Concentration Of Suspended Particles Research Articles

Looking at the relationship of PM10 suspended particle concentration from daily observations and annual observations of the Ipoh Meteorological Department, Perak

The objective of the study is to see the relationship between the concentration of suspended particulate matter (PM10) from daily observation data and annual observation data from the Ipoh Meteorological Department. In general, the data required in this study can be divided into two groups of data, namely primary data and secondary data. Primary data is obtained through observation using the field study method and observed in the field horizontally while secondary data is from annual observation records. Observations are carried out at 34 stations determined based on the source of pollution. In this study, the selected location is in the Ipoh, Perak area and the focus of the research problem is the high data obtained from the annual observation of suspended particles. The results of the study found that there is a relationship between the annual concentration of suspended particles and the concentrations of daily observations. Studies have shown that industrial areas and factories such as cement factories, limestone factories, and stone crushing areas are the main sources of pollution with high concentrations of suspended particles in Ipoh.

Statistical analysis of air quality dataset of Kathmandu, Nepal, with a New Extended Kumaraswamy Exponential Distribution.

This paper aims to create a new probability distribution and conducts statistical analysis on air quality dataset from Kathmandu. Using this innovative distribution, we have studied the ground reality of air quality conditions of Kathmandu, Nepal. In our research, we have developed a new probability distribution known as the New Extended Kumaraswamy Exponential Distribution by introducing an additional shape parameter to the Extended Kumaraswamy Exponential (EKwE) Distribution. Statistical characteristics such as cumulative distribution function, probability density function, hazard function, reversed hazard function, skewness, kurtosis, survival function, and hazard rate function are studied. The suggested model is non-normal and positively skewed with increasing and inverted bathtub-shaped hazard rate curves. To assess the model's suitability, we utilized a real dataset comprising air quality data from Kathmandu, Nepal, during the year 2021. Study shows that the air quality data exhibit an increasing failure rate, but the P2.5, P10, and total suspended particle concentrations exhibited its lowest levels during the monsoon season and its highest levels during the winter season. Parameters of the model are estimated by using the least square estimation (LSE), maximum likelihood estimation (MLE), and Cramér-von Mises (CVM) approach for P10 at Ratnapark Station, Kathmandu. To assess the model's validity, P-P plots and Q-Q plots are employed. Model comparisons are carried out using Akaike Information Criterion (AIC), Corrected Akaike Information Criterion (CAIC), Bayesian Information Criterion (BIC), and Hannan-Quinn Information Criterion (HQIC). Furthermore, the goodness of fit of the proposed model is evaluated using test statistics such as Anderson-Darling (A2) test, Cramér-von Mises (CVM) test, and the Kolmogorov-Smirnov (KS) test along with their respective p-values. From the findings, we have found that the air quality status of Kathmandu, Nepal, was found to be poor. Proposed distribution provides a better fit with greater flexibility for forecasting air quality data and conducting reliability data analyses. Dataset is analyzed and visualized using R programming.

Variability and relationships between the size, composition and optical properties of suspended particulate matter in the coastal waters of western Spitsbergen, assessed through measurements of size-fractionated seawater samples

Measurements of inherent optical properties (IOPs) and characteristics of concentration and composition of suspended particles were made on original and size-fractionated surface water samples from Arctic fjords and coastal waters of western Spitsbergen in the Svalbard archipelago, in the summer months of 2021 and 2022. Optical measurements included the spectral scattering coefficient of particles, and spectral absorption coefficients of particles as well as depigmented (non-algal) particles and phytoplankton. Assemblages of suspended particles were characterised by measuring the mass concentrations of suspended particulate matter (SPM), particulate organic matter (POM), particulate inorganic matter (PIM), and phytoplankton pigments including chlorophyll a (Chla). All measurements were performed on original (unfiltered) seawater and on size-fractionated samples obtained by filtration using a combination of nylon meshes and membrane filters. This allowed us to determine the contribution of the fractions of very small (VS), small (S) and combined medium and large particles (ML) to the total SPM and Chla, as well as to the total scattering and absorption coefficients. The obtained results: (i) indirectly indicate a clear variability in particle size distributions occurring in the studied marine environment (e.g., the contribution of ML size fraction to SPM (the ratio SPMML/SPM) varied between 0.10 and 0.52); (ii) indicate noticeable differences in composition between size fractions (e.g., the POM/SPM ratio was on average 0.21 for the S fraction, and 0.34 and 0.32 for the VS and ML fractions, respectively); (iii) in most cases indicate that the fraction S had the largest contribution to all analysed spectral optical coefficients, followed by the VS and ML fractions (the average contributions of the S fraction to scattering coefficient of particles and absorption coefficient of particles or depigmented (non-algal) particles were above 0.6 in the entire analysed spectral ranges); (iv) allowed for the identification of statistical relationships between selected characteristics describing changes in particle size and variability of particle IOPs (e.g., we observed statistical relations between SPMML/SPM and the spectral slope of scattering coefficient by particles, as well as SPM-specific coefficients of scattering by particles).

Efficiency assessment of vortex tubular enameled coalescing devices for oil emulsion destabilization

The greatest intensity of the process of dispersion and subsequent coalescence of oil droplets in emulsified wastewater of oilfields takes place in the near-wall areas of tubular coalescing devices. Strengthening of the wall effect is possible by covering the surface of the flowing part of the coalescing device with silicate enamel, which provides the effect of sliding of the turbulent flow of waste water (emulsion) on a thin adhesive layer that appears directly on the surface of the enamel. Experimental studies to determine the effectiveness of treatment of oily wastewater in tubular vortex-type coalescing devices were carried out on an experimental unit consisting of three coalescing devices connected in series. Each coalescing device was a tubular shaft coaxially connected to the inlet and outlet chambers. Vortex tubular coalescing devices made of stainless steel (not coated with enamel) and vortex coalescing devices of similar design coated with silicate enamel were used in the experiments. The wastewater treated in the unit was sedimented, and the concentrations of oil and suspended particles were determined in the clarified water. Analysis of the data obtained showed that at the time of wastewater treatment from 1.1 to 6.3 s sedimentation effect on oil particles after coalescing devices coated with enamel on average by 1.5 to 1.8% was higher than the sedimentation effect obtained after the treatment of oil emulsion in coalescing devices not coated with enamel. The sedimentation effect on suspended solids in the second series of experiments was greater than the sedimentation effect observed in the first series by an average of 1.1-1.4 %.

Air quality assessment model

This study examines the application of machine learning methods to predict air quality in Brisbane, Australia. The main attention is paid to the creation of a model capable of predicting the concentration of PM10 suspended particles based on meteorological data. In the course of the work, a statistical analysis of the factors influencing the level of pollution was carried out, and a random forest model was developed and tested. The results showed that the model is able to explain about 69% of the variation in PM10 concentration, and also identified key meteorological parameters such as air temperature and wind speed that have the greatest impact on the concentration of pollutants. The data obtained can be used to improve the monitoring and management of air quality in cities, which in the future may contribute to reducing the harmful effects of pollution on public health.

Structure and short-time diffusion of concentrated suspensions consisting of silicone-stabilised PMMA particles: a quantitative analysis taking polydispersity effects into account.

We characterise structure and dynamics of concentrated suspensions of silicone-stabilised PMMA particles immersed in index-matching decalin-tetralin mixtures by means of static and quasielastic light scattering experiments. These particles can reproducibly be prepared via a comparatively easy route and are thus promising model systems with hard-sphere interaction. We demonstrate the hard-sphere behaviour of dense suspensions of these systems rigorously taking polydispersity effects into account. Structure factors S(Q) can in the entire range of volume fractions with liquid-like structure quantitatively be modelled using a multi-component Percus-Yevick ansatz regarding the particle size distribution and the form factor assuming a core-shell model with a scattering length density gradient in the PMMA core. Herewith, hydrodynamic functions H(Q) are in the whole accessible Q-range beyond the second maximum of H(Q) quantitatively modelled using a rescaled δγ-approach for all investigated volume fractions. With these data, previously provided characterisation of dilute systems is extended: the excellent agreement of structural and dynamic properties with theoretical predictions for hard spheres demonstrates the suitability of these particles as a model system for hard spheres.

Modeling of PM concentrations on a construction site based on IoT monitoring system

An IoT-based system framework integrating a distributed sensor network was implemented to collect real-time data at a construction site. Various sensors were utilized to gather data concerning particulate matter (PM2.5 and PM10 concentrations) as well as meteorological parameters - wind speed, humidity, pressure, and temperature. The real-time measurements results provide an overview of air pollution levels at the construction site, revealing its association with earth excavation work, the primary construction activity. This connection allows for better management aimed at reducing concentrations of suspended particles. Through on-site monitoring of two pollutant concentrations, this study identified that the dust levels resulting from excavation activities were relatively high. It can be concluded that earth excavation significantly impacts air quality in the construction area. While exploring the primary factors influencing construction dust concentrations, the correlations indicate that these concentrations were not significantly associated with meteorological factors. To predict PM2.5 and PM10 concentrations in the air using number of working machines and meteorological parameters as predictors, both Multiple linear regression (MLR) and Artificial Neural Network (ANN) models were applied. The ANN model demonstrates better alignment with the measured air concentrations compared to the MLR model. The ANN model demonstrated an R-squared value of 0.674 for PM10 and 0.618 for PM2.5, indicating a strong predictive capability. The aim of this research, through modeling PM2.5 and PM10 concentrations in the air at the construction site is to indicate importance of the topic, especially with respect to the health of the constuction site workers.

A hyperspectral view of the nearshore Mississippi River Delta: Characterizing suspended particles in coastal wetlands using imaging spectroscopy

Suspended particle concentration (Total Suspended Solids or TSS) determines sediment availability for deposition, whereas particle physico-chemical properties (e.g. composition and size) can influence sediment transport and accretion. These variables are critical to modeling and understanding nearshore sediment dynamics and coastal soil accretion and erosion. Upcoming satellite imaging spectrometers (e.g., GLIMR, SBG) have the potential to improve the detailed mapping and characterization of suspended particles in nearshore areas. Here, we conducted a detailed feasibility study assessing the capacity of imaging spectroscopy to accurately map suspended particle concentrations and physico-chemical properties in the Mississippi River Deltaic Plain (Louisiana, USA), a nearshore system with extreme coastline vulnerability. To that end, a large dataset of in situ TSS, Particulate Organic Carbon (POC) concentration, particle size, inherent optical properties (IOPs), and hyperspectral remote sensing reflectance (Rrs) was collected during the 2021 NASA Delta-X field campaigns in coastal Louisiana. Analyses of the data revealed that the enhanced spectral information provided by imaging spectroscopy (hyperspectral Rrs) improved the retrieval of TSS and POC/TSS (% organic carbon content), but highlighted the challenge of retrieving particle size in this system. Partial-least-squares-regression (PLSR) algorithms for TSS performed better than existing state-of-the-art algorithms and confirmed the importance of using local measurements and near-infrared Rrs. Implementation on Airborne Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery generated high-resolution (< 5 m), high-quality maps of TSS and POC/TSS in contrasted areas with a wide range of TSS concentrations from (0.1 to 100 mg L−1), and demonstrated the enhanced potential of upcoming missions such as SBG and GLIMR to inform studies of nearshore sediment dynamics and coastal vulnerability/resilience.

Indoor air quality improvement with filtration and UV-C on mitigation of particulate matter and airborne bacteria: Monitoring and modeling

Indoor air, especially with suspended particulate matter (PM), can be a carrier of airborne infectious pathogens. Without sufficient ventilation, airborne infectious diseases can be transmitted from one person to another. Indoor air quality (IAQ) significantly impacts people's daily lives as people spend 90% of their time indoors. An industrial-grade air cleaner prototype (filtration + ultraviolet light) was previously upgraded to clean indoor air to improve IAQ on two metrics: particulate matter (PM) and viable airborne bacteria. Previous experiments were conducted to test its removal efficiency on PM and airborne bacteria between the inlet and treated air. However, the longer-term improvement on IAQ would be more informative. Therefore, this research focused on quantifying longer-term improvement in a testing environment (poultry facility) loaded with high and variable PM and airborne bacteria concentrations. A 25-day experiment was conducted to treat indoor air using an air cleaner prototype with intermittent ON and OFF days in which PM and viable airborne bacteria were measured to quantify the treatment effect. The results showed an average of 55% reduction of total suspended particulate (TSP) concentration between OFF days (110 μg/m3) and ON days (49 μg/m3). An average of 47% reduction of total airborne viable bacteria concentrations was achieved between OFF days (∼3200 CFU/m3) and ON days (∼2000 CFU/m3). A cross-validation (CV) model was established to predict PM concentrations with five input variables, including the status of the air cleaner, time (h), ambient temperature, indoor relative humidity, and day of the week to help simulate the air-cleaning effect of this prototype. The model can approximately predict the air quality trend, and future improvements may be made to improve its accuracy.

Developing particle-based models to predict solar energy attenuation using long-term daily remote and local measurements

Iran has an annual average of 2.8–5.4 kW h/m2d of radiation and has a high capacity for extracting electricity from its solar resources. Tehran, the capital of Iran, is one of the most polluted cities in the world in terms of atmospheric aerosols. Due to the rising air pollution in Tehran, the existing research is outdated. An analysis of the loss of electricity generation due to particulates can significantly affect the feasibility of a photovoltaic power plant in Tehran. Several factors affect the electricity generation of photovoltaic systems. The most critical is solar radiation. The amount of solar radiation transmitted and, ultimately, the amount of electricity generated depends on several atmospheric factors. One of the most important factors is the concentration of suspended particles of different sizes. In the present work, linear models based on observed suspended particle concentrations, including PM10 and PM2.5, have been proposed for Tehran from 2014 to 2020 to anticipate the aerosol attenuation index due to aerosols. Based on the correlation coefficient values (R), in the first and last months of the year, November, December, and January, the models performed better to predict the aerosol attenuation index based on PM2.5. The R values were, in order, 0.1553, 0.2926, and 0.1341. As remote measurements, the NASA CERES syn 1-deg product parameters and, as ground observations, Surface Solar Radiation (SSR) and PM10 and PM2.5 concentrations were used to estimate the impacts of aerosols on radiation. With the help of the CERES syn 1-deg product, it is declared that, on average, 8.30% of the total radiation received was wasted due to the presence of aerosols. Considering observed SSR, CERES syn 1-deg product performance was validated, with RMSE and MBD values of 14.09% and 10.89%, respectively.

Anomalous Solute Transport Using Adsorption Effects and the Degradation of Solute

In this work, anomalous solute transport using adsorption effects and the decomposition of solute was studied. During the filtration of inhomogeneous liquids, a number of new phenomena arise, and this is very important for understanding the mechanisms of the filtration process. Recently, issues of mathematical modeling of substance transfer processes have been intensively discussed. Modeling approaches are based on the law of matter balance in a certain control volume using additional phenomenological relationships. The process of anomalous solute transport in a porous medium was modeled by differential equations with a fractional derivative. A new mobile—immobile model is proposed to describe anomalous solute transport with a scale-dependent dispersion in inhomogeneous porous media. The profiles of changes in the concentrations of suspended particles in the macropore and micropore were determined. The influence of the order of the derivative with respect to the coordinate and time, i.e., the fractal dimension of the medium, was estimated based on the characteristics of the solute transport in both zones. The hydrodynamic dispersion was set through various relations: constant, linear, and exponential. Based on the numerical results, the concentration fields were determined for different values of the initial data and different relations of hydrodynamic dispersion.

Effects of suspended particles and dispersants on marine oil snow formation of crude oil/diesel oil.

Marine oil snow (MOS) potentially forms after an oil spill. To fully understand the mechanism of its formation, we investigated the effects of suspended particles (SP) and dispersants on MOS formation of crude oil and diesel oil by laboratory experiments. In the crude oil experiment, the SP concentration of 0.2 g L-1 was more suitable for crude oil MOS formation. The addition of dispersants significantly stimulated N and TV during MS/MOS formation of SP at 0.4 g L-1 and 0.8 g L-1 concentration (p < 0.05). Without SP, the dispersants also stimulated crude oil MOS formation. Furthermore, the concentration of SP had a significantly positive effect on the reduction of the total amount of N-alkanes (p < 0.05). In the diesel oil experiment, after adding dispersants to diesel oil, the maximum N, Dm, and TV values at a SP concentration of 0.2 g L-1 were significantly higher than those at 0.4 g L-1 and 0.8 g L-1 (p < 0.05). Besides, we found that dispersants stimulated MOS formation in diesel oil at a SP concentration of 0.2 g L-1. However, the dispersants had an inhibitory effect on diesel oil MOS formation without SP. Notably, the MOS formed by diesel oil appeared white, unlike the black MOS associated with crude oil. These findings are important for the environmental impact of oil spills and elevated SP concentrations.

Drivers of microbial food-web structure along productivity gradients.

Ratios between viruses, heterotrophic prokaryotes and chlorophyll a are key indicators of microbial food structure and both virus-prokaryote and prokaryote-chlorophyll ratios have been proposed to decrease with system productivity. However, the mechanisms underlying these responses are still insufficiently resolved and their consistency across aquatic ecosystem types requires critical evaluation. We assessed microbial community ratios in highly productive African soda-lakes and used our data from naturally hypereutrophic systems which are largely underrepresented in literature, to complement earlier across-system meta-analyses. In contrast to marine and freshwater systems, prokaryote-chlorophyll ratios in African soda-lakes did not decrease along productivity gradients. High-resolution time series from two soda-lakes indicated that this lack of response could be driven by a weakened top-down control of heterotrophic prokaryotes. Our analysis of virus-prokaryote relationships, revealed a reduction of virus-prokaryote ratios by high suspended particle concentrations in soda-lakes. This effect, likely driven by the adsorption of free-living viruses, was also found in three out of four additionally analysed marine datasets. However, the decrease of virus-prokaryote ratios previously reported in highly productive marine systems, was neither detectable in soda-lakes nor freshwaters. Hence, our study demonstrates that system-specific analyses can reveal the diversity of mechanisms that structure microbial food-webs and shape their response to productivity increases.

Effect of solution pH and polyethylene oxide concentration on surface/interface properties, flocculation and rheology of concentrated monodisperse ultrafine synthetic tailings slurry

The effects of polyethylene oxide (PEO) dosage and solution pH on the flocculation, rheological and surface/interfacial properties of the slurry were investigated by sedimentation, rheology, adsorption and surface force experiments. The results demonstrate that the initial settling rate (ISR) of the tailings is at its lowest in strongly acidic solutions. The ISR reaches its peak in strongly alkaline solutions. The PEO dosage exhibits a modest impact on the yield stress of the concentrate in strong acid solutions, while it wields a notable influence on the yield stress in neutral and strongly alkaline solutions. Quartz crystal microbalance with dissipation (QCM-D) measurements reveal that strong alkaline solutions enhance the adsorption of PEO chains on silica surfaces. Strongly acidic solutions partially inhibit the adsorption of PEO chains. Surface force measurement results indicate that PEO chains can bridge the tailings particles in concentrated suspensions through hydrogen bonding, and consequently elevating the suspension's yield stress.

Dynamics of wire frame glasses in two dimensions.

The dynamics of wire frame particles in concentrated suspension are studied by means of a 2D model and compared to those of rod-like particles. The wire frames have bent or branched structures constructed from infinitely thin, rigid rods. In the model, a particle is surrounded by diffusing points that it cannot cross. We derive a formal expression for the mean squared displacement (MSD) and, by using a self-consistent approximation, we find markedly different dynamics for wire frames and rods. For wire frames, there exists a critical concentration of points above which they become frozen with the long time MSD reaching a plateau. Rods, on the other hand, always diffuse by reptation. We also study the rheology through the elastic stress, and more striking differences are found: the initial magnitude of the stress for wire frames is much larger than for rods, scaling such as the square of the point concentration, and above the critical concentration, the stress for wire frames appears to persist indefinitely while for rods it always decays.

Source Identification and Characterization of Indoor Particulate Matter in Potala Palace Museum

This study aims to determine the sources of indoor particulate matter at the Potala Palace Museum in Tibet, China, and evaluate the potential hazards of these pollutants for cultural relics. Long-term monitoring of indoor and outdoor suspended particulate matter concentrations was conducted, and sediment particle samples were collected. The chemical composition of the deposited particles was determined using X-ray fluorescence analysis (XRF). The outdoor suspended particulate concentration was much lower than that indoors; the indoor PM1-10 concentration was much higher than that outdoors and was less affected by outdoor sources. The sources of indoor deposited particles in the high-plateau museum can be classified into four categories: soil dust brought in by tourists from the outdoors, incense ash, pollution from human activities, and ores. Based on data analysis and discussion, proper ventilation can dilute indoor suspended particulate matter, and the installation of air conditioning systems can control temperature and humidity at 20 °C and about 45–60%, respectively, and reduce the fluctuation value, so as to promote particle deposition and better protect the museum’s cultural relics.

Modeling the concentration of suspended particles by fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS) techniques: A case study in the metro stations

Background: Today, the usage of artificial intelligence systems and computational intelligence is increasing. This study aimed to determine the fuzzy system algorithms to model and predict the amount of air pollution based on the measured data in subway stations. Methods: In this study, first, the effective variables on the concentration of particulate matter were determined in metro stations. Then, PM2.5, PM10, and total size particle (TSP) concentrations were measured. Finally, the particles’ concentration was modeled using fuzzy systems, including the fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS). Results: It was revealed that FIS with modes gradient segmentation (FIS-GS) could predict 76% and ANFIS-FCM with modes of clustering and post-diffusion training algorithm (CPDTA) could predict 85% of PM2.5, PM10, and TSP particle concentrations. Conclusion: According to the results, among the models studied in this work, ANFIS-FCM-CPDTA, due to its better ability to extract knowledge and ambiguous rules of the fuzzy system, was considered a suitable model.

Deriving particulate backscattering coefficient at 400 nm from small-scale optically shallow waters using Landsat-8 data: a case study at Luhuitou Peninsula, Sanya.

The particulate backscattering coefficient (bbp) plays an important role in the growth of coral reefs by influencing the light field conditions. Small-scale optically shallow waters are commonly found in coastal fringing reefs, making it challenging to monitor the spatial and temporal patterns accurately using Aqua satellites with a low spatial resolution. In this study, six existing optimization-based algorithms for deriving bbp at 400 nm (bbp(400)) were evaluated with three simulated Landsat-8 (spatial resolution = 30 m) data sets and in situ data from the Luhuitou Peninsula, Sanya. The comparison results indicated that the HOPE (hyperspectral optimization process exemplar) (Fix-H-error or Fix-H-error-free) algorithm which sets an input value of the water depth alone outperformed other algorithms. However, the estimated bbp(400) from all the algorithms tended to be either overestimated and underestimated due to the improper the spectral shape value of the backscattering coefficient. The HOPE (Fix-H-error) algorithm estimated-bbp(400) from in situ reflectance also had a good correlation with the in situ total suspended particle concentrations data derived-bbp(400), with a correlation coefficient of 0.83. Therefore, the HOPE (Fix-H-error) algorithm was selected to estimate the bbp(400) from satellite-based Landsat-8 data of the Luhuitou Peninsula, Sanya. Time-series (2014-2021) results from these Landsat-8 images reveal the seasonal variation of bbp(400). The bbp(400) was low from May to September every year. From October to December or January, bbp(400) had an increasing trend, and then it decreased until May. Spatial analysis indicated that bbp(400) decreased with increasing water depth. The spatial and temporal patterns of bbp(400) were consistent with in situ observations reported in the literature. This study preliminarily showed the efficiency of an optimization-based algorithm in deriving bbp(400) in small-scale optically shallow water region using Landsat-8 data.

Charge fluctuations in charge-regulated systems: dependence on statistical ensemble.

We investigate charge regulation of nanoparticles in concentrated suspensions, focusing on the effect of different statistical ensembles. We find that the choice of ensemble does not affect the mean charge of nanoparticles, but significantly alters the magnitude of its fluctuation. Specifically, we compared the behaviors of colloidal charge fluctuations in the semi-grand canonical and canonical ensembles and identified significant differences between the two. The choice of ensemble-whether the system is isolated or is in contact with a reservoir of acid and salt-will, therefore, affect the Kirkwood-Shumaker fluctuation-induced force inside concentrated suspensions. Our results emphasize the importance of selecting an appropriate ensemble that accurately reflects the experimental conditions when studying fluctuation-induced forces between polyelectrolytes, proteins, and colloidal particles in concentrated suspensions.

Study of traffic-related pollution and its treatment with a particular focus on microplastics in tunnel wash and road runoff water.

Treatment of tunnel wash runoff water and road runoff water before it reaches the environment is recommended to limit the negative consequences of traffic-related pollution. The efficiency of existing water treatment systems to remove traffic-related microplastic (MP) has not been sufficiently documented. Expanding the knowledge about traffic-related MP and documenting the treatment efficiency of MP in road tunnel wash water (TWW) and road runoff (RRW) treatment systems were the objectives of the presented project. TWW from the Tåsen tunnel, Norway, and RRW from the Fossbekken sedimentation pond were investigated in summer and winter situations. Six commonly available polymer types, tire rubber tread particles (TRP), and road marking paints (RMP) were analyzed in the selected samples. About 0.12 and 0.26 μg/L of polymers were identified in winter and summer TWWs. Significantly higher tire rubber and road marking paint concentrations were identified in the winter sample compared to summer sample. Suspended particle concentration in the Fossbekken RRW treatment pond effluent was lower in the summer than in the winter sample. About 0.002 and 0.0008 μg/L polymer masses were identified in winter and summer samples, respectively. TRP in the winter and summer samples were 0.7 and 0.2 μg7/L, and 13.4 μg/L RMP was found in the winter sample, while it was only 0.008 μg/L in the summer sample.