Grantee Research Project Results

2017 Progress Report: 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 , Zaveri, Rahul A. , Avise, Jeremy C. , Fast, Jerome D. , Walden, Von P. , Guenther, Alex , Vaughan, Joseph , Lee, Yunha
Current Investigators: Lamb, Brian , Lee, Yunha , Walden, Von P. , Vaughan, Joseph , Guenther, Alex , Avise, Jeremy C. , Zaveri, Rahul A. , Fast, Jerome D.
Institution: Washington State University , Pacific Northwest National Laboratory
Current Institution: Washington State University , University of California - Irvine , California Air Resources Board , Pacific Northwest National Laboratory
EPA Project Officer: Keating, Terry
Project Period: January 1, 2016 through December 31, 2018 (Extended to December 31, 2020)
Project Period Covered by this Report: January 1, 2017 through December 31,2017
Project Amount: $789,547
RFA: Particulate Matter and Related Pollutants in a Changing World (2014) RFA Text | Recipients Lists
Research Category: Air , Climate Change

Objective:

Our overall goal is to improve our understanding of the effects of global change on future PM levels in the western US. Our specific objectives are the below.

Develop a novel application of Lagrangian air quality modeling using an ensemble of high resolution and bias corrected downscaled climate data based on the Multivariate Adaptive Constructed Analogs (MACA) method to provide comprehensive descriptions of PM changes due to meteorological changes.
Employ this method to examine the effects of the full range of climate projections upon PM levels associated with representative air quality issues in the western US, including wintertime stagnation events, summertime urban to rural transport cases, and wildfire impacts on rural and urban populations.
Incorporate changes in US anthropogenic emissions, background concentrations, and land use changes within the ensemble of Lagrangian modeling cases to assess the sensitivity of PM to these factors in the western US.
Integrate the results from these simulations to present the results in forms suitable to inform effective air quality management in the western US and elsewhere.

Progress Summary:

We have evaluated a Lagrangian air quality box-scale modeling framework (HYSPLIT-MOSAIC) against the DOE CARES field campaign conducted over Sacramento, CA in June 2010 as well as various AQS sites over California (during June 2010) and the Pacific Northwest (during spring 2018). Utilizing the MACA statistically downscaled climate data for the air quality research has been challenging because MACA provides a daily resolution (instead of hourly) near the surface (not vertically resolved), which caused major problems on running HYSPLIT (requiring 3-D hourly data) and running HYSPLIT-MOSAIC (requiring hourly data). To overcome this, we created climatological back-trajectories based on cluster analysis with the available reanalysis meteorological data, which we will apply to both present-day and future climate cases. To provide hourly meteorological conditions for emissions and chemical modeling, we reconstructed hourly MACA data using available reanalysis meteorological data for June 2005-2015. The reconstructed hourly MACA data compared to the observation reasonably well. With the CLM model, we have simulated the biogenic VOCs emissions from 2010-2017 over the western US. The simulated sensitive and latent heat fluxes were evaluated against 39 flux sites for a wide range of land cover types. We are currently investigating the impact of ENSO on biogenic VOCs emissions during 2010-2017.

Future Activities:

Applying the hourly construction approach to various locations and to longer periods. Developing another new reconstruction approach based on “machine-learning” in order to improve the hourly reconstruction and retrieving missing variables in MACA (e.g., PBL height)
Perform CLM simulations to understand the impact of future land use to biogenic VOCs emissions.
Applying our modeling framework to a longer period to simulate a climatological case. We will perform the present-day climate case first and evaluate our results against available long-term observations (e.g., AQS). After that, we will simulate future air quality scenarios such as summertime urban-rural transport, wildfires, and wintertime stagnation conditions with ensemble analysis using the MACA downscaled climate data.

Journal Articles:

No journal articles submitted with this report: View all 13 publications for this project

Supplemental Keywords:

Air quality, climate change, Lagrangian air quality modeling

Progress and Final Reports:

Original Abstract

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.