ance scheme indicated that MOBILE 1overestimated emissions by 50% for a given traffic condition, how would the scheme be used to estimate the emissions for a different traffic pattern? Although AP-42 or MOBILE 1 provides only approximate emission rates, they are capable of forecasting the changes in emission rates with changing traffic patterns. Furthermore, the approximate emission rate is not too critical in the model calibration procedure since model estimates are linearly proportional to the emissions. This can be incorporated in projecting future pollutant levels once a good correlation between measured and the corresponding observed concentrations is established. The correlation coefficient is related to the model’s handling of the physical processes of atmospheric transport and dispersion. The data presented in their Table I show that, although the average calculated and measured emissions agree well, the variability is anywhere from 39% underestimation to 32% overprediction at tower 1.The errors are even larger at tower 2. The calculations with the SRI data base show (Tables I1 and 111) considerable disagreement between calculated and measured tracer gas emission rates. There were significant wind directional shifts between many of the hours during which the SRI experiments were conducted (6). One consequence of using these periods without subdividing the hour into shorter intervals is that it gives the impression of having significant upwind concentrations when, in fact, part of the hour had those receptors downwind, while they were upwind for the balance of the hour. Further, there were several hours when small tracer concentrations were seen upwind of the highway. These consistently occur with light winds and reflect either the natural meandering of the wind under these conditions or the influence of the vehicle-induced drag flows. The authors do not indicate whether the data used in the paper excluded the above situations. The emission rates for CO data were calculated (see Tables IV-VII) from CO measurements at two heights only. In addition, if these towers are sufficiently far from or very near the highway, significant errors will occur in the estimation of the emission rate. In the computation of the emission factors from
SIR: We believe that the comments by Rao, Sedefian, and Peterson in their letter to you are largely due to misinterpretation of the method used and the intent of the paper. In fact, many of the items that the correspondents said were omitted from the paper are very clearly included. We did not present the method or the paper as a panacea. We point out in the paper that much more data are needed to adequately describe vehicular emission rates. This method is the only known means for checking MOBILE 1, and we think it deserves further consideration and work. In response to the second paragraph, a t no time did we suggest that the mass balance method be applied to parallel wind situations. For nonparallel wind situations, edge effects have no influence at all on the method if they are uniform. End effects would be very important, but the paper clearly states that the roadway must be effectively infinitely long and straight. Thus, the simplification shown as eq 2 in the correspondents’ letter is valid. The wind angle with respect to the roadway is included for each case in the paper. The wind angle had a small standard deviation and the speed was moderately strong for essentially all cases. In the Texas data, the background values at both locations on the upwind tower had to be within 1 ppm of each other. For the tracer gas data from 0013-936X/81/0915-0365$01.25/0 @ 1981 American Chemical Society
AP-42 or MOBILE 1,county-wide traffic information instead of on-site traffic information was used which could result in a considerable error in the emissions model predictions. It is unclear how such large differences in calculated emission/ vehicle could occur in Table IV. The mass balance technique as given in eq 1is a theoretically sound method to determine emissions from the roadways, but numerous problems arise in its application. The methodology proposed by the authors with eq 2 has very limited practical applicability. Because of the various limitations to the proposed methodology, and the way it has been applied to estimate source strengths for CO, the authors’ contention that the emission factors are underpredicted 43-60070 from AP-42 and 8-40070from MOBILE 1is unjustified. Literature Cited (1) U.S. Environmental Protection Agency, Office of Air Programs,
Research Triangle Park, NC, 1975, AP-42. (2) U.S. Environmental Protection Agency, Office of Transportation and Land Use Policy, Washington, D.C., 1978, Report No. EPA40019-78-006, MOBILE 1. (3) Rao, S. T.; Sedefian, L.; Czapski, U. H. J.App2 Meteorol. 1979, 18, 283. (4) Rao, S. T.; Keenan, M. T.; Sistla, G.; Wilson, J. S. “Atmospheric Turbulence and Pollutant Dispersion Near Roadways”; Final Report to EPA on Project R-806017-01. (5) Sedefian, L.; Rao, S. T.; Czapski, U. H. Atmos. Enoiron., in press. (6) Dabberdt, W., personal communication.
Leon Sedefian S. Trivikrama Rao Division of Air New York State Department of Environmental Conservation Albany, NY 12233
William B. Petersen Meteorology and Assessment Division U S . Environmental Protection Agency Research Triangle Park, NC 2771 1
GM or SRI, no cases were used where the far upwind monitors showed any of the tracer. In response to the third paragraph, if the upwind and downwind monitors are sufficiently far from the roadway, the modifications of the wind flow field will be negligible. In the Texas data, the upwind station was usually -150 ft from the upwind edge of the roadway and the downwind station used in the mass balance calculations was usually -50 f t from the downwind edge of the roadway. In the GM data, the towers were -50-100 ft from the respective road edge. We think the correspondents will agree that the modifications in the wind flow field due to the roadway will be negligible at this distance. However, in the truest sense, the wind angle shift across the roadway has no bearing on the problem, as long as the wind speeds are taken at the points of pollution measurements. The paper stated this quite clearly, just as i t stated that the meteorological instruments were located near the downwind pollutant monitors. We did not try to take a mass balance in the mixing cell, as the letter suggests, since the effective wind in this region is too highly turbulent to even properly assess wind direction. In response to the fourth paragraph, the mass flux profile, CU,, for all cases was such that a well-behaved curve through Volume 15, Number 3, March 1981
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the data points would approach zero shortly after the last data point. The error in the area under the curve for different approaches to zero at the upper levels was less than 5%. In all cases the curve fitted to the data was smooth and passed through all points. In general, the shapes closely followed an equation of the form AeBzZ= Z c , which can be defended theoretically as a superset of the Gaussian diffusion equation multiplied by the power law wind profile. Two measurements are not sufficient to define the plume. A minimum of three points are needed, and four to six are better. At this point, we would like to comment that the integration process greatly reduces the error in a calculational procedure. Thus, essentially the same results are obtained for several curve shapes through the data. In response to the fifth paragraph, more than one monitor was used on the upwind side, as previously mentioned. The inequality in eq 3 in the correspondents’ letter would be true if Uxlwere not related to Uxz.However, the two wind-velocity profiles are related. If the air can be treated as a constantdensity fluid across the roadway (e.g., AF’< 1.5 in. Hg and AT < 25 O F for 5% error), every cubic foot of air leaving through a downwind plane must have entered through the upwind plane. If the pollutant burden that it carried when entering the upwind plane is uniform, then it can be simply subtracted off, no matter where it entered. In response to the sixth paragraph, the correspondents keep repeating the “subjectivity” of the method and appear to have made considerable effort to distort the method. All of their “assumptions” were attempts to introduce error by violating fundamental precepts of the method. Our experimentation showed that changing the profile shape by having different people draw the envelope produced errors of less than 20% in all cases when the people were given only the instructions detailed above. The paper implies that the wind speeds used must be the local wind speed a t the point of pollutant measurement. Deliberately choosing the wind speeds a t other points defeats the entire philosophy of the method. We are puzzled by the reference to “correcting or not correcting for the angle of the tower line,” since the paper clearly states that the wind angle must be measured with respect to the roadway. A shift of coordinate axes to parallel the tower line has no possible justification. The only reason to do this is an attempt to introduce errors which approach infinity as the wind approaches a normal to the line of towers. Consider the absurdity of this: if the towers were arranged parallel to the roadway, the correspondents would have one believe that one could make the “cross wind” parallel to the roadway. This distortion alone could easily cause the factor of 2 that the correspondents noted. In response to the seventh paragraph, this method was not and is not being offered as a replacement or even as a supplement for MOBILE 1 or AP-42. Firstly, it was meant to be a check on the accuracy of MOBILE 1and AP-42. EPA would have us believe that their accuracy is perfect, when in actuality the type of tuning, the availability of unleaded gas, and even the state of the economy can change the emission rates. People tuning their cars for performance, people removing catalytic converters to burn leaded gasoline, and people skipping maintenance because of lack of funds can all change emission rates severely. Secondly, the use of the method is to provide “calibration factors” in the models more quickly and accurately. If 4 instruments out of 10 are used for mass balance and then the model is calibrated by using the calculated emission factor predictions on the other six positions, the transport and
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dispersion errors can be isolated from the emission factor errors. The method was never i x - a d e d as a panacea for all of the ills of air-pollution mdnitoring. For instance, it was considered too obvious to mention that the only way that this method could produce an emission factor along a projected roadway is to construct the roadway. We apologize if the correspondents have gotten this impression. In addition, the correspondents appear to have left a t least one stone unturned in stating that the approximate emission rate is not too critical in the model calibration procedure since model estimates are linearly proportional to the emission. They further state that this can be incorporated in projecting future pollutant levels once a good correlation between measured and observed concentrations is established. The above remarks suggest that the accuracy of MOBILE 1 is constant for all situations. This is highly doubtful. Thus, a calibration factor for the dispersion models would be needed for ep.ch input scenario for MOBILE 1.We feel certain that this is one of the reasons that the plots of predicted vs. observed pollutant concentrations have so much of a “shotgun” pattern. In response to the eighth paragraph, the large individual variations are probably caused by both holdup due to wind speed and direction shifts and by the fact that the source of SFGwas not continuous but instead was discrete, with 16 release vehicles placed such that 8 passed the site in a group approximately every 30 s. This produced a pulsating rather than steady plume which required many sample periods to stabilize. The point about breaking up the hourly sampling periods in the SRI data was well taken. This would have given us more points as well. Unfortunately, the experimenters elected to use 1-h bag samples, and there is no way to ‘(unscramble” the 1-h integrated sample into either 4 15-min samples or 12 5-min samples. We suspect that the variations in some of the results arise from lack of care in experimental method, real variations in source strength, and possibly some unknown factors in the dispersion process. In response to the ninth paragraph, we fail to understand how the correspondents obtained the false impression that only two heights were used in the Texas data. The paper clearly states that pollutant monitors were located a t four heights downwind of the roadway and that all four heights were used. In addition, the next time that we collect data on the dispersion of pollutants from roadways, we will invite the correspondents to assist us in stopping an eight-lane freeway full of traffic to get the vehicle age distribution and the number of hot and cold starts so that we will not have to use county-wide information. In conclusion, every complaint by the correspondents would cause an increase in the mass balance emission factor. We submit that it is extremely important to quantify the emissions in order to validate models over a range of traffic and meteorological conditions. We further submit that the quantifications of emissions from vehicles has not been achieved with the precision that some have led us to believe, and that more careful research needs to be performed along roadways rather than on dynamometers. J. A. Bullin J. C. Polasek Department of Chemical Engineering Texas A & M University College Station, TX 77843
