Observation-Based Approaches to VOC Emissions Inventory Reconciliation And Control Strategies for Photochemical Smog

EPA Grant Number: R826238
Title: Observation-Based Approaches to VOC Emissions Inventory Reconciliation And Control Strategies for Photochemical Smog
Investigators: Henry, Ronald C.
Current Investigators: Henry, Ronald C. , Chang, Yu-Shuo
Institution: University of Southern California
EPA Project Officer: Shapiro, Paul
Project Period: February 1, 1998 through January 31, 2001 (Extended to August 31, 2003)
Project Amount: $441,574
RFA: Ambient Air Quality (1997) RFA Text |  Recipients Lists
Research Category: Air , Air Quality and Air Toxics


The three-year project will develop new methods to reconcile Volatile Organic Compound (VOC) observations with emissions inventories, and develop new techniques to derive empirical relationships between VOCs and photochemical ozone. The emphasis is on ozone but the methods should also be applicable to fine particles. The basis of the approach is multivariate receptor modeling of Volatile Organic Compound (VOC) and related data from the Photochemical Assessment Monitoring Stations (PAMS) network. Multivariate receptor modeling is the preferred method for this study because of the richness of the PAMS database in species and number of observations and the model's ability to deduce the number of sources and associated compositions directly from the data. This is especially important for VOC receptor modeling since adequate source compositions from source sampling are almost non-existent. Even transportation source compositions are constantly changing because of reformulated fuels and seasonal changes. Multivariate receptor models also automatically take changes in composition caused by chemical reactions into account.


The PAMS and all other data will be taken from the AIRS database or from special studies such as the COAST project. Receptor models do not directly estimate source emission rates as given in the inventories. Special methods are needed to relate the source contributions estimated by the receptor model and emission rates. (Henry et al., Proceedings of the National Academy of Sciences, 94:6596-6599). Direct reconciliation of VOC observations and inventories for transportation and other area sources is more difficult. The comparison is improved by using multivariate receptor modeling to separate vehicle related CO and NOx from emissions of other sources. The results of the VOC receptor modeling will also be used to identify possible changes in source profiles due to chemical reactions.

Expected Results:

Finally, the VOC source contributions from receptor modeling will be used to derive statistical relationships with ozone concentrations with an emphasis on developing control strategies for the existing and proposed standards. The results of this project should be improved risk assessment and management of ambient exposure to ozone and fine particles based improved source-oriented modeling using much-improved VOC emissions inventories and alternative empirical models of the dependence of ozone and fine particle loadings on VOC.

Publications and Presentations:

Publications have been submitted on this project: View all 15 publications for this project

Journal Articles:

Journal Articles have been submitted on this project: View all 14 journal articles for this project

Supplemental Keywords:

air, tropospheric, ozone, particulates, VOC, modeling, receptor-based, observational, PAMS, emissions., RFA, Scientific Discipline, Air, particulate matter, Environmental Chemistry, mobile sources, tropospheric ozone, Atmospheric Sciences, Ecological Risk Assessment, Ecology and Ecosystems, photochemical assessment monitoring, phototchemical modeling, fine particles, multivariate receptor modeling, air quality models, ambient air, ambient measurement methods, ozone, VOCs, photochemical smog, photochemistry, air sampling, atmospheric transport, emissions inventory, Volatile Organic Compounds (VOCs), measurement methods , atmospheric chemistry, chemical speciation sampling, fine particle formation

Progress and Final Reports:

  • 1998
  • 1999
  • 2000 Progress Report
  • 2001 Progress Report
  • 2002
  • Final Report