Number Of Particles Research Articles

Effect of droplet charge density on stabilization of oil‐in‐dispersion emulsions co‐stabilized by binary mixed surfactants and nanoparticles

AbstractIonic surfactant and similarly charged nanoparticles can co‐stabilize oil‐in‐dispersion (OID) emulsions at extremely low concentrations (0.001 cmc/0.001 wt%), in which particles do not adsorb at the oil/water interface but distribute in the aqueous phase forming a dispersion. In this paper, the effect of droplet charge density on stabilization of the n‐decane‐in‐water OID emulsion was examined by using a cetyl trimethyl ammonium bromide (CTAB)/C12B (dodecyl dimethyl carboxyl betaine) binary mixture at a low fixed total concentration (0.01 mM) with varying molar fractions of CTAB. A model based on the Derjaguin‐Landau‐Verwey‐Overbeek (DLVO) theory is proposed to calculate interaction energies between droplets and between droplets and particles. It is found that the droplet charge density can be well compensated by particle concentration along the stabilization boundary, and the OID emulsion still follows the DLVO stabilization. Particles tend to surround droplets at large distances but may form a monolayer between approaching droplets at shorter distances, which significantly reduces the van der Waals attraction between droplets. In addition, the induced auxiliary droplet–particle repulsion is proportional to the number of particles per unit area of droplet surfaces, which together with the droplet–droplet repulsion ensures a large total repulsion preventing droplets from flocculation and coalescence. This work explains quantitatively the stabilization of OID emulsions, which have potential applications in emulsion products such as foods, cosmetics, pesticides, and various industrial emulsion systems. Moreover, the development of the OID emulsions represents an important advancement in green chemistry as it substantially reduces the required amounts of emulsifiers and their environmental impact after use.

Modelling particle number size distribution: a continuous approach

Abstract Particulate matter (PM) is well known to be detrimental to health, and it is crucial to apportion PM into the underlying sources to target policies. Particle number size distribution (PNSD) is the most accessible data to identify these sources, which provides information on the PM sizes. Here, we propose a new functional factor model for PNSD, which allows to disentangle PM into sources and contributions while considering the complex dependencies of the data across different sizes and periods. Through a simulation study, we show that this method is able to identify sources correctly, and we use it to analyse hourly PNSD data collected in London for 7 years, finding 6 well-defined sources. Our proposed methodology is fast, accurate, and reproducible.

Analytical study of the time-fractional Smoluchowski coagulation equation in light of different integrodifferential operators

AbstractThis article presents the derivation of the fractional Smoluchowski coagulation equation via the variational principles technique. We use the variational iteration method to solve the Caputo-type fractional coagulation equation. Furthermore, we analyze the time-fractional coagulation equation using the homotopy perturbation transform approach, considering three different fractional operators: Caputo, Caputo-Fabrizio, and Atangana-Baleanu. Our findings demonstrate that the solutions for the total number of particles during coagulation align well with existing literature, particularly in the short time limit. Additionally, we examine the impact of the time-fractional order on the dynamics of particle coagulation for each fractional operator.

Comprehensive analysis of particle emissions from miniature turbojet engine

Emission of particulate matter from jet engines contribute to deterioration of air quality in the vicinty of the airports and to formation of contrails in higher layers of the atmosphere. This article presents the results of the measurements of particle emissions from a miniature jet engine GTM-120 fueled conventional aviation fuel Jet A-1. Analysis of particle size distribution, number, mass and volume emission indexes has been made, as well as the analysis of the emission intenisty and mass emission rate. Obtained results were related to LTO cycle phases. The results shows, that the particle number concentration was the lowest for low engine loads, with characteristic diameter of 69.8 nm and the particles concentration of 7.7 x 106 particles/cm3. For thrust increase, the characteristic diameter is smaller, and the particles distribution is no longer single-mode. The highest particles concentration for cm3 is for 100% thrust and is equal to 1.55 x 107 particles, with characteristic diameter of 34 nm.

Learning quantum properties from short-range correlations using multi-task networks

Characterizing multipartite quantum systems is crucial for quantum computing and many-body physics. The problem, however, becomes challenging when the system size is large and the properties of interest involve correlations among a large number of particles. Here we introduce a neural network model that can predict various quantum properties of many-body quantum states with constant correlation length, using only measurement data from a small number of neighboring sites. The model is based on the technique of multi-task learning, which we show to offer several advantages over traditional single-task approaches. Through numerical experiments, we show that multi-task learning can be applied to sufficiently regular states to predict global properties, like string order parameters, from the observation of short-range correlations, and to distinguish between quantum phases that cannot be distinguished by single-task networks. Remarkably, our model appears to be able to transfer information learnt from lower dimensional quantum systems to higher dimensional ones, and to make accurate predictions for Hamiltonians that were not seen in the training.

Global modeling of aerosol nucleation with a semi-explicit chemical mechanism for highly oxygenated organic molecules (HOMs)

Abstract. New particle formation (NPF) involving organic compounds has been identified as an important process affecting aerosol particle number concentrations in the global atmosphere. Laboratory studies have shown that highly oxygenated organic molecules (HOMs) can make a substantial contribution to NPF, but there is a lack of global model studies of NPF with detailed HOM chemistry. Here, we incorporate a state-of-the-art biogenic HOM chemistry scheme with 96 chemical reactions to a global chemistry–climate model and quantify the contribution to global aerosols through HOM-driven NPF. The updated model captures the frequency of NPF events observed at continental surface sites (normalized mean bias changes from −96 % to −15 %) and shows reasonable agreement with measured rates of NPF and sub-20 nm particle growth. Sensitivity simulations show that compared to turning off the organic nucleation rate, turning off organic initial growth results in a more substantial decrease in aerosol number concentrations. Globally, organics contribute around 45 % of the annual mean vertically integrated nucleation rate (at 1.7 nm) and 25 % of the vertically averaged growth rate. The inclusion of HOM-related processes leads to a 39 % increase in the global annual mean aerosol number burden and a 33 % increase in cloud condensation nuclei (CCN) burden at 0.5 % supersaturation compared to a simulation with only inorganic nucleation. Our work predicts a greater contribution of organic nucleation to NPF than previous studies due to the semi-explicit HOM mechanism and an updated inorganic NPF scheme. The large contribution of biogenic HOMs to NPF on a global scale could make aerosol sensitive to changes in biogenic emissions.

Evaluation of Two Particle Number (PN) Counters with Different Test Protocols for the Periodic Technical Inspection (PTI) of Gasoline Vehicles

Evaluation of Two Particle Number (PN) Counters with Different Test Protocols for the Periodic Technical Inspection (PTI) of Gasoline Vehicles

Shear rheology of confined double rings of dust particles in a dusty plasma

Abstract Shear rheology is a fundamental property of soft matter, which can be deformed. Although the shear rheology of fluids has been well studied at the macroscopic scale, understanding the microscopic processes of rheology at the single-particle level remains a challenging issue. Dusty plasma serves as an ideal platform for exploring microscopic dynamics of system at the individual particle level. Here, we study the shear rheology of confined double rings of strongly coupled dust particles in a dusty plasma. The outer ring is actively driven to rotate using laser illumination. Depending on the particle number, the inner ring may passively rotate following the outer ring at different angular speeds, resulting in shear rheology. The number of dust particles influences particle arrangement, which is characterized by the pair correlation function, bond-orientational order parameter, and triangle skewness. That further alters structural stability, significantly affecting the shear rheology.

Efficacy of Food Industry By-Product β-Glucan/Chitin–Chitosan on Lipid Profile of Overweight and Obese Individuals: Sustainability and Nutraceuticals

Fat-binding nutraceutical supplements have gained considerable attention as potential cholesterol-lowering strategies to address dyslipidemia in overweight and obese individuals. This study aimed to evaluate the effects of a polysaccharide-rich compound containing β-glucan/chitin–chitosan (βGluCnCs) on lipid profiles and lipoprotein function. In a prospective, two-arm clinical trial, 58 overweight and obese individuals were randomized to receive either 3 g/day of βGluCnCs or a placebo (microcrystalline cellulose) for 12 weeks. Serum lipids and lipoprotein functions were assessed at baseline and at 4-week intervals throughout the study. The administration of βGluCnCs led to a significant increase in HDL cholesterol (HDLc) levels and improved HDLc/non-HDLc and HDLc/total cholesterol (TC) ratios, while reducing apolipoprotein B (ApoB) levels (p < 0.05). However, the intervention did not affect HDL particle diameter, particle number, or lipoprotein functionality. Women demonstrated greater sensitivity to changes in HDLc during βGluCnCs supplementation, whereas men exhibited a significant reduction in ApoB levels. When stratified by baseline LDL cholesterol (LDLc) levels (cut-off: 130 mg/dL), the increase in HDLc and the ApoA1/ApoB ratio was found in the low-LDL group. In contrast, the high-LDL group experienced a significant reduction in atherogenic non-LDLc and LDLc, along with an improvement in HDL’s antioxidant capacity after βGluCnCs intervention. These changes were not statistically significant in the placebo group. In conclusion, our study demonstrated that daily supplementation with βGluCnCs significantly improved lipid profiles, with effects that varied based on sex and baseline LDLc levels.

Optimising the Particulate Emission Characteristics of a Dual-Fuel Spark Ignition Engine by Changing the Gasoline Direct Injection Strategy

In the current global scenario, it is essential to find more effective and practical solutions to mitigate the problem of particulate emissions from vehicles. In this research, particulate emission characteristics with changing GDI pressure or applying a split GDI strategy with different second injection timings were initially explored in a Dual-Fuel Spark Ignition (DFSI) engine, which employs Ethanol Port Injection (EPI) plus Gasoline Direct Injection (GDI). The experimental results show that by increasing GDI pressure (PGDI) from 5.5 MPa to 18 MPa, ignition delay (θF) shows a small decrease of 0.68 degrees. The parameters, such as maximum in-cylinder temperature (TMI) and exhaust gas temperature (TEG), each increase by 53.75 K and 13.84 K. An apparent reduction of 59.5% and 36.26% was achieved for the concentrations of particulate number (NP) and particulate mass (MP), respectively. Particulate emissions are effectively reduced by a split GDI strategy with an appropriate range of second injection timing (tGDI2). Under tGDI2 = −260 ºCA, NP and MP concentrations exhibit a relatively lower level. However, by delaying tGDI2 from −260 ºCA to −140 ºCA, there is an increase of more than 60% in NP concentration. The research findings help offer new and valuable insights into optimising particulate number and mass emissions from DFSI engines. Moreover, the findings could contribute novel and valuable insights into the optimisation of particulate emission characteristics in DFSI engines.

Exploration of plasma biomarkers for Alzheimer's disease by targeted lipid metabolomics based on nuclear magnetic resonance (NMR) spectroscopy.

Alzheimer's disease (AD) is the most common cause of dementia, but the disease lacks convenient and cost-effective alternative biomarkers currently. We utilized targeted lipid metabolomics based on nuclear magnetic resonance (NMR) spectroscopy to identify plasma biomarkers in AD patients. Our study was a cross-sectional study that enrolled 58 AD patients and 40 matched health controls (HCs). Firstly, we identified plasma lipid metabolites that were significantly different between the two groups based on P < 0.05 and variable importance in the projection (VIP) > 1. Then we examined the correlation between the lipid metabolites and cognitive function using partial correlation analysis and assessed the diagnostic ability of the lipid metabolites using receiver operating characteristic (ROC) curves. Seventeen lipoproteins showed significant differences between AD patients and HCs among 114 lipid metabolites. All 17 lipoproteins were subtypes of low-density lipoprotein (LDL). Among them, LDL-3 particle number, LDL-3 apolipoprotein-B, LDL-3 phospholipids, LDL free cholesterol and LDL phospholipids were significantly correlated with cognitive function. The ROC curves showed that LDL-2 triglycerides (TG) and LDL-3 TG could significantly distinguish AD patients from HCs, with the area under the curve (AUC) above 0.7. In addition, we explored a strategy of combined diagnosis that significantly improved the diagnostic efficacy for AD (AUC = 0.879). Our study provides insight into the lipoprotein alterations associated with AD and potential biomarkers for its diagnosis and cognitive function assessment.

An investigation of γ radiation detection with a CMOS imaging sensor.

In this study, a feasibility of γ radiation detection using complementary metal-oxide semiconductor (CMOS) image sensors with a neural network algorithm to extract the γ rays interacted pixels has been investigated. The responses characteristics of the CMOS imaging sensor to γ-ray is studied by placed in a γ fields produced by standard60Co or137Cs isotope sources. The supported preview frame rate of the CMOS image sensor is 25 fps, establishing the functional relationship between the gray level histograms and the dose rate through the neural network, the high energy γ-ray from60Co and137Cs source radiation dose rate in µSv/h level can be detected using the CMOS imaging sensor. The results show that the proposed method can effectively identify the number of photon particles which detected by the radiation monitoring system based on CMOS image sensor, and infer that the CMOS imaging sensor with a radiation signal extraction algorithm can be used as a dose warner for radiation protection purpose.

Microplastics contamination in three species of marine fish harvested by coastal land trawl in Banda Aceh City and Aceh Besar Regency waters, Indonesia

&lt;p style="text-align:justify;"&gt;&lt;span style="color:black;font-family:&amp;quot;Times New Roman&amp;quot;,&amp;quot;serif&amp;quot;;font-size:12pt;line-height:150%;"&gt;Banda Aceh City and Aceh Besar Regency are two of the areas experiencing rapid population growth and increased waste production, including plastics. The areas are directly adjacent to the coast, and the generated plastic waste has the potential to pollute the sea and fish. Therefore, this research aimed to analyze microplastics contamination in three species of marine fish caught in the coastal areas of Banda Aceh and Aceh Besar. The sampling was carried out for 3 months from January to March 2024 at three locations, namely Gampong Jawa (Station 1), Alue Naga (Station 2), and Krueng Raya (Station 3). The fish samples were ponyfish (&lt;/span&gt;&lt;em&gt;&lt;span style="color:black;font-family:&amp;quot;Times New Roman&amp;quot;,&amp;quot;serif&amp;quot;;font-size:12pt;line-height:150%;"&gt;Leiognathus equulus&lt;/span&gt;&lt;/em&gt;&lt;span style="color:black;font-family:&amp;quot;Times New Roman&amp;quot;,&amp;quot;serif&amp;quot;;font-size:12pt;line-height:150%;"&gt;), rabbitfish (&lt;/span&gt;&lt;em&gt;&lt;span style="color:black;font-family:&amp;quot;Times New Roman&amp;quot;,&amp;quot;serif&amp;quot;;font-size:12pt;line-height:150%;"&gt;Siganus canaliculatus&lt;/span&gt;&lt;/em&gt;&lt;span style="color:black;font-family:&amp;quot;Times New Roman&amp;quot;,&amp;quot;serif&amp;quot;;font-size:12pt;line-height:150%;"&gt;), and sardine fish (&lt;/span&gt;&lt;em&gt;&lt;span style="color:black;font-family:&amp;quot;Times New Roman&amp;quot;,&amp;quot;serif&amp;quot;;font-size:12pt;line-height:150%;"&gt;Sardinella gibbosa&lt;/span&gt;&lt;/em&gt;&lt;span style="color:black;font-family:&amp;quot;Times New Roman&amp;quot;,&amp;quot;serif&amp;quot;;font-size:12pt;line-height:150%;"&gt;). The results showed that there were four forms of microplastics, namely fibers, fragments, films, and pellets, with seven types of colors, including black, brown, clear, blue, red, yellow, and green. The dominant shape and color were fragment and black, respectively. In ponyfish, the highest and lowest number of microplastic particles were found in samples caught in Alue Naga waters (4.51 particles/fish) and Krueng Raya waters (2.80 particles/fish). Meanwhile, rabbitfish had the highest and lowest abundance in Alue Naga waters (3.60 particles/fish) and Gampong Jawa waters (2.83 particles/fish), respectively. The highest and lowest abundance of sardine fish was found in Gampong Jawa waters (3.77 particles/fish) and Krueng Raya waters (1.50 particles/fish), respectively. In general, ponny fish had a higher abundance of microplastics than the other two species, and microplastics were highest in fish from the Alue Naga station based on location. According to Fourier Transform Infrared Spectroscopy (FTIR) test on flesh samples of the species, three types of polymers were detected, namely latex, nylon, and polypropylene. In this context, the species analyzed were contaminated with microplastics and unsafe for consumption.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;

Application End Evaluation of Electrostatic Precipitation for Control PM and NOx Emissions from Small-Scale Combustions

Electrostatic precipitators (ESPs) have shown promise in reducing particulate matter (PM) emissions, but their potential for simultaneous NOx reduction in small-scale combustion systems remains underexplored. This study focuses on using non-thermal plasma generated in a corona discharge to reduce PM and NOx emissions from small-scale combustion. ESP was specifically designed for a commercially available 15 kW boiler with wood pellet combustion and used with both positive and negative discharge polarity to control emissions without any chemical additives. ESP performance was evaluated across a range of specific input energies (SIE) in terms of particle mass and number concentrations and NOx concentrations obtained by continuous gas analysis. ESP ensured the reduction in PM concentrations from 48 mg/m3 to the magnitude of PM content in the ambient air. The highest precipitation efficiency was observed for particles in the 20–200 nm range. Concurrently, NOx emissions were reduced by up to 78%, from 178 mg/m3 to 39 mg/m3. These results were achieved at specific input energies of 36 for positive and 48 J/L for negative corona, which is significantly lower than those reported for many existing separate PM and NOx control systems. This study demonstrates the potential of ESPs as a compact, energy-efficient solution for simultaneous PM and NOx removal in small-scale combustion systems, offering promising implications for improving air pollution control technologies for small-scale combustion systems.

Modeling Ocean Heat Transport to the Grounding Lines of Pine Island, Thwaites, Smith, and Kohler Glaciers, West Antarctica

AbstractPine Island, Thwaites, Smith, and Kohler glaciers in the Amundsen Sea Embayment (ASE) sector of West Antarctica experience rapid mass loss and grounding line retreat due to enhanced ocean thermal forcing from Circumpolar Deep Water (CDW) reaching the grounding lines. We use simulated Lagrangian particles advected with a looping 1 year output from the Southern Ocean high‐resolution model to backtrack the transport and cooling of CDW to these glaciers. For the simulated year 2005–2006, we find that the median time needed to reach the grounding lines from the edge of the ASE is 3 years. In addition, the Antarctic Coastal Current contributes an equal number of particles as off‐shelf sources to the grounding lines of Pine Island and Thwaites. For CDW coming from off‐shelf, results from SOhi indicate that 25%–66% of the cooling occurs within ice shelf cavities.

Virtual simulator for cystoscopy containing motion blur and bladder debris to aid the development of clinical tools

Cystoscopic data can be used to improve bladder cancer care, but cystoscopic videos are cumbersome to review. Alternatively, cystoscopic video data can be preserved in the form of a 3D bladder reconstruction, which is both informative and convenient to review. Developing algorithms for 3D reconstruction is an iterative process and often requires access to clinical data. Unfortunately, the time and access constraints of the urology clinical workflow can inhibit this technical development. In this manuscript, we present a virtual cystoscopy simulator to enable the creation of realistic and customizable cystoscopy videos through the inclusion of motion blur and bladder debris. The user can induce motion blur at set points in the video by setting the cystoscope speed between 1 and 9 cm/s. We also introduce 12 models of bladder debris particles, each model of which has a different color, shape, or size. The user can add bladder debris to the virtual bladder by specifying which debris models to include, the density of the particles, defining the number of particles in the bladder, and whether debris is stationary or blurred and moving at a user-defined speed. This simulator can be used to generate a large collection of unique and realistic cystoscopy videos with characteristics defined by the user for their specific purpose, thereby assisting the development of novel technologies for clinical implementation.

Associations of age and sex with characteristics of extracellular vesicles and protein-enriched fractions of blood plasma.

Extracellular vesicles (EVs) are nanosized particles that are released by various cell types and play vital roles in intercellular communication. They carry biological molecules reflecting the physiological and pathological states of their source cells and tissues, showing potential as biomarkers. However, the impact of demographic factors like age and sex on the properties of blood plasma EVs remains underexplored. This study aims to fill this gap by evaluating how these factors influence the particle count and proteomic profiles of plasma EV preparations and corresponding protein fractions. Plasma samples from 120 healthy volunteers were collected and pooled into six groups: young males (age: 27.6 ± 4.0), young females (27.4 ± 3.8), middle-aged males (48.8 ± 3.8), middle-aged females (48.9 ± 3.9), old males (69.3 ± 3.9), and old females (69.4 ± 4.3). EV- and protein-enriched fractions were separated by size-exclusion chromatography (SEC). Fractions were characterized for particle number concentration and protein composition to identify characteristics affected by age and biological sex. Plasma EVs and corresponding protein fractions exhibited distinct characteristics, with differential enrichment of markers related to EVs and other blood components, including lipoproteins. Proteomic profiles of both EVs and protein fractions displayed sex- and age-dependent differences. Differentially abundant proteins displayed functions previously identified in the context of aging and sex differences, highlighting their utility as biomarkers. Age and sex significantly affect the characteristics of plasma EVs and proteins, potentially influencing their efficacy and interpretation as biomarkers in clinical applications. This study lays the groundwork for detailed mechanistic research to understand how EVs mediate age- and sex-related effects in health.

A novel valve strategy for particulate matter reduction in a gasoline direct injection engine operated at cold conditions

In this study, we proposed a novel intake strategy to reduce Particulate matter (PM) emissions from gasoline direct-injection (GDI) engines during cold-start conditions emissions. This strategy is characterized by generating strong intake turbulence and low in-cylinder pressure during fuel injection through delayed intake valve opening, which theoretically promotes fuel atomization and fuel-air mixture, thereby suppressing PM formation during combustion. Experiments were conducted on a single-cylinder GDI research engine, operating at 1500 rpm, 3, 6, and 8 bar IMEP, and stoichiometric air-fuel ratio conditions with low coolant and lubricant temperatures to experimentally demonstrate the effectiveness of the proposed valve strategy in reducing PM emissions. Benchmark tests were performed using an intake camshaft with intake valve opening (IVO) at −13 °aTDC and intake valve closing (IVC) at 227 °aTDC. The novel strategy uses an intake camshaft with very late IVO at 66 °aTDC and IVC at 226 °aTDC. Two injection pressures (Pinj = 100/200 bar) were used to evaluate the pressure requirement for achieving low PM emissions with both strategies. Start of injection was swept and optimized to match the valve strategy. The results showed that the novel valve strategy leads to a 50%–90% reduction in particle number and mass emissions in cold-start conditions, and a lower injection pressure requirement to achieve comparable particle number and mass emissions compared with the normal one. For the novel valve strategy, the fuel impingement with early injection timings is largely mitigated, and thus an early injection timing shortly before the IVO is recommended.

Hypercholesterolemia and inflammation-Cooperative cardiovascular risk factors.

Maintaining low concentrations of plasma low-density lipoprotein cholesterol (LDLc) over time decreases the number of LDL particles trapped within the artery wall, slows the progression of atherosclerosis and delays the age at which mature atherosclerotic plaques develop. This substantially reduces the lifetime risk of atherosclerotic cardiovascular disease (ASCVD) events.In this context, plaque development and vulnerability result not only from lipid accumulation but also from inflammation. Changes in the composition of immune cells, including macrophages, dendritic cells, T cells, B cells, mast cells and neutrophils, along with altered cytokine and chemokine release, disrupt the equilibrium between inflammation and anti-inflammatory mechanisms at plaque sites. Considering that it is not a competition between LDLc and inflammation, but instead that they are partners in crime, the present narrative review aims to give an overview of the main inflammatory molecular pathways linked to raised LDLc concentrations and to describe the impact of lipid-lowering approaches on the inflammatory and lipid burden. Although remarkable changes in LDLc are driven by the most recent lipid lowering combinations, the relative reduction in plasma C-reactive protein appears to be independent of the magnitude of LDLc lowering. Identifying clinical biomarkers of inflammation (e.g. interleukin-6) and possible targets for therapy holds promise for monitoring and reducing the ASCVD burden in suitable patients.

Investigation of the potential of in-line particle concentration measurements in gas particle separation processes by using low-cost particulate matter sensors

In addition to the costly laboratory-based particle measurement devices, low-cost particulate matter sensors for ambient air quality measurements can also be employed for the detection of PM in gas cleaning devices. The ability to spatially resolve the actual level of particle number concentration with high temporal resolution within a gas-particle separation process is of significant value for process monitoring and control. The quantitative reliability of the measurement data from low-cost particulate matter sensors remains uncertain when the particle concentrations in the apparatus exceed the upper measurement limit of the sensors, whether temporarily or permanently. This study examines the potential of low-cost particulate matter sensors for in-line particle concentration measurements in gas-particle separation processes. The measurement performance of the low-cost particulate matter sensors is initially examined under idealised conditions in a dust chamber. This is done in order to quantify the deviations of the low-cost particulate matter sensors in comparison to a state-of-the-art precision laboratory high-cost sensor. Subsequently, both sensor types are installed at a wet separator test facility, following the quantification of their respective measurement performances. The low-cost particulate matter sensors are capable of measuring particle number concentration above their specified limit (up to ≈6.1×104cm−3), depending on the measurement conditions. By applying a 3rd polynomial correction function, obtained from the initial quantification measurement, the low-cost particulate matter sensors are able to reproduce the particle number concentration measured by the high-cost sensor. Furthermore, the low-cost particulate matter sensors are capable of reproducing short-term fluctuations in the particle number concentration.