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Internal SFUND Box Number _36 OF _283 

Initials/Date: LDS__/_3-15- 2007_ 
T P.2 

United »« . / D ^ ^ ~ f^-J^^-S 

Environmental Protection 

Agency 

&EPA OFFICE OF SOLID WASTE JANUARY 1985 

DRAFT REPORT 

LINER LOCATION 

RISK AND COST 

ANALYSIS MODEL 

M 
f y . .. 

• LINER LOCATION RISK 

| AND COST ANALYSIS MODEL 

-"- DRAFT REPORT 

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/ _ -

; SUBMITTED TO THE 

1 . . -

| • - " " .- OFFICE QE SOLID WASTE 

ECONOMIC ANALYSIS BRANCH 

U.S. ENVIRONMENTAL PROTECTION AGENCY 

(Under"Contract No. 68-01-6621) 

EPA Project Officer 

Cliff Rothenstein 

JANUARY 1985 

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EXECUTIVE SUMMARY 

The Liner Location Risk and Cost Analysis Model estimates the chronic risk 

to human health from land.disposal of hazardous wastes under different 

technology, location, and waste stream scenarios. It also estimates the 

cost of different designs and sizes of landfills and surface impoundments. 

Together, this cost and risk information enables EPA to investigate the 

cost/risk and cost-effectiveness implications of various technology, waste, 

and "location-standards. -

This report documents the first phase of.the model's~.development. It 

describes the basic model andvthree policy applications pf the model. The 

EPA project team is currently revising several components of the model and 

expects to make additional revisions in response to reviews of this report. 

The team will .also perform additional policy, analyses.- Thus, the 

conclusions presented here-are preliminary and" exploratory. Furthermore,! 

while the report and its appendices provide a sound fundamental explanation 

of the methodology and structure of the model,_ they are not entirely up to 

date on all-points,, since the model is currently being improved. EPA 

expects to prepare a second report explaining improvements in the model and 

the results of additional applications. 

This summary provides a general description of.the model, its structure, 

inputs, and outputs; a brief discussion of the three applications; and our 

plans for the future of this project. 

1. THE LINER LOCATION RISK AND COST ANALYSIS MODEL COUPLES 

- A RISK AND A COST MODEL 

The Liner Location Risk and Cost. Analysis Model-links a risk and-a cost 

model. The risk model simulates the chronic risk to human health from land 

disposal facilities (landfills and surface impoundments) with different 

design technology, location, and waste stream combinations. It integrates 

a series of submodels and algorithms that trace constituent releases from 

1 
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landfills and surface impoundments to their movement through the air and 

ground, then to resulting human exposures, and finally to the resultant 

human risk. To do so, model components predict: 

• Releases to groundwater and subsurface transport. A failure "and 

release submodel estimates facility failure and the quantity of 

leachate released; an unsaturated zone algorithm calculates the 

time required for the leachate to reach an underlying aquifer; 

and a saturated zone submodel calculates the time and 

concentrations of constituents reaching a down-gradient well. 

• Releases to air and atmospheric transport. A volatilization: 

algorithm calculates the quantity of constituents that volatilize 

over time; an atmospheric transport algorithm calculates the 

concentrations of these constituents at the exposure points. 

• v Human exposurey An exposure algorithm calculates the exposure 

• - ' ." from drinking water and from .breathing constituents" in air. 

• Health risks. A hazard estimation submodel calculates expected 

cancer and noncancer risks from the exposures. . 

The model calculates risk over a 400-year time horizon. In doing so, it 

embodies many assumptions: facilities operate for 20 years with a 30-year 

post-closure period; contamination goes undetected and uncorrected;" 

multiple contaminants do not interact; and few constituents degrade over 

time, with degradation beginning only after facility-failure. The model" 

also assumes that aquifers are homogeneous and isotropic. In.general, we 

believe that the model overestimates risk. 

The companion cost model estimates the costs of land disposal facilities 

with differing technologies and sizes. The results of the risk model 

combined with cost data from the cost model provide EPA with the capability 

to perform cost/risk and cost-effectiveness analysis. 
P.6 

1.1 Risk Model 

The failure and release submodel estimates the probability and time of 

failure and the quantity of subsequent leachate release through the use of 

a Monte Carlo simulation model. The model uses a "fault tree" structure;. 

that is, it traces each possible failure event (leakage from the.facility) 

from all possible Combinations of more elementary events which could 

combine to cause failure: infiltration of liquid, liner failure, etc. The 

model assumes that each of these elementary events occurs at random, 

following specified probability.distributions. The failure probabilities 

over time are the average of probabilities for a-large number of 

facilities. Using this fault tree analysis, the model" predicts the year of 

failure and the release rates for ten different landfill and surface 

impoundment designs in five different climates. Liner arid cover type and 

material define facility designs, while average net infiltration of 

moisture per year and depth to ground water correspond to Climate type. 

In the release component of the submodel, we assume that-ch'ssolutionin -f 

leachate releases waste constituents to ground water and that - •: . '"-

volatilization releases constituents to air. Although the-failure submodel 

is stochastic and provides a probability distribution for liner failure, 

the "downstream" exposure modeling components are all deterministic, and 

thus produce risk estimates for a given release rate starting at a specific 

time in the simulation period. To link the failure component-of the .model 

with the subsequent exposure submodel, we used the convention-that release- . 

to the unsaturated zone begins to occur when the probability of .failure 

"exceeds 0701. Preliminary sensitivity analysis shows that over the 

400-year simulation period, risks are not very "sensitive to the probabil-ity 

of failure selected to trigger releases. 

The submodel performs a yearly mass balance to simulate the release of 

constituents. The annual potential release mass to groundwater "is equal: to 

the leachate volume multiplied by the aqueous solubility. Potential 

release mass to air is calculated using empirical formulas for 

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volatilization rate. After failure, release of constituent occurs until 

all of the mass has been leached or volatilized from the facility. 

Although the failure and release submodel predicts different probabilities 

of.failure and average-release volumes for different designs, the submodel 

does not remove a. corresponding amount of constituent mass from facilities 

with intact leachate collection and removal.-systems.. Because single-lined 

land disposal facilities generally fail sooner than double-lined 

facilities, the submodel may understate the contribution of delaying liner 

failure to-reducing risk. 

The exposure modeling for the groundwater route examines both the 

unsaturated.zone.and the saturated zones. It uses the McWhorter-Nelson 

wetting front equation to calculate the delay from the time liners fail to 

the time that- the leachate comes in contact with an underlying aquifer. 

The mass breaking through the unsaturated zone then disperses through and 

dilutes_in groundwater. Using an adaptation of Prickett's Random-Walk 

Particle Tracking Model, we model groundwater concentrations over a 

400-year time'horizon at distances corresponding-to locations of wells." We 

calculate .these concentrations for nine different groundwater flow 

scenarios that involve variations in aquifer configuration and velocity; 

all scenarios apply only to homogeneous, isotropic aquifers. 

The rate of flow of the groundwater and retardation caused by adsorption to 

organic carbon in the earth materials govern the transport of constituents 

"through the unsaturated and saturated zones. Retardation calculations use 

the Freundlich isotherm algorithm, which assumes direct proportionality 

between^constituent velocity (relative to the groundwater front) and the 

water: organic carbon partition coefficient. 

To estimate the transport of volatile constituents, we used the OTS 

"Atmospheric Transport Model (ATM-SECPOP). We calculated annual average 

ground level concentrations at ten sample scenarios that represent 

meteorological conditions at locations in the U.S. to determine whether 

site-specific differences in meteorology result in significant differences 

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in estimated concentrations. They did not; the site-to-site variation in 

concentrations was small and concentration was linearly proportional to 

emissions rate. We thus calculated a linear scaling factor to translate 

volatilization rate into concentrations at various distances from the 

source, and then used these factors to estimate annual average ambient air 

concentrations for populations exposed to emissions of volatile 

constituents. 

The groundwater concentrations cause exposure doses as a result of the 

assumption that all receptors drink two liters of water per day. Air :. 

concentrations cause exposure doses as a result of the assumption that -

receptors have, an air intake of 22 cubic meters per day. In both cases we 

assume the average weight of receptors is 70 kg, and in most cases we 

assume equal absorption through all exposure routes. The lifetime dose is 

the running 70-year average dose. 

To.produce a risk estimate; we multiply dose by a dose-response factor.: The 

hazard submodel uses the same risk estimation formula as the OSW Risk/Cost 

Analysis Model. The Liner'Location Risk and Cost Analysis Model uses 

continuous functions to model potency for these threshold pollutants; these 

functions.predict less risk below no-effect levels than more traditional 

methods such as acceptable daily intakes (ADIs) would predict. Thus, while 

we treat risk from carcinogenic contaminants in a manner consistent with 

traditional EPA methods, our approach to contaminants which pose threshold 

risks differs from the traditional approach. 

The hazard submodel, reports-risk"estimates as average risk (i.e., the 

time-weighted lifetime risk over the 400-year period) and maximum risk 

(i.e., the risk for the-70-year period with the highest running average 

exposure). By using population data, the submodel can also calculate the 

additional number of cases of adverse health effects over the 400--year 

simulation period. 

Finally, a single computer model links all the algorithms and submodels 

described above. 

iwrwuw n w' '«g>°y-ay>-- w ~ >• -nqpiinn i 
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1.2 Cost Model 

To calculate costs for landfills and surface impoundments we: 

-t Specified designs and sizes; -• y 

• Estimated the engineering costs for those designs and sizes; and 

t Discounted the engineering costs, to produce comparable economic 

• measures. 

We used EPA's .Facilities Design Computer Cost Model to estimate 

const-ruction and closure costs for landfills and surface impoundments of 

different liner configurations" and varying sizes. In implementing the 

model, we estimated initial capital costs (land, constructing the first 

year's cell for landfills or excavating"and installing liners for surface 

impoundments, building the infrastructure, etc) , annual capital costs 

(building the next year's cell and closing.the last year's cell for 

landfills), closure costs, (covering the final cell for landfills or" ~ 

covering the surface impoundment, .decontaminating equipment, monitoring, 

and certifying closure), and"O&M.costs associated with the technical 

aspects of operating the facility. .For surface impoundments, we also 

estimated the frequency and cost of dredging. Since our costs were 

developed"to compare relative technology costs, we did not include O&M 

costs for recordkeeping, reporting, financial responsibility, or any other 

costs that do not change as the stringency of liner regulations changes. 

Thus, for a particular-liner designyour costs underestimate the total cost 

of disposing of hazardous waste. ""••-• . • ~ 

Important assumptions underlie these engineering cost estimates. First, we 

assumed that facilities are able to use on-site, recompacted clay in all 

designs which require clay. If they are unable to do so, engineering costs 

will-be from 12 to 53_percent greater than our calculations indicate, 

depending on facility design and size. We assume that all surface 

impoundments and smaller landfills are on-site and will not require fences 

and gates, office buildings, scales, and equipment that the larger off-site 

facilities will require. 

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To convert engineering costs to economic measures we calculated total 

present values for each facility design and size by discounting the 

engineering costs in each year of the facility's life and summing the 

discounted costs over all years. We used a three percent real discount 

rate to calculate present values. 

OSW's standard assumptions for economic analysis pertaining to facility 

life and operating procedures applied to the cost model: surface 

impoundments and landfills both operate for 20 years; operators open the 

first cell in a landfill at the beginning of year one and cover it at the 

beginning of year two, and cover the last "cell at the beginning of year 

21; and operators line surface impoundments at the beginning of year one 

and cover them at the beginning of year 21. 

After calculating the present values, we also annualized them. Costs are 

often unevenly distributed through time; annualizing spreads them evenly 

over the ltfe'of the facility. We annualized by multiplying the present 

value af each^facility size and design by a capital recovery factor. With 

a three percent real rate of return and a "20-year facility life, the 

capital recovery factor is 0.0672. 

Finally, we calculated the annualized present-value oh a per.unit basis by 

dividing the annualized cost for each facility size and design by its 

capacity. This results in annualized costs per ton for landfills, and 

annualized costs per acre and per gallon for surface impoundments. 

2. APPLICATIONS FOR THE MODEL EVALUATE THE COST/RISK IMPLICATIONS 

OF TECHNOLOGY STANDARDS AND COMPARE RISKS OF DIFFERENT 

ENVIRONMENTAL SETTINGS AND DIFFERENT WASTES 

We have applied the Liner Location Risk and Cost Analysis Model on several 

occasions, both to test and debug it and.to use it for policy analysis. 

Given the complexity of the model and restrictive time schedules, we often 

performed the policy analysis closely following and sometimes concurrent 

with testing and debugging the model. Also, those instances where we know 
P.11 

the distributions around input values, we have not carried this information 

through to final estimates but have only determined point estimates. In 

other instances, we do not currently have estimates of the distribution of 

values, and have not performed sensitivity analyses to determine how 

changing values would change our risk estimates. Therefore,' we have not 

yet calculated error bands or confidence intervals for the risk and cost 

estimates." We therefore, view the results of the first three sets of 

applications as tentative and exploratory rather than conclusive. 

In the first application, we evaluated national technology standards from a. 

cost/risk perspective; inthe second we compared- the risk of environmental 

settings, holding technology and"waste streams constant; and in the third, 

we compared the risk of different waste .streams, holding technology-and 

environmental setting constant. In-general, we found:-that-risks of land 

disposal vary widely depending on wastes, environments, and technologies. 

We also found that risks are more sensitive to wastes and environments than 

they are to technology. J -..-" - 1 

2.1 Evaluating National-Technology Standards - . -• 

In this application of the Liner Location Risk and Cost Analysis Model, we 

used two different sets of input-data. The first set represents a cross 

section of 17 landfills and 31 surface impoundments using actual data for 

the facilities wherever possible. While we fhirvk-these s.ites comprise a 

reasonably representative sample of landfills and surface"impoundments, 

they are not a statistically valid random samp-le. ... -

:..... - . -

Among the "actual sites," only two of the landfills and five of the surface 

impoundments.have nearby populations using ground water as their source of 

drinking water. Of these, only one landfill and three impoundments show 

any risk, even for the unlined design. Moreover, more stringent liner 

designs (single, double, and triple liners) provided little incremental 

risk abatement at these facilities. Consequently, requiring liners at all 

of these facilities would result in a ^ery high cost per case avoided. 

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Because these estimated risks are largely driven by the number of 

receptors, we repeated the analysis using 44 additional landfill sites and 

assuming that receptors exist at all sites. (Figures showing these results 

are labeled "Augmented Sites.") 

Among the sites augmented with hypothetical populations, risks are 

substantially larger. "Almost two-thirds of the unlined facilities which 

were modeled showed some level of risk, although most of this risk was 

concentrated at a small number of sites and slightly more than one-third of 

these unlined facilities had no risk. Further, the results indicate that 

liner technology is not particularly effective in abating these risks at 

all modeled sites. Even so, combining technology cost information with the 

risk information, suggests that the cost/risk ratios of requiring liners at 

all modeled sites.is favorable. However, tailoring the requirements to 

site-specific factors that increase risk rather than requiring the same 

standards for all facilities could provide even better cost/risk ratios. 

2.2 -Comparing the Risk of Environmental Settings 

In this application we examined the effect that environmental setting has 

on risk. Holding technology constant (double synthetic liners) we examined 

the distribution of risk to exposed populations under varying climate, 

hydrogeologic setting, and well distance scenarios. Thus, for three waste 

constituents (chromium, carbon tetrachloride, and parathion) we examined 

risk to individuals under 135 possible combinations of environmental 

setting (five climates, nine hydrogeologic settings, and three well _ -

distances). We performed the simulations for landfills and for. surfaceimpoundments. 

The. results indicate that differences in environmental settings lead to 

large differences in risks to exposed individuals from disposing of a waste 

stream "with a given management"practice and technology. Approximately 

one-third of the scenarios for chromium in surface impoundments produce 

risks of 10" (one in ten) to exposed individuals while about one-third of 
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the scenarios produce no risks. For landfills, almost 40 percent of the 

scenarios produce risk < 

produce no risk at all. 

scenarios produce risk of 10" , but about 25 percent of the scenarios 

The results for carbon tetrachloride show a similar pattern of both high 

and low risk. However, the overall risks are lower (nearly three-quarters 

of the scenarios produced no risk) because carbon tetrachloride is less 

mobile than chromium and exposures occur in fewer scenarios. 

None of the parathion scenarios result in any exposures; due to its low 

mobility and high rateof degregation, no significant concentration breaks 

through the unsaturated zone during the simulation period. 

In addition to showing that environmental setting causes large differences 

in risks, this application also begins to suggest how the three 

environmental factors we varied are important in determining risk. First,_ 

drier climates "produce less risk because there is less leachate "and 

therefore releases after failure are smaller". Next, the results illustrate 

the effect of distance on risk as zero risk scenarios are far more likely 

• at" longer distances from wells. Finally, in comparing scenarios with, y . 

slow-moving aquifers to scenarios with faster ones, we observe that for -

persistent constituents in the fast aquifers, the peak,and average 

constituent concentrations are lower, the period of exposure is shorter, 

and the average risk ranges from two to as much as five orders of magnitude 

lower. For degradable constituents, the period of exposure is shorter in -'-• 

fast aquifers but the peak"and average concentrations may be higher and 

consequently, risks may also be higher. -;- - . '••:_ -.-

In summary, this application shows that risks are extremely sensitive to 

environmental setting. Juxtaposed with the evaluation of national 

technology standards, it shows risk is far more"dependent on environmental ; 

setting than on liner technology. 

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2.3 Comparing the Risk of Different Wastes 

To compare the risks of different wastes, we simulated risks for 15 waste 

Streams in landfills and 30 waste streams in surface impoundments, holding 

design," liner technology, and environmental setting constant. We selected 

waste streams by examining responses to OSW's mail survey. We modeled the 

risk for a waste stream either in landfills, surface impoundments, or both 

if (1) it appeared in landfills,, surface impoundments, waste piles, 

injection wells, or land treatment as one of any facility's ten largest 

waste streams; (2.) it can be managed in landfills or surface impoundments; 

and (3) we could characterize its constituents and find the physicochemicai 

properties.necessary to simulate its risks. 

Our re.sults showed that there is wide variability in risk for different 

waste streams holding all other factors constant. In landfills, eight of 

15 wastes we modeled showed average risks of less than 10 (one in a ; 

biTlion)-, yet all but one of the remaining seven waste streams showed risks 

- - -"-4 / • " ' ~ -

of 10 - (one in ten thousand) or greater. In surface impoundments, nine" of 

- _g 

- 30 waste streams showed risks of less than 10 , while 17 showed risks of 

_ 4 •'•'• . -

"10 or more.- - . 

This application juxtaposed with the evaluation of national technology 

standards indicates that risk is far more sensitive to changes in waste 

stream composition than to changes in technology. 

..'-'."_ ' i. -PLANS FOR THE PROJECT'CALL FOR IMPROVING THE MODEL, : 

: .VALIDATING IT, AND ISSUING A PHASE II. REPORT 

We have not currently completed all the sensitivity analyses, nor have we 

examined all the assumptions and limits to determine the constraints they 

impose on future use of the model for policy purposes. As the tasks are 

completed, EPA will issue a second report. 

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3.1 Improving and Validating the Model 

In building and applying the model we have noticed several areas that we 

can improve; basic areas of effort include the failure and release 

submodel, the subsurface transport submodel, the exposure submodel, the 

hazard model, and the cost model. 

In the failure and release submodel, we will (1) perform sensitivity 

analyses to determine how important the underlying, probability 

distributions are in determining failures and releases; ("2) modify the 

assumption that leachate collection systems remove water, but not hazardous 

waste from.facilities; ahd (3.) change the basic structure of the submodel 

so we can report statistics associated with the estimates of failure 

percentages and leachate volume releases. 

We are-also-working on ways to model constituent degradation prior to 

release from the site as well as other modifications to the estimates~of_:-' 

waste mass available to enter the unsaturated zone. 

The subsurface transport submodel will be expanded to consider-attenuation . 

in the unsaturated zone, dispersion into a third dimension, dilution of 

contaminants at the well site, and transport through fractured, not 

homogeneous and isotropic, aquifers. 

We "will also relax our worst-case assumptions about exposure: first, that 

peopledrink contaminated water, even if contaminants exceed their odor, 

taste, and physical appearance thresholds; and second, that groundwater " 

monitoring is not in place. 

In the hazard submodel we will further evaluate some of the basic 

assumptions underlying the risk estimation algorithm for noncarcinogens, 

compare our risk estimates with those derived by other methods, and 

ermine the sensitivity of results to changes in input values. 

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In the cost model, we will include the cost of treating leachate from the 

facility, whether on or off-site, the cost and effectiveness of taking 

corrective or remedial actions as well as the cost of repairing or 

replacing covers and other facility components. 

Because of the difficulty in measuring some of the complex processes we 

model, it is not possible to.verify directly the performance of the model, 

but we can infer the accuracy of several key elements by reviewing some 

types of empirical data. As one example, we plan to review results of 

ongoing air monitoring at landfills and surface impoundments in order to 

verify that-pur approximations of air emissions are realistic Some of the 

other material we.wi11 review includes data on effectiveness of groundwater 

monitoring and contaminant-concentration in groundwater at CERCLA sites. 

3.2 Phase II Report 

When we complete the work described above,-EPA will issue and circulate for 

peer-review the final-Liner Location Risk and Cost Analysis Model Report. 

This will present the model, modified to incorporate the improvements 

- discussed previously and comments from this first round of review. 

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