Volume Particle Size Distribution Research Articles

A Regional Aerosol Model for the Oceanic Area around Eastern China Based on Aerosol Robotic Network (AERONET)

A regional aerosol model can complement globally averaged models and improve the accuracy of atmospheric numerical models in local applications. This study established a seasonal aerosol model based on data from the Aerosol Robotic Network (AERONET) of the sea area around eastern China, and its performance in calculating the aerosol optical depth (AOD) was evaluated. The seasonal columnar volume particle size distributions (VPSDs) illustrated a bimodal structure consisting of fine and coarse modes. The VPSDs of spring, autumn, and winter roughly agreed with each other, with their amplitudes of fine and coarse modes being almost equal; however, the fine mode of the summer VPSD was approximately twice as high as that of the coarse mode. Lognormal mode decomposition analysis revealed that fine and coarse modes comprised two sub-modes. Fitting the seasonal VPSDs to the four-mode lognormal distribution yielded a parameterized aerosol size distribution model. Furthermore, seasonal variations in complex refractive indices (CRIs) indicated unignorable changes in aerosol compositions. Overall, error analysis validated that the proposed model could meet accuracy requirements for optical engineering applications, with median AOD calculation errors of less than 0.01.

Fibre alignment in fresh concrete with coarse aggregates and its visualization in transparent model concrete

Steel fibres distributed in concrete can greatly improve the mechanical performance of concrete, especially flexural and tensile behavior, if their orientations align to the direction of principal tensile stress. The study attempts to find diversified characters of fibre alignment in fresh concrete with consideration of adding coarse aggregates. A transparent concrete model, consisting of Carbopol gel, glass beads and crystals, is designed for the observation of fibre orientation. It shows good transparency and visibility, and can consider the effect of coarse aggregates since the volume fraction and particle size distribution of crystals are the same as coarse aggregates in real concrete mixture. The rheological properties of the model can be adjusted by the dosage of Carbopol and glass beads. Using this concrete model, the distribution and orientation of fibres can be directly observed and analyzed, considering the effect of aggregate sizes, concrete rheology and vibration time. The results show that coarse aggregates could limit the distribution space of fibres and lead to the decrease of fibre orientation coefficient. Fibre dispersion coefficient also decreases with the increase of aggregate sizes.

Sensory Evaluation, Physico-Chemical Properties, and Aromatic Profile of Pasteurised Orange Juice with Resistant Maltodextrin.

The beneficial health effects of prebiotics have been demonstrated in numerous research papers. However, their incorporation into daily food remains unfamiliar to consumers. This work evaluates the effects of the addition of resistant maltodextrin (RMD) on the sensory attributes of pasteurised orange juice, together with the physico-chemical properties and the aromatic profile. RMD addition increased the sweetness and decreased the acidity and bitterness, resulting in a higher overall panellists' rating of orange juice. It also proportionally increased °Brix together with density and decreased acidity. Colour changes were registered with higher RMD concentrations. Orange pulp presence affected the volume particle size distribution analysis, while RMD addition did not have any effect. The aroma volatile compounds were also analysed. Pulp-added samples showed a higher quantity of alcohol and aldehydes, whereas pulp-free samples registered higher terpene and terpenoid values. Ketones and acids were also quantified. RMD had a moderate impact on volatile compound quantifications, with the orange pulp presence playing a much more decisive role. A correspondence analysis was also performed to relate instrumental and sensory determinations for all samples. This work proves that the addition of RMD to orange juice is technologically feasible while also achieving a good response at the sensory level.

A MISR-Based Method for the Estimation of Particle Size Distribution: Comparison with AERONET over China

Aerosol particle size has a crucial impact on the environment and public health. Current satellite-based regression models focus on the total amount of particles and are limited by surface observations. This study proposes an algorithm to derive the long-term normalized volume size distribution (VSD) of aerosol particles, which is independent of ground measurements. The size distribution and aerosol optical depth of Multi-angle Imaging SpectroRadiometer (MISR) components are employed. We find the estimated MISR VSD is consistent with Aerosol Robotic Network (AERONET) observations, with R = 0.56, 0.54, 0.59, and 0.68 for daily, monthly, seasonal, and annual levels. The stratified validations of radius, stations, and years further confirm the stable performance of derived VSD ( R = 0.28 to 0.73). The application of the random forest model demonstrates the potential improvements of predicted VSD by 10-fold cross-validation R = 0.86 at the monthly level. We apply MISR VSD to quantify the normalized volume of fractional aerosol particles at a resolution of 0.2° × 0.2° during 2004 to 2016 in China. We also calculate the proportion of small and medium particles to indicate the contribution of anthropogenic aerosols. The highest ratios are concentrated in the northeastern regions especially during winter while relatively lower in the Taklamakan Desert of western China. The case study demonstrates that the application of MISR data can yield valuable and resolved size distributions of aerosol particles.

Retrieval of Aerosol Microphysical Properties from Multi-Wavelength Mie–Raman Lidar Using Maximum Likelihood Estimation: Algorithm, Performance, and Application

Lidar plays an essential role in monitoring the vertical variation of atmospheric aerosols. However, due to the limited information that lidar measurements provide, ill-posedness still remains a big challenge in quantitative lidar remote sensing. In this study, we describe the Basic algOrithm for REtrieval of Aerosol with Lidar (BOREAL), which is based on maximum likelihood estimation (MLE), and retrieve aerosol microphysical properties from extinction and backscattering measurements of multi-wavelength Mie–Raman lidar systems. The algorithm utilizes different types of a priori constraints to better constrain the solution space and suppress the influence of the ill-posedness. Sensitivity test demonstrates that BOREAL could retrieve particle volume size distribution (VSD), total volume concentration (Vt), effective radius (Reff), and complex refractive index (CRI = n − ik) of simulated aerosol models with satisfying accuracy. The application of the algorithm to real aerosol events measured by LIlle Lidar AtmosphereS (LILAS) shows it is able to realize fast and reliable retrievals of different aerosol scenarios (dust, aged-transported smoke, and urban aerosols) with almost uniform and simple pre-settings. Furthermore, the algorithmic principle allows BOREAL to incorporate measurements with different and non-linearly related errors to the retrieved parameters, which makes it a flexible and generalized algorithm for lidar retrieval.

Evaluation of a Laboratory-Scale Gas-Atomized AlSi10Mg Powder and a Commercial-Grade Counterpart for Laser Powder Bed Fusion Processing.

Laser powder bed fusion (LPBF) is an additive manufacturing technology that implies using metal powder as a raw material. The powders suitable for this kind of technology must respect some specific characteristics. Controlled gas atomization and post-processing operations can strongly affect the final properties of the powders, and, as a consequence, the characteristics of the bulk components. In fact, a complete characterization of the powders is mandatory to fully determine their properties. Beyond the most used tests, such as the volume particle size distribution (PSD) and flowability, the PSD number, the Hausner ratio and the oxidation level can give additional information otherwise not detectable. The present work concerns the complete characterization of two AlSi10Mg powders: a commercial-grade gas atomized powder and a laboratory-scale gas atomized counterpart. The laboratory-scale gas atomization allows to better manage the amount of the fine particles and the oxidation level. As a consequence, a higher particle packing can be reached with an increase in the final density and tensile strength of the LPBF bulk samples.

The mechanisms study of the effect of sludge hydrolysis residual preparation on the performance of composite phase change materials

Composite phase change materials composed of hydrated salts for heat storage have become a hot research topic, in which the carrier plays a decisive role in preventing phase separation. Little sawdust was mixed into municipal sludge when directly hydrolyzed in an autoclave for the preparation of residual. The separated and dried hydrolysis residue was used as a carrier for loading sodium acetate trihydrate (SAT) with a mass ratio of 1:6 to prepare composite phase change materials (CPCM) for heat storage. The influence of hydrolysis temperature and pressure on the characteristics of the residue carrier and the heat storage performance of CPCM was then investigated. Multiple cycles of melting and solidification were undergone with CPCM in the plastic tube immersed in a water bath. The thermal stability of CPCM was evaluated by the multi-cycle step-cooling curves, DSC, and XRD. The results show that the residue hydrolyzed at 264 °C and 5 MPa (residue R5) has the highest pore volume and uniform particle size distribution compared with the residues hydrolyzed at other conditions. The latent heat storage density of the CPCM-R5 is 256.3 kJ/kg. After 100 melting-solidification cycles, the difference between the latent heat of CPCM-R5 and its theoretical value is only −2.5 %–4.4 %. The XRD patterns of CPCM-R5 are consistent before and after multiple cycles, indicating that CPCM-R5 is of better thermal and chemical stability, and its thermal conductivity is increased.

Impact of the Non-Uniform Catalyst Particle Size on Product Selectivities in Consecutive Reactions

The analysis of consecutive reactions A→B→C in porous catalyst particles, where the simultaneous processes of diffusion and chemical reactions take place and both reactant and products are subjected to diffusion limitations, was performed for catalyst particles with non-uniform sizes, a fact that has not been considered so far. The system comprises first-order consecutive irreversible reactions that proceed on spherical catalyst particles with a log-normal volume particle size distribution (PSD), which is typical in many catalytic applications. Regardless of the prevailing diffusion regime (chemical control, transition situation or intraparticle diffusion control), the yield of the intermediate product (B) reaches a maximum value as a function of the conversion of reactant (A), then decreases as a consequence of the prevalence of the secondary reaction that converts it into the secondary product (C). If intraparticle diffusion resistances affect the reactant species, given the relationship between the kinetic constants and the mean particle size, the selectivity to the intermediate product is negatively affected by the dispersion in PSD. The larger the dispersion in PSD, the stronger the negative impact.

Suspended Particulate Matter Investigations by the Optical Method in the Franz-Victoria Trough, the Barents Sea

The article describes results of the suspended particulate matter during 80th cruise of the RV Akademik Mstislav Keldysh in the Franz-Victoria Through, northern Barents Sea. Two perpendicular transections were carried out by means of small-angle laser diffractometer LISST-Deep operating in the red range with a wavelength of 670 nm. Observed data consist 7 thousand volume concentration and particle size distributions (PSD) measurements. Weather conditions during expedition allowed to extend the transection to southern part of Nansen basin. The volume concentration of suspended matter varied up to 7.58 μl/l in the euphotic zone and layer and from 0.2 to 0.5 μl/l in the nepheloid layer. Paper demonstrates construction possibilities of the particle size distributions profiles by depth. Transection comparison with measurement results by the conductometric method on a Coulter Counter of the bathometric samples were carried out.

Soot nanoparticle sizing in counterflow flames using in-situ particle sampling and differential mobility analysis verified with two-colour time-resolved laser-induced incandescence

The emphasis of this work is on the development of an intrusive particle sampling system to track the evolution of soot nanoparticles in ethylene counterflow diffusion flames. The overarching objective is to determine the mobility size distributions in a spatially resolved manner using the developed probe system coupled with differential mobility analysis, i.e., a scanning mobility particle sizer (SMPS). The probe system involves a tailor-made quartz probe, gas supply, pressure control periphery, and a traverse system enabling a precise positioning along the flame axis. In preliminary experiments, the dilution ratio of the quartz probe as function of boundary conditions as well as particle losses during intrusive particle sampling are studied. To demonstrate the capability of the developed particle sampling system, results from ethylene counterflow diffusion flames with different fuel mass fractions and strain rates are presented and compared with results derived by non-intrusive laser-based diagnostics, i.e., two-colour time-resolved laser induced incandescence (2C-TiRe-LII). Results of these experiments indicate that the particle sampling system is capable of tracking the development of particle size distributions – independent of the distribution function, i.e., mono-, bi- or multimodal shape – in counterflow flames. Likewise, the agreement between soot volume fractions and particle size distributions measured via intrusive particle sampling coupled with differential mobility analysis and non-intrusive laser-based 2C-TiRe-LII is excellent at varying the fuel mass fractions and strain rates of the ethylene counterflow flames.

Long-term effects of ilmenite on a micro-scale bubbling fluidized bed combined heat and power pilot plant for oxygen carrier aided combustion of wood

Small-scale solutions for the application of solid biomass fuels for the generation of heat and power with fluidized beds are hardly available. The main issues comprise agglomeration and slagging, incomplete burnout of combustibles and low efficiencies. During so-called oxygen carrier aided combustion, an oxygen carrier replaces the conventional bed material and balances the local and temporal oxygen supply in the fluidized bed. This results in a more homogeneous combustion and increased heat release in the fluidized bed area. Especially for small-scale bubbling fluidized bed solutions, these effects require an adapted plant setup. However, applications of oxygen carriers in small-scale bubbling fluidized bed boilers are barely reported. Process parameters differ significantly from large-scale circulating fluidized beds regarding resident times, particle volume fractions and size distributions. Hence, this research examines the enhancing effect of 50 wt% ilmenite in a 45 kWth bubbling fluidized bed fired combined heat and power plant. Long-term measurements in a field test environment promise a potential decrease of the carbon monoxide emissions of up to 75 %. Lower fluidized bed temperatures and apparently poor combustion conditions even enhance the positive effect of ilmenite. Moreover, the porous ilmenite particles interact with ash compounds such as potassium, calcium and magnesium. The migration of potassium into the inner particle mitigates the formation of low-melting layers around the particle. Calcium and magnesium form titanium oxide phases in the outer particle layer, below an iron enriched particle shell. Thereby, ilmenite prevents the formation of sticky particle layers, which addresses agglomeration and slagging issues. The particle shell is subject of ongoing attrition leading to a constant entrainment of active material from the combustion chamber. Therefore, a continuous addition of fresh material is essential to sustain the beneficial impact of the oxygen carrier. The optimal operation period for the oxygen carrier additive is supposed to cover 1–2 weeks.

Kinetics of viscous flow sintering of glass–zircon composites. Effect of zircon volume fraction and particle size distribution

Viscous flow sintering of glass–zircon composites was studied by isothermal and constant-rate heating experiments. The sintering curves fitted very well to the developed kinetic model, based on the Kohlrausch–Williams–Watts (KWW) function. Increasing the zircon volume fraction and decreasing the zircon–glass particle size ratio was verified to slow down the sintering rate. The combined effect of these variables on sintering was interpreted on the basis of percolation theory. The influence of temperature on the composite sintering rate corresponded to the influence of this variable on glass matrix flowability. Dimensionless relationships between the kinetic parameters and zircon volume fraction and the particle size ratio were obtained, which were independent of the thermal treatment used.

How do the oxygenated functional groups in ether, carbonate and alcohol affect soot formation in Jet A2 diffusion flames?

Four oxygenated fuels: ethanol (EtOH), dimethyl carbonate (DMC), dimethoxymethane (DMM) and polyoxymethylene dimethyl ether (PODE3) were blended with Jet A2 to investigate the sooting behaviour of the fuel mixtures. The smoke point was measured using wick-fed laminar diffusion flames as per the ASTM D1322 standard. The oxygen extended sooting index (OESI) was calculated to determine the sooting tendency of each mixture. Colour-ratio pyrometry and differential mobility spectrometry were used to measure the soot volume fraction (fv) and particle size distribution (PSD). The addition of oxygenated fuels caused a strong reduction in sooting tendency (i.e. OESI) at low blend strengths (5%) and a weaker linear reduction at higher blend strengths (10% and 20%). Each mixture showed a similar reduction at a given mole fraction of oxygenated fuel. The OESI broadly correlated with the soot volume fraction and particle size measurements. Increasing blend strengths resulted in smaller particles at the tip of the flame. The average particle size at the tip was influenced by the oxygen content but not the molecular structure of the oxygenated fuels, whereas the soot volume fraction in the wings was influenced by both the molecular structure of the oxygenated fuels and the oxygen/carbon ratio of the mixture. For the first time, fv and PSD have been reported for flames produced using Jet A2 blends in an ASTM D1322 lamp. The ability to relate data gathered using the ASTM D1322 standard for the sooting behaviour of different mixtures is going to be increasingly important as the aviation industry seeks to switch to sustainable fuels.

The effect of radial diffusion on nanoparticle formation in laminar flow reactors

The present work examines two-dimensional effects during nanoparticle formation in laminar flow reactors using two approaches: a 2D model and a simplified 1D model. The investigated cases consist of carbon nanoparticle synthesis via ethylene pyrolysis in laminar flow. The simplified 1D simulations are conducted using the 1D plug flow solver Nano PFR, while the 2D simulations have been performed using CoFlame in an axisymmetric configuration. Both models utilize a sectional population balance model coupled with gas-phase chemistry to simulate detailed particle formation processes.The effects of radial diffusion of the 2D approach are analyzed in a reference case of an isothermal reactor by comparing a diffusion model against a no-diffusion model. Results show that radial diffusion sufficiently mixes the gas phase species along the radius to approximate plug flow. While radial diffusion effects are apparent in particle formation, it is not nearly enough to develop a uniform radial profile for the primary particle and agglomerate number densities and volume fraction. Next, experimental data from the literature are simulated, examining the suitability, differences, and limitations between the 1D and 2D domains. Both models perform similarly in prediction accuracy for the gas-phase species, including fuel pyrolysis and PAH formation. Moreover, by integrating particle mass across several regions (i.e. radial integration approach), the 1D model can achieve accuracy on par with the 2D model for particle formation predictions. Both models can adequately capture SMPS measurements for particle volume fraction, number densities, and size distributions. Ultimately, within the range of experimental conditions typically found in current laminar flow reactor studies for carbon nanoparticle formation, a modified 1D approach can sufficiently describe the gas-phase chemistry and particle formation processes with lower computational costs than the 2D approach.

Particle Size Analysis of African Dust Haze over the Last 20 Years: A Focus on the Extreme Event of June 2020

Over the last decades, the impact of mineral dust from African deserts on human health and climate has been of great interest to the scientific community. In this paper, the climatological analysis of dusty events of the past 20 years in the Caribbean area has been performed using a particulate approach. The focus is made on June 2020 extreme event dubbed “Godzilla”. To carry out this study, different types of data were used (ground-based, satellites, model, and soundings) on several sites in the Caribbean islands. First, the magnitude of June 2020 event was clearly highlighted using satellite imagery. During the peak of this event, the value of particulate matter with an aerodynamic diameter of less than 10 μμm (PM10) reached a value 9 times greater than the threshold recommended by the World Health Organization in one day. Thereafter, the PM10, the aerosol optical depth, and the volume particle size distribution analyses exhibited their maximum values for June 2020. We also highlighted the exceptional characteristics of the Saharan air layer in terms of thickness and wind speed for this period. Finally, our results showed that the more the proportion of particulate matter with an aerodynamic diameter of less than 2.5 μμm (PM2.5) in PM10 increases, the more the influence of sea salt aerosols is significant.

Aerosol Particles Generated by Coughing and Sneezing of a SARS-CoV-2 (COVID-19) Host Travel over 30 m Distance

A fast-computational 3D model comprising fluid dynamics with heat transfer, mass transfer and diffusion of diluted species has been adapted and employed to evaluate dispersion of aerosol particles in various environments. Effects of convection flow, atmospheric diffusivity and humidity on evolution and travel distances of exhaled aerosol clouds by an infected person are modelled. The modelling clearly demonstrates how aerosol particle dispersion is influenced by weather and geometry of the environment. The results obtained demonstrate that aerosol particles of sizes from 10 µm to 100 µm that potentially can carry SARS-CoV-2 (COVID-19) viruses travel over 30 m in some atmospheric conditions. Modelling of the evolution of aerosol clouds generated by coughing and sneezing enables us to evaluate the deposition dose of aerosol particles in healthy individuals. In realistic weather scenarios viruses can be deposited in the respiratory tract of a healthy individual at up to 200 virus copies in several minutes. A metric based on aerosol particle (volume) size distribution and the ICRP lung deposition model is suggested.

A novel method of retrieving low visibility during heavily polluted episodes in the North China plain

Abstract The prediction of visibility is an ongoing problem in air quality models, particularly that of low visibility during heavily polluted episodes. In this study, a new method of calculating visibility based on the particle mass concentration of PM2.5 (particles with diameter ≤ 2.5 μm) and relative humidity (RH), data for which are generally available in most regions of China, is developed. The method also considers the particle number size distribution (PNSD) and hygroscopic parameter (κ), and focuses on visibility below 10 km. First, the PNSD was re-constructed under dry condition (PNSDdry,rec) based on the relationship between PM2.5 and the particle volume size distribution modal parameters obtained in a previous study conducted in the North China Plain. Then, the ambient PNSD (PNSDamb,rec) was retrieved based on the PNSDdry,rec and κ, and the light extinction was calculated by applying the Mie code (σext,amb). Finally, the visibility was calculated based on the Koschmieder experimental equation, and denoted as Viscal. A parameterization scheme was proposed based on the σext,amb, PM2.5, and RH to simulate the visibility (Vissimu), which is more applicable than the theoretical calculation described above. This method was validated at different locations in different regions in China. The values calculated by the scheme showed agreed well with the observed data in general, especially for low visibility of ≤5 km, associated with severe haze. Although a large bias occurred at some sites, both the hourly and daily averages for almost every event with visibility lower than 5 km were captured. The method reported in this work exhibited smaller bias below 2 km than the other visibility parameterization scheme, and will be available for improving the prediction of visibility in air quality models.

Insights into capacitance variance mechanisms via a machine learning-biased evolutionary approach

Dielectric particles are often added to ink formulations to tailor the macro level permittivity of printed dielectric substrates and coatings. In these inks, the combined role of particle morphology, discrete spatial arrangement and material properties on variance is difficult to distinguish experimentally and hence poorly understood. This is primarily due to the large parameter space of processing variables as well as electrical sensitivity to local heterogeneities. We address this challenge by combining a finite element capacitor model with a neural network biased genetic algorithm (NBGA) to optimize the volume fraction, particle size, and permittivity distributions of dielectric particles to identify systems with high capacitance variance. Analysis of the database generated from the optimization process provided insights on effect of polydisperse particles on variance of the system. Design rules/strategies were also identified for achieving target variance. Unsupervised machine learning techniques were applied to the NBGA-created database to extract correlations between the spatial/material distributions of the dielectric particles and the capacitance variance. Collectively, this study provides a useful framework to correlate electrical performance with both macro- and microstructural variation sources, which is key to accelerating the development of 3-D printing materials.

Representations of dynamics size distributions of mineral dust over East Asia by a regional sand and dust storm model

Particles larger than 5.0 μm in diameter are important to keep the size distribution for mineral dust but it is difficult to represent them in numerical models due to the complex emission process and quick gravitational deposition. To improve this situation, the cumulative distribution function of the Weibull distribution is used to represent the instant wind larger than the model grid-mean wind speeds of the sectional dust forecast model, China Meteorological Administration Unified Atmospheric Chemistry Environment/Dust (CUACE/Dust). Size distributions for dessert soil texture in China and mass median diameters for the three lognormal populations of dust flux released are also improved from observations in Asian source areas. With all these updating, the mass size distribution of dust flux from the model is much closer to the observed value, which changes the original unreasonable single-peak distribution, coming close to the distribution trend with increasing particle size bins. It then improves the emission for coarse particles larger than 10.0 μm in source areas. Moreover, both the varied values and changing shape patterns of column volume particle size distributions simulated in the downwind areas compatible to the observed by the global AErosol RObotic NETwork (AERONET) achieving an obvious improvement for the size distribution of coarse particles larger than 5.0 μm in these downwind areas.

Synthesize of magnetite Mg-Fe mixed metal oxide nanocatalyst by urea-nitrate combustion method with optimal fuel ratio for reduction of emissions in diesel engines

Abstract In the present study, Mg0.25Fe2.75O4 nanocatalyst for reduction of emissions in diesel engine was fabricated via urea-nitrate combustion method. The effect of urea concentrations as fuel on its structural characteristics and Oxygen Storage Capacity (OSC) was thoroughly investigated. The results of various characterization analyses showed that fuel ratio significantly affects crystallinity, textural, size and morphology of particles, and thermal stability of nanocatalyst. These are mainly due to increase in combustion temperature and duration. The Mg0.25Fe2.75O4 fabricated at fuel ratio of 2.5 times of stoichiometric ratio exhibited the lowest weight loss/high crystallinity (less than 1 wt %) and lowest lattice parameter (8.346 A) which are related to well diffusion of Mg cations into ferric oxide as host. The Raman and FTIR analyses showed the existence of strong peaks correspond to formation of tetrahedral and octahedral sublattices and also the formation of spinel structure of MgFe2O4. The reduction in crystalline size, obtained with higher amount of fuel, resulted in a higher surface area (23.6 m2/g), higher pore volume (0.0950 cc/g) and proper particle size distribution (25–35 nm). These cause a better catalytic activity. Moreover, the enhanced OSC (8661 μmol H2/g) along with shifting the reduction peaks to lower temperatures, as major attributes in relation to catalytic technologies, confirmed the strong effect of fuel ratio of 2.5 on fabrication process of Mg0.25Fe2.75O4. Finally, the highest reduction in HC (33%), CO (14-17%), PM1.0 (16%), and CO2 (12%) achieved, using the optimum sample-mixed diesel fuel at 90 ppm.