API PUBL 4616-1994

$40.95

The Importance of Using Alternative Base Cases in Photochemical Modeling

Published By	Publication Date	Number of Pages
API	1994	359

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Description

Satisfactory photochemical model performance is apparently possible despite evidence suggesting significant biases in emissions estimates. This study assessed the influence of compensating modeling input errors on estimates of the effects of emission control scenarios. Specifically, a series of Urban Airshed Model (UAM) sensitivity studies have been carried out using simulations of two summer ozone episodes from the Southern California Air Quality Study (SCAQS) of 1987. These episodes were chosen because they provided the most comprehensive databases available at the inception of this study for supporting photochemical grid modeling. Existing simulations yielded inadequate performance, so it was necessary to identify UAM performance problems, implement appropriate modifications to model inputs, and assess the model's suitability for use in subsequent analyses. Plausible alternative conditions were established to define acceptable base cases; some alternative base cases were identified that provided a level of UAM performance comparable to the best achieved for the episodes. Several UAM sensitivity runs were made to determine whether the choice of base case had a significant influence on simulation results for hypothetical emission reduction strategies. The alternative base cases used in this study produced significant differences in estimates of the air quality benefits associated with hypothetical emission control scenarios. For example, one set of base cases indicated NO, controls would be counterproductive in reducing the estimated peak 03 concentration in part of the modeling domain; another base case suggested that such controls would yield almost no change in the peak value. These analyses provide a lower bound estimate of the uncertainty attending modeling results of the air quality benefits associated with emission control plans. It is strongly recommended that current photochemical modeling practice be extended to include such analyses. These efforts will help reduce the risk of focusing emission control efforts on the wrong precursors, underestimating control requirements needed to meet air quality goals, or incurring costs to implement unnecessary controls.

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