Chemistry Across Multiple Phases (CAMP) version 1.0: An integrated multi-phase chemistry model

TL;DR

The paper introduces CAMP v1.0, a flexible, integrated multi-phase chemistry model adaptable to various atmospheric modeling scales, enabling comprehensive simulation of gas and aerosol chemical processes with user-friendly configuration.

Contribution

It presents a novel, object-oriented framework that allows customizable, multi-process atmospheric chemistry modeling with flexible aerosol representations and runtime configurability.

Findings

Successfully deployed in regional and global models.

Enables complex multi-phase chemical mechanism customization.

Supports future extensions including GPU-based solvers.

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 pre-processors, solvers or compilers. This new treatment compiles as a stand-alone library and has been deployed in the particle-resolved PartMC model and in the MONARCH chemical weather prediction system for use at regional and global scales. Results from the initial deployment will be discussed, along with future extension to more complex gas-aerosol systems, and the integration of GPU-based solvers.