Expert systems for environmental problems Although 21 have been developed, few are in use today Judith M. Hushon Roy M. Weston,Inc. Mhington, D. C. 20024 Expert systems comprise a branch of artificial intelligence. Defined as “man and machine systems with specialized, problem-solving expertise,” expert systems rely on a data base of knowledge about a particular subject area, an understanding of the problems addressed within that subject area, and skill at solving these problems. Expert systems software was developed during the early 1970s and was initially applied to well-defmed problem areas. Gradually this software has become more robust and has evolved into domain-independent software that can facilitate the construction of applications. These expert system software tools are referred to as “shells.” Currently a number of these shells are available on microcompnters, and some come on minicomputers as well. The following types of situations are ideal candidates for expert systems solutions: situations that occur often, situations that are complex, situations that require knowledge of experts (higher reasoning), situations in whicb uncertainty is involved, situations that are dynamic, and situations that demand consistent responses. Waterman recently assemhled a list of 181 expert system applications, which are arranged in the 16 groups listed in the sidebar (I). This list is interesting because environmental systems are noticeably lacking. This omission can be attributed to two factors: Environmental expert systems generally require expertise in a number of areas, and the rules of thumb for environmental decision making are not ccdified. Nonetheless, expert systems are starting to be used to recognize and manage environmental problems. In general, expert systems can be divided into a number of functional categories: planning, monitoring and control, instruction, interpretation, production, diagnosis and repair, and design. Table 1 shows the environmental systems, 838 Environ. Sci. Technol.. Voi. 21, No. 9, 1987
classified according to this scheme. Note that no environmental systems were found that were devoted to monitoring and control, instruction, or design.
Interpretation systems In reviewing the environmental expert system activity, attention can be focused f i t on the systems developed primarily to provide interpretation. This category shows the greatest level of environmental expert system development. Within this category, the systems can be p u p e d by functionality: site assessment systems, permit generators, aquifer classification systems, and chemical emergency response systems. Site Bssessment systems. These systems define the extent of environmental damage resulting from hazardous wastes. Several thousand sites have been identified as part of the Superfund effort, and the goal has been to identify and quantify the hazards present. RPI site assessment system. This expert system helps to characterize a site by emulating the procedures an expert would follow prior to using the MITRE Hazard Ranking System (HRS). The production rules in this system are written in OPS5, and exterrial functions are coded in common LISI: a programming language particularly well adapted to artificial intelligence. This prototype system can produce an HRS score for site permeability and direction of groundwater flow. In the future, other HRS parameters will be included (2).
GEOTOX. This howledge-based expert system ranks waste disposal site remediation technologies for use at a specific site. The user first enters sitespecific information using key words. The system then updates its howledge base and requests further inputs. The system is written in Prolog and consists of more than 250 production rule. The system is designed to determine the contribution of each characteristic to the overall site hazard rating. The confidence of the user regarding the certainty of his or her inputs is also taken into account. The system has been tried
Application area? for expert system Manufacturing Mathematics Medicine Meteorology Military science Physics Process control Space technology Agriculture Chemistry Computer systems Electronics Engineering Geology Information management Law Source: Referenr
W15936X18710921-0W8~1.~/00 1987Arnerican Chemical Society
on two test scenarios. Further develop ment is being done, including the addition of computer graphics capabilities
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lbxic waste advisor. This expert system assists with the analysis of alternative remediition technologies applicable to hazardous-waste sites. Currently the system focuseson cleanup of sites where soil and groundwater have been contaminated with solvents or hydrocarbons. The system design is complete, and a prototype has been built using the TI Personal Consultant expert system shell on an IBM-compatible PC.System subroutines are beiig expanded and refined to improve their accuracy and agreement with expert judgment (5). DEMOTOX. This system focuses on estimating the potential for groundwater contamination. Sorption, biodegradation rates, transformation rates, recharge rates, and the seepage velocity of water through soil are used to model the passage of chemicals through soils and into groundwater aquifers. This system is written in the M.l shell language and is currently beiig evaluated. To date, 12 constituents have been ranked by the system and by experts. The system assigned slightly higher values for groundwater classification, but the constituents were in the same order (6). Permit generators. Permit generation is a natural application of expert systems; the data to be evaluated are similar from site to site, and the criteria for assigning a permit are specified by law. The purpose of these systems is to issue permits in a consistent manner following rigorous evaluation of the supporting data. Permit writer’s assistant. This system is designed to help pollutantdischarge permit writers in EPA regional ofices to prepare permits that are tailored to a particular facility. System modules have been developed to cover municipal sewage treatment plants, the fruit and vegetables industry, and metal f ~ s h i n gplants. Separate sections are included to help defme the discharging facility and the effluent discharges. This system NIB in an IBM-PC environment and is KES. It is currently being evaluated by EPA (7). RCRA permit generator. RCRA permits are required for all waste disposal sites. In most cases, these permits are issued by state agencies responsible for implementing RCRA provisions locally. EPA recently awarded a contract for the development of a system to ensure that these permit application data would be evaluated and that the permits would be issued in a uniform manner. This system is still in its early stages of development.
SEPIC. This system issues permits for on-site private sewage disposal systems. The system evaluates the situation to determine whether permit issuance is required and what regulations apply, whether an applicant can to a public sewer, and whether conventional septic tank systems can be used. It then recommends alternative types of disposal systems that may be applicable. SEPIC asks for site-spific information as well as local conditions. This expert system is presently beiig used to issue permits. The Rulemaster shell language was used to construct a set of interactive modules that make up this expert system (8). AQUISYS. This expert system classifies groundwater aquifers according to their vulnerability to contamination and their importance. AQUISYS has been developed using the most recent guidelines from EPA’s Office of Groundwater Protection. It is expected that such a structured methodology can determine the appropriate protection or remediation measures necessary for safeguarding groundwater resources in the near future. This system, which was built in KES for use on micros, is currently beiig evaluated. Emergency response lends itself to the application of expert systems because of the volumes of highly technical data that need to be evaluated and inteqmted to properly respond to an emergency involving chemicals. It is also import--- note that r--A fmt I-
responders generally are not expert in the disciplines required to understand the standard reference materials. lkro related systems, FRES and CORKES, represent the first emergency response expert systems. First Responders’ Expert System 0. This prototype system was developed in the KES shell supplemented with a dBasem+ data base and C interface routines. It provides information on the acute and chronic toxicity of the pollutants present as well as on the optimal response strategy. The nature of the incident, the chemicals present, and the site and meteorological conditions are taken into account. The system CUIrently is being evaluated by response personnel (9, lo). community Right-t*Know Expert System (CORKES). This expert system is based on the FRES modules, but it provides facility-specific information in the event of an emergency. An industrial facility enters data on the identity, lccations, and quantities of chemicals as is required by the Superfund Amendments and Reauthorization Act (SARA) right-to-know provisions, and CORKES can provide tailored emergency response information that can serve as part of the Community Emergency F’re paredness Plan (CEPP) for that facility. This system also supports comparison of a facility’s chemicals with those on the SARA list and helps with the preparation of the necessary papers to be filed with the local authorities. This ex-
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Envimn. Sci. Technol.. MI. 21. NO.9. 1887 839
pert system helps facilities comply with the S A R A Title III provisions by using the information they already have on their material safety data sheets.
Planning Planning is a traditional application area for expert systems, and the expert systems in the environmental area are very similar to those in other, more traditional fields such as computer system design and investment strategy development. Work assignment/work plan memo generator. This system facilitates the management of waste site cleanup operations. It relies on inputs concerning the nature of the site, including its location, the meteorological and soil conditions, and the surface and subsurface geology, as well as the wastes present there. This information has been reduced to a few “critical” questions. Based on this information, the system issues a draft work assignment and work plan. The application of this system has greatly speeded up completion of the initial paperwork associated with a site cleanup (11). SCEES. This prototype system relies on the data from the HRS included in the National Contingency Plan to identify work required on a waste cleanup site and to provide an estimate of the cost and a schedule to clean it up. Currently the system is only implemented for one type of waste site: landfills. The system uses the NEXPERT shell, which supports extensive windowing. LABSYS. This expert system helps environmental engineers select an appropriate analytical laboratory to evaluate a set of environmental samples. To select appropriate candidates, the system relies on a data base of information about laboratories’ capabilities, location, their willingness to undertake rapid turnaround work, and their accreditation. It also allows for feedback from system users with regard to rating past performance. Prediction A number of systems have been developed that attempt to predict the impact of certain actions on environmental management or environmental contamination. FLEX. Flexible membrane liners are used in landfills and surface impoundments to prevent migration of hazardous wastes into groundwater and surface water. Modules have been developed to predict the performance of three types of liner materials: highdensity polyethylene, polyvinyl chloride, and chlorosulfonated polyethylene. The system takes into account the properties of the liners and the materials and conditions to which they are 840 Environ. Sci. Technol., Vol. 21, No. 9, 1987
likely to be exposed. A Lotus 1-2-3 supervisory shell manages the Prolog modules. The system currently is being evaluated; the system’s results are being compared with those of human experts (12, 13). MUMS. The Multiple-Use Management Strategist is an expert system that assists in managing a multiple-use watershed. This system regulates the operation of reservoirs by incorporating the expertise of hydrologists and dam gate operators to maximize hydropower generation and water conservation. In addition, the system also has a goal to minimize environmental impacts of reservoir operation. This KES-based system is currently being validated against actual data. Eventually, it will act as an interface between several models and data bases performing a variety of related functions. QUALZE advisor. This expert system, developed using the M.l shell, suggests initial parameters for input into the QUAL2E water quality simulation model. Depending on the options chosen, the model can require more than 100 input parameters. The system relies on the knowledge of experienced users of the QUAL2E model to estimate the coefficients used in modeling stream temperature, the type of hydraulic model to be used, and its associated coefficients: biological oxygen demand removal, sediment oxygen demand, and re-aeration rate coefficients. In its present form, the QUAL2E advisor only handles one section of a river at a time and does not attempt to calibrate the recommended parameter values against measured water quality data. The system is being expanded to include coefficients related to the modeling of nutrients and algae and to handle multiple stream sections. The system’s developers plan to submit the system to evaluation and field-testing (14). Flood advisor. This system assists with the selection of an appropriate model for estimating flood conditions. The choice of flood simulation model depends on the importance of the engineering project, the consequences of failure, and the availability and quality of data. First, the user defines the assumptions to be used. Next, the system invokes appropriate procedures to ensure that each of these assumptions is met, The system then recommends the most appropriate model and makes suggestions for proper use. Depending on the responses during the session, the system may run external estimation routines. The state of validation of this model is unknown. The system is still being developed, and there are plans to incorporate numerical results into the reasoning mechanism and interactive graphics (15).
EXSRM. This expert system is used to estimate initial parameter values for input into the model for runoff from melted snow, a Fortran program that simulates and forecasts daily stream flow in mountain river basins. The model, which uses satellite data as input, has been successfully applied to a number of U.S. and European basins. Predictions are based on snow cover, daily temperature, and precipitation data. The expert system derives a number of secondary parameters from these data that are required by the SRM model. The expert system is built on a Symbolics 3670 using the ART shell. Interactive graphics and overlays display snow melt conditions. The system is still being developed (16). HAWAMAX. The Hazardous Waste and Management Expert System is being developed to provide advice about reducing health and environmental risks at hazardous waste sites. The Inference Module is written in LISP, and the RisWDecision Analysis Module (RIDAM) is being developed in Fortran 80. The RIDAM module provides risk assessment, risk management, and evaluation of the consequences in the risk management process. It actually consists of a number of small decision components. This system is still being developed as a prototype (17). Diagnosis and repair This is one of the traditional areas of expert system application. Most applications have been focused on mechanical or electronic systems to assist with troubleshooting. The environmental disciplines have some unique problems because of the broader range and reduced predictability in living systems and in the uncontrolled natural environment. Waste incineration. This prototype expert system diagnoses malfunctions in hazardous-waste incinerators. A fault tree analysis approach, coupled with uncertainty estimation techniques, is used to identify potential causes of malfunction. Fault trees model the decisions to be made. A person selects branches of the tree, depending on the conditions of the situation, and then moves out a branch to the end, which determines the action to be taken. The waste incineration system, which uses the M.l shell, was problematic to design because of the difficulty inherent in estimating failure probabilities for rare events. Currently, either the user can estimate the probabilities or the system will do it using a trapezoidal fuzzy set function. This system is still being developed (18). Activated sludge diagnosis. This prototype expert system facilitates the operation of an activated sludge waste-
Advisor (TWA) Expert System," internal Eport, 1986. (6) Ludvigscn, P. 1.; Sims, R. C.; Grenney, W. 1. In Proceedings of ASCE Fourrh Con-
ference on Cmnpuring in Civil Engineering, American Society of Chemical Engineers, New York, October 1986, pp. 687-98. (7) Spooner, C. S. In Proceedings, Experr Systems in Governmenr SynQosium; Karna, K. N., Ed.;McLean, Va.: MITRE Corp., 1985, pp. 573-77. (8) Hadden, W. I., Jr.; Hadden, S . G. In Erperf Systems in Governmenr Symposium; Kama, K.N., Ed.; McLean, Va.: MITRE
Corp., 1985, pp. 558-66. (9) Hushon, 1. M. Environ. Sci. Technol. 1986,20, 118-21. (IO) Hushon, 1. M. Resented at the 1% National Meeting of the American Chemical Society, New York, NY, April 1986. (11) Paquette, IS.; Woodson. L.; Bissex, D.A. In Proceedings, Superfund '86, Hazardous Materials Control Research Institute, 1986, pp. 208-12. (12) Rossman, L. A.; Haxo, H.E., Ir. In Pro-
ceedings. Envrronmenral Engineering Specialty Conference, Amcrican Society of Chemical Engineers, New York, 1985, pp,
water treatment faciity. It relies on quantitative data from instrument readings and laboratory results, as well as rules of thumb. The uncertainties that exist in the diagnosis of problems based on sometimes vague symptoms, and appropriate respnse for dealing with the effects of toxic substances on the plant's performance, are taken into account. The system is being expanded to include more extensive symptom-diag nosis relationships (19). Rogaapis It is interesting to note that the environmental expert systems reviewed above fall into only four of the traditional seven expert system categories: interpretation, planning, prediction, and diagnosis and repair. Design system often require a higher level of knowledge than currently may be feasible to program into an environmental expert system. Although monitoring and control systems are possible, the conversion of environmental monitoring data into automated decision system input is a complex task. Undoubtedly, inshuction systems will soon be surfacing in the environmental area.Their development lags a bit bebind the interpretation, diagnosis, and prediction systems, but it is inevitable. Table 1 shows that currently there are relatively few coxporate developers of environmental expert systems. As might be expected, they are supplemented by a number of universities, most of which have active environmental engineering departments. Table 2 shows that the programs used with these systems also differ significantly. Some developers, mostly nniversities, are using the programming languages themselves; commercial d e velopers appear more willing to rely on expert system shells. Among those using programming languages, some are
relying on traditional languages such as Fortran and C, whereas others are using the AI languages such as LISP and hlog. The power of the expert systems is determined to some extent by the hardware on which they are developed. The majority of the reviewed systems have been buiit on micros (almost exclusively IBM-compatible systems). The minicomputers offer greater power but also represent a significant increase in cost. In the future, the trend is l i l y to be toward minicomputers for develop ment of environmental systems requiring simulation modeling because of the demands of these models for computing power. Minicomputers also provide the potential for a more highly developed graphical interface. Despite the identification of these 21 expert systems, very few of them are presently in practical use. Many systems were developed at universities and have yet to be applied to real-life situations. For this reason, the systems developed by commercial companies are being applied more rapidly and therefore are being improved and adapted so that they can be of practical use in the business of environmental management.
583-90. (13) Schwope, A. D.; Ojha, H. E. "Prelimi-
nary Expert System for LinerMlaste Chemical Resistance"; internal interim report, U.S. Environmental Protection Agency, Hazardous Waste Engineering Research Laboratory: Cincinnati, Ohia, 1986. (14) Barnwell, T. 0..Jr.; Brown, L. C.; Marek. W. "Development of a Prototype Expert System for the Enhanced S t m Water Quality Mcdel QUALZE; internal report, U.S. Environmental Protection Agency, Environmental Research Laboratory: Athens, Ga , 19x6 ... . .
(15) Fayegh. D.; Ruswll, S . 0. In Expen Syst e m in Civil Engineering: Kostcm. C. N.; Maher. M.L..Ed%: 1986. DD. 174-81. (16) E n g m ? E. T;kango; A.; Martinec, 1.
In Proceedings, M e r Forum '86,American Society of Chemical Engineers, New York, 1986, pp. 174-80. (17) Shih, C. S.; Bernard, H. In Proceedings, Superfwul '86. Hazardous Materials Control Research InsuNlc. 1986. 463-64 (18) Huang, Y W et al lnxpcrr Syrrem tn Civil E ~ R ~ ~ w zKmtern. ~ R . C. N . Maher. M. L., &Is.; 198"6, pp. 145158. (19) Johnston, D. M. In Proceedings. Com-
purer Applications in Water Resources, American Society of Chemical Engineers, New York, 1985, pp. 601-06.
Reference3
(1) Waterman, D. A Guide ro Expert Sys-
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Judith M. Hushon is head of the Art$ciaI Intelligence and w e n System Department for Roy E Weston, Inc., where she supervises the development of expert sys-
Environmenral Ceorecknology,
tems in environmental engineering applicarionr a r e a . She has 18 years of experience in chem'col information management and in using chemkd informafionfor regurotOry support, risk assessmenr, and environmental decision nmking. She holds &grees in biology and biochem'stry and currently is working toward a Ph.D. in Management of Informntion Systems Tech-
1OPA
(2) Law, K. H.; Zimmie,
R. In Erpcrr Systems in Civil Engineering: Kostem, C. N.; Maher, M.L., Eds.; American Society of Chemical Engineers: New Ymk, 1986, pp. 159-73. (3) Mikroudis, 0. K.; Fang, H. Y.; Wilson, 1. L. la Proceedings, lsr lmernarional Sym-
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