18 research outputs found

    Monte Carlo simulations of molecular clusters in nucleation

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    A better understanding of the limiting step in a first order phase transition, the nucleation process, is of major importance to a variety of scientific fields ranging from atmospheric sciences to nanotechnology and even to cosmology. This is due to the fact that in most phase transitions the new phase is separated from the mother phase by a free energy barrier. This barrier is crossed in a process called nucleation. Nowadays it is considered that a significant fraction of all atmospheric particles is produced by vapor-to liquid nucleation. In atmospheric sciences, as well as in other scientific fields, the theoretical treatment of nucleation is mostly based on a theory known as the Classical Nucleation Theory. However, the Classical Nucleation Theory is known to have only a limited success in predicting the rate at which vapor-to-liquid nucleation takes place at given conditions. This thesis studies the unary homogeneous vapor-to-liquid nucleation from a statistical mechanics viewpoint. We apply Monte Carlo simulations of molecular clusters to calculate the free energy barrier separating the vapor and liquid phases and compare our results against the laboratory measurements and Classical Nucleation Theory predictions. According to our results, the work of adding a monomer to a cluster in equilibrium vapour is accurately described by the liquid drop model applied by the Classical Nucleation Theory, once the clusters are larger than some threshold size. The threshold cluster sizes contain only a few or some tens of molecules depending on the interaction potential and temperature. However, the error made in modeling the smallest of clusters as liquid drops results in an erroneous absolute value for the cluster work of formation throughout the size range, as predicted by the McGraw-Laaksonen scaling law. By calculating correction factors to Classical Nucleation Theory predictions for the nucleation barriers of argon and water, we show that the corrected predictions produce nucleation rates that are in good comparison with experiments. For the smallest clusters, the deviation between the simulation results and the liquid drop values are accurately modelled by the low order virial coefficients at modest temperatures and vapour densities, or in other words, in the validity range of the non-interacting cluster theory by Frenkel, Band and Bilj. Our results do not indicate a need for a size dependent replacement free energy correction. The results also indicate that Classical Nucleation Theory predicts the size of the critical cluster correctly. We also presents a new method for the calculation of the equilibrium vapour density, surface tension size dependence and planar surface tension directly from cluster simulations. We also show how the size dependence of the cluster surface tension in equimolar surface is a function of virial coefficients, a result confirmed by our cluster simulations

    Temperature-Dependent Diffusion of H2SO4 in Air at Atmospherically Relevant Conditions : Laboratory Measurements Using Laminar Flow Technique

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    We report flow tube measurements of the effective sulfuric acid diffusion coefficient at ranges of different relative humidities (from similar to 4 to 70%), temperatures (278, 288 and 298 K) and initial H2SO4 concentrations (from 1 x 10(6) to 1 x 10(8) molecules.cm(-3)). The measurements were carried out under laminar flow of humidified air containing trace amounts of impurities such as amines (few ppt), thus representing typical conditions met in Earth's continental boundary layer. The diffusion coefficients were calculated from the sulfuric acid wall loss rate coefficients that were obtained by measuring H2SO4 concentration continuously at seven different positions along the flow tube with a chemical ionization mass spectrometer (CIMS). The wall loss rate coefficients and laminar flow conditions were verified with additional computational fluid dynamics (CFD) model FLUENT simulations. The determined effective sulfuric acid diffusion coefficients decreased with increasing relative humidity, as also seen in previous experiments, and had a rather strong power dependence with respect to temperature, around proportional to T-5.6, which is in disagreement with the expected temperature dependence of similar to T-1.75 for pure vapours. Further clustering kinetics simulations using quantum chemical data showed that the effective diffusion coefficient is lowered by the increased diffusion volume of H2SO4 molecules via a temperature-dependent attachment of base impurities like amines. Thus, the measurements and simulations suggest that in the atmosphere the attachment of sulfuric acid molecules with base molecules can lead to a lower than expected effective sulfuric acid diffusion coefficient with a higher than expected temperature dependence.Peer reviewe

    Charged and Neutral Binary Nucleation of Sulfuric Acid in Free Troposphere Conditions

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    We present a data set of binary nucleation of sulfuric acid and water, measured in the CLOUD chamber at CERN during the CLOUD3 and CLOUD5 campaigns. Four parameters have been varied to cover neutral and ion-induced binary nucleation processes: Sulfuric acid concentration (1e5 to 1e8 molecules per cm^(−3)), relative humidity (10% to 80%), temperature (208-293K) and ion concentration (0-4000 ions per cm^(−3)). In addition, classical nucleation theory implemented with hydrates and ion induced nucleation is compared with the data set. Our model and data are also compared with nucleation rates measured at Puy de Dome in the tropopause

    Explaining global surface aerosol number concentrations in terms of primary emissions and particle formation

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    We use observations of total particle number concentration at 36 worldwide sites and a global aerosol model to quantify the primary and secondary sources of particle number. We show that emissions of primary particles can reasonably reproduce the spatial pattern of observed condensation nuclei (CN) (R2=0.51) but fail to explain the observed seasonal cycle at many sites (R2=0.1). The modeled CN concentration in the free troposphere is biased low (normalised mean bias, NMB=−88%) unless a secondary source of particles is included, for example from binary homogeneous nucleation of sulfuric acid and water (NMB=−25%). Simulated CN concentrations in the continental boundary layer (BL) are also biased low (NMB=−74%) unless the number emission of anthropogenic primary particles is increased or an empirical BL particle formation mechanism based on sulfuric acid is used. We find that the seasonal CN cycle observed at continental BL sites is better simulated by including a BL particle formation mechanism (R2=0.3) than by increasing the number emission from primary anthropogenic sources (R2=0.18). Using sensitivity tests we derive optimum rate coefficients for this nucleation mechanism, which agree with values derived from detailed case studies at individual sites

    Understanding the surface temperature response and its uncertainty to CO2, CH4, black carbon, and sulfate

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    Understanding the regional surface temperature responses to different anthropogenic climate forcing agents, such as greenhouse gases and aerosols, is crucial for understanding past and future regional climate changes. In modern climate models, the regional temperature responses vary greatly for all major forcing agents, but the causes of this variability are poorly understood. Here, we analyze how changes in atmospheric and oceanic energy fluxes due to perturbations in different anthropogenic climate forcing agents lead to changes in global and regional surface temperatures. We use climate model data on idealized perturbations in four major anthropogenic climate forcing agents (CO2, CH4, sulfate, and black carbon aerosols) from Precipitation Driver Response Model Intercomparison Project (PDRMIP) climate experiments for six climate models (CanESM2, HadGEM2-ES, NCAR-CESM1-CAM4, NorESM1, MIROC-SPRINTARS, GISS-E2). Particularly, we decompose the regional energy budget contributions to the surface temperature responses due to changes in longwave and shortwave fluxes under clear-sky and cloudy conditions, surface albedo changes, and oceanic and atmospheric energy transport. We also analyze the regional model-to-model temperature response spread due to each of these components. The global surface temperature response stems from changes in longwave emissivity for greenhouse gases (CO2 and CH4) and mainly from changes in shortwave clear-sky fluxes for aerosols (sulfate and black carbon). The global surface temperature response normalized by effective radiative forcing is nearly the same for all forcing agents (0.63, 0.54, 0.57, 0.61KW 1 m(2)). While the main physical processes driving global temperature responses vary between forcing agents, for all forcing agents the model-to-model spread in temperature responses is dominated by differences in modeled changes in longwave clear-sky emissivity. Furthermore, in polar regions for all forcing agents the differences in surface albedo change is a key contributor to temperature responses and its spread. For black carbon, the modeled differences in temperature response due to shortwave clear-sky radiation are also important in the Arctic. Regional model-to-model differences due to changes in shortwave and longwave cloud radiative effect strongly modulate each other. For aerosols, clouds play a major role in the model spread of regional surface temperature responses. In regions with strong aerosol forcing, the model-to-model differences arise from shortwave clear-sky responses and are strongly modulated by combined temperature responses to oceanic and atmospheric heat transport in the models.Peer reviewe
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