Evaluation of Fate and Exposure Models

Research Articles

Evaluation of Fate and Exposure M o d e l s

Pesticides and Groundwater Quality Protection - Calibrating a Simple Model for Ranking the Contamination Potential Eros Bacci 1, Alessandro Franchi 2, Luano Bensi 2, Carlo Gaggi 1 1 Department of Environmental Biology, University of Siena, Via delle Cerchia 3, 1-53100 Siena/Italy 2 SMP Environmental Chemistry Division, USL 30 Area Senese, Via Ettore Bastianini 18, 1-53100 Siena/Italy Corresponding author: Prof. Dr. Eros Bacci

Abstract A simple approach for ranking the leaching of pesticides from surface soil is presented and tentatively calibrated with field data from an agricultural area. The approach is based on the calculation of a leaching index indicating the proportion of active ingredient, with respect to the quantity applied, leaching from a soil model in a given time interval (one year). In the selected area, 85 wells tapping a n unconfined aquifer were sampled for groundwater pesticide residue analysis, in order to explore the index region between leachers and nonleachers.

1

Introduction

In recent years, the mobility of pesticides from contaminated soils by air and water transport has received increasing attention, stimulating investigations with integrated approaches based on the combination of findings from field studies and modeling. Among the variety of methods to simulate pesticide behaviour in soils, the lowest level of complication is that of evaluative and ranking models. These are based on simple deterministic approaches and require only little information for their application. The basic assumption is that environmental variables do not significantly change the relative results of the simulation. Evaluative and ranking models are not suitable for environmental fate studies but may be applied to group chemicals into relatively broad behavioural classes (WAGENET and RAO, 1990). In the present paper a new simple approach for ranking pesticide transport from soils to groundwater is tentatively calibrated with field data collected in 1992 in a reference area.

2

Materials and Methods

The study site was the Piana del Luco, an agricultural area of about 2 000 ha, 10 km SW of Siena (Italy), around the river Luco, located in the northern part of the river Merse valley. Maize and sunflower are the main crops, each ac-

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count for 40 % of the cultured area, the rest being dedicated to vineyards, wheat, and horticulture. The soil is generally constituted by quaternary fluviolacustrine deposits with the texture of a sand containing a minor clay component. The water table depth of the unconfined aquifer ( ~ Fig. 1) varies from 5 to 25 m from the surface soil; in the same area at 50 to 100 m, there is also an important confined aquifer, currently exploited for the public water supply by the municipality of Siena. The 85 wells studied are private, for domestic use only (washing and garden irrigation) and tap the unconfined aquifer. The main nonpolar pesticides applied in the area, at a minimum rate of 50 kg/yr, are shown in Table 1, plus some polar compounds (such as 2,4-D and paraquat), for which analytical data are not yet available. The estimate of pesticide input was made by direct inquiry of farmers and pesticide sellers in the area. Nonpolar chemicals were detected in 1992 by a multiresidual technique based on a solid-phase extraction of water samples (1 L) with C-18 columns, followed by elution and concentration (JUNK and RICHARD, 1988), and HRGC detection with electron capture and nitrogenphosphorus detectors. All active ingredients found in the water were confirmed by GC-MS (STAN, 1989). The selected leaching index is derived from the surface soil model by MACKAY(1991) as modified by BACC!and GAGGI (1993). According to this approach, the chemical is applied to the soil in a single input M o (g/m2); it is assumed that the substance becomes homogeneously distributed in a given volume of soil (e.g. surface area: 1 m2; depth: 0,1 m). The equilibrium partitioning in all soil components (air, water, organic matter, and mineral matter) is determined by simple fugacity calculations from the physical and partition properties of the chemical, after the volumes (m 3) and densities (kg/L) of the compartments having been defined. Assuming first-order kinetics and selecting a water leaching rate, the initial degradation, volatilization, and leaching rates (and fluxes) of the pesticide are obtained, together with the disappearance kinetics of the chemical from the soil model (MACKAY, 1991). A leaching index indicating the proportion of the chemical leached in a selected time interval (t2- ta, h) is obtained by calculating the ratio of the total amount of ESPR-Environ. Sci. & Pollut. Res. 1 (2) 94-97 (1994) 9 ecomed publishers, D-86899 Landsberg, Germany

Research Articles

Evaluation of Fate and Exposure Models

Fig. 1: Schematic representation of the area selected for the first calibration of a simple leaching index. The 85 wells tap the unconfined aquifer only and are located in the selected agricultural area (2 000 ha). The water table depth ranges from 5 to 25 m.

Table 1: Properties of nonpolar active ingredients for the calculation of the leaching index. From the SCS/ARS/CES Pesticide Properties Database (WAUCHOPEet al., 1992); terbuthylazine and terbumeton properties were taken from WORTHING and HANCE (1991) chemical

molar Solubility mass in water a

Vapour Pressure a

Koc

L/kg

g/mol

g/m 3

Pa

atrazine

215.69

33

3.85 x 10 -5

100

terbumeton

225.3

130

2.70 x 10 -4

450 c

simazine

201.66

2.95 x 10 -6

130

metolachlor 283.80 linuron

249.11

terbuthylazine

229.70

alachlor

269.77

carbaryl

201.23

trifluralin

335.28

6.2

Degradation half-life b days 60 300 60

530

4.18 x 10 -3

200

90

75

2,23 x 10 -3

400

60

1.50 x 10 - 4

450 c

60

240

1.87 x 10 -3

170

15

120

1.60 x 10 -4

300

10

1.47 x 10 -2

8 000

60

8.5

0.3

a For solids: as solid; for liquids (metoIachlor): as liquid; at 20 ~ b To a first approximation, field disappearance half-life values may be applied. All data reported here is referred to field disappearance. c Calculated from the relationship Koc = 0.41 K ow (KAIUCKHOFF,1981).

ESPR-Environ. Sci. & Pollut. Res. 1 (2) 1994

the pesticide leaching from the soil layer (LMt, in mass/surface units) to the input (Mo, in the same units), as follows

(BACCI,1994): L M J M o = JL(o) 1/k [ e x p ( - k t l ) - e x p ( - k t z ) ] / M o

(1)

where JL(o)is the initial leaching flux from the soil compartment in g/(m 2 h), and k the first order disappearance rate constant ( l / h ) including degradation, volatilization, and leaching. When t2 = 8 760 h and tl = 0 h (one year time interval), eq I may be reduced to the simpler form: LMt/Mo = JL(o) 1/k [ 1 - e x p ( - k

8 760)]/M o

(2)

The soil properties selected to calculated the leaching index were as follows: area: 1 m2; depth: 0.1 m; soil porosity: 0.5 m3/m3; field capacity: 0.1 m3/m3; air filled porosity: 0.4 m3/m3; organic carbon (OC) mass (and volumetric) fraction, foc: 0.01 g/g; OC density: 1 kg/L; mineral matter volumetric fraction: 0,49 m3/m3; density of mineral matter: 2.5 kg/L (model soil density = 1.335 kg/L),

For simplicity, soil organic carbon was taken as soil organic matter (this makes the calculations of the leaching index a little different from previous publications, without significantly changing the ranking). The water leaching rate was set at 8.33 x 10 -s m / h (2 mm/day), the pesticide input was 0.1 g / m 2 (1 kg/ha). All these values were entered as default conditions in the BASIC program ( ~ appendix, p. 97).

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Evaluation of Fate and Exposure Models

The properties of the chemicals required: polarity (by means of the acid or base dissociation constant) to select the appropriate partition coefficient (Kor or Kpm , see below); molar mass, g / m o l ; water solubility, mol/m3; vapour pressure, Pa; degradation half-life (days).

The program transforms Ko~ into its dimensionless form by multiplying the current values (generally expressed as reciprocal density in L/kg) by a standard soil bulk density, 0r, taken to be 1.3 kg/L. The option to introduce the density of that soil from where Ko~ data is derived was discarded, due to the approximation of the method (and to the relative complexity in finding this information in literature). For polar compounds, instead of Ko~, the mineral matter/water partition coefficient, Kpm, is required; in this case, when using the program in the appendix, it is suggested to introduce "0" for Kor It is important to remember that the soil model selected for the simulation has an organic carbon mass (and volumetric) fraction of 0.01 and a mineral matter volumetric fraction of 0.49. This may require the transformation of some "pseudo-Ko," values i n t o Kpm. According to WAUCHOPE et al. (1992), pseudo-Ko~ indicates the partition coefficient for polar chemicals, which would correspond to the Ko~ of a soil containing 1 % organic carbon if organic carbon were the adsorbing phase. The transformation into Kpm in relation to the mineral matter volumetric fraction can be carried out as follows: pseudo-Koo L/kg x Pb (soil bulk density) x foe (organic carbon mass fraction: 0.01) = Kow (dimensionless soil/water partition coefficient); then KDWis divided by the volumetric fraction of mineral matter (0.49 in this case) to give the dimensionless Kpm, in (mass/vol)/(mass/vol) units. In this way a correct balance between Ko~ and Kpm c a n be achieved. The properties of the active ingredients for the simulations were obtained from the SCS/ARS/CES Pesticide Properties Database (WAUCHOPE et al., 1992) and from WORTHrNG and HANCE (1991); selected input parameters are reported in Table 1. A major problem in these simulations consists in finding reliable degradation rate measurements: laboratory data may be very accurate but may not represent more or less different "real" conditions; on the other hand, field data may overestimate degradation due to the combination of reaction and mobility in the disappearance phenomena, particularly in the case of extremely volatile or water-mobile compounds. In addition, mobility phenomena affecting disappearance are largely dependent on environmental factors which are typically site-specific and change with time. Disappearance may also occur by the formation of "bound residues". Another aspect is the "homogeneity" of available degradation rate data: the applicability of a model for ranking the potential to reach groundwater implies that the degradation rates of different chemicals are sufficiently homogeneous (i.e. derived from the same - or very similar - soils and from similar environmental conditions). This is unlikely for data obtained from literature. In general, however, when extreme conditions are excluded, the properties of the chemicals seem to play a major role in determining their reactivity in different soils and environments. A practical way to overcome this impasse is to apply "selected" values, such as those in the database of WAUCHOPE et al. (1992), one of the best

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Research Articles

sources of information presently available, with the approximation that disappearance from soils is assumed to be mainly due to chemical transformation.

3

Results and Discussion

The results are summarized in Table 2. The approach for calculating the leaching index can be applied to both nonpolar and polar chemicals by selecting the appropriate soil/water partition coefficient. However, in the present study polar chemicals were not included, because field data was not available. Due to differences in the input of the various pesticides in the area of influence of each well, the number of positive findings cannot be considered as a direct field measurement of the leaching potential. However, it is reasonable to assume that the combination of the number of positive wells, the levels found in the groundwater, and the analytical detection limit provide an indication of the critical region separating leachers from nonleachers. The findings relative to metolachlor and linuron (only one positive well each) are probably due to the higher detection limit (0.1 instead of 0.01 pg/L): with this detection limit, terbumeton and terbuthylazine appear as perfect nonleachers, the concentration in water ranging from 0.01 to 0.09 pg/L. Table 2: Calibrating the L M t / M o leaching index under field conditions

in the Piana del Luco (Siena, Italy) chemical a

LMt/o

No. of positive wells b

levels found in groundwater ~g/L)

detection limit (,ug/L)

atrazine

5.5 x 10 -1

41

0.01 - 1 . 3 0

0.01

terbumeton

5.2 x 10 -1

22

0.01-0.09

0.01

simazine

4.9 x 10 -1

22

0.01 - 0 . 9 3

0.01

metolachlor

4.9 x 10 -1

1

0.41

0.10

linuron

2.5 x 10 -1

1

0.12

0.10

terbuthyl-

2.2 x 10 -1

20

0.01 - 0 . 0 9

0.01

alachlor

1.6 x 10 -1

3

0.10-0.15

0.10

carbaryl

6.7 x 10 - 2

0

--

0.01

trifluralin

1.5 x 10 - 2

0

-

0.01

azine

a Annual application rates are in the range 1 - 4 kg/ha, generally involving only a part of the study area (2 000 ha); a minimum application rate of 50 kg/yr was the criterion used to select chemicals for the study. b Out of a total of 85 wells

4 Conclusions Calculations with known leachers and nonleachers have shown that the range of the leaching index as applied here is limited to 4 orders of magnitude: from about 9 x 10 -1 to 10 -4 (BACCI and GAGG[, 1993; BACCI, 1994). By means of ranking models, it is relatively easy to identify the extremes: for instance, it can be seen that chemicals with values ESPR-Environ. Sci. & Pollut. Res. 1 (2) 1994

Research Articles

of the present index below 1 x 10 -3 (e.g.: cypermethrin, diquat) are typical nonleachers, in agreement with current experience. The m a i n p r o b l e m consists in locating the critical transition region o f the index between leachers and nonleachers. T h e negative findings for carbaryl and trifluralin, even with a detection limit o f 0 . 0 1 / t g / L and application rates in the study area (2 000 ha) of the o r d e r of 250 kg per year suggest that the separation zone corresponds to a leaching index value around 1 x 10 -1. A research is in progress to provide further support to these preliminary conclusions.

5

Literature

BACCI, E.: Ecotoxicology of organic contaminants. CRC Press, Inc., Boca Raton, FL, 1994 BACCI,E.; C. GAGGI:Simple models for ranking pesticide mobility from soils. In: A. M. Del RE, E. CAPRi,S. P. EVANS,P. NATAl.I,and M. TREVISAN (Eds.). Proceedings of the IX. Symposium on Pesticide Chemistry. Mobility and degradation of xenobiotics. Piacenza, 1 2 - 13 October 1993. Edizioni Biagini, Lucca (Italy), 1993, pp. 209 - 219 JUNK, G. A.; J. J. RICHARD:Organics in water: solid phase extraction on a small scale. Anal. Chem. 6 0 : 4 5 1 - 4 5 4 (1988) KARiCKHOFF, S.W.: Semiempirical estimation of sorption of hydrophobic pullutants on natural sediments and soils. Chemosphere 1 0 : 8 3 3 - 8 4 9 (t981) MACKAY, D.: Multimedia environmental models. The fugacity approach. Lewis Publishers Inc., Chelsea, MI, 1991 SWAN,H.: Application of capillary gas chromatography with mass selective detection to pesticide residue analysis. J. Chromatogr. 467: 85 - 98 (1989) WAGENET, R. J.; P. S. C. RAO: Modeling pesticide fate in soils. In: H. H. CHENG(Ed.) Pesticides in the Soil Environment: Processes, Impacts, and Modeling. Soil Science Society of America, Inc., Madison, WI, 1990, pp. 3 5 1 - 399 WAUCHOPE, R.D.; T . M . BUTTLER; A . G . HORNSBY; P. W. M. AUGUSTIJN-BECKERS;J. P. BURT:The SCS/ARS/CES pesticide properties database for environmental decision-making. Rev. Environ. Contam. Toxicol. 123: 1 - 1 5 5 (1992) WORTHING,C. R.; R. J. HANCE:The pesticide manual. Ninth edition. The British Crop Protection Council, Farnham, Surrey, UK, 1991

6

Appendix

10 R E M P r o g r a m to calculate a leaching index 20 P R I N T "Chemical name": I N P U T N$ 30 P R I N T " T e m p e r a t u r e , deg C": I N P U T T C 35 P R I N T " M o l a r mass, g / m o P ' : I N P U T W 40 P R I N T " W a t e r solubility, g/m3": I N P U T S 45 P R I N T " V a p o u r pressure, Pa": I N P U T P 50 P R I N T " O r g a n i c c a r b o n / w a t e r partition coefficient; Koc, L / k g " 55 P R I N T "if the chemical is p o l a r , please input 0" 60 I N P U T K O C D 65 R E M Calculating dimensionless Koc for a s t a n d a r d soil density o f 1.3 k g / L 70 K O C = K O C D , 1.3 75 P R I N T " M i n e r a l m a t t e r / w a t e r partition coefficient, Kmw, dimensionless" 80 P R I N T "(for polar chemicals only; if not, please input 0)"

ESPR-Environ. Sci. & PoUut. Res. 1 (2) 1994

Evaluation of Fate and Exposure Models

90 I N P U T K M W 100 P R I N T "Degradation half-life in soil, T D , days": INPUT T D 110 T H = T D 9 24'Half-life in hours 120 R E M Selected system variables and units: A -- area, m2; Y = soil layer depth, m; YD = diffusion distance, m 1 3 0 A = I : Y = 0 , 1 : Y D = 0.05 140 R E M System variable and units, continued: VF (1) = volume fraction of air; VF (2) = volume fraction of water; VF (3) = volume fraction o f O C ; VF (4) = volume fraction of mineral matter; APRA -- application rate, k g / h a ; LR = water leaching rate, m m / d a y 150 VF (1) = 0.4: VF (2) = 0.1: VF (3) = 0.01: VF (4) = 0.49 160 APRA = 1 170 LR = 2 180 R E M Densities of the soil model c o m p o n e n t s , k g / m 3 190 D E N (1) = 1.2: D E N (2) = 1 000: D E N (3) = 1 000: D E N (4) = 2 500'A, W , O C & M M densities 200VT = 0:MST = 0 210 F O R I = 1 T O 4 : V ( I ) = A,Y,VF(I):MS(I) = V ( I ) , D E N (I) 220 V T = V T + V ( I ) : M S T = M S T + MS ( I ) : N E X T I 230 D E N T = M S T / V T ' s o i l model bulk density, k g / m 3 240 R E M Calculate Z values 250 Z (1) = 1 / ( 8 . 3 1 4 9 (273 + TC)) : Z (2) = ( S / W ) / P : Z(3) = Z(2) x K O C : Z(4) = Z ( 2 ) , K M W 260 M G = A P R A , A / 1 0 : M O L = M G / W 270 R E M Calculate fugacity, Pa 280 V Z T = V(1) 9 Z(1) + V ( 2 ) , Z(2) + V(3) 9 Z(3) + V(4) 9 Z(4) : F = M O L / V Z T 290 R E M Calculate D values, m o l / ( P a h) 300 KR = 0.693/TH : D R = V Z T 9 K R ' D reaction 310 GL = LR 9 000 9 24) : DL = GL 9 Z(2)'D leaching 320 D I F M A = 0 . 4 3 / 2 4 : D I F M W = 0 . 0 0 0 0 4 3 / 2 4 ' M o l e cular diffusivities m2/h 330 Q A = VF (1)a(10/3)/(VF(1)+VF(2))a2 340 Q W = VF ( 2 ~ 1 0 / 3 ) / ( V F ( 1 ) + V F ( 2 ) ) a 2 350 D I F E A = Q A 9 D I F M A : D I F E W = Q W , D I F M W 360 D A = A 9 DIFEA , Z ( 1 ) / Y D : D W = A 9 D I F E W , Z ( 2 ) / Y D ' D i f f u s i o n in air & water 370 KEV = DIFMA/O.O0475 : DE = A , K E V , Z(1)'Air b o u n d a r y layer 380 DV = 1 / ( 1 / D E + 1 / ( D A + DW))'Volatilization 3 9 0 D T = DV + D R + DL 400 R E M Calculate leaching fluxes 410 FXL = DL 9 F'Leaching flux, m o l / ( m 2 h) 420 FXLG = FXL . W'Leaching flux, g/(m 2 h) 430 Calculate disappearance rate constant, KO 440 KO = DT/VZT : MO = MG/A 450 REM Calculate the LEACHING INDEX (leac), at one year (8 760 h) 460LEAC = (FXLG . 1/KO . (1-2.718281828a( - K O *

8 760)))/M0 470 P R I N T "The leaching index for" N $ " is "LEAC 480 I N P U T "DO Y O U W A N T T O R E T U R N T O T H E S T A R T Y / N ? " , R$ 490 If R$ = "Y" O R R$ = "y" G O T O 20 500 E N D

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