1994
DOI: 10.1080/1073161x.1994.10467291
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Airshed Model Evaluation of Reactivity Adjustment Factors Calculated with the Maximum Incremental Reactivity Scale for Transitional-Low Emission Vehicles

Abstract: The California Air Resources Board recently adopted regulations for light-and medium-duty vehicles that require reductions in the ozone-forming potential or "reactivity," rather than the mass, of nonmethane organic gas (NMOG) emissions. The regulations allow sale of all alternatively fueled vehicles (AFVs) that meet NMOG exhaust emission standards equivalent in reactivity to those set for vehicles fueled with conventional gasoline. Reactivity adjustment factors (RAFs), the ratio of the reactivity (per gram) of… Show more

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Cited by 12 publications
(13 citation statements)
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“…The two classes of photochetnical models that have been used most extensively are chetnically detailed but phystcally si~npl~fied zero-dimensional box models (8-1 3) and more comprehensive, phystcally detailed, three-dimensional (3D) airshed models 110,11,[14][15][16][17]. The method currentlv used for react~vity quantification in California was developed by Carter (8), who used a box model, and is based on the SAPRC90 chemical mechanism (18) to quantify how an incremental change in the etnissions of a specific VOC \vould affect ozone.…”
mentioning
confidence: 99%
“…The two classes of photochetnical models that have been used most extensively are chetnically detailed but phystcally si~npl~fied zero-dimensional box models (8-1 3) and more comprehensive, phystcally detailed, three-dimensional (3D) airshed models 110,11,[14][15][16][17]. The method currentlv used for react~vity quantification in California was developed by Carter (8), who used a box model, and is based on the SAPRC90 chemical mechanism (18) to quantify how an incremental change in the etnissions of a specific VOC \vould affect ozone.…”
mentioning
confidence: 99%
“…Because of this, such models must have highly condensed chemical mechanisms. For example, the CB4 mechanism in the UAM model (the most widely used model in regulatory applications), uses only 11 model species to represent the hundreds of types of VOCs emitted, and the Lurmann, Carter, and Coyner (LCC) mechanism (Lurmann et al, 1987) in the CMU model (used in a number of alternative fuel assessments and other research applications [e.g., Russell et al, 1989Russell et al, , 1990McNair et al, 1992McNair et al, , 1994), is similar in its level of detail, though it uses somewhat different condensation approaches. Such mechanisms were developed and optimized to simulate current ambient mixtures, and were not designed for use in evaluating scenarios where the emissions speciation may change significantly.…”
Section: Chemical Mechanismsmentioning
confidence: 99%
“…LCC actually refers to two mechanisms, both developed by Lurmann et al (1987) as condensations of a more detailed mechanism developed earlier by Carter et al (1986a). The most condensed version is used in the CIT model by Russell and eo-workers in a number of assessments of alternative fuel use and VOC reactivity evaluations (McNair et al, 1992(McNair et al, , 1994Russell et al, 1989Russell et al, , 1990. The less condensed version was developed for use in single-cell models such as EKMA.…”
Section: Lurmann Carter and Coyner (Lcc)mentioning
confidence: 99%
“…The box model on which CARB relies uses Carter's mechanism with time-varying photolysis conditions and temperatures that [1][2][3][4][5][6] control the chemical reaction rates. The box model formulation assumes instantaneous mixing of time-varying emissions throughout a single cell with a variable mixing height.…”
Section: Carb Lev Regulations and Reactivity Adjustment Factorsmentioning
confidence: 99%
“…one fuel as another, and it is not clear how. best to account for these differences in [1][2][3][4] estimating the average composition of exhaust emissions. To assign the incremental reactivity values needed in Equation (l.l), CARB adopted the MIR scale.…”
Section: Carb Lev Regulations and Reactivity Adjustment Factorsmentioning
confidence: 99%