Ensemble Analysis of Global Change Projections for US Air Quality Using a Novel Combination of Lagrangian and Gridded Air Quality Models

EPA Grant Number: R835874
Title: Ensemble Analysis of Global Change Projections for US Air Quality Using a Novel Combination of Lagrangian and Gridded Air Quality Models
Investigators: Lamb, Brian , Avise, Jeremy C. , Chung, Sandra , Edburg, Steven Lee , Fast, Jerome D. , Guenther, Alex , Walden, Von P. , Zaveri, Rahul A.
Current Investigators: Lamb, Brian , Avise, Jeremy C. , Fast, Jerome D. , Guenther, Alex , Lee, Yunha , Vaughan, Joseph , Walden, Von P. , Zaveri, Rahul A.
Institution: Washington State University , Pacific Northwest National Laboratory
EPA Project Officer: Keating, Terry
Project Period: January 1, 2016 through December 31, 2018 (Extended to December 31, 2019)
Project Amount: $789,547
RFA: Particulate Matter and Related Pollutants in a Changing World (2014) RFA Text |  Recipients Lists
Research Category: Air , Climate Change


Our overall goal is to improve our understanding of the effects of global change on future PM levels in the western US. Our research design primarily addresses the first two EPA overarching questions related to how PM will change in the US and what global change factors contribute to these changes.


Our primary objectives are to develop and apply a novel application of Lagrangian box modeling using an ensemble of high resolution and bias corrected downscaled climate conditions to provide comprehensive descriptions of PM changes due to various global change factors.


Daily, high resolution (4 km grids) statistically downscaled  climate data based upon the Multivariate Adaptive Constructed Analogs (MACA) method will be used as input for emission modeling and for the chemical box modeling. The MOSAIC box model provides a full and explicit treatment of gas and aerosol phase chemistry and dynamics.  It will be applied for specific source-trajectory locations that represent key PM air quality issues including wintertime stagnation events, summertime urban to rural transport cases, and wildfire impacts on rural and urban populations. For this study, we will focus on the western US but the approach we develop will be applicable to other regions. We will also focus on two future time periods: 1) a regulatory relevant time period centered around 2030, and 2) a future time period centered around 2050, where global changes are expected be larger and have a greater impact on air quality. The global change factors to be addressed include climate change, US anthropogenic emissions, wildfire emissions, biogenic emissions, land cover changes, and background concentration changes associated with long range transport. The model will be evaluated using data from recent field campaigns related to these winter and summer situations. An attribution approach will be used to assess the individual impacts of the different global change factors upon future PM and ozone levels for each of the air quality cases. Because the MOSAIC model is computationally efficient, a large number of cases can be simulated to treat the full range of climate projections superimposed upon a range of future global change factors.

Expected Results:

The end products of this research will be an extensive set of simulations explicitly addressing the effects of climate change, emission changes and land cover changes upon PM and ozone for key air quality issues and locations in the western US. A special effort will be made to summarize the full range of results in terms accessible and useful for air quality managers.

Publications and Presentations:

Publications have been submitted on this project: View all 6 publications for this project

Supplemental Keywords:

particulate matter, ozone, western US, climate change;

Progress and Final Reports:

  • 2016 Progress Report
  • 2017 Progress Report
  • 2018