Improved Prediction of the Vertical Profile of Atmospheric Black Carbon: Development and Evaluation of WRF-CMAQ

EPA Grant Number: R835041
Title: Improved Prediction of the Vertical Profile of Atmospheric Black Carbon: Development and Evaluation of WRF-CMAQ
Investigators: Carlton, Annmarie
Institution: Rutgers, The State University of New Jersey
EPA Project Officer: Hunt, Sherri
Project Period: September 1, 2011 through August 31, 2014 (Extended to February 29, 2016)
Project Amount: $449,916
RFA: Black Carbon's Role In Global To Local Scale Climate And Air Quality (2010) RFA Text |  Recipients Lists
Research Category: Global Climate Change , Climate Change , Air

Description:

Advanced model descriptions of cloud processing of atmospheric pollutants will improve predicted vertical profiles of optically active particulate carbon (e.g., black carbon (Be) and other short lived climate forcers (SLCFs) such as "brown" carbon). More accurate prediction of vertical profiles will improve raditative transfer calculations (because scattering is altitude dependent) and better describe long-range pollution transport. Effective control strategies for climate and air quality can be designed using models, often used in regulatory applications (e.g., CMAQ) when they better represent the vertical structure of atmospheric pollution.

Objective:

1) Develop condensed chemical and/or meteorological mechanisms suitable for inclusion in 3-dimensional photochemical transport models (CTMs), to simulate cloud production of particulate "brown" carbon (BCcld) from a variety of organic precursors, 2)Identify conditions and precursors that have the largest impact on BCcld for climate (e.g., those for which the vertical distribution is the most sensitive) and for air quality. Conduct CMAQsimulations for the continental U.S. using different emissions to simulate a variety of control strategies to estimate the controllable fraction of BCcld and assign relative importance to individual source sectors. 3) Incorporate findings into the coupled Weather Research Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model to be released to the public in Fall 2011. Explore the magnitude and change in radiative calculations when the vertical profiles of BC and other SLCFs change as a consequence of more robust representation of cloud processing.

Approach:

1) Update existing chemistry and chemistry/cloud models to include newly-identified compounds likely to contribute to BCcld) , (e.g., methacrolein, glycoaldehyde, phenols. Conduct a variety of cloud parcel model simulations to develop mechanisms with condensed chemistry and/or meteorological inputs, suitable for incorporation into CTMs. 2) Use the updated mechanisms in CMAQ's aqueous chemistry module (aqchem.F) to explore the sensitivity of BCcld formation to anthropogenic pollution by individual source sector and calculate the controllable fraction. Analyze the results separately for climate and air quality effects. 3) Conduct coupled WRF-CMAQ simulations for the continental U.S. and/or Northern Hemisphere with and without the expanded BCcld mechanism using base and new BC emission inventories developed from other STAR grantees funded by this call. Evaluate forcing predictions using existing data sources (e.g., IMPROVE and AERONET). All code developments will be open source and findings will be made widely available.

Expected Results:

1) more accurately characterize the atmospheric burden of BC/SLCFs and develop tools to quantify their effects by source sector (RFA goals #1,2,3). 2) Develop more accurate regulatory tools (e.g., CMAQ) evaluated with readily-available data sets and tools (e.g., AERONET, IMPROVE) to evaluate SLCFs amongst themselves and relative to long-lived green house gases (LLGHGs) (RFA goal #4).

Publications and Presentations:

Publications have been submitted on this project: View all 50 publications for this project

Journal Articles:

Journal Articles have been submitted on this project: View all 17 journal articles for this project

Supplemental Keywords:

atmospheric brown clouds, SLCFs, cloud processing, PM2.5,

Progress and Final Reports:

2012 Progress Report
2013 Progress Report
2014 Progress Report
2015 Progress Report
Final Report