Evolution Of Size Distribution Research Articles

Large eddy simulation-bivariate sectional model for non-spherical TiO2 nanoparticle synthesis in flame

Numerical simulation of nanoparticle synthesis in flame necessitates a high level of fidelity for turbulent flame, as well as delivers more detail insight into the evolution of structure and size distribution of particles undergoing various dynamic events. In the present work, a new simulation approach coupling large-eddy simulation (LES) and bivariate sectional model is proposed to explore the synthesis of nanoparticles in turbulent flame. More specifically, the nonlinear LES-partially stirred reactor model (NLES-PaSR) is utilized to simulate the turbulent flame, wherein the gradient-type structural subgrid-scale (SGS) model for turbulent flow and partially stirred reactor (PaSR) model for turbulent combustion are considered. In addition, the volume-based bivariate sectional model is thoroughly coupled with the LES model for the first time to describe the spatiotemporally resolved formation and growth of nanoparticles using particle number concentration and surface area concentration as two sets of variables. Compared directly with the LES-monodisperse (LES-Mono) and LES-univariate sectional (LES-UniSe) models, the LES-bivariate sectional (LES-BiSe) model has significant advantages in its ability to analyze and predict the size, morphology, as well as polydispersed particle size distribution (PSD) evolution of nanoparticles at a moderate computational cost simultaneously. In the LES framework, the proposed model successfully simulates the spatiotemporally resolved formation and growth of non-spherical TiO2 nanoparticle in turbulent diffusion burner. The predicted results derived from the LES-BiSe model are in good agreement with the experimental measurements. Also, the aggregate and primary particle size distribution shows highly temporal fluctuation, which mainly results from the continuous variations of particle path induced by the unsteady turbulent combustion. Furthermore, the present work demonstrates the profound dependence of particle morphological on both spatiotemporal evolution and their intrinsic size distribution. In particular, the large aggregates in the higher sections are commonly found as irregular structure with fractal-like dimensions.

Modelling of droplet multiple breakage accounting for entire energy spectrum bottleneck effect and eddy-droplet discrepancy

This work focused on the contribution of the two aspects of entire energy spectrum bottleneck effect and eddy-droplet discrepancy to droplet multiple breakage simulation. The droplet breakage mechanism model was closured by more accurate turbulent parameters determined by accounting for the bottleneck effect and a formula was proposed to consider the effect of the eddy-droplet discrepancy. The influences of the two aspects on collision/interaction frequency density, breakage probability, breakage frequency and daughter size distribution (DSD) were analyzed. The proposed model agreed well with the measured breakage frequency, relative proportion of multiple breakage modes and DSDs from single droplet experiments and drop swarm experiments. The predicted size distribution evolution also exhibited a better agreement with experimental data by comparing with other models. An obvious quantitative prediction difference on whether to consider the two aspects proved the necessity and advantage of model development.The bottleneck effect represents a physical phenomenon fully validated by experimental data and direct numerical simulation results. Ignoring bottleneck effect hinders the acceptable reproduction of longitudinal velocity gradient skewness, while considering it obviously increases the quantitative prediction accuracy of turbulence parameters. Considering the physical fact that turbulent eddies will disappear, the eddy-droplet discrepancy neglected by existing mechanism model is used to characterize the impact of eddy lifetime on eddy-droplet collision/interaction. To summarize, the improvements of this work are beneficial for consolidating the breakage model physical foundation.

Modeling the distribution characteristics of vapor bubbles in cavitating flows

Dispersed vapor bubbles are the dominant rheology in cloud cavitation, and their size distribution is directly associated with cavitation noise and erosion. However, the numerical resolution of large numbers of dispersed bubbles remains a challenge. In this work, we establish a new cavitation model based on the population balance equation (PBE) that can predict the size distribution and spatiotemporal evolution of bubbles within cloud cavitation under different cavitation numbers. An expression for the phase transition source term without empirical parameters is derived based on the bubble size distribution (BSD) function, enabling the coupling of mass transfer in the governing equations with the PBE cavitation model. The cavitation model is solved alongside the Eulerian homogeneous mixture flow. The mass transfer between water and vapor, and the bubble coalescence and breakup under turbulent flows, are modeled to determine the BSD. The numerical model is carefully validated through comparisons with experimental results for cavitation flows on a wedge-shaped flat plate, and good agreement is achieved with respect to the pressure distribution, void fraction, and BSD. This confirms that our proposed cavitation model can accurately predict the void fraction and BSD within the cloud cavitation region.

Experimental and numerical investigation on soot formation and evolution of particle size distribution in laminar counterflow ethylene flames

A detailed investigation of the process of soot formation in ethylene-fueled laminar counterflow diffusion flames is conducted using dedicated experiments and numerical simulations. Two different strategies based on the Discrete Sectional Method (DSM) and the Split-based Quadrature Method of Moments (S-EQMOM) are considered to model the evolution of soot particle size distributions, and their comparative assessment is carried out for soot formation prediction and particle growth. A consistent chemical reaction mechanism describing the oxidation of hydrocarbon fuels and the prediction of soot precursors with the growth of polycyclic aromatic hydrocarbons (PAHs) up to pyrene ( ▪ ) is examined. Experiments for various strain rates and fuel compositions are performed to assess the sensitivity of soot production to these two parameters. The results show that both modeling strategies captured well the qualitative trends of soot volume fraction under variations in strain rate and mixture composition, with slight over-prediction of the peak values. For both soot models, a higher sensitivity of soot formation is noticed by changes in mixture composition compared to those of strain rate variation. Additionally, the soot models demonstrated promising performance in capturing the experimentally observed evolution of the soot particle size distribution (PSD).

Turning fly ash and waste gypsum into a resource for backfilling applications

Flue Gas Desulfurization Gypsum (FGDG), an industrial by-product generated by power plants, was thermally treated and incorporated in cement-free fly ash bricks. This study aimed to determine the effects of using a thermally treated FGDG as an additive to improve the mechanical and structural properties of cement-free fly ash bricks. FGDG was thermally treated for 2 h at different temperatures. The influence of varying amounts (10–50%) of thermally treated FGDG on the performance of cement-free bricks was analyzed through mechanical properties, micrography, durability, the evolution of particle size distribution and environmental characteristics experiments. The effect of curing temperatures and curing age on the strength development and microstructural properties was also investigated. A Toxicity Characteristic Leaching Procedure (TCLP) was carried out to determine the leachability of metals from the synthesized FA cement-free brick. The results showed that the FGDG had a high calcium oxide content. In contrast, FA is mainly composed of silica, and both materials carry cementitious properties making both good raw materials for this study. The FA cement-free bricks containing 30% of thermally treated FGDG, oven-cured at 60 ℃, yielded the highest unconfined compressive strength (UCS) of 7.14 MPa. However, curing at ambient temperature for 28 days yielded a better UCS of 7.37 MPa. The particle size distribution showed that particles transformed from fine particles at 7 days to larger particles at 28 days due to particle growth. Durability tests showed that the developed bricks could withstand 7 wet/dry cycles. The TCLP showed that the leachability concentrations of all metals are within the limit and, therefore, can be potentially used as a building material in backfilling. The synthesis of FA/FGDG composite will aid in reducing the generated waste gypsum in landfills consequently eradicating human health challenges and loss of biodiversity. This paper showed that developing FA/FGDG composites will reduce their environmental impact and make them a resource for other valuable products such as backfilling applications and green building bricks.

A one-dimensional model for Pt degradation and precipitation in proton exchange membrane fuel cell considering Pt nucleation, particle size growth, and band formation

Reducing Pt catalysts amount without sacrificing the performance and durability is critical for the commercialization of proton exchange membrane fuel cells (PEMFCs). Pt degradation in the cathode catalyst layer (CCL) decreases the electrochemically active surface area (ECSA), and Pt precipitation, especially Pt band formation, has a significant effect on proton exchange membrane (PEM) stability, resulting in severe PEMFC degradation during long-term operation. In this study, a one-dimensional model is developed focusing on Pt catalyst degradation and precipitation, including Ostwald-ripening, mass loss, precipitation in the PEM from nucleation, particle size growth, to Pt band formation. The model accuracy is comprehensively validated against the corresponding experimental data, including ECSA loss and particle size distribution (PSD) evolution in the CCL under different operating conditions (temperature, relative humidity, and loading mode), as well as the precipitated Pt size distribution characteristics and local potential in the PEM. Using this model, the Pt band formation process is comprehensively analyzed, and the effects of operating conditions on Pt degradation and Pt band formation are investigated in detail. It is found that the nucleation stage is brief, and then the significant inhomogeneity at the size growth stage causes Pt band formation. In addition, the high activation enthalpy of dissolution under low humidity can effectively inhibit Pt degradation, and Ostwald-ripening is the mean cause of Pt degradation, which is likely to occur during the rapid voltage change period.

Dynamic coassembly of nanodiamonds and block copolymers in organic solvents

Nonaqueous suspensions of nanoparticles have potential value in a wide range of applications, from coatings to environmental remediation. However, organic solvents often lead to nanoparticle agglomeration, and few methods developed to counteract this phenomenon. We present a novel approach to achieve stable nanoparticle suspensions in both nonpolar and polar aprotic solvents. Our method utilizes nanodiamonds (NDs) as a model system, due to the rich nature of their surface chemistry. This technique involves three key steps: (1) ultrasonication of air-oxidized NDs (OXNDs) in dimethylacetamide (DMAc), (2) the introduction of amphiphilic dispersants primarily composed of PVA-b-PMMA block copolymers (BCPs), and (3) exchanging DMAc with organic solvents to promote composite micelle formation, where BCP forms the micelle corona encapsulating OXND as the micelle core. Our method yields stable suspensions with particle sizes strongly influenced by thermokinetic interactions between OXND, BCP, and the solvent. Dynamic light scattering measurements of OXND–PVA-b-PMMA suspensions demonstrate that stabilization in toluene is governed by steric hindrance, while in THF or CHCl3 both electrostatic repulsion and steric hindrance contribute to particle stabilization. Characterization through electron microscopy and AFM reveals the efficacy of our coassembly method for producing uniformly-sized composite micelles. We identify a critical BCP:OXND weight ratio, analogous to the critical micelle concentration in surfactant-stabilized suspensions, crucial for effective particle stabilization. By analyzing the evolution of particle size distribution with varying solvent composition, we propose a dynamic coassembly mechanism between OXND and BCP, wherein OXND particles and encapsulating BCP chains dynamically rearrange to reach an equilibrium structure as the thermodynamic quantities of the surrounding medium change. Furthermore, BCP micellization is shown to play a vital role in preventing OXND aggregation during solvent exchange, resulting in uniformly sized particles. This enhanced understanding of the OXND–BCP coassembly mechanism in organic solvents holds promise for the development of novel functional materials. Our study provides insights into fabricating stable nanoparticle suspensions with diverse applications to coatings, lubricants, drug delivery, nanocomposite materials, biosensing, medical imaging, and environmental remediation.

Modelling droplet size distribution in inline electrostatic coalescers for improved crude oil processing

Water-in-oil emulsions pose significant challenges in the petroleum and chemical industrial processes, necessitating the coalescence enhancement of dispersed water droplets in emulsified oils. This study develops a mathematical model to predict the evolution of water droplet size distribution in inline electrostatic coalescers (IEC) as a promising means to improve the water separation efficiency of current oil processing systems. The proposed model utilizes the population balance modelling approach to effectively simulate the dynamic and complex processes of coalescence and breakage of droplets in crude oil which directly influence the separation efficiency of the process. The method of classes as an effective mathematical technique is selected to solve the population balance equation (PBE). The accuracy of the model and considered assumptions agree well with experimental data collected from the literature. The results demonstrate the model's ability to accurately simulate droplet coalescence and breakage in emulsified oil while predicting droplet size distribution and water removal efficiency. The electric field strength, residence time, and fluid flow rate significantly influence the coalescence of droplets. At 4 kV and 5 m3/h after 4 s the mean diameter of droplets (D50) and separation efficiency reach the maximum of 94.3% and 432 µm, respectively. The model enables the optimization of operational conditions, resulting in increased performance and reliability of oil-processing systems while reducing the energy consumption and use of chemical demulsifiers. Additionally, utilization of the device in optimized conditions significantly reduces the size and weight of downstream separation equipment, which is particularly advantageous for heavy oils and offshore fields.

Microstructural evolution and mechanical property of friction stir welded joints in AlSi10Mg alloys fabricated by laser powder bed fusion

Friction stir welding (FSW) was introduced to join laser powder bed fusion (LPBF) AlSi10Mg alloys in this study. Microstructure and texture evolution, microhardness distribution and tensile properties of the FSW joints were investigated. The evolution of grain size, grain boundary and misorientation angles distribution, dynamic recrystallization and crystallographic texture in various regions of the FSW joint concerning base metal (BM), thermo-mechanically affected zone (TMAZ), upper part of nugget zone (UPNZ) and low part of nugget zone (LPNZ) was characterized by using electron back-scattered diffraction (EBSD). The analysis reveals a strong texture evolution of shear components on the TMAZ, UPNZ and LPNZ as well as a fully recrystallized grain structure on the UPNZ and LPNZ. Additionally, a gradual evolution in Si-rich eutectic from continuous cellular networks in the BM to totally globularized particles in the UPNZ and LPNZ occurs in the FSW joint. The microhardness rapidly decreases to the TMAZ from the BM through heat affected zone (HAZ) reaching the lowest value of ∼65.0 HV at the TMAZ/NZ boundary. The FSW joint in LPBF AlSi10Mg alloys exhibits an ultimate tensile strength (UTS) of 247 MPa and an elongation-to-failure (EI) of 8.8%. The UTS of FSW joints is reduced compared to the BM, but the EI has been increased by 160%, implying an improvement in tensile ductility.

Modeling the Precipitation of Aluminum Nitride Inclusions during Solidification of High‐Aluminum Steels

High‐aluminum advanced high‐strength steels have received increasing interest due to their excellent combination of strength and ductility. The control of nonmetallic inclusions in steel is among the most important issue for the production of high‐aluminum steel. This study proposes a model for the evolution of size distributions of AlN inclusions during solidification of steel based on the Kampmann–Wagner numerical model and microsegregation calculation. Both homogeneous (pure AlN) and heterogeneous precipitations (AlN+oxide or MnS) are described using homogeneous nucleation and free growth models of Greer et al. respectively. The model is applied to calculate the size distributions of AlN in high‐Al (up to 5%) Fe–Cr–Al steels and high‐ and medium‐manganese steels and validated by the experimental data in the literature. The model correctly describes the influence of cooling rates on the precipitation of AlN in Fe–Cr–Al steels and high‐manganese steels, and the sizes of AlN are reduced and the number densities of AlN inclusions are increased by increasing the cooling rate. The effects of nitrogen and aluminum concentration in medium‐manganese steel on inclusion precipitation are investigated by the model calculation. The increases in nitrogen and aluminum concentration facilitate the homogeneous precipitation of AlN inclusions.

Comparison of Grain-Growth Mean-Field Models Regarding Predicted Grain Size Distributions.

Mean-field models have the ability to predict the evolution of grain size distribution that occurs through thermomechanical solicitations. This article focuses on a comparison of mean-field models under grain-growth conditions. Different microstructure representations are considered and discussed, especially regarding the consideration of topology in the neighborhood construction. Experimental data obtained with a heat treatment campaign on 316L austenitic stainless steel are used for the identification of material parameters and as a reference for model comparisons. Mean-field models are also applied to both mono- and bimodal initial grain size distributions to investigate the potential benefits of introducing neighborhood topology in microstructure prediction models. This article demonstrates that improvements in the predictions can be obtained in monomodal cases for topological models. In the bimodal test, no comparison with experimental data was performed as no data were available. But relative comparisons between models indicated few differences in the predictions. Although of interest, the consideration of neighborhood topology in grain-growth mean-field models generally results in only small improvements compared to classical mean-field models, especially in terms of implementation complexity.

Influence of sugar beetroot microsheets on the hydration kinetics of cementitious composites: Electrochemical characterization

This paper examines the influence of novel sugar beetroot-based micro sheets (SMSs) on the hydration of cement. The SMS material was added to cement pastes in different concentrations and the hydration kinetics of the cementitious composites were studied via cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The effect of SMS on the hydration development of cement, change in the pore size distribution and microstructural evolution were also quantified. The CV and EIS results revealed that the synergetic effect of the reactive SMS surface functional groups and tricalcium silicate (C3S) increased the ionic strength of the pore solution, ion diffusion rate and charge transport properties within the cementitious pastes. The CV and EIS measurements correlated well with the two main indicators of the cement hydration rate: the degree of hydration (DOH) and the calcium hydroxide (Ca(OH)2) content. The delineated hydration kinetics suggested that the SMS sheets accelerate the dissolution of C3S and increase the hydration depth by channelling water from the pore solution to the unhydrated cement core thereby amplifying the growth of the hydration phases. As a result, the mechanical properties of the SMS doped cementitious composites were improved. The proposed SMS sheets are a potential sustainable and renewable biomaterial for improving the performance and reducing the carbon footprint of cementitious materials.

Nonequilibrium Behavior in Isoprene Secondary Organic Aerosol.

Recent studies have shown that instantaneous gas-particle equilibrium partitioning assumptions fail to predict SOA formation, even at high relative humidity (∼85%), and photochemical aging seems to be one driving factor. In this study, we probe the minimum aging time scale required to observe nonequilibrium partitioning of semivolatile organic compounds (SVOCs) between the gas and aerosol phase at ∼50% RH. Seed isoprene SOA is generated by photo-oxidation in the presence of effloresced ammonium sulfate seeds at <1 ppbv NOx, aged photochemically or in the dark for 0.3-6 h, and subsequently exposed to fresh isoprene SVOCs. Our results show that the equilibrium partitioning assumption is accurate for fresh isoprene SOA but breaks down after isoprene SOA has been aged for as short as 20 min even in the dark. Modeling results show that a semisolid SOA phase state is necessary to reproduce the observed particle size distribution evolution. The observed nonequilibrium partitioning behavior and inferred semisolid phase state are corroborated by offline mass spectrometric analysis on the bulk aerosol particles showing the formation of organosulfates and oligomers. The unexpected short time scale for the phase transition within isoprene SOA has important implications for the growth of atmospheric ultrafine particles to climate-relevant sizes.

Universal behavior in fragmenting brittle, isotropic solids across material properties.

A bonded particle model is used to explore how variations in the material properties of brittle, isotropic solids affect critical behavior in fragmentation. To control material properties, a model is proposed which includes breakable two- and three-body particle interactions to calibrate elastic moduli and mode I and mode II fracture toughnesses. In the quasistatic limit, fragmentation leads to a power-law distribution of grain sizes which is truncated at a maximum grain mass that grows as a nontrivial power of system size. In the high-rate limit, truncation occurs at a mass that decreases as a power of increasing rate. A scaling description is used to characterize this behavior by collapsing the mean-square grain mass across rates and system sizes. Consistent scaling persists across all material properties studied, although there are differences in the evolution of grain size distributions with strain as the initial number of grains at fracture and their subsequent rate of production depend on Poisson's ratio. This evolving granular structure is found to induce a unique rheology where the ratio of the shear stress to pressure, an internal friction coefficient, decays approximately as the logarithm of increasing strain rate. The stress ratio also decreases at all rates with increasing strain as fragmentation progresses and depends on elastic properties of the solid.

Application of Single Particle ICP-MS for the Determination of Inorganic Nanoparticles in Food Additives and Food: A Short Review.

Due to enhanced properties at the nanoscale, nanomaterials (NMs) have been incorporated into foods, food additives, and food packaging materials. Knowledge gaps related to (but not limited to) fate, transport, bioaccumulation, and toxicity of nanomaterials have led to an expedient need to expand research efforts in the food research field. While classical techniques can provide information on dilute suspensions, these techniques sample a low throughput of nanoparticles (NPs) in the suspension and are limited in the range of the measurement metrics so orthogonal techniques must be used in tandem to fill in measurement gaps. New and innovative characterization techniques have been developed and optimized for employment in food nano-characterization. Single particle inductively coupled plasma mass spectrometry, a high-throughput nanoparticle characterization technique capable of providing vital measurands of NP-containing samples such as size distribution, number concentration, and NP evolution has been employed as a characterization technique in food research since its inception. Here, we offer a short, critical review highlighting existing studies that employ spICP-MS in food research with a particular focus on method validation and trends in sample preparation and spICP-MS methodology. Importantly, we identify and address areas in research as well as offer insights into yet to be addressed knowledge gaps in methodology.

Size-segregated aerosol measurements during Diwali festival in an elevated background location

Recent studies in the direction of identifying signatures of aerosol emission from fireworks stressed on the need of simultaneous measurements of mass, number and chemical compositional characteristics. Such an identification is tricky when the measurements are performed in an elevated background environment and/or in presence of an additional wide source term. This work studies the modifications in atmospheric aerosol characteristics due to firework induced emissions in Bathinda city of Punjab, North India. This study presents interpretations based on the results obtained from the measurements performed for 14 days covering the days of Diwali festival, 2021 as well as the baseline database gathered from a year-long campaign to measure mass concentration in different size-ranges. Highest mass concentration for the study duration was observed to be PM10- 382 μg/m3, PM2.5–299 μg/m3, PM1- 240 μg/m3, respectively in the month of November 2021. A clear increase of concentration was noted for Diwali days and the averaged concentration for PM10, PM2.5 and PM1 reached to 445 μg/m3, 363 μg/m3 and 304 μg/m3 on Diwali day, respectively. Number size distribution evolution analysis for the data measured from an optical particle counter (size range: 0.25–1 μm) showed that emissions for Diwali days occurred mostly at night times and in smaller size channels (<0.5 μm). Chemical compositional data of selected samples close to Diwali days was interpreted in terms of factor of increase of mass density of collected particles in different size-ranges. Mass density of elements K, Cl, S, Al, Zn, P, Mn, Pb, Br and Zr in PM1 samples was observed to be higher for Diwali days in comparison to their pre-Diwali levels. Few elements viz. Ba, Sr and Nb were found to be only present in the samples taken during Diwali days. In addition to Ba, Sr and Nb, elements V, Mg, Br and Se were observed to be present in PM2.5 and PM10 samples taken during the Diwali days. This study provides combined ambient aerosol characteristics during Diwali days when the air quality was affected by stubble burning as well.

Lagrangian and Eulerian Supersaturation Statistics in Turbulent Cloudy Rayleigh–Bénard Convection: Applications for LES Subgrid Modeling

Abstract Turbulent fluctuations of scalar and velocity fields are critical for cloud microphysical processes, e.g., droplet activation and size distribution evolution, and can therefore influence cloud radiative forcing and precipitation formation. Lagrangian and Eulerian water vapor, temperature, and supersaturation statistics are investigated in direct numerical simulations (DNS) of turbulent Rayleigh–Bénard convection in the Pi Convection Cloud Chamber to provide a foundation for parameterizing subgrid-scale fluctuations in atmospheric models. A subgrid model for water vapor and temperature variances and covariance and supersaturation variance is proposed, valid for both clear and cloudy conditions. Evaluation of phase change contributions through an a priori test using DNS data shows good performance of the model. Supersaturation is a nonlinear function of temperature and water vapor, and relative external fluxes of water vapor and heat (e.g., during entrainment-mixing and phase change) influence turbulent supersaturation fluctuations. Although supersaturation has autocorrelation and structure functions similar to the independent scalars (temperature and water vapor), the autocorrelation time scale of supersaturation differs. Relative scalar fluxes in DNS without cloud make supersaturation PDFs less skewed than the adiabatic case, where they are highly negatively skewed. However, droplet condensation changes the PDF shape response: it becomes positively skewed for the adiabatic case and negatively skewed when the sidewall relative fluxes are large. Condensation also increases correlations between water vapor and temperature in the presence of relative scalar fluxes but decreases correlations for the adiabatic case. These changes in correlation suppress supersaturation variability for the nonadiabatic cases and increase it for the adiabatic case. Implications of this work for subgrid microphysics modeling using a Lagrangian stochastic scheme are also discussed.

Langevin dynamics simulation and collision frequency modification in population balance model of nanoparticle coagulation during simultaneous agglomeration and sintering

Coagulation of nanoparticles from the free-molecular to the transition regime under a high-temperature environment is investigated by coupling Langevin Dynamics (LD) model with agglomeration and finite-rate sintering. The effect of temperature on the evolution of particle size and structure is investigated, variations in agglomeration-sintering dynamics are obtained. The fractal dimension of agglomerates at different temperatures can be expressed as a function of the ratio between the characteristic collision time and sintering time. The overall collision frequency (β) is enhanced by the polydispersity and fractal properties of agglomerates compared to the monodisperse collision kernel functions. Finally, the classic function of β is modified based on the LD simulations and used in a one-dimensional population balance equation, which reproduces a better prediction of the evolution of particle size distribution during particle coagulation with agglomeration and sintering.

A dynamic parameterization of sulfuric acid–dimethylamine nucleation and its application in three-dimensional modeling

Abstract. Sulfuric acid (SA) is a governing gaseous precursor for atmospheric new particle formation (NPF), a major source of global ultrafine particles, in environments studied around the world. In polluted urban atmospheres with high condensation sinks (CSs), the formation of stable SA–amine clusters, such as SA–dimethylamine (DMA) clusters, usually initializes intense NPF events. Coagulation scavenging and cluster evaporation are dominant sink processes of SA–amine clusters in urban atmospheres, yet these loss processes are not quantitatively included in the present parameterizations of SA–amine nucleation. We herein report a parameterization of SA–DMA nucleation, based on cluster dynamic simulations and quantum chemistry calculations, with certain simplifications to greatly reduce the computational costs. Compared with previous SA–DMA nucleation parameterizations, this new parameterization was able to reproduce the dependences of particle formation rates on temperature and CSs. We then incorporated it in a three-dimensional (3-D) chemical transport model to simulate the evolution of the particle number size distributions. Simulation results showed good consistency with the observations in the occurrence of NPF events and particle number size distributions in wintertime Beijing and represented a significant improvement compared to that using a parameterization without coagulation scavenging. Quantitative analysis shows that SA–DMA nucleation contributes significantly to nucleation rates and aerosol population during the 3-D simulations in Beijing (&gt;99 % and &gt;60 %, respectively). These results broaden the understanding of NPF in urban atmospheres and stress the necessity of including the effects of coagulation scavenging and cluster stability in simulating SA–DMA nucleation in 3-D simulations. Representing these processes is thus likely to improve model performance in particle source apportionment and quantification of aerosol effects on air quality, human health, and climate.

Development and evaluation of a bulk three-moment parameterization scheme incorporating the processes of sedimentation and collision-coalescence

There are a few three-moment schemes that consider other processes besides sedimentation. Thus, a performance assessment of these types of schemes due to the combined effect of sedimentation and other microphysical processes is a matter of interest. In this study, a warm rain bulk three-moment parameterized scheme was developed and evaluated through a detailed comparison with a bin microphysical scheme. To evaluate the impact of sedimentation and the combined effect of sedimentation and collision-coalescence on the droplet size distribution (DSD), a rain shaft model was applied to the DSD with different initial values of the shape parameter. For pure sedimentation, a good correspondence was obtained between the three-moment scheme and the explicit model, with a practically perfect coincidence of bulk quantities for larger values of the gamma distribution’s initial shape parameter and, in general, the three-moment parameterization scheme performing much better than the two-moment scheme. The simulations performed for this case confirm (as reported in previous studies) that for pure sedimentation, the three-moment parameterization schemes deliver a physically more complete representation of the evolution of droplet size distribution. The impact of the combined effect of sedimentation and collision-coalescence processes on DSD was also assessed. We could observe that certain differences arise between the parameterized scheme and the spectral model when the collision-coalescence process is incorporated, as the onset of precipitation occurs earlier in the three-moment parameterized scheme. It can be concluded that, in general, the three-moment warm rain bulk microphysics scheme is able to reproduce the results of the reference bin microphysical model.