Airborne particles affect human health and significantly influence visibility and climate. A major fraction of these particles result from the reactions of gaseous precursors to generate low-volatility products such as sulfuric acid and high-molecular weight organics that nucleate to form new particles. Ammonia and, more recently, amines, both of which are ubiquitous in the environment, have also been recognized as important contributors. However, accurately predicting new particle formation in both laboratory systems and in air has been problematic. During the oxidation of organosulfur compounds, gas-phase methanesulfonic acid is formed simultaneously with sulfuric acid, and both are found in particles in coastal regions as well as inland. We show here that: (i) Amines form particles on reaction with methanesulfonic acid, (ii) water vapor is required, and (iii) particle formation can be quantitatively reproduced by a semiempirical kinetics model supported by insights from quantum chemical calculations of likely intermediate clusters.Such an approach may be more broadly applicable in models of outdoor, indoor, and industrial settings where particles are formed, and where accurate modeling is essential for predicting their impact on health, visibility, and climate.kinetics modeling | multi-component nucleation | cluster enthalpy | flow tube reactor | atmospheric nanoparticles U nderstanding how gas phase precursors lead to the formation and growth of new particles that are important for scattering light, for serving as cloud condensation or ice nuclei, and for transport deep into the lung, is one of the most pressing scientific problems (1-5). The most studied system is the conversion of gas-phase SO 2 to sulfuric acid and sulfate particles, but even in this case, models typically underestimate particle formation by an order of magnitude or more (3, 4, 6). However, an accurate predictive capability based on molecular-level understanding is critical for projecting the impacts of particles and developing optimal control strategies.Classical nucleation theory (CNT) has been used for almost a century (7, 8) to predict new particle formation. At its heart, CNT is a thermodynamics approach that assumes that the precursor clusters have bulk liquid properties such as surface tension, and that addition to and evaporation from the clusters occurs via monomers. Modifications to CNT using kinetics approaches have been described (9, 10). More recently, dynamical nucleation theory (11-13) examined intermolecular interactions and used them to obtain rate constants for the individual steps through variational transition-state theory. This theory has been applied to particle formation in relatively simple systems and clusters of relatively few molecules. Recent data from field and laboratory studies, however, suggest that multicomponent systems with multiple reaction steps are likely involved in new particle formation in the atmosphere (14-22).We report here a combination of experimental and theoretical studies of new particle fo...
New particle formation from gas-to-particle conversion represents a dominant source of atmospheric particles and affects radiative forcing, climate and human health. The species involved in new particle formation and the underlying mechanisms remain uncertain. Although sulfuric acid is commonly recognized as driving new particle formation, increasing evidence suggests the involvement of other species. Here we study particle formation and growth from methanesulfonic acid, trimethylamine and water at reaction times from 2.3 to 32 s where particles are 2-10 nm in diameter using a newly designed and tested flow system. The flow system has multiple inlets to facilitate changing the mixing sequence of gaseous precursors. The relative humidity and precursor concentrations, as well as the mixing sequence, are varied to explore their effects on particle formation and growth in order to provide insight into the important mechanistic steps. We show that water is involved in the formation of initial clusters, greatly enhancing their formation as well as growth into detectable size ranges. A kinetics box model is developed that quantitatively reproduces the experimental data under various conditions. Although the proposed scheme is not definitive, it suggests that incorporating such mechanisms into atmospheric models may be feasible in the near future.
Sulfuric acid (H 2 SO 4 ), formed from oxidation of sulfur dioxide (SO 2 ) emitted during fossil fuel combustion, is a major precursor of new airborne particles, which have well-documented detrimental effects on health, air quality, and climate. Another precursor is methanesulfonic acid (MSA), produced simultaneously with SO 2 during the atmospheric oxidation of organosulfur compounds (OSCs), such as dimethyl sulfide. In the present work, a multidisciplinary approach is used to examine how contributions of H 2 SO 4 and MSA to particle formation will change in a large coastal urban area as anthropogenic fossil fuel emissions of SO 2 decline. The 3-dimensional University of California Irvine-California Institute of Technology airshed model is used to compare atmospheric concentrations of gas phase MSA, H 2 SO 4 , and SO 2 under current emissions of fossil fuel-associated SO 2 and a best-case futuristic scenario with zero fossil fuel sulfur emissions. Model additions include results from (i) quantum chemical calculations that clarify the previously uncertain gas phase mechanism of formation of MSA and (ii) a combination of published and experimental estimates of OSC emissions, such as those from marine, agricultural, and urban processes, which include pet waste and human breath. Results show that in the zero anthropogenic SO 2 emissions case, particle formation potential from H 2 SO 4 will drop by about two orders of magnitude compared with the current situation. However, particles will continue to be generated from the oxidation of natural and anthropogenic sources of OSCs, with contributions from MSA and H 2 SO 4 of a similar order of magnitude. This could be particularly important in agricultural areas where there are significant sources of OSCs. methanesulfonic acid | sulfuric acid | new particle formation | atmosphere | fossil fuel
Abstract. We present the dust module in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) version 2.0, a chemical weather prediction system that can be used for regional and global modeling at a range of resolutions. The representations of dust processes in MONARCH were upgraded with a focus on dust emission (emission parameterizations, entrainment thresholds, considerations of soil moisture and surface cover), lower boundary conditions (roughness, potential dust sources), and dust–radiation interactions. MONARCH now allows modeling of global and regional mineral dust cycles using fundamentally different paradigms, ranging from strongly simplified to physics-based parameterizations. We present a detailed description of these updates along with four global benchmark simulations, which use conceptually different dust emission parameterizations, and we evaluate the simulations against observations of dust optical depth. We determine key dust parameters, such as global annual emission/deposition flux, dust loading, dust optical depth, mass-extinction efficiency, single-scattering albedo, and direct radiative effects. For dust-particle diameters up to 20 µm, the total annual dust emission and deposition fluxes obtained with our four experiments range between about 3500 and 6000 Tg, which largely depend upon differences in the emitted size distribution. Considering ellipsoidal particle shapes and dust refractive indices that account for size-resolved mineralogy, we estimate the global total (longwave and shortwave) dust direct radiative effect (DRE) at the surface to range between about −0.90 and −0.63 W m−2 and at the top of the atmosphere between −0.20 and −0.28 W m−2. Our evaluation demonstrates that MONARCH is able to reproduce key features of the spatiotemporal variability of the global dust cycle with important and insightful differences between the different configurations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.