Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

Anthropogenic enhancements to production of highly oxygenated molecules from autoxidation

Metadata Updated: May 2, 2021

Atmospheric oxidation of natural and anthropogenic volatile organic compounds (VOCs) leads to secondary organic aerosol (SOA), which constitutes a major and often dominant component of atmospheric fine particulate matter (PM2.5). Recent work demonstrates that rapid autoxidation of organic peroxy radicals (RO2) formed during VOC oxidation results in highly oxygenated organic molecules (HOM) which efficiently form SOA. As NOx emissions decrease, the chemical regime of the atmosphere changes to one in which RO2 autoxidation becomes increasingly important, potentially increasing PM2.5, while oxidant availability driving RO2 formation rates simultaneously declines, possibly slowing regional PM2.5 formation. Using a unique suite of in situ aircraft observations and laboratory studies of HOM, together with a detailed molecular mechanism, we show that although autoxidation in an archetypal biogenic VOC system becomes more competitive as NOx decreases, absolute HOM production rates decrease due to oxidant reductions, leading to an overall positive coupling between anthropogenic NOx and localized biogenic SOA from autoxidation. This effect is observed in the Atlanta, Georgia urban plume where HOM is enhanced in the presence of elevated NO, and predictions for Guangzhou, China, where increasing HOM-RO2 production coincides with increases in NO from 1990 to 2010. These results suggest added benefits to PM2.5 abatement strategies come with NOx emission reductions and have implications for aerosol-climate interactions due to changes in global SOA resulting from NOx interactions since the pre-industrial era.

Datasets include links to CMAQ, F0AM, and WAM model code as well as the SENEX aircraft campaign data archive.

Files include data shown in Figure 3 (C10H18O7 HOM from SENEX), data used to construct Figure 4 and S10 (CMAQ model predictions of oxidants and intermediate species), additional supporting data in Figure S11 (SENEX C10 HOM species), and observed particle and gas composition from SOAFFEE laboratory experiments (Figure S6 and elsewhere).

This dataset is associated with the following publication: Pye, H., E. D’Ambro, B. Lee, S. Schobesberger, M. Takeuchi, Y. Zhao, F. Lopez-Hilfiker, J. Liu, J. Shilling, J. Xing, R. Mathur, A. Middlebrook, J. Liao, A. Welti, M. Graus, C. Warneke, J.d. Gouw, J. Holloway, T. Ryerson, I. Pollack, and J. Thornton. Anthropogenic enhancements to production of highly oxygenated molecules from autoxidation.. PNAS (PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES). National Academy of Sciences, WASHINGTON, DC, USA, 116(14): 6641-6646, (2019).

Access & Use Information

Public: This dataset is intended for public access and use. License: See this page for license information.

Downloads & Resources



Metadata Created Date November 12, 2020
Metadata Updated Date May 2, 2021

Metadata Source

Harvested from EPA ScienceHub

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date May 2, 2021
Publisher U.S. EPA Office of Research and Development (ORD)
Data Last Modified 2019-01-29
Public Access Level public
Bureau Code 020:00
Schema Version
Harvest Object Id 4f5fca9d-e51a-416c-8dba-1d0294b71509
Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
Harvest Source Title EPA ScienceHub
Program Code 020:094
Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
Related Documents
Source Datajson Identifier True
Source Hash ecd0ba8ccb844a0539b1056f714b8ee909ae871b
Source Schema Version 1.1

Didn't find what you're looking for? Suggest a dataset here.