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ABSTRACT Numerous studies of ambient ozone ([O.sub.3]) in the Los Angeles (LA) area have found both increases and decreases in elevated [O.sub.3] levels on weekends, depending on location and year. [...]

Photochemical modeling has been used to determine the effect of fuels and vehicles on the urban ozone. Input data was lifted from the Auto/Air Quality Improvement Research Program (AQIRP). Multiday simulations were performed for gasolines in various AQIRP test matrices and for a methanol/gasoline blend. Among the gasoline changes which were recommended to reduce light-duty vehicles' role in ozone formation were olefin content and vapor pressure reductions and 90% distillation temperature.

The decoupled direct method (DDM) is an efficient and accurate way of performing sensitivity analysis to model inputs. As the impact of atmospheric particulate matter (PM) on human health and visibility became evident, the need to extend the DDM to PM sensitivity has grown. In this work, the DDM is implemented in the three PM modules employed in the Comprehensive Air-quality Model with extensions (CAMx): ISORROPIA for inorganic gas/aerosol partitioning, SOAP for secondary organic gas/aerosol partitioning, and RADM-AQ for aqueous-phase chemistry. The PM modules are complex and the DDM implementation is discussed in detail. Stand-alone tests are performed for each PM module in which first-order sensitivities computed by the DDM are compared to the traditional brute-force method (BFM). The DDM sensitivities are shown to be accurate and agree well with the BFM within the linear response range. The SOAP module showed nearly linear response for up to ±30% changes in concentration inputs. The RADM-AQ module showed moderately nonlinear response in some tests but first-order sensitivities accounted for most of the response for input changes up to ±20%. ISORROPIA shows greater deviation from linear response than the other PM modules and the near-linear range can be as restricted as ±10% changes in concentration inputs. Nonlinearity in ISORROPIA results both from the equations that describe thermodynamic equilibrium and the computational approaches within ISORROPIA that are employed to boost efficiency. [ABSTRACT FROM AUTHOR]

Two efficient methods to study relationships between particulate matter (PM) concentrations and emission sources are compared in the three-dimensional comprehensive air quality model with extensions (CAMx). Particulate source apportionment technology (PSAT) is a tagged species method that apportions concentrations of PM components to their respective primary precursors, e.g., sulfate is apportioned to SOx, nitrate to NOx, etc. The decoupled direct method (DDM) calculates first-order sensitivities of PM concentrations to model inputs. Both tools were applied to two month long (February and July) PM modeling episodes and evaluated against changes in PM concentrations due to various emission reductions. The results show that source contributions calculated by PSAT start to deviate from the actual model responses as indirect effects from limiting reactants or nonprimary precursor emissions become important The DDM first-order sensitivity is useful for determining source contributions only if the model response to input changes is reasonably linear. For secondary inorganic PM, the response is linear for emission reductions of 20% in all cases considered and reasonably linear for reductions of 100% inthe case of on-road mobile sources. The model response for secondary organic aerosols and primary PM remains nearly linear to 100% reductions in anthropogenic emissions.