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Environmental Potential Risk Indicator for Pesticides


Environmental Potential Risk Indicator for Pesticides

Introduction :

M. Trevisan, G. Errera, E. Capri, L. Padovani, and A. Del Re developed EPRIP for Italian environments. EPRIP calculates a predicted environmental concentration in the groundwater, surface water, soil, and air compartments. To arrive at the predicted environmental concentration in each compartment, the indicator uses a variety of equations that take into account toxicity information, chemical parameter information, and site specific application data. After this predicted environmental concentration is calculated, it is divided by some measure of toxicity that reflects potential harm to organisms residing in that specific environmental compartment. This is the potential risk index.

References:

  • Kosmas, C., Danalatos, N., Cammeraat, L., Chabart, M., Diamantopoulos, J., Farand, R., Gutierrez, L., Jacob, A., Marques, H., Martinez-Fernandez, J., Mizara, A., Moustakas, N., Nicolau, J., Oliveros, C., Pinna, G., Puddu, R., Puigdefabregas, J., Roxo, M., Simao, A., Stamou, G., Tomasi, N., Usai, D., Vacca, A. 1997. The effect of land use on runoff and soil erosion rates under Mediterranean conditions. CATENA 29, 45-59.
  • Trevisan, M., Errera, G., Capri, E., Padovani, L., and A.A.M. Del Re. 1999. Envrionmental potential risk indicator for pesticides. In J. Reus, P. Leendertse, C. Bockstaller, I. Fomsgaard, V. Gutsche, K. Lewis, C. Nilsson, L. Pussemier, M. Trevisan, H. van der Werf, F. Alfarroba, S. Blümel, J. Isart, D. McGrath, T. Seppälä (eds), Comparing Environmental Risk Indicators for Pesticides: Results of the European CAPER Project. Utrecht, The Netherlands: Centre for Agriculture and the Environment. 141- 147.
  • Reus, J., Leendertse, P., Bockstaller, C., Fomsgaard, I., Gutsche, V., Lewis, K., Nilsson, C., Pussemier, L., Trevisan, M., van der Werf, H., Alfarroba, F., Blumel, S., Isart, J., McGrath, D., Seppala, T. 2002. Comparison and evaluation of eight pesticide environmental risk indicators developed in Europe and recommendations for future use. Agriculture, Ecosystems, and Environment 90, 177-187.


Equations :

  • Potential Risk Index groundwater = PECgw/0.1mg/L
    PECgw = LG = 2.739*AF*Rate(1-fint)/P
    AF = exp-0.693*tr/HF
    tr = L*RF*FC/q
    RF = [1+(BD*OC*Koc)/FC+(AC+Kh)/FC]


  • Potential Risk Index soil = PECsoil/LC50 earthworm
    PECsoil = rate*(1-fint)/(100*Depth*BD)

    For repeated applications:
    PECn = PECsoil * (1-exp-nki)/(1-exp-ki)
    k = LN2/HF

  • Potential Risk Index surface water = PECdrift/LC50aquatic organisms
    PECdrift = rate * fdrift / V
    V = [h*(b+h)] / (b+2*h)
  • Potential Risk Index surface water = PECrunoff/LC50 aquatic organisms
    PECrunoff = Pr * Rate3d * Faq / Dr

    Pr = Fst * Fs * Fr * [0.55 * logKoc + 1.47]
    Fs = 0.124 * SL + 0.0082(SL)2
    Fr = 0.0208 * RE + 0.00011 * (RE)2
    RE = Rmax - 17

    Faq = [1/(1+Q)]
    Q = 2 * Koc * OC / 100 * Runoff
    Dr = (0.47 * Rmax) - 10

  • Potential Risk Indexair = PECair/LC50 rat
    PECair = Cair
    Cair = Jo/Vf
    Jo = Da*Csa/d
    Da = 0.036*(76/MW)1/2
    Csa = PECs*BD*Pa/Ac
    Pa = (Za*Va)/(Za*Va+Zw*Vw*Zs*Vs)
    Za = 1/(R*T)
    Zw = S/VP
    Zs = Kd*BD*Zw/(1-P)

For the groundwater risk index, the predicted environmental concentration is divided by 0.1mg/L. 0.1mg/L is the admissible legal concentration in water of a chemical in Italy. For the surface water compartment, a predicted environmental concentration is calculated due to drift of the pesticide onto surface water and runoff of the pesticide onto surface water. A potential risk index due to drift and due to runoff is calculated for algae, crustaceans, and fish. As such, for the surface water compartment, six potential risk indices are calculated.

Each potential risk index for each compartment is ranked on an EPRIP scoring methodology from 1-5 according to the following methodology.

PEC <0.01
EPRIP Risk Point = 1
PEC <0.1
EPRIP Risk Point = 2
PEC <1.0
EPRIP Risk Point = 3
PEC <10.0
EPRIP Risk Point = 4
PEC >10.0
EPRIP Risk Point = 5

As such, a score value range from 1-5 is calculated for the groundwater compartment, the soil compartment, the air compartment, and the six variables in the surface water compartment. To arrive at a final value for the surface water compartment, the maxim value among the six variables is used to arrive at a final EPRIP water value score. Thus, the maximum EPRIP score among the variables surface water runoff for fish, surface water runoff for crustaceans, surface water runoff for algae, surface water drift for fish, surface water drift for crustaceans, and surface water drift for algae is used to determine a final EPRIP score for the surface water compartment. Afterwards, each compartment's value is multiplied to arrive at a final EPRIP score.

For each EPRIP score, penalty points are also considered. A penalty system is used so that for any one environmental compartment, a risk point of 4 adds 25 penalty points and a risk point of 5 adds 50 penalty points. In addition, to be considered for certain classes, a certain number of total risk points in the 4 or 5 value range must be taken into account.


EPRIP Table 1: EPRIP Classification with Penalty Point System

EPRIP Score
Penalty Consideration
Final Potential Risk Classification
1
"none"
2-16
no risk points ≥ 4
"negligible"
17-81
cannot have two risk points ≥ 4
"small"
82-256
cannot have three risk points = 5
"present"
257-400
"large"
>400
"very large"

As a result, the final EPRIP score is obtained with the following equation

  • EPRIP final score =
    (Scoregroundwater * Scoresoil * Scoresurface water * Scoreair) +
    ∑ penalties

List of Symbolsm :

Symbol
Description & Units
AC
soil air content (%)
b
width of ditch bottom (m)
BD
soil bulk density (kg/m3)
C
concentration of air at 1.5 m (g/m3)
Csa
soil-air concentration (kg/m3)
d
thickness boundary layer (m)
Da
diffusion coefficient in free air (m2/h)
Depth
mixing depth of soil (m)
Dr
runoff depth (mm)
Faq
pesticide fraction dissolved in runoff water (kg*mm/m3)
FC
soil field capacity
fdrift
fraction of pesticide lost to drift during application (%)
fint
crop interception (%)
Fr
rainfall factor
Fs
slope factor
Fst
soil type factor
h
ditch depth (m)
HF
soil half-life (days)
i
days between applications
Jo
boundary layer flux (m2/h)
Kh
henry's constant (unitless)
Koc
sorption coefficient (m3/kg)
L
groundwater level (m)
MW
molecular weight of the pesticide's active ingredient (g/mol)
n
number of applications
OC
soil organic carbon content (%)
P
soil porosity (unitless)
Pa
mass fraction in air (unitless)
PD
particle density (kg/m3)
PECair
predicted environmental concentration in air (g/m3)
PECdrift
predicted environmental concentration in surface water due to drift (g/m3)
PECgw
predicted environmental concentration in groundwater (mg/L)
PECrunoff
predicted environmental concentration in surface water due to runoff (g/ha*m3)
PECsoil
predicted environmental concentration in soil (g/m)
Pr
fraction of pesticide lost by runoff
q
net recharge of groundwater (m/year)
rate
pesticide active ingredient application rate (g/m2)
S
water solubility (mol/m3)
SL
slope of the ground (%)
R
gas constant (L*atm/K*mol)
Rate3d
quantity of applied pesticide remaining after 3 days on soil (g/ha)
RE
rain amount in excess (mm)
Rmax
average maximum daily rainfall (mm)
Runoff
quantity of water loss (mm/year)
T
temperature in Kelvin
V
volume of water in a ditch (m)
Va
volume fraction of air
Vs
volume fraction of soil
Vw
volume fraction of water
Vf
dilution velocity (m/h)
Za
fugacity in air compartment (mol/L*atm)
Zw
fugacity in water compartment (mol/L*atm)
Zs
fugacity in soil compartment (mol/L*atm)


Analysis :

This indicator was specifically designed for Mediterranean weather conditions. As a result, when this indicator is used outside of that region, the final results may not be accurate. This is an especially significant problem when calculating runoff values and the predicted environmental concentration in surface water. Those values depend on runoff values from the Mediterranean region calculated from graphs and equations contained in an article by C. Kosmas et al. This indicator also has complex unit conversion schemes that could pose a significant barrier to successful use by some individuals. For example, the units for the PECrunoff variable are hard to interpret.

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