612 Air Pollution - WIT Press · In a series of meetings with a panel of ex-perts in air pollution...

Multi-attribute decision theory

methodology for pollution control measure

analysis

A.S. Barrera Roldan," A. Corona Juarez," R.W. Hardie/

G.R. Thayer*

"Gerencia de Energeticos Alternos y Quimica Ambiental,

Instituto Mexicano del Petroleo, Apdo. Postal 14-805,

Mexico D.F., 07730, Mexico

*PO Box 1663, Mail Stop F611, Los Alamos National

Laboratory, Los Alamos, New Mexico 87545, USA

ABSTRACT

A methodology based in Multi-Attribute Decision Theorywas developed to prioritize air pollution control mea-sures and strategies (a set of measures) for MexicoCity Metropolitan Area (MCMA). We have developed aframework that takes into account economic, technicalfeasibility, environmental, social, political, and in-stitutional factors to evaluate pollution mitigationmeasures and strategies utilizing a decision analysisprocess. In a series of meetings with a panel of ex-perts in air pollution from different offices of themexican government we have developed General and Spe-cific Criteria for a decision analysis tree. Withthese tools the measures or strategies can be gradedand a figure of merit can be assigned to each of them,so they can be ranked. Two pollution mitigation mea-sures were analyzed to test the methodology, the re-sults are presented. This methodology was developedspecifically for Mexico City, though the experiencegained in this work can be used to develop similarmethodologies for other metropolitan areas throughoutthe world.

INTRODUCTION

Air pollution in the MCMA is representative of criti-cal air quality problems which exist in many majormetropolitan areas worldwide and has became one of the

Transactions on Ecology and the Environment vol 1, © 1993 WIT Press, www.witpress.com, ISSN 1743-3541

612 Air Pollution

biggest concerns of the mexican government. We havedeveloped a methodology based in Multi-Attribute Deci-sion Theory*' 2, 3 to help the mexican decision makersto prioritize air pollution control measures andstrategies (a set of measures) taking into accounteconomic, technical feasibility, environmental, so-cial, political, and institutional factors so they cancount with a tool that help them choose measures andstrategies to obtain the best results with the leastcost.

When comparing different strategies to reduce airpollution the two common elements considered are, theamount the air quality is improved (or alternativelythe amount the emissions of pollutants are reduced)and the cost of obtaining this improvement. Howeverthere are many more factors that need to be consideredwhen choosing a strategy to reduce air pollution. Fac-tors such as the increase in imports required, theability of the administrative structure to administerthe new rules and regulations, the popularity of themeasures being proposed, who pays,etc., are also an im-portant part of the decision. One method of consider-ing these factors in a structured and transparent wayis to use decision analysis techniques.

The procedure for the Multi-Attribute Decisionanalysis methodology starts with choosing the impor-tant criteria in the decision and weighting them rela-tive to each other. Next an evaluation is determinedfor each criterion. These evaluations are then normal-ized on a scale of 0 to 1 using an utility function.This utility function provides the relationship be-tween the criteria evaluation and its utility.

The importance of the output of the decisionanalysis method is not only the resulting scores forthe strategies, but also the process of going throughthe methodology. The formal process insures that im-portant factors in the decision have been considered.The weights for the criteria and the utility valuesassigned for each strategy, provide a record of howthe decision was made. This record is useful when thedecision needs to be explained or defended.

Two pollution mitigation measures were analyzed^to test the decision analysis framework: "The instal-lation of catalytic converters on new vehicles sold inMexico from October 1990 onward" and "The substitutionof natural gas instead of fuel oil in the two majorelectric power plants in the MCMA". The analysis re-sults show the capabilities of the methodology.


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This methodology was developed as a part of theMexico City Air Quality Research Initiative (MARI)*,an ongoing project between the Institute Mexicano delPetroleo and Los Alamos National Laboratory. The MAR Iobjective is to create or develop tools to evaluateair pollution control measures in the MCMA.

METHODOLOGY

Based on Multi-Attribute Decision Theory*' %' ̂ we havedeveloped a decision tree. The decision tree was de-veloped in a series of meetings with a panel of ex-perts in air pollution formed with representativesfrom: Departamento del Distrito Federal, DDF (MexicoCity Government), Comision Estatal de Ecologia, Edo.de Mexico (State of Mexico Government), Secretaria deDesarrollo Social, SEDESOL (Secretary of Social Devel-opment, Federal Government) , Secretaria de Salud(Secretary of Health, Federal Government), PetroleosMexicanos, PEMEX (The Mexican Petroleum Company), In-stitute Mexicano del Petroleo, IMP (The Mexican Insti-tute of Petroleum), and Los Alamos National Labora-tory, LANL. In these meetings we used the Delphi tech-nique to divide the problem in General and SpecificCriteria, assign weighting factors to each of them ac-cording to their estimated importance in Mexico, anddefine utility functions for the Specific Criteria orAttributes. The main branches of the decision analysistree or General Criteria were chosen to be:Technical.Economic.Environmental.Social, Political and Institutional.

Each of these General Criteria were subdivided inSpecific Criteria and some of them were also subdi-vided in more Specific Criteria. The whole decisionanalysis tree is shown in figure 1.

The utility functions for each of the Attributesand the weighting factors for the General Criteria andAttributes are shown below:

Technical Criterion 27.00

1.- Technological Evaluation. 37.50Availability. 28.00Available and Applicable. 1.00Available but needs some adaptation. 0.75Available but needs large adaptation. 0.50Exists but not available. 0.25It does not exist. 0.00

Technological Level. 23.50


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INPUT MATERIALAND

ENERGETICSAVAILABILITY

ANDCONSUMPTION

AVAILABILITY

TECHNOLOGICALEVEL

[-I

L_

INITIALINVESTMENT

FINANCING

IMPLEMENTATION CAPABILITIES ANDTECHNOLOGICAL INNOVATION

TECHNOLOGYEFFICIENCY

Figure 1.- Customized Multi-Attribute Decisio Analysis tree to rank airpollution control measures and strategies for Mexico City.


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High. 1.00Medium. 0.50Low. 0.00

Implementation Capabilities and TechnologicalInnovation. 23.20

It can be implemented and innovated. 1.00It can be implemented but notinnovated. 0.75Difficult to implement. 0.25Impossible to implement. 0.00

Technology efficiency. 25.30Percentage reduction of pollutants. 0.00 to 1.00

2.- Input Materials and Energetics Availability andConsumption. 34.40

High availability and low consumption. 1.00High availability and medium consumption. 0.75Medium availability and consumption. 0.50Low availability and medium consumption. 0.25Low availability and high consumption. 0.00

3.- Service and Repair. 28.10Available. 1.00Available with few limitations. 0.75Available with limitations. 0.50Available with lots of limitations. 0.25Not available. 0.00

Economic Criterion 24.20

1.- Investment and Financing. 26.00Initial Investment. 48.90Very Low. 1.00Low. 0.75Medium. 0.50High but manageable. 0.25High notmanageable. 0.00

Financing (financed by). 51.10Users. 1.00National Enterprises. 0.75Financial Institutions. 0.50Government. 0.25No Existence. 0.00

2.- Operation, Maintenance Costs and Investment. 21.30Low variable cost and low initial investment. 1.00Low variable cost and medium initial investment. 0.75Medium variable cost and high initial investment. 0.50High variable cost and high initial investment. 0.00

3.- Good or Service Price. 18.20Market defined. 1.00Subsidized. 0.50Free. 0.25

4.- Operation Cost and Implementation Time. 17.40Low cost and short time. 1.00Low cost and long time. 0.75


616 Air Pollution

High cost and short time. 0.50High cost and long time. 0.25

5.- Balance of Payments. 17.10No international help required. 1.00Small international help required. 0.75Medium international help required. 0.50Large international help required. 0.25Total international help required. 0.00

Environmental Criterion 25.30

1.- Air Quality. 28.90Ic = Current IMECA.la = After implementation IMECA.N = Impact.F = Utility function.

100 200

1.= 0.

0.0.

00755025

ifififif

100

.0 :

.5 :

.2 :

N> N> N> N

> 1> 0> 0

.0

.5

.2

2.- Pollutant Emission Reductions. 26.40(THC, NOx, SOx, Pb, TSP,CO)

Tci = Current emission tons of pollutant i.Tai = After implementa. emiss. tons of pollut. i.Tj_ = Toxicity factor of pollutant i.R = Emission reductions factor.F = Utility function.

6

2[T .-T .]*T.L ci ai J iR =

Max(j=l,2..,6)[TV*T.]

1.00 if 0.25 < R

F =0.0.0.0.

75502500

ifififif

000

.1

.05 <

.0

: R( Rc R

R

< 0< 0< 0< 0

.25

.1

.05

.0

3.- Visibility. 23.60V = Visibility factor.Vc = Current visibility.Va = Visibility after implementation.V# = Visibility without implementation

(evaluated at the same time as VQ).


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VV 2Va -

F =

4 . - Time

ImmecShortLong

TT.T5

1.000.750.500.250.00

Impactiiately: (1-3(after

Imp<

ififififif

years)3 yea

act +

10 <5 <3 <1 <

.rs).

Range

RR iR 1R <R <

10.50.25

10531

KmKmKmKm

21.10Range

Permanent . 1Medium range. 0.5Temporary. 0

Social, Political and Institutional Criterion 23.50

1.- Income and Employment Impact. 20.50Income or employment increase in low income sects. 1.00Income or employment increase in high income sects. 0.75No income neither employment impact. 0.50Income or employ, decrease in high income sects. 0.25Income or employment decrease in low income sects. 0.00

2.- Public Opinion 19.80High. 1.00Medium. 0.50Low. 0.00

3.- Citizen Participation 18.40No need. 1.00Government participation required. 0.75Industrial or commercial associations.participation required. 0.50Civilian associations participationrequired. 0.25All citizens participation required. 0.00

3.- Political Interest 20.50Presidential initiative. 1DDF or Edo. de Mex. initiative. 0Institutional initiative. 0Measure without political interest. 0.00

4.- Administration Capabilities 20.00There exist administration entitieswith technical and professionalcapabilities, normative facultiesand established norms. 1.00There exist administration entitieswith technical and professional

.00

.75

.50


618 Air Pollution

capabilities, normative faculties,but there are no norms established. 0.75There exist administration entitieswith technical and professionalcapabilities, but no normativefaculties neither established norms. 0.50No administration entities exist. 0.00

The methodology was designed so the sum of theGeneral Criteria weighting factors would be equal to100, i. e., if A, B, C, and D are the weighting fac-tors for the General Criteria then:

A + B + C + D = 100.

Similarly the weighting factors for the At-tributes under a General Criterion must sum 100, i.e., if ai is one of the Attribute weighting factorsunder one of the General Criterion then:

&1 + &2 + ••• + a^ = 100

This is true for Attribute weighting factors ofthe four General Criteria and is the same for anyother subdivision of an Attribute, i. e. , if an At-tribute is subdivided in Sub-Attributes then the Sub-Attribute weighting factors must sum 100 as well.

An utility function was assigned to each one ofthe Attributes. The utility function for a certain At-tribute was defined by the experts to evaluate thespecific characteristic or characteristics, of a mea-sure or strategy, that was (were) considered withinthis Attribute, so a measure or a strategy could begraded according to this evaluation in a scale from 0to 1. For example in constructing a utility functionfor cost, any costs up to a certain amount would havea utility of 1 (i. e. up to a certain amount the costwould have no effect on the desirability of choosingthe strategy), then as costs increase the utilitywould decrease until at a certain maximum cost afterwhich the utility would be 0 (i. e. , any strategy thatcosts more than this amount is too expensive to beconsidered).

Based on this definition the total grade or Fig-ure of Merit, FOM, of a measure or strategy wasdefined as follow:


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A n.4 J

FOM = 2,GCW. — /% AG,, AW,,j=l 1=1

where

GCWj = Weighting factor of the j-th General Criterion.AGji = Grade obtained by the measure or strategy cor-

responding to the i-th Attribute under the j-thGeneral Criterion.

AWji = Weighting factor of the i-th Attribute underthe j-th General Criterion.

nj = Number of Attributes under the j-th GeneralCriterion.

If an Attribute is subdivided in Sub-Attributesthen:

n..

AG.. = /, SAG.., SAW..ji 100

where

i = Grade obtained by the measure or strategy cor-responding to the k-th Sub-Attribute under thei-th Attribute that is under the j-th GeneralCriterion.

i = Weighting factor of the k-th Sub-Attribute un-der the i-th Attribute that is under the j-thGeneral Criterion.

nji = Number of Sub-Attributes under the i-th At-tribute that is under the j-th GeneralCriterion.

Comparing the FOM of different measures orstrategies we can rank them in order of importance ac-cording to the highest FOM to the lowest.

The production of a decision analysis frameworkis an interactive process. A completed framework mustbe tested with sample measures or strategies to seeif it is practical to implement and if it produces thedesired results. Once this test is completed changeswill be made to the framework and another test per-formed. This process continues until a decision analy-sis framework is obtained that is appropriate for theparticular problem.


620 Air Pollution

RESULTS

The main result of this work was the development of theMulti-Attribute Decision Analysis tree shown in figure1, with its weights and utility functions (shown in themethodology). Also important was the formation of apanel of experts representing the principal governmentoffices of the MCMA. Using this methodology we have an-alyzed two measures: "The installation of catalyticconverters on new vehicles sold in Mexico from October1990 onward" and "The substitution of natural gas in-stead of fuel oil in the two major electric powerplants in the MCMA". The analysis was also based in aresearch made by the IMP on these two issues. The Gen-eral Criteria grades and the FOM obtained by these twomeasures are shown in table 1. Figure 2 shows the FOMof the two measures.

Table 1. General Criteria grades and FOM obtained bythe: "Catalytic converter installation on new vehi-cles" and "Use of natural gas instead of fuel oil inpower plants in the MCMA" measures.

Measure

Criteria 'TechnicalEconomicEnvironmentalSocial, Polit-ical and In-stitutionalFigure ofMerit

Installationof C. C. onNew Vehicles

18.021.419.8

18.9

78.0

Natural GasInstead ofFuel Oil inPower Plants

18.316.517. 0

20.0

71.8

The C. C. measure obtained the highest FOM mainlybecause of the economic and environmental evaluation.Economically the C. C. measure was graded higher be-cause basically all the costs are charged to theusers, whereas with the Gas measure the government isthe economic supporter (CFE the Mexican Electric Com-pany is government owned), so in the long run is easyto economically support the C. C. measure; on theother hand the Gas measure could help to increase in-flation. Another advantage of the C. C. measure recog-nized by the experts was that it promotes the pol-luters pay principle philosophy. Environmentally themain reason why the C. C. measure got the higher gradewas that it reduces emissions in 1.9 % from MCMA totalemissions, and the Gas measure reduces only 1.1 %&.


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FIGURE OF MERIT

621

100

80-

CATALYTIC C. NAT. GAS

I TECHNICAL #3 ENVIRONMENTAL CZ] ECONOMIC EE SOCIAL

Figure 2. - Figure of Merit comparison between the"Catalytic converter installation on new vehicles" and"Use of natural gas instead of fuel oil in powerplants in the MCMA" measures.

DISCUSSION AND CONCLUSIONS

The importance of this methodology is that it takesinto account not only objective factors like cost orair quality improvement but also incorporates in theanalysis more subjective factors like public accep-tance, political interest, etc., factors that are veryimportant in the decision making process, specially inMexico. Another important characteristic of thismethodology is that it is planned to use modeling resultsobtained from air quality simulations using the HOTMAC(High Order Turbulence Modeling of Air Circulation)program, a meteorologic simulator, in conjunction withthe CIT (California/Carnegie Institute of Technology)airshed model adjusted to the MCMA conditions to eval-uate the air quality improvements due to measure orstrategy implementations. The modification and adjust-ing of the models to the MCMA conditions are also partof the MARI project and the models are about ready tobe used. Nevertheless we should keep in mind that themethodology we are reporting here can be used without


622 Air Pollution

modeling results, though the evaluation would be lessprecise. The methodology can be used cis it is nowthough as a result of the two measure analysis modifi-cations to some attributes are being considered. Thesemodifications will be published later on.

The decision tree was generated using the Delphitechnique with a panel of experts representing thevarious governmental units responsible for attackingthe air pollution problem in MCMA. Thus the decisiontree structure represents a consensus from people inthe agencies that will be making the decisions onstrategies to combat air pollution. This should in-crease the credibility of the structure that has beengenerated and improve its usefulness.

REFERENCES

1. Book:1. Saaty, T.L. The Analytic Hierarchy Process McGraw-Hill, Inc., New York, 1980.

2. Book:2. Adelman, Leonard. Evaluating Decision Support andExpert Systems, John Wiley & Sons, Inc., New York,1992.

3. Book:3. Hwang, Ching-Lai and Yoon, Kwangsun. MultipleAttribute Decision Making - Methods and Applications -A state-of-the-art Survey, Springer-Verlag, New York,1981.

4. Internal Report:4. Barrera Roldan, A. S., Corona Juarez, A., Hardie,R. W. , Lanes Mollinedo, L. R. y Thayer, G. Metodologiade Atributos Multiples para la Evaluacion deEstrategias, report IAIT-92009, Institute Mexicano delPetroleo, may 1992.

5. Paper in Conference Proceedings:5. Guzman, F. , Ruiz, M. E. and Sosa, G. 'Mexico CityAir Quality Research Initiative', vol. 1.1, pp. 321-333, Proceedings of the World Energy Council. 15thCongress, Madrid, September 1992.

6. Report:6. Departamento del Distrito Federal. ProgramaIntegral contra la Contaminacion Atmosferica de laZona Metropolitana de la Ciudad de Mexico, Cd. deMexico, October 1990.


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