economic analysis of environmental benefits of...

Journal of Agricultural and Applied Economics, 29,2(December 1997):243–2530 1997 Southern Agricultural Economics Association

Economic Analysis of EnvironmentalBenefits of Integrated Pest Management

Jeffrey D. Mullen, George W. Norton, and Dixie W. Reaves

ABSTRACT

Public support for integratedpest management(1PM) is derived in partfrom concerns overfood safety and the environment, yet few studies have assessed the economic value ofhealthand environmentalbenefits of 1PM.An approach is suggested for such an assessmentand applied to the Virginia peanut 1PM program. Effects of 1PM on environmental risksposed by pesticides are assessed and society’s willingness to pay to reduce those risks isestimated. The annualenvironmentalbenefits of the peanut 1PM program are estimatedat$844,000. The estimatesof pesticide risks and willingness to pay can be applied elsewherein economic assessmentsof 1PM.

Key Words: environmental benefits, integratedpest management, willingness to pay.

Effective pest management is essential to theeconomic vitality of U.S. agriculture. Sincethe 1950s, crop damage from pests has beenmanaged in a relatively effective and inexpen-sive manner by synthetic pesticides. However,growing concerns about potential environmen-tal and health risks associated with pesticideuse, increased problems of pest resistance topesticides, loss of established pesticides due toregulatory decisions, and increased costs ofnew pesticides have stimulated the search fornew pest management strategies. Consequent-ly, integrated pest management (1PM) strate-gies are being developed and implementedthat combine biological, cultural, physical, and

Jeffrey D. Mullen is a graduateresearch assistant,George W. Norton is a professor, and Dixie W. Reavesis an assistant professor, all in the Department of Ag-ricultural and Applied Economics, Virginia Tech.

This study was funded in part by the U.S. Depart-ment of Agriculture under Grant No. 92-EPMP- 1-0027. It has not been subjected to the department’speer and administrative review, and therefore does notnecessarily reflect the views of the USDA; no officiatendorsement should be inferred. The authors wouldlike to thank Ames Herbert for helpful comments.

chemical control tactics to minimize econom-ic, environmental, and health risks.

Many 1PM strategies are being developedand implemented with the assistance of publicresearch and extension. Much public supportfor 1PM research and extension has resultedfrom concerns over food and farm workersafety, over groundwater contamination, andfrom increased environmental awareness. De-spite these concerns, most economic evalua-tions of 1PM programs have concentrated onfarm-level profitability or risk, or on aggregateeconomic benefits resulting from IPM-inducedcost reductions or yield changes (e.g., Fergu-son and Yee; White and Thompson; Hatcher,Wetzstein, and Deuce; Rajotte et al.). A fewhave assessed the economic impacts of acutehuman health effects associated with pesticideexposure (Antle and Pingali; Rola and Pingali)or the relative environmental risks associatedwith specific pesticides (Kovach et al.; Higleyand Wintersteen), but none have provided aneconomic assessment of the environmentaland health impacts of an 1PM program.

The purpose of this study is to provide an

244 Journal of Agricultural and Applied Economics, December 1997

approach for such an assessment and to applyit to the peanut 1PM program in Virginia. Theapproach contains two primary components.The first is to estimate the effects of 1PM onthe risks posed by pesticides to the environ-ment and human health (hereafter referred tosimply as the environment). The second is todetermine society’s willingness to pay to re-duce those risks. Implementing these twocomponents requires five basic steps: (a) iden-tifying risks posed by individual pesticide ac-tive ingredients to the environment, (b) defin-ing the degree of 1PM adoption, (c) assessingthe effects of 1PM adoption on pesticide use,(d) estimating society’s willingness to pay toreduce pesticide risks, and (e) combining thewillingness-to-pay and pesticide risk-reductionestimates to calculate the economic value ofthe environmental benefits of the 1PM pro-gram.

Results for the peanut 1PM program eval-uation in Virginia show substantial environ-mental benefits to the Early Leaf Spot Advi-sory program. Some of the risk levelscalculated for specific pesticide active ingre-dients and all of the willingness-to-pay esti-mates (based on a national survey) can be ap-plied in 1PM evaluations in other states,thereby facilitating replication of the ap-proach.

Identifying Pesticide Risks to theEnvironment

Identifying pesticide risks is essential for val-uing the environmental benefits of 1PM pro-grams. Pesticide risk to the environment is re-lated to the amount of active ingredients (a.i.)applied. However, total pounds of a.i. appliedper year is not the best indicator of risk, be-cause pesticides differ with respect to theirtoxicity, mobility, and persistence. A givenpesticide also may pose different levels of riskto different components of the environment.Substitution of one pesticide for another mayreduce the risk to one environmental compo-nent, but raise it for others. To address thisissue in the current study, the environment isdivided into eight broad categories: ground-water, surface water, acute human health,

chronic human health, aquatic species, birds,mammals, and arthropods. Further, three levelsof pesticide risk are identified: high, moderate,and low. 1

Active ingredients are assigned one risklevel (j = 1 to 3) for each environmental cat-egory (i = 1 to 8), resulting in 24 risk/envi-ronmental classes for pesticides. Rather than

measuring the change in total pounds of all

a.i., the change in pounds of a.i. in each ijpesticide class attributable to 1PM adoption ismeasured. Separate criteria are used for eachenvironmental category to classify the riskposed by each a.i. A brief summary of thosecriteria is presented below (with additional de-tails available from the authors).

The criteria presented below make use of

the current state of knowledge with respect to

data that indicate pesticide risk to individualenvironmental categories. A more completemodel of pesticide hazards to these categorieswould trace vector and timing of exposurefrom the application of pounds of a.i. in a par-ticular form, at specific points in time, underspecific environmental conditions (e.g., soilpH, moisture level, the length of time beforeit rains), and other factors (e.g., method of ap-plication, potential toxic synergies from mixi-ng chemicals) to human exposure and envi-ronmental contamination, and then to health

and other environmental impacts. These im-pacts would depend on the age distribution ofthe population, types of aquatic species, mam-mals, insects present, etc. Recognizing thelimitations of available data and information,the criteria and hazard categories below makethe ceteris paribus assumption that highly tox-ic, persistent chemicals pose a greater risk to

human health and other categories of the en-vironment than pesticides that are inherentlyless toxic and deteriorate quickly.

‘ The environmental categories are the same asthose used by Higley and Wintersteen, and similar tothose used by Kovach et al., thereby facilitating com-parison of results even if the methods differ. The cri-teria do involve some overlap, particularly betweengroundwater and chronic human health, and betweensurface water and aquatic species.

Mullen, Norton, and Reaves: Environmental Benejits of 1PM 245

Groundwater Criteria

The assignment of groundwater risk to an ac-tive ingredient is based on the PesticideLeaching Matrix developed by the U.S. De-partment of Agriculture’s Soil ConservationService (SCS) (Becker et al.). This matrix ac-counts for both soil and pesticide propertiesand classifies pesticides as having high, mod-erate, or low risk to groundwater based on thesoil leaching rating (high, intermediate, nom-inal) where the pesticide is applied and on theleaching rating for the pesticide (large, medi-um, small). Not all pesticides have a pesticideleaching rating. When leaching ratings are notavailable, Gustafson’s Groundwater UbiquityScore (GUS) is used to assign the groundwaterrisk level to the pesticide. The GUS is definedin terms of the soil half-life of the pesticide,tiir, and the pesticide’s soil adsorption index,

Oc. Measures of ti~~K and Koc are obtainedfrom Wauchope et al.:

(1) GUS = log,o(t~[) X [4 – log, O(Koc)].

Gustafson classifies pesticides as leachers(GUS > 2.8), nonleachers (GUS < 1.8), andtransition (1.8 < GUS < 2.8), which translateto high, low, and moderate groundwater risk,respectively.

Su#ace Water Criteria

The assignment of surface water risk to an ac-tive ingredient is based on the Surface RunoffMatrix developed by the SCS (Becker et al.).This matrix accounts for both soil and pesti-cide properties and classifies pesticides as hav-ing high, moderate, or low risk to surface wa-ter based on the soil surface loss rating wherethe pesticide is applied and on the surface lossrating for the pesticide. Not all pesticides havebeen assigned a surface loss rating. When run-off ratings are not available, three pesticidecharacteristics are evaluated: (a) water volu-bility, (b) soil Koc, and (c) soil half-life. TheU.S. Environmental Protection Agency (EPA)has deftned “red flag” values for each char-acteristic (water volubility > 30 ppm, soil Koc

< 300, and soil half-life >21 days) (Becker

et al.). For this study, if two or more of thered flag values are exceeded, the pesticide isconsidered a high risk to surface water; if onered flag value is exceeded, it is considered amoderate risk; and if no red flags are exceed-ed, it is considered a low risk.

Acute and Chronic Human Health Criteria

The assignment of acute human health risklevels is based on the signal words assignedby the EPA to the formulated product (Beckeret al.). Because the EPA requires all pesticidesto be labeled with “Danger,” “Warning,” or“Caution” based on toxicity [LD~Osfor oral,dermal, and inhalation exposure, and for eyeand skin effects (table 1)], ever y pesticide hasa corresponding signal word which can cor-relate with a high, moderate, or low rating.z

Criteria for assigning chronic health risklevels are based on the results of tests evalu-ating the teratogenicity, mutagenicity, and car-cinogenicity of each pesticide. The classifica-tions and their definitions are: (a)

“negative” —conclusive evidence that thepesticide is not a teratogenic, mutagenic, orcarcinogenic agent; (b) “no evidence’ ‘—todate, there is no evidence indicating the pes-ticide is a teratogenic, mutagenic, or carcino-genic agent; (c) “inconclusive’ ‘contradict-ory results have been observed; (d) “datagap’’ —reliable studies have not beenconducted; (e) ‘ ‘possible’’ —while there is noconclusive information to date, the pesticidehas certain physical properties that warrantfurther testing; (~) “probable’’-the same as“possible,” except the physical properties of“probable” pesticides lend themselves morereadily to teratogenic, mutagenic, or carcino-genic effects than do pesticides classified“possible”; and (g) “positive’’ -conclusiveevidence is available demonstrating the pesti-cide is a teratogenic, mutagenic, or carcino-genic agent. A pesticide is assigned a highchronic health risk if it has one or more “pos-itive” classifications, a moderate risk if it hasone or more “data gap,” “possible,” or

2LD50 is the pesticide dose that kills 50% of thetest population.


“probable” classifications, and a low risk ifresults of all three tests are classified either“negative,” “no evidence, ” or “inconclu-sive. ”

Aquatic Species Criteria

A given pesticide does not affect all aquaticspecies to the same degree. In this study, thehighest level of risk a pesticide poses to anyaquatic species is the risk level assigned to thatpesticide. Because a pesticide poses little riskto aquatic species if it does not reach surfacewater, the aquatic species risk level is weight-ed by the surface water risk level. A high ormoderate surface water risk will not alter theaquatic species risk. A low surface water risk,however, will drop a high aquatic species riskto a moderate risk, and a moderate aquaticspecies risk to a low risk (table 2).

Avian and Mammalian Criteria

Assignment of risk to a pesticide with respectto the avian and mammalian categories isbased on the highest level of risk the pesticideposes to any species within the category: highif LD~Ois < 50 ppm, moderate if LD~Ois be-tween 50 and 500 ppm, and low if LD~Ois >500 ppm. Risk levels are not weighted by amobility factor due to the ability of these spe-cies to enter the target area. There are somepesticides for which toxibiological tests havenot been conducted. A pesticide is assumed topose a moderate level of risk to any categorywhere “data gaps” exist.

Nontarget Arthropod Criteria

In most cases, the toxicity of pesticidal com-pounds to arthropods has not been formallyassessed. To assign an arthropod risk level toan active ingredient, a variety of references areconsulted: EXTOXNET, Smith; Higley andWintersteen; Kovach et al.; Worthington; Hart-ley and Kidd; and U.S. EPA re-registration re-ports. If any of these references report an

active ingredient as “highly toxic” or “ex-tremely toxic” to any beneficial arthropodspecies, a high level of risk is assigned to that

Mullen, Norton, and Reaves: Environmental Benefits of 1PM 247

Table 2. Risk Assignment Criteria for Aquatic Species

High Risk Moderate Risk Low Risk

LC50 < 1 ppm 1 ppm < LC~O< 10 ppm LC~O> 10 ppm

and and or

High or Moderate High or Moderate 1 ppm < LC50 < 10 ppmSurface Water Risk Surface Water Risk and

or LowLC50 < 10 ppm Surface Water Risk

and

LowSurface Water Risk

Note: All Lc,” notationsin this table are 96-hour LC,OS;this termis defined as the concentrationof active ingredient.thatkills half the testpopulation within 96 hours.

pesticide, If none of the references report theactive ingredient as “highly toxic” to arthro-pods and any reference reports the a.i. as“moderately toxic” to any arthropod, a mod-erate level of risk is assigned. A low level ofrisk is assigned to pesticides if none of thereferences identify the pesticide as posing ahigh or moderate level of risk to arthropods.

Defining Levels of 1PM Adoption

Integrated pest management involves a varietyof practices that are specific to individualcrops and locations. In some cases, an 1PMprogram may be limited to a single practice,but typically, multiple practices are involved.Therefore, 1PM adoption is usually a matter ofdegree. Adoption can be defined by level (i.e.,high, medium, low, none) for each specificcrop and location, with the levels based ongroupings of particular sets of practices (see,for example, Rajotte et al.) or on the assign-ment of points to individual practices so thatadoption along a scale is identified (Hollings-worth et al.). Alternatively, one could baseadoption on the degree of adoption of 1PMpractices by utilizing an algorithm that tran-scends crops and locations but takes into ac-count the proportion of available practices em-

ployed by producers and the importance ofeach class of pests.

Regardless of approach, the degree ofadoption must be assessed based on informa-tion provided both by scientists and by pro-

ducers. Often it is necessary to involve otherstakeholders as well (e.g., consumers or rep-resentatives of environmental groups) if dif-ferent weights are placed on particular 1PMpractices in defining the degree of adoption.

Assessing Effects of 1PM on Pesticide Use

To estimate the reductions in external costs at-tributable to an 1PM program, an estimate isneeded of the proportional change in pesticideuse induced by adoption of 1PM on the studycrop. Estimating this change entails comparingthe current level of pesticide use under 1PMto an estimate of what use would be in theabsence of the 1PM program.

Using the environmentalhisk criteria de-veloped above, pesticide active ingredients ap-plied within the study area can be classifiedwith respect to their environmental category,i, and risk level, j. The total pounds of an ac-tive ingredient class applied per year to theentire study area is denoted Useti. For exam-ple, the pounds of a.i. applied that represent ahigh risk to aquatic species or a medium riskto acute human health, etc. are calculated.UseO is composed of two elements, use on thestudy crop (Useti,) and use on other crops inthe study area (Use,].), so that

,,–1

(2) Use,, = ~ (Use,,u) + Use,,,,.=l

where n = number of crops grownarea.

in the study


An 1PM program for the study crop affectsUseti, and hence the external cost in the studyarea, through Useti,,. Use of pesticide active in-gredients represents an input demand derived,at least in part, from profit-maximizing behav-ior. Hence, one might expect Useij~ to be afunction of output and input prices, acreage,pest pressure, and producer characteristics, inaddition to 1PM adoption (a substitute input).In a study area, prices received and paid byfarmers are relatively uniform, and hence thegeneral form of the relationship between 1PMadoption and Use,l, can be represented by

(3) Use,,, = F(ZPM Adoption, Acreage of the

Study Crop, Pest Severity,Farmer Characteristics),

Regression analysis can be used to examinethe relationship between Use,l, and variouslevels of adoption of 1PM. For example, fourlevels of 1PM adoption can be included asdummy variables, and variables such as farmsize, farmer age, farmer education, and an in-dex of pest infestation severity can be includ-ed. If the 1PM program involves only a singlepractice, and farm size and pest severity arerelatively homogeneous across farms, it maybe possible to assess adoption based on a sim-ple survey. If pest severity is relatively ho-mogeneous across years, it may be possible toassess adoption by surveying the same farmersover time. Otherwise, a relatively detailed sur-vey and a regression analysis are needed tocontrol for variation in acreage, pest severity,and farmer characteristics.

A proportional reduction in Use,, resultingfrom 1PM adoption can be expressed as fol-lows:

(4) Reduction,j = 1 –E(Uset, with 1PM)

E(Use,, without 1PM)’

where E denotes expected, and E( Use,j with

1PM) is derived as follows:

(5) E(Usel, with 1PM)

,*—1

= ~ E(Use,j.) + ~ E(Use,,,,).“=!

The subscript k refers to 1PM adoption levels,where k c {none, low, medium, high}. In oth-er words, E(Useti,,~) is the expected use of ac-tive ingredients with risk level j for environ-mental category i on the study crop byproducers with a k level of 1PM adoption.E(Use,l without 1PM) is the same as in equa-tion (5) when k = “none” for all producers.3,4

Willingness to Pay to Reduce PesticideRisks

Estimates are needed of society’s willingnessto pay to avoid pesticide risks to the eight en-vironmental categories. Willingness to pay isrelated theoretically to risk perceptions andmay be influenced by factors such as gender,age, income, household size, where peoplelive, and other socioeconomic characteristics.5Unfortunately, there are few market proxiesfor the willingness to pay to avoid risk to anyof the eight categories, and none that wouldserve for all of them. Therefore, a contingentvaluation survey (CVS) was administered to arandom sample of U.S. residents.6

~The derivation of Usez,y~with 1PM is made by es-timating equation (3) for a particular set of variables(farmer characteristics, etc.) and then calculatingE(USe,,J for each k by substitutingthe mean values ofthose variables for thatk back into the estimated equa-tion. For example, if farmer age, farmer education, pestseverity, and farm size were the variables, thenE(Use,lf~) = 60 + d~IPM~ + d2(Education) +dS(Severity) + ti~(AcreageJ would be calculated usingthe mean values of the variables for each k in estimat-ing Use,, with IPM. In estimating Use,, without 1PM (ifk = “none” for all producers), the mean values of thevariables fo~ the entire sample would be substitutedinto this equation (without the 1PM intercept dum-mies).

4Potential reductions in Use,, also can be estimatedthat would represent potential reductions in the use ofactive ingredients in class ij that would result if all thestudy crop areas adopted a given level of 1PM: Poten-tial,,~ = 1 – E(Usetl with all IPMJIE(Useq without1PM),

5 Questions related to socioeconomic characteris-tics were included in the survey mentioned below. Thesurvey questionnaire is available from the authorsuponrequest.

GContingent valuation remains a controversialtechnique due to many potentiat biases (Portney).However, it is one of a limited set of procedures avail-able for valuing nonmarket goods, some of the biases

Mullen, Norton, and Reaves: Environmental Benejits of 1PM 249

The survey contained an introduction witha brief overview of the value of pesticides asan agricultural input and of the potential forpesticides to damage the environment and hu-man health. The purpose of this introductionwas to inform the survey respondent about thenature of the risks posed by pesticides. Thequestionnaire began by asking the amount ofthe respondent’s average monthly grocery bill.This question was relatively easy to answerand served to get the respondent involved inthe survey. It also provided a baseline for asubsequent question on willingness to pay.

The willingness-to-pay (WTP) questionsbegan with a brief definition of “high risks tothe environment and human health from pes-ticide use. ” Respondents were asked theirwillingness to pay to avoid high risks via anincrease in their monthly grocery bill. Thispayment vehicle was chosen because groceryprices might increase if the use of an entireclass of pesticides was restricted.7 After an-swering the WTP questions, the respondentswere asked to rate (on a scale of O to 6) howimportant it is to avoid high risks to each ofthe eight environmental and human health cat-egories considered in the study. The same for-mat—risk definition, willingness-to-pay ques-tions, and assignment of importance levels—was repeated for moderate and low risks.

The survey was mailed to 3,000 individu-als drawn randomly from motor vehicle reg-istration records and local telephone directo-ries throughout the United States. A secondmailing was sent 25 days later to 833 address-es, selected at random from those that had notreturned the survey. Several surveys (384)were returned as undeliverable, and 454 re-sponses were received.

To minimize the length of the question-

can be minimized in the survey process, and evidencesuggests it can, in some cases, provide reasonable es-timates of willingness to pay (Arrow et al.; Hane-mann).

7A second vehicle, an increase in yearly federalincome tax liability, also was used, but the results wereexcluded from the analysis after testsrevealed paymentvehicle bias. This bias likely is due to aversion to tax-es. Information is available from the authors on non-parametric tests used to determine thatvehicle bias ex-ists.

naire, the CVS respondents were asked to re-veal their willingness to pay to avoid a givenlevel of risk to the environment as a whole(lVTP,), rather than their willingness to pay foreach category ( WTPZJ). The importance rank-ings by category from the survey were thenused to infer the respondent’s ~Plj from theirWPjZ

Importancet(6) WTPt, = , x WTP,.

~ Importance,,=1

The results of the contingent valuation survey,with 46 outliers deleted, are presented in table3. Following previous studies (Desvousges etal.; Mitchell and Carson), responses are con-sidered outliers if the WTPj exceeds 5% of therespondent’s annual income.

Application of the Model to VirginiaPeanuts

The environmental risk, 1PM adoption, pesti-cide use, and willingness-to-pay analyses werecombined in an analysis of the environmentalbenefits of the Virginia 1PM program on pea-nuts.8’9 Eight southeastern Virginia countieswere chosen as the peanut study area. Pesti-

8Analysis also was completed of the Virginia Ap-ple 1PM program, with results available from the au-thors.

yAlthough this study was concerned with the pea-nut 1PM program in Virginia, the contingent valuationsurvey was administered to a sample of the entireUnit-ed States population so that the data can be used toevaluate 1PM programs in other states. To ensure thatthe countrywide estimates are valid for each state, in-dividually, the sample mean for each state should becompared to the sample mean of every other state.Theminimum number of observations needed to ensure thestatistical validity of a comparison of sample meanshas not been conclusively defined in the statistics lit-erature,but a sample size of 15 generally is agreed tobe sufficient. Whh this in mind, the sample means foreach state with more than 15 usable responses (11states including Virginia) were compared using theKruskal-Wallis nonparametric F-test. The null hypoth-esis is that the mean willingness to pay to avoid agiven level of risk to a given environmental categoryis the same for each comparison state. In all 24 tests,the null hypothesis is sustained. Tables of the resultgof these tests are available from the authors.


Table 3. Contingent Valuation Survey Results: Willingness to Pay to Reduce EnvironmentalRisk ($/month)

High Risk Moderate Risk Low Risk(N = 397) (N = 392) (N = 388)

Environmental Std. Std. Std.Category Mean Error Mean Error Mean Error

Acute Human 4.28 .23 2.89 .17 1.74 ,14Chronic Human 4.59 .24 3.14 .19 1.89 .15Groundwater 4.56 .24 3.08 .18 1.86 .15Surface Water 4.40 .23 2.93 .17 1.76 .14Aquatic Species 4.37 .23 2.88 .17 1.75 ,14Avian Species 4.15 .23 2.72 .16 1.63 .14Mammalian Species 4.13 .22 2.71 .16 1.65 .14Arthropods 3.76 .22 2.49 .16 1.50 .13

Note: Based on 1992 dollars.

tides used on all the crops in the peanut studyarea were classified with respect to environ-mental risk levels (tables are available fromthe authors), using the methods describedabove. It was necessary to classify all pesti-cides and not just the ones used on peanuts,because any risk reduction on peanuts must beconsidered as a proportion of the total risk as-sociated with pesticide use in the area.

The Virginia 1PM program in peanuts fo-cused on developing a disease forecasting sys-tem to reduce fungicide use. In 1979, the EarlyLeaf Spot Advisory (ELSA) system was im-plemented in Virginia to identify environmen-tal conditions favorable to early leaf spot in-fection. Prior to ELSA, the conventionalmethod for combating early leaf spot in Vir-ginia peanuts was to apply chlorothalonil topeanut fields at 14-day intervals. By accurate-ly predicting periods of early leaf spot infec-tion, the ELSA forecasts and fungicide rec-ommendations have allowed farmers to applychlorothalonil in a more judicious manner.

In a four-year study from 1987 through1990, it was found that farmers followingELSA recommendations made, on average,339. fewer applications of chlorothalonil thanfarmers using the 14-day spray regime(Phipps). Yields from the ELSA farms werenot significantly different than yields from the14-day spray farms, nor was there a significantdifference in the value of those yields. By1990, 94?Z0 of Virginia’s peanut producers

were applying chlorothalonil based on ELSArecommendations (Phipps).

Recall that Use,j is comprised of two com-

ponents, the total amount of active ingredient

class ij applied to all crops in the study area

other than the study crop (Z UsezJ.), and the

total amount of active ingredient class ~ ap-

plied to the study crop (UseO,). The calculation

of Use,jo is represented by

(7) Use,,. = ~ (Acres,, x Treat., X Ra~e.P),

where m = number of active ingredients ofclass ij applied to crop a, Acres. = number ofacres of crop a harvested in the study area,Treat.,, = proportion of study area acres ofcrop a treated with active ingredient p, and

Rate.v = pounds of active ingredient p appliedper acre per year to crop a.

Similarly, Use,j,,W,~L~~, the amount of active

ingredient of class ij actually applied to pea-

nuts in the study area in 1992, is calculated by

(8) usetjs,w[ELSA = “$ (Acres, x Treat,p x Rate.,),

where m = number of active ingredients ofclass ~ applied to peanuts, Acres. = number

of harvested acres of peanuts in the study area,

Treat,P = proportion of study area peanut acres

treated with active ingredient p, and Rate$P =

Mullen, Norton, and Reaves: Environmental Benejts of 1PM 251

Table 4. Contingent Valuation Survey Results: Estimates of Chlorothalonil Use With and Whh-out ELSA, and Savings in External Costs (environmental benefits)

Reduction Savings inin Usev Due External

Use,j,W,~UA Use,j,Wlo~UA to ELSA costs

Active Ingredient Class (1,000 lbs.) (1,000 lbs.) (%) ($1 ,Ooosy

Low Risk to Groundwater 747 844 11.56 142

High Risk to Surface Water 1,937 2,035 4.80 139

High Risk to Aquatic Species 1,857 1,954 4.99 144

High Risk to Acute Human Health 1,745 1,842 5.30 149

Moderate Risk to Chronic Human Health 2,268 2,366 4.13 85

Low Risk to Avian Species 2,241 2,338 4.17 45

Low Risk to Mammalian Species 965 1,063 9.18 100

Low Risk to Nontarget Arthropods 2,325 2,423 4.03 40

Total Savings 844

aAmounts are in 1992 dollars.

pounds of active ingredient p applied per acreper year to peanuts.

The total amount of active ingredient classzj’ applied to the entire study area in 1992 isgiven by the following:

,,—1

(9) Usei,,w,m. = ~ (Use,,o) + usel,,,jvlEl~A9

where n = number of crops grown in the studyarea. It was not necessary to use equation (3)in assessing the effect of 1PM adoption on pes-ticide use because only one practice was in-volved, and the survey had determined that 94%of the producers were adopters and that chloro-thalonil use was reduced 33’% for adopters.

Assuming that producers following ELSArecommendations applied 33~o less chloro-thalonil in 1992 than producers using a cal-endar spray schedule, and that 94% of Virgin-ia’s peanut producers used ELSA while 6940used calendar sprays, one can solve for theamount of chlorothalonil that would have beenapplied in the absence of ELSA using the fol-lowing: X = 1.5 X Y, and Z = Acres, X (.94X Y X ,06 X X), where X = pounds of chlo-rothalonil applied per acre per year to farmsusing a 14-day spray schedule, Y = pounds ofchlorothalonil applied per acre per year tofarms following ELSA recommendations,Acres. = number of peanut acres harvested inthe study area in 1992, and Z = total pounds

of chlorothalonil applied to peanuts in thestudy area in 1992.

Equation (10) is used to estimate theamount of a.i. class O that would have beenapplied to the study area without ELSA,Use@’,O~~s*~

,,–1 m-l

(lo) Use,,,,vlo~B.= ~ (Use,l.) + ,3 (use,,,,)

+ X X Acres,,

where n = number of crops grown in the studyarea, m – 1 = number of active ingredientsof class ij other than chlorothalonil applied topeanuts in the study area, and X X Acress =

total pounds of chlorothalonil that would havebeen applied to the study area in the absenceof ELSA.

The estimates of Use@,~~s* and Usell,W,O~~s*for the relevant active ingredient classes arepresented in table 4. The savings in the exter-nal costs for each of the risk/environmentalcategories is represented by Savingsi, = WTP,J

x POP X Reductionij, where POP = numberof households in the study area, and Reduc-

tion~ = the realized proportionate reduction inUseti as defined in equation (4). 1° The total

10Respondents to the survey were asked how muchthey would be willing to pay to avoid a risk, but thereduction in pesticide use resulted in only a fraction ofthe risk being eliminated. The formula for calculating


savings in external costs (environmental ben-

efits) attributable to the ELSA program is sim-

ply the sum of the savings for each of the eight

relevant tj categories (table 4).The total savings in external costs are ap-

proximately $844,000 per year (in 1992 dol-lars). Each of the nearly 59,000 households inthe peanut study area would have been willingto pay an extra $14 per year for groceries torealize the reduction in pesticide use thatELSA provides. Annual public expenditureson the ELSA program are approximately

$10,000 per year including personnel, equip-ment, and operating costs. In addition, farmersexperience substantial direct cost savings as-sociated with reduced pesticide use, The returnto the ELSA program is clearly very high,

Conclusions and Implications

A method for assessing the environmentalbenefits of 1PM has been presented. Applica-tion of the method to the peanut 1PM programproved straightforward and demonstrated ahigh environmental return. One of the majoraccomplishments of this study is the estima-tion of societal willingness to pay for pesticidehazard reduction for eight environmental cat-egories. These willingness-to-pay estimatescan be applied in other studies without theneed to repeat the CVS. Procedures also weredeveloped for assessing risk levels to eight en-vironmental categories, and risk levels wereassigned to more than 130 pesticidal active in-gredients in Virginia. Tables with these risklevels (available from the authors) can reducethe time and effort required in future studies.These risk assignments also may be used byfarmers to guide their selection of pesticides.

Integrated pest management was conceivedas a means of easing producers’ reliance onchemical pesticides while maintaining agricul-tural production and preserving profitability.Certainly, many 1PM programs have attained

Savings,, assumes a linear relationship between a frac-tional risk reduction and risk elimination within a par-ticular level. While the relationship is not likely to belinear, the assumption may not be unreasonable over asmall range.

these goals, but evaluations are needed toquantify the degree of success. Analyses of thesocial/environmental benefits of reduced pes-ticide use must examine the toxicity, mobility,and persistence characteristics of the pesti-cides being used. When farmers reduce the to-tal pounds of pesticidal active ingredient ap-plied, but simultaneously substitute highlytoxic, mobile, and persistent chemicals for rel-atively benign ones, it is difficult to argue thatsociety has gained.

The results of the CVS administered forthis study indicate that society values the non-target resources that are adversely affected bypesticide use. Applying those results to theELSA peanut program has illustrated the mag-nitude of environmental benefits that an 1PMprogram can generate. In these times of tightbudgets, integrated pest management pro-grams will be subject to the same scrutiny asother publicly funded activities. If public fund-ing for 1PM research and extension is to con-tinue, 1PM must demonstrate net social bene-fits, particularly of an environmental nature. Ifsuch benefits exist, this study illustrates howthey can be assessed.

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