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A critical review of the Benefits Analysis that accompanies EPA's Great Lakes Water Quality. Initiative (GLI) shows that the benefits have been signif...
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ENVIRONMENTAL POLICY ANALYSIS

REGULATIONS

A Critical Review of the Benefits Analysis for the Great Lakes Initiative DANIEL W. SMITH SMITH Technology Corporation One Plymouth Meeting Plymouth Meeting, PA 19462

A critical review of the Benefits Analysis that accompanies EPA's Great Lakes Water Quality Initiative (GLI) shows that the benefits have been significantly overestimated. Benefits accrue from the estimated reduction in human cancer risk as a result of the decrease in point source loading due to the initiative. EPA estimated cancer reduction for fish consumers as the product of the numbers of consumers, fish consumption rate, chemical concentrations in fish, percent point source contribution to total loading, expected decrease in loading with GLI, and EPA cancer slope factor. For these components EPA used values that were higher than likely and that overestimated final benefits. EPA estimated GLI benefits of about $17,000 for each $1 million invested, but using more likely values produced estimated benefits of about $5 for each $1 million invested. Over the long term, one cancer should be averted sometime between now and the year 8086 after an expenditure of about $1.3 trillion.

In April 1995, EPA released the Great Lakes Water Quality Initiative (GLI), a controversial, potentially expensive new ruling that could significantiy tighten controls on point source pollution across the Great Lakes. To demonstrate the GLI's cost-effectiveness (J3), EPA also released a favorable cost-benefit analysis. In this article the benefits portion of that analysis (4), hereafter called the Benefits Analysis, is critically examined. The Benefits Analysis estimated GLI benefits in two ways: a whole-watershed analysis and a more detailed analysis of three Great Lakes Areas of Concern (AOC): Green Bay, Saginaw Bay, and Black River. The whole-watershed analysis estimated reductions in pollutants from a random selection of minor and major dischargers across the basin and men extrapolated those figures to the entire watershed. For the AOC subwatersheds, reductions in loading from all dischargers were estimated. The whole-watershed analysis considered only human health benefits. The AOC watershed analyses also considered other benefits, including "nonuse" benefits and benefits to commercialfisheries.However, almost all the benefits to the three AOC subwatersheds were direcdy or indirectly related to reductions in risk to human health. The two methods yielded quite different results. Benefits based on the whole-watershed analysis ranged from $0.7 to $6.7 million per year because of reductions in cancer deaths associated with the consumption of Great Lakes fish. Based on EPA's estimated cost of $60 million to $380 million per year, the whole-watershed analysis predicted that 0.2 cents to 11 cents of benefit could be expected for every dollar spent. In contrast, the AOC analyses predicted benefits of, on average, about 72 cents for each dollar spent on compliance. Only the whole-watershed analysis will be considered in the following review, because the AOC benefit analyses are flawed. They incorporate a crucial polychlorinated biphenyl (PCB) point source loading estimate to Green Bay that is known to be incorrect {5-7). EPA's whole-watershed benefits analysis The estimated benefits across the whole watershed accrue from reduced cancer mortality because of decreases in chemical concentrations in fish. EPA estimated cancer reduction for fish consumers in each Great Lake subwatershed with the following equation: Cancer deaths averted = numbers of consumers x fish consumption rate x fish concentrations of chemicals x % point source contribution to total loading x expected decrease in loading with GLI x EPA cancer slope factor

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The number offish consumers, chemical concentrations in fish, and percent point source contributions vary considerablyfromlake to lake and were calculated on a lake-specific basis. Numbers of fish consumers for each lake were estimated from fishing licenses sold in the watershed. These anglers were then exposed to a lake-specific chemical concentration in fish, and the corresponding value was reduced as a function of a lake-specific percent point source contribution. For the other three parameters in the equation, a single value was derived for the Great Lakes watershed as a whole and applied to the calculation for each lake. The number of human deaths from cancer that were averted was then calculated for each lake and summed across all Great Lakes. The equation above highlights two important points. First, the accuracy of the estimated benefits depends on the accuracy of each value used in the equation. Second, given the power of multiplication, a small consistent bias in the estimation of these values produces a very large inaccuracy in the final estimate. Given the high numbers of licensed anglers in the Lake Michigan subwatershed and the high chemical concentrations in Lake Michiganfish,about 70% of the current risk and 70% of GLI estimated benefits were predicted to accrue to consumers of Lake Michigan fish. Thus, an assessment of the accuracy of each component for Lake Michigan follows. However, the comments below apply generally to each of the lake-specific analyses and to the sum of benefits as well. Fish consumption rates EPA's exposure assessment is based on the following assumed average consumption rates of Great Lakesfish:low-income minorities, 43 g/day; other minorities, 11 g/day; and other sport anglers, 16.7 g/ day. These rates were taken from a study in the state of Michigan (8). In choosing to use these values, EPA made the critical assumption that anglers in the Lake Michigan watershed eat only "recreationally" caught fish from Lake Michigan, even though the study by West et al. included all freshwater sources. Thus, the extrapolation of these consumption values to anglers in the Great Lakes basin assumes that all anglers in the Great Lakes watershed eat as much recreational fish as do anglers in all of Michigan, and that all anglers in the Great Lakes watershed eat only Great Lakes fish. These two assumptions are not supported by other existing studies. For example, Wisconsin anglers reportedly eat considerably less recreationally caught fish, about 12.3 g/day (9), and most of them do not fish the Great Lakes [10). Similarly, those anglers who fish Lake Ontario reportedly eat only about 4 g/day of Lake Ontario fish {11), about one-fourth the daily ration of

fish assumed for Great Lakes watershed anglers. Thus, these other studies suggest that the EPA's assumed consumption rates are much higher than likely. Fortunately, consumption rates for Michigan anglers can be checked against numbers offish caught in Lake Michigan. EPAs exposure assessment for Lake Michigan is based on 42,853 low-income minorities, 33,900 other minorities, and 980,011 other sport anglers estimated to reside in the watershed. Thus, EPA's exposure assessment assumed the following rate of fish consumption from Lake Michigan: Low-income minorities: 42,853 people x 0.0431 kg/ day x 365 days/year = 674,000 kg/year Other minorities: 33,900 people x 0.0110 kg/day x 365 days/year = 137,000 kg/year Other sport anglers: 980,011 people x 0.0167 kg/ day x 365 days/year = 5,974,000 kg/year Total fish consumed = 6,785,000 kg/year Data on the number of fish caught (12), however, indicate that Lake Michigan recreational anglers catch only enough to supply about 2,200,000 kg per year offish on the table, because about threequarters of fish mass is lost during gutting, cleaning, and cooking (13). Thus, the Benefits Analysis is based on a rate of consumption estimated to be 310% higher than the reported catch. Fish contamination The Benefits Analysis bases the concentrations of chemicals in Lake Michigan fish primarily on data for lake trout. However, these fatty fish are at the top of the food chain and have concentrations of lipophilic chemicals that are 2-20 times higher than those in other recreationally caught fish. Therefore, conclusions drawn from lake trout data significantly overestimate the risk to anglers. To accurately portray this risk, the chemical exposure must be based on the mix of species actually eaten. According to EPA'sfishcatch ("creel") survey (14), chinook salmon make up 37% of the catch, and 25% is made up by yellow perch. About 70% of the catch is salmonids (lake, brown, and rainbow trout, and chinook and coho salmon); perch and walleye make up most of the rest. Assuming that the average salmonid tissue can be estimated by the chinook salmon data and that the yellow perch have, on average, about one-third of the chemical concentrations found in the walleye, the average concentration for Lake Michigan fish can be estimated by the following equation: Avg. concentration = 0.7 x chinook salmon + (0.25 walleye/3) + (0.05 x walleye) VOL.31, NO. 1, 1997 /ENVIRONMENTAL SCIENCES TECHNOLOGY/ NEWS • 35 A

Thus, EPA's methods assume that the current sources of the banned pesticides, which were dispersed widely in the environment and which are now Chemical concentrations in Lake Michigan fish banned, would be similar to source dynamics for Comparison of chemical concentrations in fish used in the Benefits compounds that remain in use today. Of this group, Analysis compared with those found in cooked Lake Michigan fish the use of cadmium, lead, and mercury is espe(73). All concentrations are in mg/kg, wet weight. t-DDT cially misleading; these are naturally occurring heavy concentrations are the sum of DDT, DDE, and DDD concentrations, metals that are unlikely to approximate the source and t-chlordane concentrations are the sum of a- and g-chlordane, dynamics of a group of anthropogenic, hydrophooxychlordane, and cis and trans nonachlor. Chinook salmon bic, banned chlorinated pesticides. The inclusion of concentrations are average values for charbroiled and baked with cadmium is particularly inappropriate and also cruskin on and skin off from Table S-4 (13\. Walleye values are average cial to EPA's analysis. It is inappropriate because cadfor baked, charbroiled, and deep fat fried from Table W-5 (13). mium is not considered a problem in the Great Lakes Average Lake Michigan fish = 0.7 x chinook salmon + 0.25 x walleye/3 and will, consequently, not have its loading re+ 0.05 x walleye. duced by the GLI. It is very important because cadmium has, by far, the highest point source loading t-DDT t-Chlordane Dieldrin PCBs Toxaphene of the four chemicals—15 to 40% of total loading due to point sources—almost exactly an order of magBenefits Analysis 0.27 Concentrations (mg/kg) 0.47 0.10 2.00 0.96 nitude higher than that found for the more logical Cooked chinook (mg/kg) 0.51 0.18 0.90 0.28 0.09 surrogate, PCBs. 0.10 0.04 Cooked walleye (mg/kg) 0.23 0.03 0.01 PCBs are closer to the pesticides in chemistry and Average Lake Michigan history. According to the unpublished data production fish (mg/kg) 0.37 0.13 0.07 0.66 0.20 presented by EPA (4, Table 5.1), only 1.7-3.8% (54 kg/ EPA/average fish (%) 130 210 150 300 480 year) of total PCB loading to the lakes in 1992 could be attributed to U.S. point sources. More recent estimates of loading, presented in Table 4.5 of the Benefits Analysis, suggest that point sources now conConcentrations used in this equation should also take into accountfishpreparation. Zabik et al. (13) stud- tribute only 27.7 kg/year, producing current point ied the contaminants infishprepared and cleaned by source contribution of 0.8-1.9% of total PCB loadmethods likely to be used by Great Lakes anglers. Their ing. In contrast, on a mass-weighted basis using total loading data for each Great Lake from Strachan samples were also geared toward fish sizes similar to and Eisenreich (15), the point source contributions those found in creel surveys; this is important beassumed in the Benefits Analysis indicate that 8.2cause chemical concentrations depend onfishsize. Average concentrations for Lake Michigan chinook salmon 13% of total PCBs loading to the Great Lakes is comand walleye, as well as the values used in the GLI Ben- ing from point sources. Thus, EPA's assumed point source contributions are about an order of magniefits Analysis, are presented in Table 1. tude higher than warranted by the relevant data. As shown, using concentrations in species actually caught and in fish as it is actually eaten produces The usage history of the banned pesticides also substantially lower chemical concentrations, and lower provides no evidence for significant point source conexposure levels, than the concentrations used in EPA's tributions. Dieldrin, and its precursor aldrin, were Benefits Analysis. The overestimates ranged from a low used widely on corn in the Great Lakes states (16), of 1.3 for DDT to a high of 4.8 for toxaphene. On avso nonpoint sources are likely to be very signifierage, EPA overestimated fish concentrations, the risk cant. Toxaphene inputs also should be dominated by offish consumption, and the benefits of avoiding those nonpoint inputs. There are not likely to be signifirisks by approximately 250%. cant point sources of toxaphene to Lake Michigan, because none of the major manufacturers of toxaphene were in the Great Lakes basin (16,17). The lack Point source contributions of point and aquatic nonpoint sources on the Great GLI benefits accrue from reductions in external loadLakes has, in fact, been used to demonstrate that toxing to the lakes, calculated as the product of point aphene inputs are almost exclusively via atmosource reductions multiplied by the percent of total loading caused by point sources. Although PCBs and spheric transport from agricultural uses in the southern United States (17). 2,3,7,8,-tetrachlorodibenzo-p-dioxin (TCDD) make up almost all the EPA cancer risk, both compounds Clearly the use of loading data for these pestiare already so tightly controlled that neither was precides would be the best approach for estimating their dicted, in the watershed Benefits Analysis, to uncurrent point source contributiorfs. Reliable data for dergo any reduction in loading after the GLI. Thus, most of these pesticides, apart from DDT, are limthe benefits were based on reductions in the banned ited. Total external loading to the Great Lakes is about pesticides: DDT, chlordane, toxaphene, and diel580 kg/year of DDT and its breakdown products (15). drin. For these pesticides, EPA "assumed" that point EPA's random sampling of point sources across the sources contribute 5-10% of total external loading to Great Lakes basin estimated that point sources conLake Michigan. According to the Benefits Analysis, tribute a total of about 4.6 kg/year (Table 4.5 of the this value is based on two sets of data: unpublished Benefits Analysis), about 0.8% of total DDT loading— EPA-collected data for four widely used industrial substantially less than EPA's estimate of 5-10% for compounds (cadmium, mercury, lead, and PCBs) and DDT and the other pesticides. Thus, the point source point source contributions estimated by Strachan and contribution of 5-10% assumed in the Benefits AnalEisenreich (15) for PCBs and lead. ysis is too high by a factor of 6.3-12.6. ConservaTABLE 1

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tively assuming the former adds another 630% error to the estimated benefits. Fish concentrations and current loadings Another Benefits Analysis assumption is that present chemical concentrations in fish are in equilibrium with total external loading and that future concentrations will rapidly equilibrate with future loading. This assumption implies that a given reduction in external loading translates, immediately, into the same reduction in fish concentrations. But this ignores the complexity of chemical interactions within the lake ecosystem. It is also contradicted by much observational data and theory suggesting that the sediments and water column act as long-lived reservoirs for chemicals [18-22). The long residence time of chemicals in the Great Lakes and resulting lags in system response to reductions in loading are actually one of the primary bases for the GLI (23). Why is this lag relevant to an attempt to estimate benefits resulting from the GLI? The chemical concentrations currently measured in fish have not yet caught up with reductions in loading that occurred over the past two decades or so. Because current fish concentrations may be 2, 3, or more times higher than current loading will support, further cuts in external loading will have a lesser effect than that assumed by the Benefits Analysis. Consider the case of Green Bay. According to data presented in EPA's modeling, PCB loading in 1989 was only sufficient to maintain water concentrations at about half of that actually measured. Thus, reducing loading by 9.4% would have only half that effect, e.g., 4.8%, on the final water concentrations in Green Bay. A recent mass balance for Lake Michigan (24) and mathematical modeling (25) suggest that PCB concentrations in the lake have not reached a steadystate with external loading. The mass balance estimated that total PCBs losses from the lake in 1991 were more than four times higher than total external loading, suggesting that much of the total loading is coming from PCBs stored in the sediments. Similarly, a mathematical model suggests that PCB concentrations in Lake Michigan lake trout are higher than can be sustained by current loading. According to this model (25), PCB concentrations in large lake trout are expected to fall about 340% even if external loading remained constant into the future. Because smaller recreationally caught fish are likely to respond more quickly to changes in external loading, a conservative estimate of current disequilibrium between loading and contamination for the average food fish would be about 200%. Cancer slope factors Lastly, the Benefits Analysis uses EPA's cancer slope factors (CSF) as predictors of the most likely events. However, CSFs purposely overestimate most likely cancer risk (26-28). The net effect of this conservative approach will be estimated for PCBs, which represent the bulk of the EPA calculated cancer risk. The CSF for PCBs is based on liver tumor data for female rats from Norback and Weltman (29). This CSF ignores observed suppression of cancers in other tissues (30); the male rat data from this same experiment, which showed almost no response (31,32); data

from other experiments (33,34); and current methods for classifying tumors (31). In each case, these exclusions result in an overestimate of the cancer rate compared with that predicted by the whole data set. Looking only at liver tumor data for all valid experiments, Smith et al. (35) calculated an upper bound potency of 1.9 (mg/kg/dayT1 for Aroclor 1260, about 25% of the value used by EPA. This CSF applies to Aroclor 1260, and other PCB formulations have proven to be either less carcinogenic (30) or not carcinogenic at all (35). Because only about 25% of the PCBs in Lake Michigan fish are Arochlor 1260 (36) with lesser proportions in the sediments (37), applications of a cancer potency factor for Aroclor 1260 to PCBs found in fish, again, probably overestimates most likely cancer incidence resulting from eating fish. To translate dose in lab animals to dose in humans, CSFs also rely on a conservative body weight scaling factor that also is likely to overestimate risk. Currently, CSFs are based on a ratio of body weights of humans to laboratory animals scaled to the (1/ 3)"1 power, a value EPA itself no longer recommends as valid (38). Other federal agencies (e.g., the Food and Drug Administration) converted dose using body weight without scaling at all. If EPA's new proposed scaling factor of (1/4)"1 is correct, use of current CSFs overestimates risk by factors of 5593%, depending upon whether rats or mice were used in the toxicological studies. On the other hand, in those cases in which the appropriate scaling should be body weight without scaling, the CSF overestimates likely risk by factors of 6-14, again depending on whether the critical studies are based on rats or mice. Assuming that scaling to the (1/4)"1 power is correct half the time and that half the potency factors are based on mice and half are based on rat bioassay suggests a geometric mean overestimate of about 400% [i.e., (1.55 x 1.93 x 6 x 14) ~25]. The CSF is also based on the upper 95% confidence interval for the slope as compared with the most likely slope, which represents another systematic error when attempting to estimate likely cancer rates. Most likely cancer estimates for a number of Great Lakes pesticides and PCBs ranged from 1.3 to 6 times lower than the 95% upper confidence limits, when both were estimated with the linearized multistage model (39). A value of 200% appears to be a reasonable average estimate for this error. To calculate the error inherent in using a CSF to predict likely cancer incidence, the following values were used: 200% error for use of the 95% upper confidence limit, 400% for the conservative body weight scaling factor, and 400% for the systematic exclusion of contradictory data. This produces an average overestimate of 3200% compared with most likely estimate using all appropriate data. By comparison, other attempts to quantify the discrepancy between the EPA's cancer potency factors and the true most likely estimate have found ratios of 4300 (Sielkin et al., quoted in 40) for dioxin, and about 1.4 billion times for formaldehyde (41). With specific reference to cancer risks posed by consuming PCBs in Great Lakesfish,the Michigan Environmental Science Board (27) concluded that EPA's default methods probably overestimate likely cancer risk by "orders of magnitude." V0L31.N0. 1, 1997/ENVIRONMENTAL SCIENCES TECHNOLOGY/NEWS • 37 A

Risks overestimated EPA's Benefits Analysis estimated between 17 and 34 cancers would be averted over 70 years for Lake Michigan fish consumers. But the product of the combined errors reviewed above gives a total estimation error of about 312,000%. Correcting for the 312,000% error produces more likely cancer reductions of between 0.005 and 0.011 cancers over the next 70 years. Assuming that the remainder of the watershed is similarly overestimated, the total cancers averted will not be 25 to 47 over the next 70 years, as suggested by the Benefits Analysis, but between 0.008 and 0.015. This corrected estimate produces a range of likely yearly benefits of $230 to $2140, using the value of $2-10 million of benefit for each statistical life saved (4). Comparing the midpoint of the likely benefits with that of EPA's estimated costs of 460 million-$380 million per year— $1186 per year in benefits versus $220 million in costs— produces a median cost-benefit ratio of about 185,000 to 1. This represents a benefit of about $5 for each $1 million invested in pollution control. Over the longterm, one cancer should be averted sometime between now and the year 8086 after an expenditure of about $1.3 trillion. In a specific sense, this review suggests that the GLI should be reconsidered because its costs will likely dramatically exceed its benefits. In a general sense, tiiis analysis illustrates the problem of estimating the benefits of environmental regulation, as well as the specific problem of having an agency review its own policies. I present this critique to spur thought and open debate on these important issues. Acknowledgments This work was supported, in part, by the Occidental Chemical Corporation. I thank Ruth Anderson, Steve Jones, John Westendorf, Alan Weston, Jim Wilson, and Bob Tardiff for their comments. Four anonymous reviewers and the editor were also especially helpful.

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(5) (6) (7) (8) (9) (10) (11) (12)

(13)

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