management. The particle size distribution in this study revealed significant fractions: <0.63 μm (6–20%), 0.63–20 μm (38–52%), and >20 μm (11–16%). Pre-treatment with Na4P2O7 and H2O2 enhances settling and lowers total dissolved solids (TDSs) but results in variation of size distribution. Additionally, this study investigates further water reuse in paper mills, focusing on the quality of ultrafiltration (UF) permeate obtained from the digestate of short fibres. UF permeate analysis reveals deviations from freshwater standards in paper mills. Despite effective TS removal, UF permeate falls short of paper mill water standards due to high TDSs, electrical conductivity, and nutrient concentrations, necessitating further downstream treatment with nanofiltration or reverse osmosis. A substantial reduction of permeate flux from 31 to 5 L/(m2·h) over the time indicated fouling and inefficient membrane wash. The silt density index of the UF membrane at 30 min registered 2.1, suggesting potential fouling. Further investigations on optimizing UF operations to enhance permeate flux and exploring alternative UF membranes are required.

Assessing the Drying Sensitivity of Alkali-Activated Binders Through Mechanical Reliability: Effect of Particle Size and Packing

Despite the steady progress of research on the alkali activation of wastes or subproducts from established industrial processes, the brittleness of the hardened alkali-activated materials frequently results in questionable mechanical reliability, particularly in industrial applications beyond construction materials. This work used a 33 factorial Design of Experiments to examine the effect of three different particle size distributions on the compressive strength and mechanical reliability (Weibull modulus) of a sodium silicate-activated blast-furnace slag under the same processing conditions. As expected, curing temperature and time were strongly correlated, and the corresponding response surfaces showed that, for all studied particle sizes, compressive strengths above 60 MPa with mechanical reliability above 5.0 could be obtained by curing at ~60 °C for ~40 h. The particle size differences caused no significant changes in the extent of alkali activation, as seen in the infrared-spectroscopy results. However, the intersection of the response surfaces showed that a coarser and narrower particle size distribution extended the working area (time × temperature) and favored mechanical reliability. Thus, the precursor’s particle size distribution, which governs particle packing and viscosity during processing, also determines the permeability of the set binder, which affects water removal during drying and the dried binder’s mechanical performance.

Microstructural characterization of DEM-based random packings of monodisperse and polydisperse non-convex particles

Understanding of hard particles in morphologies and sizes on microstructures of particle random packings is of significance to evaluate physical and mechanical properties of many discrete media, such as granular materials, colloids, porous ceramics, active cells, and concrete. The majority of previous lines of research mainly dedicated microstructure analysis of convex particles, such as spheres, ellipsoids, spherocylinders, cylinders, and convex-polyhedra, whereas little is known about non-convex particles that are more close to practical discrete objects in nature. In this study, the non-convex morphology of a three-dimensional particle is devised by using a mathematical-controllable parameterized method, which contains two construction modes, namely, the uniformly distributed contraction centers and the randomly distributed contraction centers. Accordingly, three shape parameters are conceived to regulate the particle geometrical morphology from a perfect sphere to arbitrary non-convexities. Random packing models of hard non-convex particles with mono-/poly-dispersity in sizes are then established using the discrete element modeling Diverse microstructural indicators are utilized to characterize configurations of non-convex particle random packings. The compactness of non-convex particles in packings is characterized by the random close packing fraction fd and the corresponding average coordination number Z. In addition, four statistical descriptors, encompassing the radial distribution function g(r), two-point probability function S2(i)(r), lineal-path function L(i)(r), and cumulative pore size distribution function F(δ), are exploited to demonstrate the high-order microstructure information of non-convex particle random packings. The results demonstrate that the particle shape and size distribution have significant effects on Z and fd; the construction mode of the randomly distributed contraction centers can yield higher fd than that of the uniformly distributed contraction centers, in which the upper limit of fd approaches to 0.632 for monodisperse sphere packings. Moreover, non-convex particles of sizes following the famous Fuller distribution of the power-law distribution of the exponent q = 2.5, have the highest fd (≈0.761) with respect to other q. In contrast, the particle shapes have an almost negligible effect on the four statistical descriptors, but they are remarkably sensitive to particle packing fraction fp and size distribution. The results can provide sound guidance for custom-design of granular media by tailoring specific microstructures of particles.

Particle Size as an Indicator of Wheat Flour Quality: A Review

Wheat flour is one of the most important food raw materials, with its quality determined by various indicators. One such indicator is particle size and granulometric distribution. In recent years, numerous studies have focused on the effect of flour and bran particle size on the properties of cereal products such as bread, pasta, noodles, and cookies. The aim of this review was to analyze the extent to which this parameter influences the properties of these cereal products. Additionally, the relationships between flour particle size and its chemical composition were presented. Key factors affecting the granulometric composition of flour, related to wheat grain properties and the grinding process, were also discussed. The study specifically focuses on research conducted in the last five years.

Effect of ZnO/EAF slag doping on removal of methyl red dye (MR) from industrial waste water

Zinc oxide doped with EAF slag (ZnO/ EAF slag) nanoparticles in different contents (10, 20) % of waste were synthesized in a controlled and reproducible way using spin-coater. The produced nanomaterial’s physicochemical and structural characteristics were ascertained by means of particle size distribution, TEM, SEM, UV-Vis spectroscopy, XRD, FTIR, and XRF. The role and effect of EAF slag with constant percent doping with ZnO on the ability to remove pollutants was determined by observing the methyl red (MR) elimination in an aqueous solution at λmax = 413 nm and MR dye removal concentration was evaluated from its optical density. Irradiation of the compounds in sunlight intensity 250 KW/nh.m2 and temperature 36 °c resulted in a larger degree of MR removal from the solution, resulting in ZnO/EAF slag samples exhibiting increased photo activity. As a conclusion ZnO nanoparticles saturated with 20% EAF slag as a waste material were the most efficient in removing methyl red (MR) achieving ~ 96% removal and a completely transparent solution after 2 h of testing.

Self-supply of hydrogen peroxide by a bimetal-based nanocatalytic platform to enhance chemodynamic therapy for tumor treatment

The tumor microenvironment (TME) is characterized by low pH, hypoxia, and overexpression of glutathione (GSH). Owing to the complexity of tumor pathogenesis and the heterogeneity of the TME, achieving satisfactory efficacy with a single treatment method is difficult, which significantly impedes tumor treatment. In this study, composite nanoparticles of calcium-copper/alginate-hyaluronic acid (HA) (CaO2-CuO2@SA/HA NC) with pH and GSH responsiveness were prepared for the first time through a one-step synthesis using HA as a targeting ligand. Nanoparticles loaded with H2O2can enhance the chemodynamic therapy effects. Simultaneously, Cu2+can generate oxygen in the TME and alleviate hypoxia in tumor tissue. Cu2+and H2O2undergo the Fenton reaction to produce cytotoxic hydroxyl radicals and Ca2+ions, which enhance the localization and clearance of nanoparticles in tumor cells. Additionally, HA and sodium alginate (SA) were utilized to improve the targeting and biocompatibility of the nanoparticles. Fourier transform infrared, x-ray diffraction, dynamic light scattering, SEM, transmission electron microscope, and other analytical methods were used to investigate their physical and chemical properties. The results indicate that the CaO2-CuO2@SA/HA NC prepared using a one-step method had a particle size of 220 nm, a narrow particle size distribution, and a uniform morphology. The hydrogen peroxide self-supplied nanodrug delivery system exhibited excellent pH-responsive release performance and glutathione-responsive •OH release ability while also reducing the level of reactive oxide species quenching.In vitrocell experiments, no obvious side effects on normal tissues were observed; however, the inhibition rate of malignant tumors HepG2 and DU145 exceeded 50%. The preparation of CaO2-CuO2@SA/HA NC nanoparticles, which can achieve both chemokinetic therapy and ion interference therapy, has demonstrated significant potential for clinical applications in cancer therapy.

In silico formulation optimization and particle engineering of pharmaceutical products using a generative artificial intelligence structure synthesis method

Pharmaceutical drug dosage forms are critical for ensuring the effective and safe delivery of active pharmaceutical ingredients to patients. However, traditional formulation development often relies on extensive lab and animal experimentation, which can be time-consuming and costly. This manuscript presents a generative artificial intelligence method that creates digital versions of drug products from images of exemplar products. This approach employs an image generator guided by critical quality attributes, such as particle size and drug loading, to create realistic digital product variations that can be analyzed and optimized digitally. This paper shows how this method was validated through two case studies: one for the determination of the amount of material that will create a percolating network in an oral tablet product and another for the optimization of drug distribution in a long-acting HIV inhibitor implant. The results demonstrate that the generative AI method accurately predicts a percolation threshold of 4.2% weight of microcrystalline cellulose and generates implant formulations with controlled drug loading and particle size distributions. Comparisons with real samples reveal that the synthesized structures exhibit comparable particle size distributions and transport properties in release media.

Direct Recycling of LixNi0.5Mn0.3Co0.2O2 from Production Scrap and End‐Of‐Life Batteries, Using Solid‐State Relithiation

AbstractDirect recycling of Li‐ion battery cathodes offers a sustainable and potentially cost‐effective alternative to conventional methods, often involving complex chemical processes and significant material losses. This study focuses on the relithiation of cathode materials from quality control reject (QCR) and end‐of‐life (EoL) Li‐ion cells to restore their physical structure, morphology, and electrochemical performance. Two NMC532/graphite pouch cells from the same manufacturer were studied. QCR cells, stored under ambient conditions, experienced corrosion and degradation before recycling, while EoL cells were cycled to the end of life. The cells were disassembled, and the cathode materials were delaminated using NaOH solution, then relithiated with LiOH at 700 °C for 15 hours in the air. Extensive characterization analyzed elemental composition, structural properties, thermal stability, and particle size distribution. Results indicated that relithiation successfully restored lithium content and improved the structural ordering and morphology of the cathode materials. The electrochemical performance of the relithiated cathodes exhibited good stability over 100 charge‐discharge cycles. The relithiated QCR samples achieved a capacity of 155.57 mAh g−1, while EoL samples reached 152.53 mAh g−1, comparable to pristine materials. This study highlights relithiation's potential to extend the lifecycle of Li‐ion cathodes, contributing to a more sustainable circular economy for battery materials.

PRELIMINARY STUDY ON ALGINATE CONCENTRATION AND ANTIBACTERIAL ACTIVITY OF PALMAROSA ESSENTIAL OIL

Objective: Palmarosa (Cymbopogon martinii (Roxb.)) essential oil has volatile active compounds, therefore, it requires modification of encapsulation to obtain optimum potency. This study investigated the relationship between various alginate concentrations in microencapsulation against the quality of the formula and antibacterial activity. Methods: The study use Palmarosa Essential Oil (PEO) that distillated at Rumah Atsiri, Indonesia. Ionic gelation was used to prepare microencapsulations at different alginate concentrations of 0.5%, 0.75%, and 1.5%. The investigation involved Fourier Transform Infrared (FTIR), organoleptic, morphological, microencapsulated weight, Encapsulation Efficiency (EE), and antibacterial activity. Results: The organoleptic observation results for all formulas are white in color, have a pronounced PEO scent, and contain spherical particles with macrometer-sized morphology similar to soft beads. The result FTIR showed that F1, F2, and F3 contain aromatic ring, primarily alcohol, alkene, alkyl, and alcohol. The results showed that F1, F2, and F3 were included in the microencapsulation range, namely 5-5,000 µm. Formula III had the greatest EE of 86.53±0.75% and antibacterial activity against Staphylococcus epidermidis and Pseudomonas aeruginosa, respectively showed inhibition zones with diameters of 12.30±0.16 mm and 7.60±0.24 mm. Conclusion: This study revealed that the findings of this study demonstrate that the concentration of alginate in microencapsulation influences the properties and antibacterial activity of PEO. Higher alginate concentrations can lead to increased EE, particle size distribution, and ultimately leading to enhanced antibacterial activity.

Primary Modes of Northern Hemisphere Snowfall Particle Size Distributions

Abstract A comprehensive understanding of snowfall microphysics is crucial for enhancing the accuracy of remote sensing snowfall retrievals. However, variations in regional and seasonal snow particle size distributions (PSDs) contribute substantial uncertainty. Here, we examine snowfall PSDs from across the Northern Hemisphere, applying Principal Component Analysis (PCA) to disdrometer observations with the aim of identifying dominant modes of variability across varying regional climates. The PCA revealed three Empirical Orthogonal Functions (EOFs) that account for a combined 95% of the variability across the dataset, which are attributed to latent linear embeddings of snowfall intensity (EOF1), snowfall character (EOF2) and snowfall regime (EOF3). Examining point clusters with the highest combined EOF values reveals six distinct modes of variability (i.e., Principal Component [PC] groups) with unique PSD traits. These groups are then correlated with environmental factors using data from collocated vertically pointing radar, surface meteorology, and reanalysis to assist in assigning physical attributes. The first and second PC groups, linked to EOF1’s intensity embedding, are described by their PSD intercepts, snowfall rates, and reflectivity and Doppler velocity values, representing low and high intensity snowfall modes, respectively. The third and fourth PC groups, associated with EOF2’s character embedding, are defined by temperature, fall speed, and density, indicative of cold, fluffy snowfall and warm, dense snowfall, respectively. The fifth and sixth PC groups, related to EOF3’s regime embedding, are distinguished by their PSD slope, snowfall rate, and reflectivity profiles, signifying shallow, weak convective systems with small particles, and deep, stratiform snowfall events with large aggregates, respectively.

Comminution Energy Based on Particle Size Distribution and Crushing Mechanism During Coal and Gas Outburst

Comminution Energy Based on Particle Size Distribution and Crushing Mechanism During Coal and Gas Outburst

New Copper(I) oxide biocatalyst based on functionalized olive stone for the synthesis of 1,4-disubstituted-1,2,3-triazoles under very mild conditions

An efficient methodology for coating silanized olive stone with copper(I) oxide has been described and fully characterized using various techniques, including X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR-ATR), X-ray fluorescence (XRF), electronic microscopy, thermogravimetric analysis (TGA), moisture content, electrophoretic mobility and particle size distribution. The applicability of this new biocatalyst in the 1,3-dipolar cycloaddition click reaction between alkynes and azides has been demonstrated leading to the obtention of a great variety of 1,4-disubstituted-1,2,3-triazoles with good to excellent conversions. The new biocatalyst showed promising features in terms of recyclability and industrial or biomedical application. It could be recycled up to five times with minimal loss of catalytic activity when synthezing compound 3a-3n. Additionally, it was effective in the multi-gram scale synthesis of compounds 3b and 3e, which were tested for the first time in cells, specifically on the human fibroblast-derived M1 cell line, demonstrating that these compounds are non-cytotoxic and thus suitable for potential uses in biomedicine.

Particle Size Inversion Based on L1,∞-Constrained Regularization Model in Dynamic Light Scattering

Dynamic light scattering (DLS) is a highly efficient approach for extracting particle size distributions (PSDs) from autocorrelation functions (ACFs) to measure nanoparticle particles. However, it is a technical challenge to get an exact inversion of the PSD in DLS. Generally, Tikhonov regularization is widely used to address this issue; it uses the L2 norm for both the data fitting term (DFT) and the regularization constraint term. However, the L2 norm’s DFT has poor robustness, and its regularization term lacks sparsity, making the solution susceptible to noise and a reduction in accuracy. To solve this problem, the Lp,q norm restrictive model is formulated to examine the impact of various norms in the DFT and regularization term on the inversion results. On this basis, combined with the robustness of DFT and the sparsity of regularization terms, an L1,∞-constrained Tikhonov regularization model was constructed. This model improves the inversion accuracy of PSD and offers a better noise-resistance performance. Simulation tests reveal that the L1,∞ model has strong noise resistance, exceptional inversion precision, and excellent bimodal resolution. The inversion outcomes for the 33 nm unimodal particles, the 55 nm unimodal, and the 33 nm/203 nm bimodal experimental particles show that L1,∞ reduces peak errors by at most 6.06%, 5.46%, and 12.12%/3.94% compared to L2,2, L1,2, and L2,∞ models, respectively. These simulations are validated by experimental data.

Underestimated role of sea surface temperature in sea spray aerosol formation and climate effects

The uncertainty regarding the correlation between sea spray aerosol (SSA) formation and sea surface temperature (SST) hinders the accurate estimation of SSA’s impact on global climate. Here, we developed a temperature-controlled plunging SSA simulation tank to investigate the impact of SST on SSA formation from two perspectives: SSA particle size distribution and organic enrichment. Our findings show that SSA particle size decreases with decreasing SST, as exhibited by an increase in SSA within Aitken mode and a decrease in SSA within accumulation and coarse modes. SST can significantly enhance organic enrichment in SSA particles, while the multiplicative increases vary from 2 to 10 times depending on the organic matter species and the SSA particle size. Based on our experimental results, it is predicted that SST reduction may lead to a significantly higher contribution of Aitken modal SSA-derived CCN in cold waters (0 °C) than in warm waters (30 °C). Additionally, we incorporate SST for the first time in estimating the global flux of dissolved organic carbon (DOC) emitted via SSA, yielding a value ranging from 23.45 to 55.78 Tg C yr−1. Compared to previous works, our study reveals the crucial role of SST in influencing both cloud formation and the atmospheric organic burden of SSA.

How ultrasonication treatment drives the interplay between lysinoalanine inhibition and conformational performances: A case study on alkali-extracted rice residue protein isolate.

Lysinoalanine (LAL) formed during alkaline extraction of rice residue protein (RRPI), which limited its application in the food industry. In this study, the influence of ultrasonication parameters (acoustic power density, ultrasound duration, and ultrasound temperature) on the inhibition of LAL formation and conformational attributes of RRPI during alkaline extraction was elucidated. The results suggested that the acoustic power density substantially modified the chemical interaction forces between RRPI molecules. At a power density of 60W/L, the ionic bonds (14.37%) and hydrophobic interactions (49.28%) reached the maximum, while hydrogen bonds (15.29%) and disulfide bonds (21.06%) reached the minimum. Moreover, acoustic power density at 60W/L caused a decrease of 18.02% and 12.2% in α-helix, and β-turn, respectively, shifting toward β-sheet, random coil, with an increase of 7.31% and 36.16%. Following ultrasonication, the protein particle size distribution curve shifted in the direction of smaller particle size, forming a relatively concentrated and uniform protein distribution. Sonication power, temperature, and time decreased the absolute value of Zeta potential. Furthermore, significant destruction in microstructure was elicited by sonication, which made the structure looser and more microparticles. Pearson correlation analysis suggested that the inhibition in the levels of LAL was most influenced by the increase of sulfhydryl groups and Zeta potential, as well as the reduction of α-helix content, in which the alteration of the total sulfhydryl group content had a great impact on the Zeta potential and the free sulfhydryl group. The principal component analysis demonstrated a notable correlation between the total sulfhydryl group and both the Zeta potential and free sulfhydryl group of RRPI.

Numerical simulation for spray spatial distribution of swirl nozzle and its target dustfall area prediction.

The droplet breakup and distribution of the internal flow field and external spray field of a nozzle were obtained under different pressures. The thickness of the liquid film increased with pressure as a quadratic function. The maximum value of 0.281mm at 2MPa decreased to 0.172mm at 10MPa, equivalent to 38.8% decrease. The MATLAB was used to obtain the particle size distribution characteristics of the droplets under different pressures. At 2MPa, droplet breakup dominated the axial interval [0-700mm]. With the increase of pressure, D50 distribution as a whole continues to decrease, 2-6MPa change, the particle size reduction is larger, every increase of 2MPa reduced by about 15%. 6-10MPa change, the particle size reduction is smaller, every increase of 2MPa reduced by about 8%. A model to predict the optimal dust reduction areas under varying pressures was developed. The prediction results indicate that at pressures of 5MPa and 9MPa, the target dust removal areas were [344mm, 710mm] and [424mm, 942mm] along the axial direction, respectively.

Use of lignocellulose-degrading enzyme bio-cemented soils in the construction industry

In their activity, termites break down biomass into glucose, forming cementitious compounds. This results in rainfall-resistant mounds for their shelters, which interests the construction industry. This study explored the potential application of the abundant naturally bio-cemented termite mound soils in highway construction. Experimental investigations compared these mound soils to surrounding soils, revealing that mound soils are 68.2% finer in particle size distribution and have 81.4% lower organic content. Atterberg limits indicated 14.6% higher plasticity and a 5.3% increase in specific gravity for mound soils. Atomic Absorption Spectroscopy (AAS) showed no significant difference in chemical composition. Proctor tests indicated that the compaction characteristics of the soils were comparable, confirming their engineering viability without modifications. Mound soils exhibited a twofold increase in Unconfined Compressive Strength (UCS) and a 33.9% increment in California Bearing Ratio (CBR) strength. One-way ANOVA tests confirmed these differences with p-value ranges of 0.0056-0.0361 below the 0.05 significance threshold. The study advocates utilising eco-friendly naturally bio-cemented mound soils in highway construction, meeting minimum standards. Mound soils from one acre can construct up to 2,500m highway, optimising resource use, promoting sustainability by repurposing natural materials, and significantly reducing carbon emissions. Further research on soil improvement using lignocellulose-degrading enzymes is recommended.

A Study of the Potential of Solidago virgaurea Extract as a Raw Material for Cosmetic Macroemulsions

The use of Solidago virgaurea extract as a raw material for cosmetics production fits the eco-tendency prevalent in the cosmetic industry for many years now perfectly. The study reported in this paper included an evaluation of the potential of the above-mentioned plant extract as a natural cosmetic ingredient applied in the form of cosmetic macroemulsions. The physicochemical parameters (pH, viscosity, particle size distribution) and physical stability (multiple light scattering) of the cosmetic formulations containing Solidago virgaurea (1.0 wt.%) were studied. An in vivo study was carried out on a group of 20 female volunteers. The results showed a high compatibility of the tested extract with the other components in the macroemulsion in the form of a serum for the body, which was the formulation containing Sorbitan Stearate as an emulsifier. Analysis of the results revealed a relation between the compatibility of the investigated herbal extract with the components of the cosmetic base and the effectiveness of this extract as an active substance. As a result of an improvement in the application parameters, an over 70% increase in the level of epidermis moisturization was observed along with other beneficial changes in the parameters of skin macrorelief and topography.

Microplastic pollution unveiled: the consequences of small unregulated dumping in villages, spanning from soil to water.

Microplastic contamination in soil ecosystems is a major environmental concern in the world. The current study aims to explore the extent of microplastic pollution in unregulated village dumpsites in India, focusing on the movement of these pollutants from soil to aquatic environments. Soil samples from eight distinct sites (A to H) in six villages were analyzed for various properties, including pH, bulk density, porosity, water retention capacity, hydraulic conductivity, and particle size distribution. The attenuated total reflection-Fourier-transform infrared spectroscopy (ATR-FTIR) method was used to identify prevalent plastic types. The research classifies microplastics by their shape and color, identifying a wide range of particles such as sheets, fibers, foams, fragments, and films. The study also examines the presence and concentration of microplastics in both soil and sediment samples. It was found that PE and PP microplastics are significantly present across different size fractions. Sample A contains a variety of items in the 1-5mm size range, mainly PE, while the 0.3-1mm fraction is largely PP. Samples B to H are mostly composed of PE microplastics in different forms. Sample F is unique with a mix of PE, EPS, and a higher amount of red and blue foam particles in the 0.3-1mm fraction. Microplastics were quantified using stereomicroscopy, revealing concentrations between 80 and 840 numbers per kilogram in soil and 20 to 60 numbers per kilogram in sediments. The findings emphasize the widespread nature of microplastic pollution across ecosystems and the importance of developing effective strategies for monitoring and mitigating their impact on environmental health and human well-being.