Scalable chemical mechanisms of emerging sources for community air quality predictions

EPA Grant Number: R840007
Title: Scalable chemical mechanisms of emerging sources for community air quality predictions
Investigators: Barsanti, Kelley , Carter, William , Orlando, John , Emmons, Louisa
Institution: University of California - Riverside , National Center for Atmospheric Research
EPA Project Officer: Chung, Serena
Project Period: August 1, 2020 through July 31, 2023
Project Amount: $784,743
RFA: Chemical Mechanisms to Address New Challenges in Air Quality Modeling (2019) RFA Text |  Recipients Lists
Research Category: Air Quality and Air Toxics , Air


With significant decreases in major emissions sources across the United States (US), our attention has shifted to emerging sources of pollutants such as wildland fires and volatile consumer products, for understanding, predicting, and mitigating air pollution. New chemical mechanisms are needed to describe the atmospheric reactivity of compounds emitted from such sources, including (oxygenated-) aromatics and terpenes. These chemical mechanisms must be scalable for a range of applications (e.g., research to regulatory) and must be considered community resources to support continued development, evaluation, and application.


Therefore, the objectives of the proposed research are to: 1) derive and evaluate explicit chemical mechanisms for representative individual compounds identified in emerging sources using well-established and peer-reviewed protocols; 2) develop approaches to reduce explicit chemical mechanisms, scalable to specific applications; and 3) apply and evaluate new chemistries and reduced chemical mechanisms in air quality model simulations.


Mechanism derivation will be achieved using the Generator for Explicit Chemistry and Kinetics in the Atmosphere (GECKO-A) and the SAPRC mechanism generation system (MechGen), with input from peer-reviewed literature and structure activity relationships (SARs). Mechanism reduction methods will allow for scalability in the number of reactions and products, and chemical and physical properties of interest; and will be developed using existing and novel approaches. A community global chemistry model (MUSICA: Multi-Scale Infrastructure for Chemistry and Aerosols) will be used to evaluate predictions of selected air toxics, ozone (O3), fine particulate matter (PM2.5), and important intermediates using the reduced mechanisms. Model output will be compared with measurement data from surface monitors and recent field campaigns (including vertical profile data), and satellite observations.

Expected Results:

The outcomes and outputs of the proposed research include: 1) regional analysis of the potential contributions of emerging sources to air toxics, O3, and PM2.5; 2) evaluation of reduced mechanisms for predicting O3 and PM2.5 (including as a function of complexity and reduction approach); 3) mechanism reduction tools that allow community users to scale chemical mechanisms based on application needs; and 4) a community library of explicit and reduced chemical mechanisms, including supporting data and SARs, to allow continued and sustained development of reduced mechanisms for research and regulatory air quality modeling. The results of the project will: 1) provide a sustainable platform for chemical mechanism development, evaluation, and application; and 2) allow more accurate predictions of the contribution of emerging sources to air toxics, O3, and PM2.5 in urban and rural areas, which are required for robust risk analysis and development of appropriate mitigation strategies.

Supplemental Keywords:

chemical transport, oxidants, organics, environmental data