(6) Leatherland, T . M.; Burton, J. D.; Culkin, F.; McCartney, M. J.; Morris, R. J. Deep-sea Res. 1973,20,679. (7) Baker, C. W. Nature (London) 1977,270,230. (8) Fukai, R.; Huynh-Ngoc, L. Anal. Chim. Acta 1976,83,375. (9) Davies, I. M.; Graham, W. C.; Pirie, J. M. Mar. Chern. 1979, 7, 111. (10) Egawa, H.; Tajima, S. “Proceedings of the 2nd U.S.-Japan Expert Meeting,” Tokyo, Japan, Oct 1976. (11) Balley, G. E.; Gardner, D. Water Res. 1977,II, 745. (12) “Official Methods of Analysis of the Association of Analytical Chemists”; Washington, 1975; p 454.
(13) Wittenbach, A.; Bajo, S. Anal Chem. 1975,47, 1813. (14) Burton, J . D.; Leatherland, T . M. Nature (London) 1971,231, 440. (15) Baker, C. W. Nature (London) 1977,270,230. (16) Vostal, J. “Mercury in the Environment”; Friberg, L., Vostal, J., Eds.; CRC Press: Cleveland, OH, 1972; p 25.
Received for review August 26,1980 Accepted March 17,1981. This work was supported i n part by grants from the Ministry of Education, Japan.
Effect of NO, Emission Rates on Smog Formation in the California South Coast Air Basin David P. Chock,* Alan M. Dunker, Sudarshan Kumar, and Christine S. Sloane Environmental Science Department, General Motors Research Laboratories, Warren, Michigan 48090
The effect of changes in NO, emissions on downwind regions of the California South Coast Air Basin was investigated with the ELSTAR trajectory model. Smog formation was simulated in air parcels which originated near Los Angeles in the early morning, passed through the San Gabriel Valley, and arrived at or near San Bernardino in the mid to late afternoon on days of moderate to high ozone. With nonvehicular emissions held fixed at the 1973 levels, the planned reduction in motor vehicle emissions is predicted to result in reduced atmospheric concentrations of CO, NO, NO2,03, PAN, and “03 along the air parcel trajectories. However, when the hydrocarbon emissions are held fixed at a projected future level, a decrease in NO, emissions will result in a decrease in NO2 concentrations, but an increase in 0 3 and PAN concentrations at all positions along the trajectories. H
I. Introduction There is a consensus in the technical community that hydrocarbon (HC) control is required to reduce photochemical oxidants. However, there has been no such consensus as to the role of oxides of nitrogen (NO,) ( I ) . I t has been known for some time that NO, both inhibits and promotes smog formation (2). Recently, there has been a controversy concerning the effect that reducing motor vehicle NO, emissions will have on cities such as Riverside and San Bernardino, which are downwind of the Los Angeles metropolitan area. To study this problem, we have utilized a simulation approach. There are two simulation tools that can be used to predict the effect of emissions changes on air quality. These are laboratory (or smog-chamber) simulations and mathematical simulations. Both tools have been used with specific applications to determine the effects of NO, emissions changes on smog in the South Coast Air Basin of California. The smogchamber simulation has been presented by Glasson ( 3 ) .The present paper describes a mathematical simulation. While smog chambers have provided the backbone of our current understanding of air pollution photochemistry, they encounter difficulties in simulating many complex aspects of ambient smog formation. In particular, the spatial and temporal variations of primary pollutant emissions, mixing height, transport, and diffusion cannot be simulated satisfactorily in smog chambers. Indeed, mathematical simulation is an attempt to circumvent these difficulties by coupling the knowledge of photochemistry gained from laboratory studies with a detailed representation of the emissions and dispersion which occur in the real world. 0013-936X/81/0915-0933$01.25/0 @ 1981 American Chemical Society
To answer the specific question of how future motor-vehicle NO, emissions affect smog in the downwind areas of the California South Coast Air Basin, we have employed the ELSTAR (Environmental Lagrangian Simulator of Transport and Atmospheric Reactions) model ( 4 , 5 ) .ELSTAR was developed and tested by using the data base provided by the 1973 Los Angeles Reactive Pollutant Program (LARPP). In section 11, a brief description of the model will be presented. The trajectory selection, emissions inventory, and the initial conditions will be described in section 111. The availability of a 1973 emissions inventory as well as the LARPP measurements (useful in providing certain meteorological information and as a guide in determining certain initial conditions) prompted us to choose 1973 for our base-case study. The model predictions for the base case were compared with interpolated observed values before future scenarios were considered. Recently, the California Air Resources Board (CARB) estimated the lifetime average emissions for 1983 and subsequent model vehicles (6). Two sets of average emissions were estimated: the first set was based on the CARB’s proposed pollution control program for post-1982 vehicles; the second set was based on the 1983 Federal emission standards. We chose as one future scenario the vehicle lifetime average emissions projected for CARB’s proposed pollution control program. Our second scenario is the same as the first except that we chose the NO, vehicle emissions projected for the less-stringent Federal standard. Comparing the model results for these two scenarios indicates the effects of NO, emissions changes on smog formation. The results of the base-case and scenario studies are presented in section 111,which is followed by a Discussion section.
II. M o d e l D e s c r i p t i o n A detailed description of the formulation, development, testing, and usage of the ELSTAR model is available elsewhere ( 4 , 5 ) .For completeness, a very brief description of the model is included here. The ELSTAR model simulates photochemical reactions of air pollutants in a column of air moving along a trajectory. A trajectory is determined by the model based on surface wind measurements. The model then calculates the vertical eddy diffusivities within the mixed layer along the trajectory, based on vertical temperature profiles, surface temperatures, and assumptions about the vertical gradients of wind and temperature. The diffusivities are further assumed to follow Volume 15, Number 8, August 1981
933
surface layer similarity, up to no more than one-tenth of the mixing height, and to follow a cubic polynomial between the mixing height and the surface layer height. Since the model does not take into account vertical wind and vertical wind shear, its application should be confined to a daytime, nonstagnant, convective period over relatively smooth terrain. The model also ignores horizontal diffusion, so it is primarily useful in regions where horizontal concentration gradients are not large. The model determines average temperature and stability categories for the elevated layer (above the surface layer) along the trajectory. In addition, it calculates ultraviolet (UV) sky-clearness ratios if UV-radiation data are available. The stability categories, average temperatures (over the lowest 100 m), and wind speeds are used to help determine the heights and entrainment within the air parcel of plumes from elevated point sources. Column-averaged temperatures and UV skyclearness ratios are used to determine certain chemical reaction rate constants. The emissions input for the model is divided into two parts: surface area sources and elevated (more than 20 m above ground) point sources. The former is further divided into mobile and stationary sources. For each emissions source, one prescribes the emission rates of total hydrocarbons (THC), nitric oxide (NO), nitrogen dioxide (NOz), carbon monoxide (CO), and sulfur dioxide (S02) as functions of time of day. Only six reactive classes of THC actually participate in the photochemical reactions. The six classes are the following: paraffins (PA), higher alkenes (ALKE), aromatics (AR), higher aldehydes (RCHO), formaldehyde (HCHO), and ethylene (CzHd). Methane is considered photochemically inert and is excluded from the classification. The composite area emissions are assigned to fixed-area grids. As the air parcel moves from one grid to the next, new surface emissions are picked up. To avoid sudden changes in the emissions picked up by the air parcel, the emissions within the parcel are smoothed as a function of time. The smoothing, however, conserves the mass of emissions. A fixed parcel area, equal to the area source grid size, is assumed for estimating the elevated plume entrainment within the parcel. The apportionment of the plume material into different vertical cells of the air parcel is based on a Gaussian distribution (with ground reflection) for the material on a vertical plane across the plume axis. The chemical reaction mechanism ( 4 ) consists of 64 reaction steps involving 39 chemical species and free radicals. SO2 is oxidized to sulfate without significantly influencing the rest of the photochemical reactions. Its input value is needed only if sulfate formation is of interest to the investigator. The lumped parameter assumption is used to characterize the reactivity of different hydrocarbons. Photolyses of nitrous acid, NOz, HCHO, and RCHO have UV-dependent rate constants, while the rates of dissociation of dinitrogen pentoxide, peroxynitric acid, and peroxyacetyl nitrate (PAN) are temperature-dependent. ELSTAR also allows for inclusion of sinks, such as dry surface deposition. In particular, deposition velocities are prescribed for ozone ( 0 3 ) and NOz. ELSTAR divides the air column into several vertical cells and assumes zero diffusive flux boundary conditions at the top and the bottom of the air column. The resulting system of ordinary differential equations is solved by using a Geartype algorithm. This is a tremendous advantage because of the algorithm’s ability to handle stiff equations which result from the wide range of reaction rate constants. ELSTAR’s requirements for computer core space and execution time are significantly less than those of grid models. However, like the grid models, because of the lack of concentration measurements for most chemical species, estimations are required in specifying the initial conditions. 934
Environmental Science & Technology
III. Model Inputs The availability of the weekday emissions data and the LARPP measurements suggested that 1973 would be a logical choice for our base-case study. Because vertical profiles of many reactive pollutants taken during LARPP could help us construct part of the initial condition, we wanted at least one of the base-case days to fall on a LARPP day. Our desire to choose only high-ozone and average-ozone days further restricted us to the summer or early fall season. Meteorological Inputs. Extensive hourly surface wind and temperature data for the period of July-October 1973 were acquired from the South Coast Air Quality Management District. Low-level wind and temperature sounding data for Los Angeles Tnternational Airport (LAX) and El Monte (ELM) were acquired from the National Climatic Center. To assess the effect of NO, reductions on air quality in the eastern part of the Basin, which is downwind of the Los Angeles Metropolitan area, we selected trajectories which arrived at or near San Bernardino by mid and late afternoon. San Bernardino was chosen as the destination because of its generally high observed ozone concentrations. The selected trajectories should originate within the Los Angeles Basin a t 0700 PST to allow for the inclusion of rush-hour emissions within the metropolitan area. They should also arrive a t or near San Bernardino between 1400 and 1700 PST. Trajectories along the San Gabriel Valley were investigated since this is probably the most frequent path for air parcels reaching San Bernardino in the summer (7). Moreover, the Valley is relatively flat and is wide enough so that the ELSTAR model should be applicable. Additional passages along the Santa Ana Canyon or over the Puente Hills may also be significant. However, air parcels along the Santa Ana Canyon path will reach Riverside but are likely to be channeled down the San Gorgonio Pass to the southeast, thus bypassing San Bernardino (see Figure 1).Trajectories traversing the Puente Hills tend to involve highly convective conditions characterized by low ozone concentrations (8).The rough terrain along these passages also precludes the applicability of ELSTAR. After a preliminary screening during which many forward and backward trajectories were investigated, two trajectories were selected. One was on October 15, a moderate-ozone day, and one was on July 31, a high-ozone day. These two trajectories were used for the base-case and scenario studies. The two trajectories for October 15 (101517) and July 31 (073115) are shown in Figure 1.Trajectory 101517 originated near Downey, skirted the northern edge of the Puente Hills, and arrived near San Bernardino at 1700. October 15 was one of the LARPP days, so both UV-radiation data and the early morning temperature sounding near Downey (which is closer to the trajectory origins than LAX) could be used in our study. In addition, there were ground and elevated measurements of HC species, NO, and NO2 in the late morning, and these were useful in specifying the initial conditions for these chemical species. Trajectory 073115 arrived near San Bernardino at 1500. On this day, earlier trajectories tended to be pushed northward into the Cajon Pass, whereas later trajectories meandered excessively in the Los Angeles Basin so that their courses at a later time became very difficult to predict. On the morning of October 15, there was a thin (-100 m) but very intense (1‘C/lO m) elevated inversion layer (the base being 250 m above ground) and a thick near-adiabatic layer above 500 m. The surface temperature along the trajectories increased rapidly to as high as 35 O C by 1300, whereupon the mixing height rose rapidly to a height of 800 m. The UV skyclearness ratios ranged from 0.8 a t 0700 to 1.0 at 1500. On July 31, the temperature soundings at ELM at 0530 and 1230 were used for the trajectory. The mixing height increased
Pasadena
x
x
tor Anqeler
’/
1
’
POllOlld
x
plco
Rivera
x
SAN GMGONlO PA)!
/
x
/
/
/
/
,
Figure 1. Trajectories for October 15 and July 31, 1973. Trajectory 101517 (solid line) started at 0700 and arrived near San Bernardino at 1700. Trajectory 0731 15 (dotted line) started at 0700 and reached San Bernardino at 1500. The dark circles correspond to the locations of the trajectory point on the hours. The crosses represent existing air quality monitoring stations.
rapidly and reached 1120 m by 1300. Mixing was also vigorous. The UV sky-clearness ratios were assumed to increase gradually from 0.8 a t 0700 to 1.0 at 1400. Emissions Inventory. Both the area source and elevated point source emissions inventories of HC, NO, NO2, and CO for the South Coast Air Basin for the years 1973-1974 were prepared by Environmental Research and Technology, Inc. (9),on the basis of data provided by Federal, State, and local governments and their contractors. The grid size for the area sources is 2 X 2 km2. The inventories cover an area of 130 X 86 km2, extending from Malibu Beach in the west to San Bernardino in the east, and from Laguna Beach in the south to San Fernando in the north. The area sources consist of surface street traffic, freeway traffic, airports, and 42 other categories. The elevated point sources include power plants, refineries, steel mills, etc. The plumes from these tall sources expand and may overlap and be entrained into the air parcel. The complex chemistry of the model requires emission inputs of NO,, CO, and the six HC classes: PA, ALKE, AR, RCHO, HCHO, and C2H4. SO2 emissions were not available to us and were not included in our present study. The diurnal variations of the above inputs from an elevated point source and from each source category within each area grid were determined from the emissions inventory. A summary of the total emission rates for the South Coast Air Basin for the 1973 base case is presented in Table I. The base-case study allowed us to compare the model predictions with interpolated observed values. Once satisfactory agreement was established, the effects of NO, emissions changes could be investigated. In order to evaluate the impact of different NO, emission standards on smog formation, two scenarios were considered. For both scenarios, the following emission rates were held fixed: 1.77 g/mi for exhaust HC, 0.17 g/mi for evaporative HC, and 13.1 g/mi for CO. They are the CARB’s projections of the lifetime average emission rates of the vehicle fleet initially meeting the CARB-proposed 1983 emission standards. (The lifetime average emissions would be realized after a vehicle
turnover period of -10 yr. The vehicle is assumed to meet the emission standard initially, with gradual deterioration thereafter. See ref 6.) For NO,, however, scenario A assumed an emission rate of 2.45 g/mi, whereas scenario B assumed an emission rate of 1.32 g/mi. Both values were again estimated by CARB. The former is the lifteime fleet-averaged emission estimate using the 1983 Federal emission standards (1.0 g/mi for passenger cars). The latter is the estimate if the CARBproposed 1983 standards (0.4 g/mi NO, for passenger cars) are implemented. Table I1 shows the lifetime average emissions for all road vehicles used in the scenarios. For comparison, the vehicle fleet-average emission rates for the base case are also included. T o apply the emission rates of the two scenarios in the model, we kept the relative proportions of the HC species the same as in the base case. Furthermore, the emission rates were adjusted by EPA speed correction factors (IO) for surface street traffic (assuming an average speed of 20 mi/h) and highway traffic (average speed of 55 mi/h). The speed correction factors for HC, CO, and NO, are 0.984, 0.986, and 1.009, respectively, for surface traffic, and 0.375, 0.433, and 1.560, respectively, for highway traffic. The summary of the emission rates for both scenarios is shown in Table I. Initial Conditions.Initial concentrations must be specified for each of the 39 chemical species in the model in each of the five vertical cells used. However, the initial concentrations for 19 species are computed from steady-state relationships. Furthermore, six species occur only as products in the reaction scheme. Their initial concentrations, which are set at low values, do not influence the photochemical reactions. Finally, SO2 and so4 were set initially at low, nominal concentrations and held constant throughout all of the simulations. These species were not considered in the present study, and the reactions involving them have little or no influence on the rest of the reaction mechanism (4). This leaves 1 2 species for which initial conditions must be chosen. HzO, OH, and HOz were assumed to have initial concentrations which did not vary with elevation. The initial Volume 15, Number 8, August 1981 935
Table 1. Summary of Emission Rates (tonslday) in South Coast Air Basin paraffins
higher alkanes
857.4 171.3
417.9
117.7
171.3
2.4 2.4
12.9 2.6 2.6
71.3
23.7 23.7
176.7 35.5 35.5
12.0
82.8 82.8
403.4 56.2 56.2
228.9 34.1 34.1
50.5
70.3
4.4
4.4
26.4
6.3 6.3
9.0 9.0
0.6 0.6
0.6 0.6
3.3 3.3
1329.1
387.5
111.6
71.1
22.1
2.7
4.2
111.8
69.7
1.7
8.9
1.2
4.9
0.9
102.3
157.9
2701.7 1668.4 1668.4
1104.0
281.5 143.3 143.3
327.0
39.7 26.3
24.9 10.8 10.8
102.8 22.8
1048.2 849.5 628.4
9757.5 1775.3 1775.3
surface street traffic base A B
freeway traffic base A B
other area sources elevated point sources total base A B
574.1 574.1
Table II. Average Lifetime Emissions (g/mi) for All On-Road Vehicles base case
scenario A
scenario B
exhaust HC evaporative HC
9.678
NO,
3.8
1.77 0.17 2.45
1.77 0.17 1.32
co a
78
THC classes higher aldehydes
THC
13.1
13.1
This value includes the contribution of evaporative HC.
concentration for HzO was determined separately for each day by taking the average of the 0700-1600 measurements of relative humidity and temperature a t the Long Beach and Los Angeles meteorological stations. For all simulations, the initial concentrations of OH and HOz were assumed to be and ppm, respectively. The final nine species are NO, NOz, CO, and the six HC classes. In the simulations with the 1973 emission rates, certain rules were followed in choosing the initial concentrations for these species: (1)CO, NO, and NO2 surface concentrations were fixed at the interpolated surface-station measurements. (2) For CO, NO, NOz, and the six HC classes, the initial concentration in any cell was never greater than the concentration of that species in any lower cell. (The initial 0 3 , which is computed from the steady-state relationship, increased in concentration with altitude.) (3) The RCHO initial concentration in each cell was taken to be the same as the HCHO initial concentration in that cell. (4) The AR initial concentration in each cell was assumed to be 20% of the corresponding PA initial concentration. (The average daily AR emissions are roughly 20% of the PA emissions on a mole basis.) (5) The initial concentrations of NO and ALKE were chosen to decline sharply with increasing elevation, whereas the initial concentrations of NO2, GO, HCHO, RCHO, CzH4, PA, and AR were chosen to decline gradually with elevation
formaldehyde
aromatics
124.5 124.5
26.3
ethylene
14.4 14.4
22.8
NOx
co
341.4 221.5 119.3
6890.0 1157.3 1157.3
336.6 257.8 138.9
2632.1 382.6 382.6
267.9
77.5
Table 111. Initial Concentrations (ppm) at 0700 PST for the Base Cases in 1973 speclesa
levelb
2
1
3
4
5
Trajectory 10 1517 NO
0.16
0.09
0.02
0.0015
0.0015
NO2
0.095 9.0 0.004
0.095 7.0 0.004
0.095
0.01 0.2 0.001
0.004 0.015
0.001 0.0003 0.007 0.070 0.014 0.031
0.01 0.2 0.001 0.001 0.0001 0.002 0.050 0.010 0.036
co HCHO RCHO ALKE
6.5 0.004
C2H4 PA
0.014 0.14
0.004 0.005 0.012 0.12
AR
0.028
0.024
03
0.002
0.004
NO
0.04
0.01
0.007
0.004
0.0015
NO2 HCHO RHCO ALKE
0.065 3.0 0.0022 0.0022 0.0083
C2H4 PA AR
0.0078 0.078 0.016
03
0.013
0.065 2.7 0.0022 0.0022 0.0028 0.0067 0.067 0.013 0.053
0.065 2.5 0.0022 0.0022 0.0011 0.0056 0.056 0.011 0.083
0.035 1.0 0.0006 0.0006 0.0002 0.0039 0.039 0.0078 0.091
0.014 0.8 0.0006 0.0006 0.0001 0.0011 0.028 0.0056 0.109
0.004 0.002 0.010 0.10 0.020 0.019
Trajectory 0731 15
co
H02 and OH were assigned the concentrations 1.0 X and 1 .O X lo-' ppm, respectively, at all elevations for each trajectory. HzO was assigned the concentration 14 500 ppm for trajectory 101517 at ali elevations and the concentration 16 200 ppm for trajectory 0731 15 at all elevations. Levels 1-5 correspond, in order, to the following elevations in m: 0,60,200,400, and 600 for trajectory 101517;0, 60, 200,550,and 1100 for trajectory 0731 15. The 0 3 concentration was calculated from the NO and NO2 concentrations via the photostationary-staterelationship. a
(4).
Within these restrictions, the initial concentrations of NO, NOz, CO, and the six HC classes were adjusted to provide the best agreement between the computed and observed surface concentrations of CO, NO, NO2, and 03. The simulations for October 15,1973, were run first because on this day some ground and elevated measurements of PA, CzH4, and ALKE were made at 1000 near Downey. Although these measurements were made a t a different location than 936
Environmental Science & Technology
the 1000 location on our trajectory, the measurements provided a check on our choice of initial conditions. Reasonable agreement was obtained between the computed concentrations of PA, CzH4, and ALKE at 1000 and the Downey measurements. As a first estimate of the initial concentrations of the six HC classes on July 31,1973, the corresponding initial concentrations on October 15 were scaled by using the 0600-0800 total
HC measurements at five stations near the origins of the trajectories. This proved to be an excellent estimate, and no additional changes were made to develop the HC initial concentrations for July 31. The initial concentrations for the base cases are shown in Table 111. The initial concentrations of NO, NOz, CO, and the six HC classes for the future scenarios were produced simply by scaling the initial concentrations for the 1973base simulations. The initial concentrations for each species were scaled according to the fractional change in the average daily emission rate of that species. In calculating the scaling factors, we included all sources in the emissions grid, both point and area sources. Both the initial NO and NO2 concentrations were scaled according to the change in the NO, emission rate. The initial concentrations of HzO, OH, and HOz were kept at the values used for the 1973 base simulations. (The initial concentrations of all other species were obtained again from the appropriate steady-state relationships.) This straightforward procedure completely defined the initial concentrations for the future scenarios.
IV. Results Base-Case Prediction. In order to compare the base-run predictions with observations, we first determined the concentrations along the trajectories by interpolating the air quality monitoring data available for those days. This was done as follows. At a specific hour, concentrations from no more than three air quality stations with locations closest to but no more than 25 km from the trajectory point were selected for weighted averaging. The weighting factor was the
inverse square of the distance between the station and the trajectory point. If a station was less than 2 km from the trajectory point, then only data from that station were used. Since the air quality data are hourly averages, the observed concentrations for the hour before and after the time of interest were averaged before weighting by the distance factor. Our procedure was very similar to that used by Lloyd et al. (4). The results of the above averaging procedure provide only a rough estimate of the true concentrations along the trajectory. Our comparison of predictions and interpolated concentrations is to assess the reasonableness of the model application, not to verify or validate the model. A comparison of the model's predictions with measurements made in moving air parcels is available elsewhere ( 4 ) . Figure 2a-d shows a comparison between the model's predictions (solid line) and the interpolated monitoring station measurements (circles) for 0 3 , NO, NOz, and CO for the base run of trajectory 101517. The surface concentrations which the model predicts are representative of the concentrations within the first 30 m above the ground. Agreement is good for 0 3 and CO, but less satisfactory for NO and NOz. The predicted NO2 values have the same qualitative behavior as the interpolated values, but the range is somewhat restricted. A dip in 0 3 and an increase in NO, at 1600 was due to the fact that the trajectory crossed the San Bernardino Freeway. For the base run of trajectory 073115, the agreement is good for NO and NO2 and acceptable for O3 and CO (Figure 3a-d). The model also predicted PAN concentrations along the trajectories. For the base runs, the predicted concentrations of less than 15 ppb are considered reasonable, although there 0 3 5 1 , , ,
Interpolated 0
I
I
0 0 0
1
0301 Scenario A - - -
........
025
fi
,
I
I
I
I
,
I
I
Interpolatedo 0 0 0 Base __ Scenario A - - - Scenario B
-
........
0.20
-.
0" 0.15
'
. ........
c
0~00' ' 0800 ' 1000 ' 1200 ' 1400 ls"O0 1800 ' Time (PST)
17.5 Interpolated 0 Scenario A Scenario B
---
........
0.25
1
O.O0
'
Scenario A --Scenario B
........
12.5
0
pn 0.20
0.05-
0 0 0
............ ' os00 '
t
...............: i
Id00 '
1200 ' 1400 ' 1600 ' 1800 '
'
5.0 2.5-
L ---.""-'-...
...... A " ...
i
-
-._. -'---"...........l.l.."
Time (PST)
Figure 2. (a)Surface O3concentrations for trajectory 101517. Ambient
measurements on October 15, 1973, were interpolated to obtain the open circles (see text). The concentrations calculated for the base case correspond to the 1973 emission inventory. The concentrations calculated for scenario A correspond to reducing the fleet average motor vehicle emissions to 1.77 g/mi HC, 2.45 g/mi NO,, and 13.1 g/mi CO. The concentrations calculated for scenario B correspond to reducing the fleet average motor vehicle emissions to 1.77 g/mi HC, 1.33g/mi NO, and 13.1 g/mi CO. (b) Surface NO concentrations for trajectory 101517. (c)Surface NOp concentrations for trajectory 101517. (d) Surface CO concentrations for trajectory 101517. Volume 15, Number 8, August 1981 937
are no atmospheric data for comparison here. The results are shown in Figures 4 and 5 for the two trajectories. The overall performance of the model for these two trajectories should be considered satisfactory in view of the complexity of the phenomena that we are simulating. Future Predictions. The results for scenarios A and B along the two trajetories are shown in Figures 2-5. Under either future scenario, the maximum concentrations of 03,NO2, CO, and PAN dropped substantially from the base cases. The maximum concentrations of NO dropped substantially from the base cases for scenario B but dropped only slightly for scenario A. CO concentrations for both scenarios are identical, as expected. Both NO and NO2 for scenario A are higher than for scenario B throughout the duration of each trajectory. 0 35
Also, NO and NO2 for both scenarios are lower than for the base cases in the morning. In the afternoon, the very high O3 concentrations in the base cases rapidly convert NO to NO2 so that the NO levels in the base cases may actually be lower than those in the scenarios. The 0 3 concentrations in scenario B (with the lower NO, emission) are actually higher than those in scenario A throughout the trajectories. Moreover, in the morning, the O3 concentrations in scenarios A and B can be even higher than those in the base cases. This is clearly because more NO is available to titrate 0 3 in the base cases. From smog-chamber studies ( 3 )one might expect to see a crossover in 0 3 levels between the two scenarios. Since the HC emission is the same in both scenarios, the higher NO, emis0 35
nI -r- -
1 -
Scenario A Scenario B
--O 0 325O I
0.00
1
"
0800 l o o 0
'
I
"
1200 1400 1600
-
Time (PST)
----r--
T -7--7-
1800 7-7 7
Interpolate& o o 0 Base - .Scenario A - - Scenario E
0 25 0.20
N
p
7 7 -
Interpolated. 0 0 0 Ease __ Scenario A - - Scenario B
0.25
E,
7 7 -
---7--7---7
- - 7 l - -
0.15
.
............ L
OS00 1Mx) 1200 1400 1600
O'O0
I
1-7-7-
I
I
v
I
,
,
I
I
I
Oe'00
' ldoo ' 1 2 0 0 ' 1400 1600
I
I
Interpolated. 0 0 o Base Scenario A - - . Scenario E
12 5
pI
-g
10.0
8
7.5
0
i
0
25
1 - 1 - d
O'OOL-'
I
1800
Time (PST)
1800
Time (PST)
Figure 3. (a)Surface O3concentrations for trajectory 0731 15. The symbols and scenarios are described in the caption to Figure 3a. (b) Surface NO concentrations for trajectory 0731 15. (c)Surface NO2 concentrations for trajectory 0731 15. (d) Surface CO concentrations for trajectory
0731 15.
150-
Base scenario^ Scenario B
-
150-
___
-% l o o -z
-
8100-
2
75-
50-
25-
25.
u--
0800
loo0
- - - - -1- - - - -i - -
-
1200
1400 1600
L
1800
Time (PST)
Figure 4. Surface PAN concentrations for trajectory 101517. The scenarios are described in the caption to Figure 3a.
938
75-
50-
00
___
125-
125-
f
Base __ ScenarioA Scenario E
Environmental Science & Technology
j-,, I r ,
O0
0800
loo0
1200
,
1 4 0 0 ' 1 6 0 0 ;E00
Time (PST)
Figure 5. Surface PAN concentrations for trajectory 0731 15 The scenarios are described in the caption to Figure 3a.
sion (scenario A) might slow down the O3 formation initially but increase the O3peak downwind. However, no such crossover occurred within the time period of any of the trajectories. We expect that this is at least partly due to the continuous injection of fresh NO, emissions along the trajectories. Because of the lack of a crossover point in the period when photochemistry was active, these results suggest that a most stringent NO, control strategy could lead to an increase of the 0 3 level throughout the South Coast Air Basin. The PAN concentrations in scenario B are also higher than the PAN concentrations in scenario A (Figures 4 and 5). Thus, reductions in NO, emissions (from scenario A to B) actually increased PAN concentrations. The similar behavior of O3 and PAN in response to changes in NO, emissions was also observed in the smog-chamber simulation (3). A check of the model predictions shows that, with the HC input fixed, increasing NO, input increases NO2, which depletes the OH radicals needed to convert PA to RCHO and subsequently to RC03 (acylperoxy radical, a precursor of PAN). The nitric acid predictions of the model are also of interest. Unfortunately, there were no nitric acid measurements available during the development of the model, so the validity of the nitric acid predictions is open to question. Nevertheless, the nitric acid predictions of the model show that either of the future scenarios will cause substantial reductions in nitric acid. The nitric acid concentrations for trajectory 073115 as it arrived near San Bernardino a t 1500 were 30 ppb in the base case, 9.9 ppb in scenario A, and 10.9ppb in scenario B. In fact, the nitric acid predictions of the two scenarios are essentially the same for each of the trajectories. In addition to the results discussed above, we have also run the model for two scenarios with even lower emission rates for motor vehicles (11).For scenario A’, the fleet average motor vehicle emissions were 0.41 g/mi HC, 1.0 g/mi NO,, and 7.0 g/mi CO. For scenario B’, the fleet average motor vehicle emissions were 0.41 g/mi HC, 0.4 g/mi NO,, and 7.0 g/mi CO. Essentially, we assumed in these scenarios that there was no deterioration in the motor vehicle emission rates. The results for scenarios A’ and B’ are qualitatively the same as the results for scenarios A and B and lead to the same conclusions regarding the effects of changing NO, emissions from motor vehicles. The O3 and PAN concentrations for scenario A’ are actually higher than the respective concentrations for scenario A (for example, for trajectory 073115, O3 and PAN at 1500 are 0.09 ppm and 0.5 ppb, respectively, for scenario A, and 0.10 ppm and 0.6 ppb, respectively, for scenario A’), and the NO, NO2, GO, and “ 0 3 concentrations calculated for scenario A’ are lower than the respective concentrations calculated for scenario A. These relationships also hold for the concentrations computed for scenarios B and B’ (again for trajectory 073115, 0 3 and PAN at 1500 are 0.13 ppm and 1.5 ppb, respectively, for scenario B, and 0.14 ppm and 2.2 ppb, respectively for scenario B’). A third trajectory was also selected in our base-case and scenario studies. The results are in agreement with those described above.
V. Discussion In summary, the model predictions indicate that with nonvehicular emissions held fixed (at the 1973 level) future motor vehicle emissions will result in reduced atmospheric concentrations of CO, NO, NO2,03, PAN, and H N 0 3 along a typical air parcel trajectory in the California South Coast Air Basin. For O3 and PAN, this results mainly from the reduction in HC emissions. However, when HC emissions are held fixed at a projected future level, then a decrease in NO, emissions will result in a decrease in NO2 concentrations but an increase in O3 and PAN concentrations. The effect on H N 0 3 is less definitive. No crossover in the 0 3 concentration was observed between the two scenarios studied, probably due to the continuous emissions of NO, along the air parcel trajectories. Note Added in Proof: There is an error in the existing ELSTAR program. The coefficient of the PAN decomposition rate should have been 1.17 X 1018, not 1.17 X This error has been corrected in this report. Acknowledgment
We thank P. H. Berzins and R. W. Herrniann for their invaluable help in modifying and running the ELSTAR program and L. G. Anderson, J. M. Heuss, and W. A. Glasson for useful discussions. Literature Cited (1) International Conference on Oxidants, 1976; “Analysis of the Evidence and Viewpoints. Part VIII: The Issue of Optimum Oxidant Control Strategy”; EPA Publication 600/3-77-120, Dec 1977. (2) Glasson, W. A.; Tuesday, C. S. Enuiron. Sei. Technol. 1970,4, 37. (3) Glasson, W. A., to be submitted for publication. See also ref 11.
(4) Lloyd, A. C.; Lurmann, F. W.; Godden, D. K.; Hut,chins, J. F.; Eschenroeder, A. E.; Nordsieck, R. A. “Development of the ELSTAR Photochemical Air Quality Simulation Model and Its Evaluation Relative to the LARPP Data Base”; Environmental Research and Technology, document P-5287-500, July 1979. (5) Lurmann, F. W. “User’s Guide to the ELSTAR Photochemical Air Quality Simulation Model”; Environmental Research and Technology, document P-5287-600, Sept 1979. (6) “An Assessment of the Air Quality Impact of Abolishing California’s Motor Vehicle Pollution Control Program”; CARB, Feb 1980. (7) Keith, R. W.; Selik, B. “California South Coast Air Basin Hourly Wind Flow Patterns”; South Coast Air Quality Management District Headquarters: El Monte, CA, Jan 1977. (8) Angell, J: K.; Dickson, C. ‘R.; Hoecker, Jr., W. H. J . Appl. Meteorol. 1976,15,197. (9) Environmental Research and Technology, Report A060, Jan 15, 1980.
(10) “Mobile Source Emission Factors”, Final Document, EPA400/9-78-005, March 1978. (11) Heuss, J. M.; Chock, D. P.; Dunker, A. M.; Kumar, S.; Sloane, C. S.; Glasson, W. A. “An Analysis of Factors Contributing to Los Angeles Oxidant and NO2 Air Quality”; GMR-3230; General Motors Research Laboratories, Feb 21, 1980. Received for review September 26, 1980. Accepted March 16, 1981.
Volume 15, Number 8 , August 1981
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