DEPENDENCIES AND SENSITIVITY OF TROPOSPHERIC OXIDANTS TO PRECURSOR CONCENTRATIONS OVER THE NORTHEAST UNITED-STATES - A MODEL STUDY

Citation
R. Mathur et al., DEPENDENCIES AND SENSITIVITY OF TROPOSPHERIC OXIDANTS TO PRECURSOR CONCENTRATIONS OVER THE NORTHEAST UNITED-STATES - A MODEL STUDY, JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 99(D5), 1994, pp. 10535-10552
Citations number
30
Categorie Soggetti
Metereology & Atmospheric Sciences
Volume
99
Issue
D5
Year of publication
1994
Pages
10535 - 10552
Database
ISI
SICI code
Abstract
Atmospheric distribution of photochemical oxidants has been a subject of interest and concern not only because of their deleterious effects on human health and vegetation but also because of their crucial role in determining the chemical composition of the atmosphere. Several imp ortant issues related to the distribution and production of photochemi cal species are examined through an analysis of results obtained from applications of a comprehensive three-dimensional regional scale photo chemical model over the Northeast United States. The Regional Oxidant Model (ROM) is used to simulate the response of various photochemical species to specific anthropogenic emission strategies involving NO(x) and hydrocarbon reductions for an episodic period during July 1988. Do main and temporal averages of predicted concentrations are examined fo r various species. Their relative influence on oxidant chemistry over the modeled domain is investigated. Further, spatial distributions of O3 with respect to those of NO(x), NO(y) and hydrocarbons over the mod eled domain are examined and the variations in O3 levels for different chemical regimes classified by characteristic NO(x)/reactive organic gases and NO(x)/NO(y) ratios are investigated. Temporal trends in doma in-averaged concentrations indicate that the model replicates the expe cted diurnal trends in species concentrations. The relative benefits o f reductions in NO(x) and hydrocarbon emissions on predicted O3 levels are also examined. In general, for this modeled domain, reductions in NO(x) emissions with or without reductions in hydrocarbon emissions h ave more impact on reducing predicted O3 levels compared to reductions only in hydrocarbon emissions.