Environ. Sci. Technol. 1982, 16, 880-803
(27) Lillian, D.; et al. Environ. Sci. Technol. 1975,9,1042-1048. (28) Simmonds, P. G.; Kerrin, S. L.; Lovelock, L. G.; Shair, P. H. Atmos. Environ. 1974.8. 209-216. ~(29) Ohta, T.; Morita, M.; Mizoguchi, I. Atmos. Environ. 1976, 10. 557-560. (30) Going, J. E.; Spigarelli, J. L. “Sampling and Analysis of Selected Toxic Substances Task IV-Ethylene Dibromide”; EPA 56016-76-021, 1976. (31) Leinster, P.; Perry, R.; Young, P. J. Atmos. Environ. 1978, 12, 2383-2387. (32) Farber, H. P. “l,l,l-Trichloroethane as an Industrial Solvent: A Review of Current Health and Environmental Knowledge”; Dow Chemicals: Midland, MI, 1979. (33) Demopoulas, H. B.; Wagner, B.; Cimino, J. “An Academic Review of the Hazards Posed by Trichloroethylene”, New York University Medical Center, unpublished. -I
I
~
(34) Mayrsohn, H.; Kuramoto, M.; Crabtree, J. H.; Sothern, R. B.; Mano, S. H. “AtmosphericHydrocarbon Concentration June-September 1975”; DTS-76-15, California Air Resources Board. (35) Joshi, S. B. ”Houston Field Study-1978 Formaldehyde and Total Aldehydes Monitoring Program”; EPA Contract 68-02-2566, Northrop Services Inc. Report ESC-TR-79-22, 1979. (36) National Academy of Sciences, “Particulate Polycyclic Organic Matter”; Washington, D.C., 1972. (37) Albert, R. E.; Burris, F. J. Cold Spring Harbor Conf. Cell Proliferation 1977, 1, 289-292.
Received for review March 12, 1982. Accepted July 23, 1982. Research funded in part by US.Enviromental Protection Agency under Grant 805990.
NOTES Ozone-Precursor Relationships from EKMA Diagrams John R. Klnoslan
California Air Resources Board, Sacramento, California 95812 Empirical kinetic modeling approach (EKMA) diagrams were used to derive equations relating ozone to the 6:OO-9:00 a.m. concentrations of non-methane hydrocarbons (NMHC) and oxides of nitrogen (NO,). Within limits of concentrations and of NMHC/NO, ratios, ozone is approximately a linear function of the geometric mean of the precursor concentrations. Data from environmental chamber studies were also examined to determine and confirm the ozone-precursor relationships.
Introduction The empirical kinetic modeling approach (EKMA) developed by the EPA provides a basis for relating maximum hourly average ozone concentrations in a receptor area with the 6:OO-9:00 a.m. average of precursor concentrations in a source area (1-3). However, the procedure is essentially graphical. The purpose of this paper is to present equations derived from EKMA diagrams that relate ozone to precursor concentrations. The equations are for the portions of the EKMA diagrams where the ozone isopleths are approximately hyperbolic and the ratio (R) of nonmethane hydrocarbons (NMHC) to oxides of nitrogen (NO,) is in the range of about 5-20. The 6:OO-9:00 a.m. NMHC/NO, ratio appears to be within this range in most cities. As reported by the EPA the median ratio at 19 sites in 12 cities ranged from 7.5to 21.3 on the five highest ozone days (2). So that the equations could be derived, both the standard and city-specific versions of EKMA diagrams were studied, and various linear, geometric, and power functions were examined to determine which, if any, was appropriate. It was found that within limits of ozone concentrations, ozone correlates very well with the square root of the NMHC-NO, product (P),and ozone is a linear function of P1I2. 880
Environ. Sci. Technol., Vol. 16, No. 12, 1982
The procedure for deriving the ozone-precursor equation is demonstrated by using the standard EKMA diagram. The derived ozone-precursor relationship is illustrated for the standard EKMA and for two city-specific EKMA diagrams that were prepared by others using the OZIPP (ozone isopleth plotting package) procedure (3). The relationship is also illustrated for published diagrams or data obtained in smog chamber studies. A rollback equation is presented and discussed. Rollback equations are based on the assumption that ambient concentrations are linearly related to emissions.
Equations f r o m E K M A Diagrams The standard version EKMA diagram, overlayed with five ratio lines, is shown in Figure 1. The lines are for R equal to 4,5,10,20,and 25. The NMHC concentrations (ppm C) were determined at each of the intersections of the R lines with the ozone isopleths. The square root of the product of NMHC and NO, was determined at each intersection by using the equation P1lz = R-1/2[NMHC]. (By definition R = NMHC/NO, and P = [NMHC]/[NO,]. Therefore P112= R-lI2[NMHC]). In all there were 39 intersectional points. The concentrations of ozone and P112at each of the 39 points are illustrated in Figure 2,and regression lines are shown for R equal to 4,5-20,and 25. As indicated for ratios at 5-20, the slope of the lines are different above and below concentrations of ozone equal to 0.3 ppm. For both the upper and lower line, most of the points are within fO.O1 ppm ozone on the regression lines. This is probably within the accuracy of the EKMA diagram and is within the accuracy of the measurement methods for NMHC, NO,, and 03. Within the range of 5-20, as indicated in Figure 2,R has little or no effect on ozone concentrations. Therefore, the regression equations shown in Figure 2 can be used to calculate ozone concentrations directly from precursor
0013-936X/82/0916-0880$01.25/0
0 1982 American Chemical Society
0
' 0 1
0.2
03
0.4
p1/2
0.6
0 1
07
0 8
,
os
(PPrnI
Figure 3. Central Valley city-specific EKMA ozone-precursor relationship: (0)R = 5, 10, 15, and 20, (0)R = 4 and 30.
NMHC IpprnCl
Flgure 1. Standard EKMA dbgram overbyed with NMHC/NO, ratio ( R ) lines of 4, 5, 10, 20, and 25.
Flgure 4. SCAB city-specific EKMA ozone-precursor relationship: (0) R = 8, 10, and 15, (0)R = 7, (A)R = 20. 0.1
0.2
0:4
0.3 1/2
0.6
0.8
0.7
h m )
Figure 2. Standard EKMA ozone-precursor relatlonshlp: (0)R = 5, R = 4, (A)R = 25. 10, and 20, (0)
concentrations when R is from about 5 to 20. However, the two regression equations apply only to the standard EKMA version. The constants, a and b, differ considerably from those for city-specific EKMAs. Two city-specific EKMAs whose ozone-precursor relationships were substantially divergent from the standard version are used as examples to show that the constants for one EKMA are not the same as for another. The first diagram was developed for a city in the Central Valley of California by the Modeling Section of the Research Division of the California Air Resources Board. The Central Valley city-specific EKMA diagram illustrated ozone isopleths at five concentrations, 0.12,0.14,0.16,0.18, and 0.20 ppm, and is typical of the diagrams for several other cities in the Valley. The ozone concentrations and P1lzvalues are shown in Figure 3. The second example is of a South Coast Air Basin (SCAB) city-specific EKMA developed by Trijonis and Mortimer (4). For this EKMA diagram, the effect of high or low ratios was greater than for the standard EKMA version. So much so, it was estimated that the range where R had little or no effect was 8-15, as compared to 5-20 for standard version. Intersectional values of ozone and P1lz were determined at R equal to 7,8, 10, 15, and 20 and are shown in Figure 4. Although there is some scatter, all of the points are within about 10% of the ozone concentrations indicated by the two regression lines. For the SCAB city-specific EKMA, R has a strong effect on the ozone-precursor relationship outside of the 8-15 range. The effect is illustrated in Figure 4 by dashed lines for ratios of 7 and 20.
Rollback Equation As shown, the basic equation of EKMA diagrams with R nominally in the range of 5-20 is
O3
a([NMHC][N0,])1/2+ b
Let the subscripts i and f denote the initial and final - 03f)/(03i concentrations, respectively, and let Do = (03i - b). Further, let DHc and D N equal the fraction NMHC and NO, are reduced by: DHC= 1 - NMHC,/NMHCi D N = 1 - NO,,/NO,i By solving for ([NMHC][N0,])1/2in the basic equation, equating final and initial concentraions, and substituting the fractional reduction term for the concentrations, the following rollback equation was derived:
As an example of the use of the rollback equation consider the following: 03i= 0.18 ppm, = 0.12 ppm, and b = 0.06 ppm. NO, is predicted to be reduced by 40%. The percentage reduction of NMHC then required to attain the national ambient air quality standard (NAAQS) for ozone (0.12 ppm for 1 h) is
DHC = 0.583, and the percentage reduction of NMHC required is 58%. Few if any areas outside of the South Coast Air Basin in California have ozone design values greater than 0.30 ppm. Therefore the rollback equation based on regression lines for 0.12-0.30 ppm is widely applicable providing the ratio constraints are observed. However, the intercept, b, must be known. Environ. Sci. Technol., Vol. 16, No. 12, 1982 881
0.41
-
0.3-
E
0"
os= 0.2-
0.1-
0.1 /
n
V 0 '
1
I
I
I
I
0.1
0.2
0.3
0.4
0.3
p1/2
I
0.6
0.7
I
condition
DE DECE CE-
cs
approx ratio range 5-16 or more 7-16 or more 7-20 8-20 1-20
equation
0, 0, 0, 0, 0,
-0.6P'/2 + 0.05 -0.6P1'2 + 0.05 ~ 0 . 8 P ' t/ ~0.04 =0.7P1'2+ 0.06 - O . 8 P 2 t 0.06
On the basis of over a dozen EKMA diagrams, the range of b is about 0.04-0.10 ppm. The range is too wide to expect that an assumed value of b would provide quantitative results. Thus rollback equations for ozone are of doubtful utility if b is not known.
Ozone-Precursor Relationships in Smog Chamber Studies Five EKMA type diagrams were shown in a recent publication by Carter et al. (5). Two were based on the EPA kinetic mechanism and hydrocarbon composition, one with aldehydes and one without aldehydes, and were abbreviated by Carter et al. as DE and D e ,respectively. Two others were based on a kinetic mechanism developed by Carter and on the EPA hydrocarbon composition with aldehydes and without aldehydes and were abbreviated as CE and CE-. The fifth was based on the Carter mechanism and on a hydrocarbon surrogate mixture (C,) that included butane, propene, formaldehyde, and carbon monoxide. The surrogate mixture was used to confirm the validity of the Carter mechanism in smog chamber experiments. For each of the five EKMA diagrams, the ozone isopleths were at concentrations of 0.12,0.30, and 0.45 ppm. The ozoneprecursor relationships under the C,conditions are illustrated in Figure 5. The equations of the lines joining the 0.12 to the 0.30 ozone concentrations for each of the five conditions are summarized in Table I. The equations apply only in the NMHC/NO, ratio ranges indicated. In another recent publication, Sakamaki et al. showed that 03m/03p was a function of R (6). OBmis the maximum ozone concentration formed when irradiating known concentrations of propene and NO, mixtures, and [0,,] is the photostationary ozone concentration in the absence of hydrocarbons at a given light intensity and initial NO, concentration. The relationship was illustrated graphically 882
I
I
1
,
I
0 1
0.2
03
04
0 5
P'/*
(ppm)
Flgure 5. Ozone-precursor relationship based on data by Carter et ai. (5),condition C,: (0)R = 8-20, range is given by horizontal bars; (A)R = 6.7. Table
0
Environ. Sci. Technol., Vol. 16, No. 12, 1982
I
0 6
0 7
(pprn)
Figure 6. Ozone-precursor relationship based on data by Sakarnaki et ai. (6): (0)R = 5-20, (0) R < 5, (v)R > 20.
but was not expressed mathematically. Sakamaki et al. also showed that at values of R less than about 9, appropriately termed the NO, excess region, OSm increased linearly with (C3H6)1/2 at constant NO, and light intensity. At values of R greater than about 15, termed the hydrocarbon excess area, Osmwas approximately linearly proportional to with C3H, and light intensity constant. These relationships may be useful to estimate precursor reductions, but as for the rollback equation, the intercept value must be known to determine necessary reductions quantitatively. Data for 22 experimental runs with constant light intensity were tabulated in the publication. The table showed the initial C3HB,NO,, and maximum O3 concentrations as well as other information. Figure 6 was preand P1l2 pared from data in the table and shows the 03m relationship. There is some scatter in the data points, which were based on measured concentrations and not smooth isopleths. Osmconcentrations were also calculated by Sakamaki et al. by using the Carter mechanisms. The scatter is much less when the calculated rather than the measured OSm concentrations are used. The regression equation shown in the figure is for concentrations of 0.12 ppm ozone or higher and for R of 5-20. Under the same conditions and for the calculated rather than measured ozone concentrations, the equation was OBm= 0.51P1/' + 0.081.
Discussion and Conclusions As shown empirically, within specified limits of NMHC/NO, ratios, ozone concentrations from 0.12 to 0.30 ppm are approximately a linear function of the geometric mean of the precursor concentrations. The ozone-precursor regression equation, 0, N aP1l2+ b, applies in the ratio range of about 5-20. In some cases the range is narrower, about 8-15. Factors such as inversion height or surface ozone transport as applied in the OZIPP procedure have the effect of changing the constants, a and b, and of changing the applicable ratio range. Likewise, hydrocarbon composition, aldehydes, and the kinetic mechanisms affect the constants and the applicable ratio range. However, under all conditions examined, ozone is approximately a linear function of the geometric mean of the precursor concentrations, subject to the limitations of concentration and ratio ranges specified. Literature Cited (1) U.S. EPA, *Uses, Limitations and Technical Basis of Procedures for Quantifying Relationships between Photo-
Envlron. Scl. Technol. 1982, 16, 883-886
pleth Model”; report prepared for EPA by Santa Fe Research Corp., Mar 1981. (5) Carter, W. P. L.; Winer, A. M.; Pitts, J. N., Jr. Atmos. Environ. 1982, 16, 113-120. (6) Sakamaki, F.; Okuda, M.; Akimoto, H.; Yamazaki, H. En-
chemical Oxidants and Precursors”;EPA-450/2-77-021a, Nov 1977. U.S. EPA, “Proceduresfor Quantifying Relationshipsbe-
tween Photochemical Oxidants and Precursors: Supporting Documentation”;EPA-450/2-77-021b, Feb 1978. U S . EPA, “Guidelinefor Use of City-Specific EKMA in Preparing Ozone SIPS”;EPA-450/4-80-027 Mar 1981. Trijonis, J.; Mortimer, S. “Analysis of Historical Ozone Trends in the Los Angeles Region Using the EKMA Iso-
viron. Sci. Technol. 1982, 16, 45-52. Received for review January 29,1982. Revised manuscript received July 16, 1982. Accepted July 26 1982.
Gas Chromatography/Mass Spectrometry Identification of Organic Volatiles Contributing to Rendering Odors Herman R. Van Langenhove,” Fredy A. Van Wassenhove, Jos K. Coppin, Marc R. Van Acker, and Nlceas M. Schamp
Laboratory of Organic Chemistry, Faculty of Agricultural Sciences, State University of Gent, B-9000 Gent, Belgium
rn Organic compounds in rendering plant emissions, both in the factory building air and in neighborhood ambient air of the plant, were identified by a gas chromatography/mass spectrometry system using capillary columns. Adsorption on Tenax GC and selective solvent absorption of volatile organic acids were used as concentration techniques. The results indicated that 80% of the identified compounds, mainly aliphatic, aromatic, or halogenated hydrocarbons and terpenes, can be considered as ubiquitous volatiles, not contributing to the odor. Twenty-six volatiles including an amine, five sulfur compounds, eight volatile acids, one alcohol, and eleven aldehydes were identified as malodorants contributing to rendering odors, by matching each GC/MS analysis with the corresponding “odorogram”.
Introduction By collecting and processing fallen animals and slaughter offal, rendering plants contribute to the conservation of public health. Worthless offal is worked up into different valuable products: glue, bone- and fish-meal, and inedible grease and tallow. Unfortunately rendering activities involve the production of a wide variety of odorous volatiles ( l ) ,and in spite of the installation of odor abatement equipment, rendering activities often remain a source of public nuisance (2). Identification of the odorous compounds emitted by rendering plants is the first step toward an objective description of the odor problem and an essential need for the chemical evaluation of odor abatement technology. GC/MS analysis (3) permits separation of complex mixtures of organic compounds and structure identification of these substances even at 10-ng amounts. It is therefore the best available method for the identification of volatiles. Due to the sensitivity of the olfactory system, with thresholds as low as 0.1 ppb (vol/vol) ( 4 ) , concentration of the volatiles prior to identification remains necessary. Cryogenic trapping, solvent absorption, and adsorption on porous polymers are well-known concentration techniques. Cryogenic trapping has the disadvantage that considerable amounts of water, interfering with the GC/MS analysis, are collected. Two other concentration methods were used in order to get a broad spectrum analysis of the compounds present in rendering emissions. Adsorption on porous media followed by thermal desorption is a powerful, nonselective concentration technique. Activated charcoal (5) and synthetic polymers as Porapak QS (6)and Tenax GC (7, 8) have 0013-936X/82/0916-0883$01.25/0
been used in air pollution studies. Because of its hydrophobic character, its thermal stability up to 400 “C, and its inertness toward most of the pollutants (9),Tenax GC was the adsorbent of choice in this study. Highly polar organics, especially volatile organic acids, were not detected with the Tenax adsorption GC/MS method. Therefore, solvent absorption, a more selective concentration technique, was used to supply information about the presence of these compounds in rendering emissions. Because FID sensitivity and human olfactory sensitivity are not correlated, dominating peaks in the chromatograms do not necessarily represent volatiles important to the odor problem. Samples were analyzed by GC in order to evaluate whether or not compounds present in the samples contribute to rendering odors. The instrument was provided with a splitter, which conducts parts of the column eluate to the open air. An analyst, observing the FID signal, sniffed at the eluate and wrote down any observed odor character. This method (10) does not give information about odor thresholds or intensity-concentration relationships of the compounds. It is a method to select malodorants out of the complex mixture of volatile organics present in the samples. Results of GC/MS identification of volatiles sampled by either adsorption or selective solvent absorption from rendering emissions are reported in this paper. Compounds that contribute to rendering odors (according to the “odorogram” method) are indicated.
Experimental Section Sampling Sites. Sampling was performed in a Belgian rendering plant with an annual capacity of 10000 t of raw material. In this plant materials are processed by cooking under vacuum. Vapors released during the cooking process pass consecutively through a grease trap, a surface condenser, and two water scrubbers before they are emitted to the atmosphere. Samples were taken in the factory building, at the outlet of the last scrubber, and in the neighborhood of the plant. Sampling Procedures. Tenax GC, used in adsorption tubes, was purified by extracting with acetone for 6 h in a Soxhlet apparatus. The moist polymer was transferred to a Rotavap, and excess solvent was evaporated. Glass tubes (0.7 cm i.d. X 15 cm long) were filled with 1 g of Tenax GC and then conditioned overnight at 240 “C under a helium flow (10 mL/min). After cooling, the tubes were closed and kept closed with glass stoppers. The air sampling flow rate was set at 0.5 L/min with a rotameter
0 1982 American Chemical Society
Environ. Scl. Technol., Vol. 16, No. 12, 1982 883
