Shawn J. Roselle

Effects of biogenic emission uncertainties on regional photochemical modeling of control strategies

Abstract The sensitivity of regional ozone (03) modeling to uncertainties in biogenic emission estimates has been studied with the United States Environmental Protection Agencys Regional Oxidant Model (ROM). Photochemical oxidants in the northeastern United States were simulated for the period 2–17 July 1988, one of the most severe air stagnation episodes in the last decade. In the simulations, biogenic hydrocarbon emissions were adjusted by a factor of 3 to account for the existing range of uncertainty in these emissions. The impact of biogenic emission uncertainties on O 3 predictions depended upon the availability of NO x . In most cases, O 3 concentrations increased in response to increases in biogenic hydrocarbon emissions. However, in some extremely NO x -limited areas, increasing the amount of biogenic emissions decreased O 3 concentrations. Two control strategies were also examined in the simulations: (1) reduced anthropogenic hydrocarbon emissions, and (2) reduced anthropogenic hydrocarbon and NO x emissions. The simulations showed that controls of hydrocarbon emissions were more beneficial to the New York City area, but that combined NO, and hydrocarbon controls were more beneficial to other areas of the Northeast. For the most part, the preference for a combined strategy persisted across the range of uncertainty in biogenic emissions. There were some localized areas where the preference for control technique depended upon the assumed level of biogenic emissions.

Assimilation of Satellite Data in Regional Air Quality Models

In regional-scale air-pollution models probably no other source of uncertainty ranks higher than the current ability to specify clouds and soil moisture. Because modeled clouds are highly parameterized, the ability of models to predict the magnitude and spatial distribution of radiative characteristics is highly suspect and subject to large error. While considerable advances have been made in the assimilation of winds and temperatures into regional models (Stauffer and Seaman, 1990), the poor representation of cloud fields from point measurements at National Weather Service stations and the almost total absence of observations of surface moisture availability has made assimilation of these variables difficult if not impossible. Yet, the correct inclusion of clouds and surface moisture are of first-order importance in regional-scale photochemistry. Consider the following points relative to these variables.