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Abstract Atmospheric aerosol and chemistry modules are key elements in Earth system models (ESMs), as they predict air pollutant concentrations and properties that can impact human health, weather, and climate. The current uncertainty in climate projections is partly due to the inaccurate representation of aerosol direct and indirect forcing. Aerosol/chemistry parameterizations used within ESMs and other atmospheric models span large structural and parameter uncertainties that are difficult to assess independently of their host models. Moreover, there is a strong need for a standardized interface between aerosol/chemistry modules and the host model to facilitate portability of aerosol/chemistry parameterizations from one model to another, allowing not only a comparison between different parameterizations within the same modeling framework, but also quantifying the impact of different model frameworks on aerosol/chemistry predictions. To address this need, we have initiated a new community effort to coordinate the construction of a Generalized Aerosol/Chemistry Interface (GIANT) for use across weather and climate models. We aim to organize a series of community workshops and hackathons to design and build GIANT, which will serve as the interface between a range of aerosol/chemistry modules and the physics and dynamics components of atmospheric host models. GIANT will leverage ongoing efforts at the U.S. modeling centers focused on building next-generation ESMs and the international AeroCom initiative to implement this common aerosol/chemistry interface. GIANT will create transformative opportunities for scientists and students to conduct innovative research to better characterize structural and parametric uncertainties in aerosol/chemistry modules, and to develop a common set of aerosol/chemistry parameterizations. 

Abstract. A flexible treatment for gas- and aerosol-phase chemical processes has been developed for models of diverse scale, from box models up to global models. At the core of this novel framework is an “abstracted aerosol representation” that allows a given chemical mechanism to be solved in atmospheric models with different aerosol representations (e.g., sectional, modal, or particle-resolved). This is accomplished by treating aerosols as a collection of condensed phases that are implemented according to the aerosol representation of the host model. The framework also allows multiple chemical processes (e.g., gas- and aerosol-phase chemical reactions, emissions, deposition, photolysis, and mass transfer) to be solved simultaneously as a single system. The flexibility of the model is achieved by (1) using an object-oriented design that facilitates extensibility to new types of chemical processes and to new ways of representing aerosol systems, (2) runtime model configuration using JSON input files that permits making changes to any part of the chemical mechanism without recompiling the model (this widely used, human-readable format allows entire gas- and aerosol-phase chemical mechanisms to be described with as much complexity as necessary), and (3) automated comprehensive testing that ensures stability of the code as new functionality is introduced.Together, these design choices enable users to build a customized multiphase mechanism without having to handle preprocessors, solvers, or compilers. Removing these hurdles makes this type of modeling accessible to a much wider community, including modelers, experimentalists, and educators.This new treatment compiles as a stand-alone library and has been deployed in the particle-resolved PartMC model and in the Multiscale Online AtmospheRe CHemistry (MONARCH) chemical weather prediction system for use at regional and global scales. Results from the initial deployment to box models of different complexity and MONARCH will be discussed, along with future extension to more complex gas–aerosol systems and the integration of GPU-based solvers. 

Abstract. Acidity, defined as pH, is a central component of aqueouschemistry. In the atmosphere, the acidity of condensed phases (aerosolparticles, cloud water, and fog droplets) governs the phase partitioning ofsemivolatile gases such as HNO3, NH3, HCl, and organic acids andbases as well as chemical reaction rates. It has implications for theatmospheric lifetime of pollutants, deposition, and human health. Despiteits fundamental role in atmospheric processes, only recently has this fieldseen a growth in the number of studies on particle acidity. Even with thisgrowth, many fine-particle pH estimates must be based on thermodynamic modelcalculations since no operational techniques exist for direct measurements.Current information indicates acidic fine particles are ubiquitous, butobservationally constrained pH estimates are limited in spatial and temporalcoverage. Clouds and fogs are also generally acidic, but to a lesser degreethan particles, and have a range of pH that is quite sensitive toanthropogenic emissions of sulfur and nitrogen oxides, as well as ambientammonia. Historical measurements indicate that cloud and fog droplet pH haschanged in recent decades in response to controls on anthropogenicemissions, while the limited trend data for aerosol particles indicateacidity may be relatively constant due to the semivolatile nature of thekey acids and bases and buffering in particles. This paper reviews andsynthesizes the current state of knowledge on the acidity of atmosphericcondensed phases, specifically particles and cloud droplets. It includesrecommendations for estimating acidity and pH, standard nomenclature, asynthesis of current pH estimates based on observations, and new modelcalculations on the local and global scale.