Modelling the gas–particle partitioning and water uptake of isoprene-derived secondary organic aerosol at high and low relative humidity

This study presents a characterization of the hygroscopic growth behaviour and effects of different inorganic seed particles on the formation of secondary organic aerosols (SOAs) from the dark ozone-initiated oxidation of isoprene at low NOx conditions. We performed simulations of isoprene oxidation using a gas-phase chemical reaction mechanism based on the Master Chemical Mechanism (MCM) in combination with an equilibrium gas–particle partitioning model to predict the SOA concentration. The equilibrium model accounts for non-ideal mixing in liquid phases, including liquid–liquid phase separation (LLPS), and is based on the AIOMFAC (Aerosol Inorganic–Organic Mixtures Functional groups Activity Coefficients) model for mixture non-ideality and the EVAPORATION (Estimation of VApour Pressure of ORganics, Accounting for Temperature, Intramolecular, and Non-additivity effects) model for pure compound vapour pressures. Measurements from the Cosmics Leaving Outdoor Droplets (CLOUD) chamber experiments, conducted at the European Organization for Nuclear Research (CERN) for isoprene ozonolysis cases, were used to aid in parameterizing the SOA yields at different atmospherically relevant temperatures, relative humidity (RH), and reacted isoprene concentrations. To represent the isoprene-ozonolysis-derived SOA, a selection of organic surrogate species is introduced in the coupled modelling system. The model predicts a single, homogeneously mixed particle phase at all relative humidity levels for SOA formation in the absence of any inorganic seed particles. In the presence of aqueous sulfuric acid or ammonium bisulfate seed particles, the model predicts LLPS to occur below ∼ 80 % RH, where the particles consist of an inorganic-rich liquid phase and an organic-rich liquid phase; however, this includes significant amounts of bisulfate and water partitioned to the organic-rich phase. The measurements show an enhancement in the SOA amounts at 85 % RH, compared to 35 % RH, for both the seed-free and seeded cases. The model predictions of RH-dependent SOA yield enhancements at 85 % RH vs. 35 % RH are 1.80 for a seed-free case, 1.52 for the case with ammonium bisulfate seed, and 1.06 for the case with sulfuric acid seed. Predicted SOA yields are enhanced in the presence of an aqueous inorganic seed, regardless of the seed type (ammonium sulfate, ammonium bisulfate, or sulfuric acid) in comparison with seed-free conditions at the same RH level. We discuss the comparison of model-predicted SOA yields with a selection of other laboratory studies on isoprene SOA formation conducted at different temperatures and for a variety of reacted isoprene concentrations. Those studies were conducted at RH levels at or below 40 % with reported SOA mass yields ranging from 0.3 % up to 9.0 %, indicating considerable variations. A robust feature of our associated gas–particle partitioning calculations covering the whole RH range is the predicted enhancement of SOA yield at high RH (> 80 %) compared to low RH (dry) conditions, which is explained by the effect of particle water uptake and its impact on the equilibrium partitioning of all components.

Chemical Dissolution of Chalcopyrite Concentrate in Choline Chloride Ethylene Glycol Deep Eutectic Solvent

Currently, the high demand for copper is in direct contrast with the decrease in the mineral grade and, more significantly, the concerns regarding the environmental impact that arise as a result of processing such low-grade materials. Consequently, new mineral processing concepts are needed. This work explores the chemical dissolution of chalcopyrite concentrate at ambient pressure and moderate temperatures in a deep eutectic solvent. Copper and iron are dissolved without changing their oxidation state, without solvent pH change, and stabilized as a chloride complex with no evidence of passivation. Chemical equilibria of the metallic chloride complexes limit the dissolution, and the step that is rate-controlling of the kinetics is the interdiffusion of species in the solvent. The chemical mechanism may involve initial chloride adsorption at positive sites of the solid surface, pointing out the importance of surfaces states on chalcopyrite particles. A model based on a shrinking particle coupled with pseudo-second-order increase in the liquid concentration of copper describes the dissolution kinetics and demonstrates the importance of the liquid to solid ratio. Iron and copper can be recovered separately from the solvent, which highlights that this concept is an interesting alternative to both redox-hydrometallurgy and pyrometallurgy to obtain copper by the processing of chalcopyrite concentrate.

Higher-order structure of DNA determines its positioning in cell-size droplets under crowded conditions

Background It is becoming clearer that living cells use water/water (w/w) phase separation to form membraneless organelles that exhibit various important biological functions. Currently, it is believed that the specific localization of biomacromolecules, including DNA, RNA and proteins in w/w microdroplets is closely related to their bio-activity. Despite the importance of this possible role of micro segregation, our understanding of the underlying physico-chemical mechanism is still unrefined. Further research to unveil the underlying mechanism of the localization of macromolecules in relation to their steric conformation in w/w microdroplets is needed. Principal findings Single-DNA observation of genome-size DNA (T4 GT7 bacteriophage DNA; 166kbp) by fluorescence microscopy revealed that DNAs are spontaneously incorporated into w/w microdroplets generated in a binary aqueous polymer solution with polyethylene glycol (PEG) and dextran (DEX). Interestingly, DNAs with elongated coil and shrunken conformations exhibit Brownian fluctuation inside the droplet. On the other hand, tightly packed compact globules, as well as assemblies of multiple condensed DNAs, tend to be located near the interface in the droplet. Conclusion and significance The specific localization of DNA molecules depending on their higher-order structure occurs in w/w microdroplet phase-separation solution under a binary aqueous polymer solution. Such an aqueous solution with polymers mimics the crowded conditions in living cells, where aqueous macromolecules exist at a level of 30–40 weight %. The specific positioning of DNA depending on its higher-order structure in w/w microdroplets is expected to provide novel insights into the mechanism and function of membraneless organelles and micro-segregated particles in living cells.

Biomass burning plume chemistry: OH-radical-initiated oxidation of 3-penten-2-one and its main oxidation product 2-hydroxypropanal

In order to enlarge our understanding of biomass burning plume chemistry, the OH-radical-initiated oxidation of 3-penten-2-one (3P2), identified in biomass burning emissions, and 2-hydroxypropanal (2HPr) was investigated at 298 ± 3 K and 990 ± 15 mbar in two atmospheric simulation chambers using long-path FTIR spectroscopy. The rate coefficient of 3P2 + OH was determined to be (6.2 ± 1.0) × 10−11 cm3 molec.−1 s−1 and the molar first-generation yields for acetaldehyde, methyl glyoxal, 2HPr, and the sum of peroxyacetyl nitrate (PAN) and CO2, used to determine the CH3C(O) radical yield, were 0.39 ± 0.07, 0.32 ± 0.08, 0.68 ± 0.27, and 0.56 ± 0.14, respectively, under conditions where the 3P2-derived peroxy radicals react solely with NO. The 2HPr + OH reaction was investigated using 3P2 + OH as a source of the α-hydroxyaldehyde adjusting the experimental conditions to shift the reaction system towards secondary oxidation processes. The rate coefficient was estimated to be (2.2 ± 0.6) × 10−11 cm3 molec.−1 s−1. Employing a simple chemical mechanism to analyse the temporal behaviour of the experiments, the further oxidation of 2HPr was shown to form methyl glyoxal, acetaldehyde, and CO2 with estimated yields of 0.27 ± 0.08, 0.73 ± 0.08, and 0.73 ± 0.08, respectively.

Turbulent Premixed Flame Modeling Using the Algebraic Flame Surface Wrinkling Model: A Comparative Study between OpenFOAM and Ansys Fluent

Hereafter, we used the Algebraic Flame Surface Wrinkling (AFSW) model to conduct numerical simulations of the Paul Scherrer Institute (PSI) high-pressure, turbulent premixed Bunsen flame experiments. We implemented the AFSW model in OpenFOAM and in Ansys Fluent, and we compared the outcome of both solvers against the experimental results. We also highlight the differences between both solvers. All the simulations were performed using a two-dimensional axisymmetric model with the standard k−ϵ turbulence model with wall functions. Two different fuel/air mixtures were studied, namely, a 100%CH4 volumetric ratio and a 60%CH4+ 40%H2 volumetric ratio. The thermophysical and transport properties of the mixture were calculated as a function of temperature using the library Cantera (open-source suite of tools for problems involving chemical kinetics, thermodynamics, and transport processes), together with the GRI-Mech 3.0 chemical mechanism. It was found that the outcome of the AFSW model implemented in both solvers was in good agreement with the experimental results, quantitatively and qualitatively speaking. Further assessment of the results showed that, as much as the chemistry, the turbulence model and turbulent boundary/initial conditions significantly impact the flame shape and height.

Functionality-Based Formation of Secondary Organic Aerosol from m-Xylene Photooxidation

Photooxidation of volatile organic compounds (VOCs) produces condensable oxidized organics (COOs) to yield secondary organic aerosol (SOA), but the fundamental chemical mechanism for gas-to-particle conversion remains uncertain. Here we elucidate the production of COOs and their roles in SOA and brown carbon (BrC) formation from m-xylene oxidation by simultaneous monitoring the evolutions of gas-phase products and aerosol properties in an environmental chamber. Four COO types with the distinct functionalities of dicarbonyls, carboxylic acids, polyhydroxy aromatics/quinones, and nitrophenols are identified from early-generation oxidation, with the yields of 25 %, 37 %, 5 %, and 3 %, respectively. SOA formation occurs via several heterogeneous processes, including interfacial interaction, ionic dissociation/acid-base reaction, and oligomerization, with the yields of (20 ± 4) % and (32 ± 7) % at 10 % and 70 % relative humidity (RH), respectively. Chemical speciation shows the dominant presence of oligomers, nitrogen-containing organics, and carboxylates at RH and carboxylates at low RH. The identified BrC includes N-heterocycles/N-heterochains and nitrophenols, as evident from reduced single scattering albedo. The measured uptake coefficient (γ) for COOs is dependent on the functionality, ranging from 3.7 × 10−4 to 1.3 × 10−2. A kinetic framework is developed to predict SOA production from the concentrations and uptake coefficients for COOs. This functionality-based approach well reproduces SOA formation from m-xylene oxidation and is broadly applicable to VOC oxidation for other species. Our results reveal that photochemical oxidation of m-xylene represents a major source for SOA and BrC formation under urban environments, because of its large abundance, high reactivity with OH, and high yields for COOs.

An Online-Learned Neural Network Chemical Solver for Stable Long-Term Global Simulations of Atmospheric Chemistry

A major computational barrier in global modeling of atmospheric chemistry is the numerical integration of the coupled kinetic equations describing the chemical mechanism. Machine-learned (ML) solvers can offer order-of-magnitude speedup relative to conventional implicit solvers, but past implementations have suffered from fast error growth and only run for short simulation times (<1 month). A successful ML solver for global models must avoid error growth over year-long simulations and allow for re-initialization of the chemical trajectory by transport at every time step. Here we explore the capability of a neural network solver equipped with an autoencoder to achieve stable full-year simulations of tropospheric oxidant chemistry in the global 3-D GEOS-Chem model, replacing its standard mechanism (228 species) by the Super-Fast mechanism (12 species) to avoid the curse of dimensionality. We find that online training of the ML solver within GEOS-Chem is essential for accuracy, whereas offline training from archived GEOS-Chem inputs/outputs produces large errors. After online training we achieve stable 1-year simulations with five-fold speedup compared to the standard implicit Rosenbrock solver with global tropospheric normalized mean biases of -0.3% for ozone, 1% for hydrogen oxide radicals, and -5% for nitrogen oxides. The ML solver captures the diurnal and synoptic variability of surface ozone at polluted and clean sites. There are however large regional biases for ozone and NOx under remote conditions where chemical aging leads to error accumulation. These regional biases remain a major limitation for practical application, and ML emulation would be more difficult in a more complex mechanism.

Investigating the Effects of Chemical Mechanism on Soot Formation Under High-Pressure Fuel Pyrolysis

We performed Computational Fluid Dynamics (CFD) simulations using a Reynolds-Averaged Navier-Stokes (RANS) turbulence model of high-pressure spray pyrolysis with a detailed chemical kinetic mechanism encompassing pyrolysis of n-dodecane and formation of polycyclic aromatic hydrocarbons. We compare the results using the detailed mechanism and those found using several different reduced chemical mechanisms to experiments carried out in an optically accessible, high-pressure, constant-volume combustion chamber. Three different soot models implemented in the CONVERGE CFD software are used: an empirical soot model, a method of moments, and a discrete sectional method. There is a large variation in the prediction of the soot between different combinations of chemical mechanisms and soot model. Furthermore, the amount of soot produced from all models is substantially less than experimental measurements. All of this indicates that there is still substantial work that needs to be done to arrive at simulations that can be relied on to accurately predict soot formation.

Potential of hydrogen/diesel reactivity controlled compression ignition (RCCI) combustion from the perspective of the second law of thermodynamics

The potential of reactivity controlled compression ignition (RCCI) combustion fueled with hydrogen and diesel (i.e. hydrogen/diesel RCCI) was evaluated using multi-dimensional simulations embedded with a reduced chemical mechanism. In hydrogen/diesel RCCI, the premixed hydrogen is ignited by the diesel, which is directly injected into the cylinder well before the top dead center. To investigate the potential benefits of hydrogen/diesel RCCI, its combustion characteristics were compared with that of gasoline/diesel RCCI from the perspective of the second law of thermodynamics. Meanwhile, the impacts of premixed energy ratio and initial pressure on the exergy distribution for hydrogen/diesel RCCI were explored. The results show that hydrogen/diesel RCCI has an advantage over gasoline/diesel RCCI in the reduction of exergy destruction due to higher combustion temperature, shorter combustion duration, and the distinctive oxidation pathways between hydrogen and gasoline. A higher proportion of exergy output work can be achieved for hydrogen/diesel RCCI under the conditions with the same total input energy and 50% heat release (CA50) point. Moreover, a larger premixed energy ratio (i.e. larger hydrogen proportion) is helpful to elevate exergy output work and reduce exergy destruction owing to higher combustion temperature and the undergoing oxidation pathways of hydrogen with less exergy destruction. A higher initial pressure yields raised exergy destruction because of lower combustion temperature and longer combustion duration, but exergy output work is increased owing to the significantly reduced exergy transfer through heat transfer.