Environ. Sci. Technol. 1087, 21, 45-51
Indoor Contaminant Emission Rates Characterized by Source Activity Factors John E. Franke and Rlchard A. Wadden"
Environmental and Occupational Health Sciences, School of Public Health, University of Illinois at Chicago, Chicago, Illinois 60680 A method was developed for determining individual emission rates from ambient air contaminant concentrations caused by multiple indoor sources. Levels of gas pollutants and particulate matter were measured in an industrial and nonindustrial building during 50 and 16 4-h periods, respectively. Observations of emission source activities were collected on a 10-min basis. Overall emission rate was calculated with a pollutant mass balance model. Emission source activities were categorized, and important activity factors were selected by analysis of variance. Multiple source emission rates were estimated with linear regression analysis by comparing overall emission rates to the source activity factors. The average source emission rates were consistent with literature rates determined under controlled conditions. These rates were used in a mass balance model to calculate indoor concentrations. The method satisfactorily determined average source emission rates in the presence of multiple sources and highly variable operating conditions on a short (4-h) time scale. Introduction The strength and nature of indoor emissions are often the most significant determinants of indoor air quality. The release rate of these emissions can be calculated if the usage rate of the source material and the emission factor associated with the process and material are known. Emission factors are usually determined experimentally and expressed as a mass of contaminant released per mass of source material. Experimental emission factors for indoor sources have been published for a limited number of contaminants, processes, and environmental conditions (1). This type of emission factor is referred to as a literature rate throughout this paper. Building ventilation has traditionally been used to control indoor air quality in factories, offices, schools, homes, and other indoor spaces. Average emission rates from interior contaminant sources are useful when evaluating the adequacy of these ventilation systems. Air contaminant sources can be highly variable in nature, being a function of process and operator activity and environmental factors. The variability of indoor rates is more striking than it is for outdoor emission rates. A distribution of emission rates is actually associated with each contaminant source. Therefore, literature rates cannot be matched exactly with conditions in the field. In this study, emission rates, expressed in terms of mass per time, were determined for a variety of contaminant sources on a short-term basis by source activity factors. Activity factors are simple expressions of contaminant source activity during a time interval (e.g., the ?umber of welders active during 10-min sampling intervals). Therefore, the emission rates are translatable to conditions in the field. Activity factors have two distinct advantages: (1)they are easily measured by observing the sources, and (2) as simplified statements of a spectrum of operating conditions, the factors provide a measure of the highly variable nature of the indoor contaminant source emissions. 0013-936X/87/0921-0045$01.50/0
Other studies have used a similar approach to quantify the effect of contaminant sources in homes (2,3). However, these used mean values of 24-h average concentrations of two contaminants, respirable dust and suspended sulfates. The research described here used much shorter averaging times, from 10 min to 4 h, for five air contaminants. Theoretical Development Overall Emission Rate. Emission rates may be determined experimentally by containing the source emissions within a well-mixed environmental chamber. The average emission rate is calculated by multiplying the chamber airflow rate by the concentration increase from inlet to outlet. If a portion of the emission mass is removed by some mechanism within the chamber, then a net emission rate is measured. In other words, the environmental chamber acts as a one-compartment mass balance model at steady-state conditions. A pollutant mass balance around a particular indoor volume also provides a general format for determining overall emission rate. One form of mass balance for pollutant flow into and out of an indoor volume, including recycling and interior sources and sinks, is
v-dCi = kq,Co(l - Fo) + kq,Ci(l - F,) + kq,C(y0 dt k(q0 + 41 + QJCi - R
+S
(1)
where C is concentration indoors (Ci) and outdoors (Co), t is time, q is volumetric flow rate for make-up air (qo), recirculation ( q J , and infiltration (qJ, Po is penetration from outdoors, F is air cleaner efficiency for make-up air (Fo)and recirculation ( F J , V is indoor volume, k, a factor that accounts for inefficiency of mixing, is the fraction of incoming air that completely mixes within the indoor volume, R is the indoor sink removal rate, and S is the indoor contaminant emission rate. Average values for the major contributions in eq 1 are defined as
Ci = -1s " C i dt ts
0
(3) (4) (5)
The term t, is the sampling time. Po, V, k, q, and F are assumed to be constants for a given sampling interval. Typical values for these constants that were used in this research are reported under Methods. With the average values expressed by eq 2-5, the difference form of eq 1 is then written as
0 1986 American Chemical Society
Environ. Scl. Technol., Vol. 21, No. 1, 1987 45
VACi 7 + kqlFICi =
.
120r
68
kqoC,(l - Fo) + kq2PoCo- (kqo + kq2)Ci - R
+S
(6)
2 grinders
\**--
./****
where ACi is the difference in concentration between the beginning and the end of a sampling interval = Ci(t,) Ci(0). Equation 6 may be solved for the overall average [ci(t,) + emission rate (Smb) by recognizing that Ci Ci(0)]/2, and consequently
Smb is the overall emission rate from all sources, inferred from field measurements of ventilation rate and concentration. This form presumes a zeroeth-order removal rate. While this is not realistic for materials with significant decay rates (e.g., 03), it will be shown that the form is reasonable for the contaminants studied. Multiple Source Emission Rates. The mass balance concept may also be used to determine emission rates from field data. In this case, a building or room serves as the environmental chamber. In a laboratory experiment, z m b is a single source emission rate. In the field, however, S m b is a measure of emission rates from all contaminant sources in the building and the variability associated with these sources. Source activity factors may be used to discriminate the individual source contributions to ambient concentrations (2). When several sources of a contaminant are identified, the respective source emissiop rates may be estimated by multiple regression analysis. S m b is fiist calculated for each sampling interval. As many samples as possible should be collected. For this study, at least 46 samples were collected on a 4-h averaging basis. From 200 to 1200 samples were collected on a 10-min averaging basis, depending on the pollutant. Simple source activity factors should be selected. Preferably, the factors should have more than two levels and should be independent of each other. If one contaminant source is welding, the activity factor could be the number of welders active during the sampling interval. For example, four levels of activity factor (0, 1, 2, and 3) are possible when a welding shop has three welders. The mean value of s m b should increase consistently with the level of activity factor. These mean values should be significantly different from each other. One-way analysis of variance (ANOVA) may be used to evaluate the latter condition. A source equation in the form of a first-order, linear regression model may be solved for the multiple source emission rates:
1 grinder
3
-
0
1 Number of welders
0
Flgure 1. Relationship of welding activity and CN concentratlon, glven three levels of nearby grlndlng actlvlty.
ient than multiple regression analysis of field data. Since averages of concentration and airflow are used, however, the graphical method explains a smaller portion of the variability associated with overall emission rate. The graphical method uses a covariance plot of mean contaminant concentration vs. the source activity factor given several levels of another source activity factor. Figure 1is illustrative of the technique. The mean concentration at each level of welding and grinding is calculated and plotted. The source being analyzed, number of welders, is assumed to be a continuous variable. Lines of equal slope are drawn for each level of covariate. The major assumption of the method is that the lines have equal slopes but different intercepts. This assumption may be tested by analysis of covariance. The steady-state mass balance relation is used to calculate the source emission rate: bi = ( A C i / X i ) k q (10) where A C i / X i is the slope of the covariance plot and kq is the average effective ventilation rate for all samples. Emission rates associated with each source activity factor are determined with covariance plots. The emission rate of other sources (bo) is the product of kq and the mean concentration when the levels of all activity factors are zero. The overall emission rate may then be estimated for a particular time interval from eq 11. The subscript in S,,, = bo blXl bzXz ... + bp-lxp-l(11)
+
+
+
where bi are least-squares estimators for the respective p - 1 independent categories of sources, Xi, and ei is a random error term. The bi are equivalent to the source emission rates per level of activity factor, Xi. Having solved for bi, the overall average emission rate may be estimated for a particular time interval: = bo blXl + bzXz + ... bp-lXp-l (9)
the overall emission rate term, S,,, refers to its derivation from the covariance plots. In summary, the overall emission rate term, Smb, is calculated from measured parameters by a mass balance model. - Source emission rates may then be estimated (using s m b ) by a multiple h e a r regression model (eq 8). Alternatively, source emission rates may be estimated by a graphical model. By observing the activity that occurs during a subsequent time period, the overall emission rate may also be predicted. If source emission rates derived by the regression method are ujed, the predicted overall emission rate is referred to as Sm,;if graphically deriyed source rags are us_ed,the overall rate is referred to as &,. Ideally, S,, and S,,, would be equal.
The subscript in the overall emission rate term, S,, refers to its prediction with the coefficients derived from multiple regression. Graphical Determination of Emission Rates. Multiple source emission rates may also be determined by a graphical technique. The method makes use of source activity factors. Graphical analysis may be more conven-
Methods Welding Shop. General area concentrations of six air contaminants were monitored indoors and outdoors at a welding shop. The three particulate and three gaseous air contaminants are listed in Table I. Four contaminants (CN, RP, NOz, and CO) were selected for emission rate analysis. Samples of these contaminants were collected
s,,
46
+
+
Environ. Sci. Technol., Vol. 21, No. 1, 1987
Table I. Air Contaminants contaminant
sym- averaging time bol
condensation nuclei respirable dust
CN
5 min
RP
4h
total dust
TSP
4
nitrogen dioxide
NO2
4h
carbon monoxide co carbon dioxide COZ
4h 5 min
sampling method environment/one model rich 100 monitor 37-mm PVC membrane filter and 10-mm nylon cyclone at 1.7 L pm 37-mm PVC membrane filter at 1.5 L pm modified sodium arsenite impinger method (2) Ecolyzer Model 2800 Wilks Miran 1A infrared spectrometer
m
coffee break during 50 4-h work periods of March, April, and May 1982. The welding shop, situated in a suburban industrial park, was a one-story concrete block structure with three 0 0850 0900 0910 0920 shipping doors and a 7079-m3 volume. Twelve workers Time fabricated and assembled local exhaust ventilation systems. Figure 2. Determination of effective building ventilation rate from CN Three welders worked mainly with stainless and galvanized concentration decay. steel duct and carbon steel plate. The welding processes used were carbon arc, mixed-gas metal arc (MIG), gasweather and the open doors. An averaging mixing factor tungsten arc (TIG), and shielded metal arc welding of 0.86 represented the best mixing conditions. However, (S-MAW). Sources of air contaminants in the shop inmixing factor was as low as 0.31 when doors were open cluded the welding processes, three pedestal grinders, one during cold weather. Therefore, use of the effective venpaint sprayer (compressed air), four gas-fired heaters, tilation rate term, kq, was appropriate for the welding shop housekeeping chores (such as sweeping),and idling trucks evaluation in order to account for the variability of both at the shipping docks. ventilation rate and mixing factor. Since CN decay repLocal exhaust at the paint spray booth was discharged resented conditions at the time of actual ambient sampling, directly outdoors at a rate of q3 = 0.7 h-l (1400 L/s). The these were chosen as more representative than the tracer system was turned on only when painting. Local exhaust gas experiment results. Effective ventilation rates deterat the welding booths was operating continuously at a rate mined by CN decay during break periods represented the of 0.49 h-l (965 L/s). However, the airstream from this effects of weather and open doors. These conditions resystem (ql) was first passed through an electrostatic premained fairly constant during each time interval. On a cipitator (ESP) and then discharged back into the shop. few days when conditions affecting infiltration during the Therefore, the particulate contaminants RP and TSP were work period were different than those at the break, the partially cleaned (Fl > 0) from the airstream. Gaseous prediction of concentration may have been less accurate contaminants were assumed to be completely recirculated because of an underestimate of kq variability. The range (F,= 0), and CN as well since these particles are typically of kqlV, as determined from fitting the CN decay data 5 X 10l2nuclei/min). Coagulation will be most significant when the number concentration is high. The highest concentrations of CN that we observed were encountered when a source, such as a welder, released an intense emission, i.e., a "spike" in concentration (typically 5 X lo4 CN/mL). Effectiveness of the thermal coagulation process decreases rapidly with time because of the rapid reduction in particle number concentration. This occurs not only because of the coagulation mechanism but also because of diffusion of particles away from the high concentration cloud. The slope of the AC/C? vs. time plot for the particle cloud represents the coagulation rate constant, KO,if coagulation is the controlling mechanism (11). The coagulation effect was only evident for 2 min out of the 10-min sampling periods in which a spike concentration was detected. In addition, the value of KOderived from the slope of the decay curve was 2 x lo8 mL/s, which was in reasonable agreement with theory [0.34 X lo8 mL/s for 0.01-pm particles ( 2 1 ) l .
Therefore, the assumption that the net CN emission rate was independent of concentration was reasonable. The consistent concentration/activity patterns of Figures 3 and 4 support this argument. When an indoor space has contaminant sinks that are not easily measured, the regression analysis or graphical method can determine net source emission rates unique to that location. The concept may also be applied to locations with emission sources that have unique operating conditions. In other words, that portion of emission rate variability that is site-specific can be accounted for by applying these methods. We have chosen to retain the concept of mixing factor in our model because this is a familiar way to express lack of homogeneity in concentration. However, we recognize that kq is ordinarily a more appropriate parameter than k and 4 individually because these variables are likely to be interdependent (e.g., see ref 1and 12). Consequently, in the case of the welding shop we chose to measure the kq product by observing the CN decay during rest periods. In the case of the lunchroom, q, measured at the doorways with a thermoanemometer and smoke tube, and k , determined independently from COz and CN decay curves, did not change a great deal. Consequently, we do not believe that using the product of these variables introduced significant error in the lunchroom analysis.
Conclusions (1) Activity factors are useful for describing indoor emissions and, through the mass balance equation, predicting indoor concentrations. (2) ANOVA and linear regression analysis were reasonable methods for discriminating the individual contributions of multiple sources to the indoor concentration of a pollutant. (3) Emission factors determined from application of these techniques to field data were in good agreement with values from the literature. (4)Expectation of a high correlation between short-term ( t , I 4 h) predicted and observed concentrations was not
reasonable because the great variability in activity within the 10-min observation intervals was not accounted for by the model.
Acknowledgments We appreciate the help of Peter A. Scheff in assisting with some of the data collection. Registry No. NO2, 10102-44-0;CO, 630-08-0; COz, 124-38-9.
Literature Cited Wadden, R. A.; Scheff, P. A. Indoor Air PollutionCharacterization, Prediction, and Control; Wiley: New York, 1983; pp 52-78, 146. Dockery, D. W.; Spengler, J. D. Atmos. Environ. 1981,15, 335-343. Sexton, K.; Spengler, J. D.; Treitman, R. D. Atmos. Environ. 1984,18, 1385-1398. Sinclair, D. Atmos. Environ. 1982, 16, 955-958. White, H. J. J. Air Pollut. Control Assoc. 1977,27, 15-21, 206-217. Offerman, F . J.; Sextro, R. G.; Fisk, W. J.; Grimsrud, D. T.; Nazaroff, W. W.; Nero, A. V.; Revzan, K. L.; Yater, J. Atmos. Environ. 1985,19, 1761-1771. Rodgers, L. C. ASHRAE Trans. 1980,86(2),99-106. Batelle-Columbus Laboratories Fumes and Gases in the Welding Environment; American Welding Society: Miami, FL, 1979; pp 162-205. USEPA Compilation of Air Pollutant Emission Factors; U.S. Government Printing Office: Washington, DC, 1973; p 3.2.5-3. Shair, F. H.; Heitner, K. L. Environ. Sei. Technol. 1974, 8, 444-451. Fuchs, N. The Mechanisms of Aerosols; Macmillan for Pergamon: New York, 1964. Ishizu, Y. Environ. Sei. Technol. 1980, 14, 1254-1257. Received for review September 26, 1985. Revised manuscript received March 7,1986. Accepted August 26,1986. The research was supported in part by NIOSH Grant 5T15-OH-07104 through the industrial hygiene program of the University of Illinois Educational Resource Center, E. R. Hermann, Ph.D., Director.
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