Application of Model to Photochemical Smog in Los Angeles County in 1975
The general least cost-air quality model of Part I is characterized for the problem of photochemical smog in Los Angeles County in 1975. Emission levels are specified by average tons/day emissions of reactive hydrocarbons (RHC) and nitrogen oxides (NO,). Air quality, also two dimensional, is specified by the expected number of days per year that oxidant and nitrogen dioxide in Central Los Angeles exceed the California 1-hr state standards. The baseline for additional control policy is the 1975 emission level with the present federal new car control program and with other sources having the degree of control existing in 1971. The least cost of reaching various emission levels is found by applying linear programming to 23 major source types and 31 potential “add-on” controls. Expected 0 3 and NO2 levels are found as functions of emission levels using empirical-statistical air quality models. These results are combined to yield the least cost of attaining various 0 3 and NO2 levels in Central Los Angeles in 1975.
T h e specific air pollution problem to be investigated with the least cost control model is photochemical smog in Los Angeles County in 1975. Los Angeles County is selected as the region of study because a fairly complete source inventory is available for the County, mostly from the Los Angeles County Air Pollution Control District (APCD) (7). Photochemical smog, the main symptoms of which are eye irritation, plant damage, visibility reduction, and high concentrations of oxidizing gases such as 0 3 and NOz, is selected because it is generally considered to be the most damaging part of Los Angeles air pollution. Photochemical smog serves as a particularly good example because the model is general enough to incorporate nonlinearities in the relationship between air quality and emissions. 1975 is selected as a control date because it is the first target date of the Federal Clean Air Act.
Problem Definition Before the control model can be solved for this example, bounds for the problem which define the parameters in the model must be established. In particular, explicit emission and air quality vectors must be chosen. First, let us consider the question of an appropriate emission vector. Starting with the work of Haagen-Smit in the early 1950’s, 20 years of research on photochemical smog have established that it results basically from hydrocarbon (HC) and nitrogen oxide (NO,) emissions [Haagen-Smit ( 8 ) , Leighton ( 9 ) , Altshuller and Bufalini (IO)]. Hydrocarbons, or organic gases, are emitted during the use of organic fuels, such as gasoline, and organic solvents, such as those found in paints. NO, emissions result almost exclusively from combustion processes wherein some of the nitrogen and oxygen in the air combine. Other emitted contaminants-e.g., SO2 and CO, may take some part in the photochemical reactions, but HC and NO, are definitely the basic precursors of photochemical smog. Thus, for emissions, HC and NO, are chosen. Actually, the emission category, hydrocarbons, is very complex. It consists of a wide variety of organic gases with different degrees of photochemical reactivity, ranging from nearly inert methane and propane to highly reactive olefins and aromatics. Photochemical reactivity is a measure of the 816
Environmental Science & Technology
potential of a HC to produce various photochemical smog symptoms when mixed with NO, and irradiated with sunlight. Reactivity can be measured according to several scales; HC consumption rate, NO, formation rate, ozone production, and eye irritation production are the principal ones, [Altshuller and Bufalini ( I O ) ] . The rankings according to these different scales are often inconsistent with one another [Altshuller ( I I ) ] , which adds to the complexity. Some allowance should be made for HC reactivity; it makes a significant difference to air quality whether a given reduction in HC emissions is obtained by controlling olefins or methane. Here, HC emissions will be actually specified by reactive hydrocarbons (RHC), using the Los Angeles APCD’s reactivity scale [Brunelle et al. (12) 19661. The emission vector is chosen. It is two-dimensional reactive hydrocarbons and nitrogen oxides. The next step is to select an air quality vector. For air quality indices, there are four major candidates: visibility reduction, eye irritation, ozone, and nitrogen dioxide. The Los Angeles APCD continuously monitors these four photochemical smog symptoms and reports air quality in terms of the number of days per year that state standards for each are exceeded. The visibility problem is very complex. It is one of the least understood aspects of photochemical smog. Visibility depends significantly on SO2 and particulate emissions as well as RHC and NO,. Since this work deals with only RHC and NO, emissions, and since it is so difficult to formulate air quality models for visibility, visibilit y reduction is not included in the air quality index even though it is a very important smog symptom. Using a statistical-empirical approach, this study has developed air quality models for eye irritation, ozone, and nitrogen dioxide which determine how the levels of these pollutants depend on RHC and NO, emission levels. These models are empirical models which estimate the relationship between pollution and emissions by using past atmospheric monitoring data. The results are stated in terms of the expected number of days per year that state standards are exceeded as a function of emission levels. Because of limitations in the availability of monitoring data, eye irritation and ozone results can only be obtained for mid-day in the Central Los Angeles area. To correspond to these results, NO2 air quality is also taken as that in Central Los Angeles. Since eye irritation is such a subjective measure of pollution and since the results for eye irritation turn out to be very similar to those for ozone, only NO2 and O 3 will be included in this discussion. Summarizing these remarks, the final choices for air quality indices are the number of days per year that state standards for 0 3 and NO1 are exceeded in Central Los Angeles. The least cost-air quality model can now be stated for the Los Angeles photochemical smog problem as follows: To find the minimum cost of reaching air quality levels PI0 and P2O Choose that minimizes
and
C = G(E1. E2)
/Q\
= the average (tons/day) emission level of RHC in Los Angeles County in 1975 = the average (tons/day) emission level of Ez NO, in Los Angeles County in 1975 = the expected number of days per year P 1 t h a t mid-day 0 3 exceeds the State standard(0.10 ppm for 1 hr) in Central Los Angeles = the expected number of days per year PP t h a t NO2 exceeds the State standard (0.25 ppm for 1 hr) in Central Los Angeles G(E1, Ez) = the minimum cost of reaching emission levels ( E l , E P ) , and F1(E1, E z ) , and F2(El, E P )= air quality as a function of emission levels
where E1
The solution to this problem now proceeds in three steps. First, the minimum cost of reaching various RHC and NO,
