Document VjgBnORGnD47L1L44EReymn9g

_ Reprinted from AMERICAN INDUSTRIAL HYGIENE ASSOCIATION JOURNAL Volume 27, March-April, 1966 Th Application of Computer Scienc to Industrial Hygiene J. E. PETERSON, H. R. HOYLE, and E. J. SCHNEIDER Th* BioehtmUal Rtttarch Laboratory, Th* Dow Chimical Company, Midland, Michigan fg Automatic sampling and analyst* of environmental atmosphere* can result in voluminous amounts of data describing exposure* to chemicals. The use of a digital computer to process such data and the advantage* and disadvantage* of the technique are presented. Introduction A UTOMATIC AIR monitoring equipment * * is expensive. Nevertheless, if it is used to signal the need for action by operating per sonnel to eliminate leaks and to effect needed repairs of equipment, its cost can easily be justified in terms of reduced exposures, re duced hazards, and reduced loss of process material. Furthermore, if sample locations are properly chosen, it provides data on the concentrations of air contaminants to which men are exposed. That information, handled properly, can be used to show long-terns trends of exposure which, correlated with plant operations, can result in still lower ex posures. In addition, such data can be used to determine the exposures of workmen in what is, in effect, a continuing industrial hygiene survey. These data, in turn, could be correlated with medical information on effects of the exposures to confirm or deny present standards or to suggest new ones. At The Dow Chemical Company, auto matic air sampling and analysis were first used in 1950 to monitor air concentrations of carbon tetrachloride in a production plant At that time no method was available for handling the mass of data generated by the air monitoring equipment Sven though the instrument was successfully employed by plant Presented *t the Annual Meetfnc of the American Confer* enec of Governmental Industrial Hygienists. Houston, Texas, May 1965, supervision to control exposures, full use of * the data to estimate the average concentra tion to which men were exposed was not feasible. To illustrate: The instrument rec orded air concentrations at the rate of one every six seconds; this is 432,000 times per month. Because the first continuous air monitor was a success at day-to-day control, others were installed in several plants during the 1950's. As each monitor was put into use, even more information on workmen's ex posures wa* "going to waste"1 simply because there was too much of it. The advent of digital computers suggested a solution. Tak ing advantage of the fact that the Computa tions Research Laboratory had a Burroughs B220 computer, the Environmental Research Laboratory in 1961 acquired a machine for translating air concentration data from a recorder to punched paper tape. Continuous air concentration data could then be com bined with computer analysis to yield a much more complete description of inhalation ex posures than had heretofore been possible. This paper recounts some of the problems involved, from the installation of air moni toring equipment to the interpretation of the data as summarized by the computer. Actual data are used, but only for illustrative pur poses, so plant, process, and even the air con taminant are immaterial. This is not a report of an environmental survey; it is a primer in the application of computer science to indus trial hygiene. 6 BOR 011305 rr -'w'--- American Industrial Hygiene Association Journal Obtaining Air Samples Ad automatic air monitoring system must be sensitive enough to detect concentrations of significance to health. Sensitivity must range from concentrations that may bo im mediately hazardous to those that have little or no significance even for prolonged, re peated exposures. The instrument should be selective; it must respond only to the mate rial^) of interest. It must be stable; it should be unaffected by minor ' (or even major) variadons of temperature, hupoidity, vibration, and line voltage. The installment must be capable of operating unattended for relatively long periods of time. Daily atten tion by the operator, minor service weekly by an instrument man, and occasional perform ance testing should be adequate to keep it in operation. Finally, because a permanent rec ord of air concentrations can be important, concentration data must be automatically re corded. Any continuous analyzer that satisfies these specifications can be used. So far we have used only combustion-conductivity in struments and long-path gaa cell infrared spectrometers; both types produce data suit able for computer analysis. Single-point monitoring in a production plant is seldom economical. Usually the analyzer is positioned at a central location in the plant, and air samples are. brought con tinuously to it through probes of some sort. Tubing used for these probes must not react with, or sorb, the air contaminant of interest Preparing Data for Analysis There is no method presently available for reading results automatically from multiplepoint chart paper into a computer. This means that a device must be used to "digi tize'* the data as they are obtained. At the minimum, the digitizer must translate the analog data (usually the position of a wiper on the slide wire of a potentiometer) to digi tal form (for example, numbers) that can be handled by the computer. Because data on the time of exposure can minimize programing difficulties, the digitizer includes a digital clock with an output of the day number, hour, and minute. A sw selects a "type of data" digit (from 0 tc which is incorporated into the digitizer ' put. An extra "type of data" (for exam from an infrared spectrometer or from a c bustion-conductivity analyzer) digit can a the computer to reject data that obviousb not belong with that being processed, minimize costs, punched paper tape is t to transfer data from the digitizer to computer. For each datum the digitizer punches "words" am the tape. The first "word" i tains the day number, hour, and minute well as the "type of'data" identification n ber. The second "word" contains the p: number and the actual datum which, in case, b a number from 0 to 999, pro tional to the concentration of the air tarninant. This information b obtained rate that may vary from tbti limes a mi: to once in 2.5 minutes. Secause collet each datum generated b not always m sary the digitizer can be programed to the collection of some data. In ever once data from probe No. 1 are punchl the tape, data from the other probes obtained in serial order, but the digitizer ignore all but every second, fifth, or t sets of analyses. Programing the Computer We decided that the minimum time ir data summary should be an eight-hour : Far tins period the Dow Computations search Laboratory programed the comp to calculate the mean concentration at location, the standard deviation of these c the percentage of time that the concentn was above several preselected levels, ant appropriate time-weighted averages. Computers are versatile. For instanc one probe is located to sample air outsidi building, the computer can be program correct automatically for deviations in "background." It n take into acc peculiarities in the calibration curve ol instrument used for air analysis and caj cognize several kinds of errors in the and use only "good" data for calculation BOR 011306 1'82 March-April, 1966 Computer Outppf -j' The bisic compute yMtaft consists of the mean concentration sfj|gpi>ddeviation, num- ber of analyses recordM^tad percentage of time the concentration was above preselected levels, all at each location for each shift dur ing the survey. Shift or daily averages can also be obtained over any selected time inter val such as a week or a month. These data, further identified as to department; air con taminant, etc., are permanently stored on magnetic tape. The computer has been programed to re ject poor data such as that caused by a stick ing punch or by a faulty encoder. If poor data are being obtained, this fact is often signaled first by an unexplained decrease in Furthermore, assume that, over the time period of interest, concentrations at these data locations behaved in this manner: % of Time Concentration Exceeds Selected Values at Specified locations Concentration Data Location Number greater than 1 7 4 12 25 ppm 50 100 250 500 26.639!i 28.68% 93.44% 31.55% 16.39 22.13 20.Q8 23.77 6.55 10.65 17.62 11.47 1.63 2.04 16.39 3.68 0.00 0.00 0.00 0.00 . The time-weighted percentage of time spent by operators in concentrations above 25 ppm* will then be: (UJ) (26.63) + (30) (28.68) + (18.S) (93.44 + (SM> (31M) + (lZ# (P -- 3S.92 100 the number of analyses used by the computer This means that on the average, during the to obtain the shift averages. This has become time period of interest, men in the opera the normal signal for nonroutine maintenance tors classification encountered concentrations of the digitizing equipment. In addition to the basic output, the com puter calculates time-weighted averages of two kinds. The first kind is the "usual" timeweighted average concentration to which men are exposed. It is obtained by combining the air analysis data v/ith "job analysis" infor above 25 ppm 38.92% of the time. Similar calculations show that these mm encountered concentrations above 50 ppm 28.24% of the time; above 100 ppm 10.95% of the time- above 250 ppm 4.00% of the timo; and abcwa 500.ppm 0.00% of the tka*. mation on the percentage of time spent by men in the vicinity of specific analyzer probes. Job analysis information is also combined with the data on the percentage of time dur ing which concentrations exceed the prese lected levels. This results in a second kind of average which is the "time-weighted percen. tage of time" exposures exceeded the prese lected levels. An example of how the time-weighted per centage of time is calculated is given below. Assume that the following information is true Data Analysis Automatic air monitoring reveals that in an industrial situation the variation of con centration with time can .be large despite the use of a rather large time base. Figure 1 is a plot of daily time-weighted average concen trations to which operators were exposed on each shift over one week. Each point on the graph is the mean of several hundred deter minations spaced equally over an eight-hour period. These are actual plant data. for an operator in a plant: Data Location Percentage of Time Spent Number atTbat Location On the second shift than was little varia tion during the first four days, but over the last three da^a of this period the shift average 1 7 4 12 Unexposed JZ5 Si .3 18.8 25.0 12.4 varied by a factor of almost four. If the threshold limit value (TLV) for this mate rial were 50 ppm, an industrial hygienist tak ing air samples during the first three days on the second shift would probably have de 100.0 clared that the hazard to health was low or nonexistent. On the other hand, if he had BOR 011307 rr American- Industrial Hygiene Association Journal 183 ppm. sampled on the last day of this period (on the second shift) he could have experienced a strong inclination to "push the panic button." Variation of concentration between shifts can also be striking, as illustrated by a com* parison of the third shift with the first or second shifts during the first three days. Figure 2 places Figure 1 in a broader con text. Data for Figure 2 are also time-weighted average concentrations to which operators were exposed. The rather extreme variation shown in Figure 1 for a time basis of one shift can be repeated for a time bads of one week. The information contained in Figure 2 is based upon hundreds of thousands of indi vidual air samples. Average concentrations and time-weighted average concentrations are not the only data summaries provided by the computer; aver age concentrations are accompanied by the standard deviation of the data. Having the standard deviation and using it quantitatively are two different things, however. We do not yet know how to use such information effi ciently. On the other hand, the spread or varia bility of the data is indicated in a more mean ingful manner by the percentage of time the concentration exceeded certain levels. Figure 3 is a plot of the time-weighted percentage of time above these levels on log-probability paper. The interval during which data were gathered and the operational classification are identical to those in Figure 2. This graph shows that the median concentration to which men on all shifts in this classification were exposed was 40 ppm and that they were exposed to 500 ppm or higher 2fo of the time. The conventional plot (Figure 2) shows a maximum concentration of about 135 ppm, but it is one of seven-day averages, whereas Figure 3 is a summation of instantaneous values. Both kinds of graph have advantages. A conventional plot illustrates better how ex posures vary with time, and any trends be come readily apparent With this kind of graph, however, the only usable index of ex posure is the time-weighted average, a num ber of limited utility because it cannot reflect OB OH308 184 March-April, 1966 concentration variations. A log-probabitiw plot such as that shown in Figure 3 is not very useful as a trend indi cator, but the fact that time-weigh ted expos ure data plot as a straight line on this graph paper offers exciting possibilities. In our limited experience all time-weighted percent age of time data have been best fitted by a straight line on log-probability paper. That straight line is a complete summary of ex posure information, including measures both of the average concentration and. of the con centration variability.1 The data in Figure 3 were obtained by a survey using the equipment described. How are these data to be interpreted? If we still assume a TLV of 50 ppm, is the exposure represented by Figure 3 a hazardous one or not? These data are among the most com plete ever gathered for men industrially ex posed to a potentially hazardous vapor; what kind of animal experiments should be con ducted to interpret these exposures? We can not yet answer these questions, but we know that they must be answered eventually. Despite this void in our knowledge, the data from this type of survey have several uses. Any information about the intensity of exposures helps to interpret medical findings. Even without complete interpretation, rank ing of exposures is possible. From graphs such as Figure 3 one can judge if the ex posure is obviously hazardous or nonhazardous. For instance, in Figure 4 the concentrations to which the men were ex posed are shown to exceed 15 ppm 50$> of  _v- 'I- J \ ) Assntritam. Industrial Hygjtne Association Journal ^ the ton*. They exceed the assumed TLV of 90 ppm only about 14% of the time. With* out any further knowledge, the exposure rep- resented hy this curve would probably be judged nonhazardous by most industrial hy- gieo&s, provided that contacts with high concentrations were more or less randomly distributed, of short duration, and of little or no consequence in themselves. The data in Figure 4 were obtained in the same plant, for the same group of men, and by the analyzer using the same sample points as for Figure 3. During the period of time when the information in Figure 2 was ob tained, the air analyzer was being virtually ignored by operating personnel in the plant On the other hand, the data in Figure 4 were obtained when the concentrations recorded Fiouxz 4. Exposures for the same people as shown in Figures 2 and 3, but for the period Jan uary 5 to June 18 when the air monitor was used to signal the need for maintenance. The time- weighted. average concentration for this period was 28.83 ppm. by the air analyzer were used to prompt cor rective action. Even plants with a large num ber of leaks and spills can be brought from a potentially hazardous situation to one that is without hazard by using the automatic air analyzer as an operational tool. This is the way an automatic air monitor should be used; it will not justify its expense unless it is so used. ignored or assumed to be similar to the day shift. t Finally, the records obtained can be stored on magnetic tape for indefinite per iods of time in a minimum of storage space. Access to records on magnetic tage is simple and easy. These are important; considera tions, because proof of past accoropfahment* can be of considerable value. Advantages of the Technique The advantages of automatic air analysis coupled with a computer analysis of the data are many. First, air monitoring gives a true Conclusions s Use of automatic air sampling and analysis equipment, coupled with a computer analysis of the data so obtained, can be an extremely potent weapon in the fight of industrial hy picture of the manner in which air concentra gienists against inhalation hazards. Mere tions of the contaminant vary with time. installation of an air monitor, however, does Coupled with a good analysis of the percent not end the battle. Data obtained by the age of time men spend in the various loca monitor must be used by operating personnel tions, this technique can give the best esti in much the same way that monitors of mate presently obtainable of the actual ex other operating variables are used, namely, posures encountered. Second, this technique to assure control. Computer analysis of the enables a correlation of air concentrations data obtained by an air monitor can give the with varying plant activities. This type of best estimate presently obtainable of the con correlation can point out "trouble spots" quite centrations of air contaminants to which men readily and, when used properly, can lead to are exposed. In fact, the environmental an jr dramatic reduction of concentrations to which alysis is so thorough that it poses a challenge idea are exposed and a corresponding reduc to toxicologists to devise animal experiments tion in materials lost. Third, automatic air that will provide a better basis for judgment monitoring is the only technique so far de than does the present threshold limit value. vised that truly shows the air concentration variation between shifts. Too often, air sam References pling is done only on the day shift, and the afternoon and midnight shifts are either 1. LnotnEiv, J. T., J*., and f. WiuaxMC A Simplified Method of Evaluating Dose-Effect Experiment!. J. Phatmmtot. Tkirmp, 96: 99 (1919). \ fr 011310 bor