Environmental Potential Risk Indicator for Pesticides
Environmental Potential Risk Indicator for Pesticides
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.
- 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 / DrPr = 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 - 17Faq = [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.
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PEC <0.01
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EPRIP Risk Point = 1
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PEC <0.1
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EPRIP Risk Point = 2
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PEC <1.0
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EPRIP Risk Point = 3
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PEC <10.0
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EPRIP Risk Point = 4
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PEC >10.0
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EPRIP Risk Point = 5
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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
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EPRIP Score
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Penalty Consideration
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Final Potential Risk Classification
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1
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"none"
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2-16
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no risk points ≥ 4
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"negligible"
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17-81
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cannot have two risk points ≥
4
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"small"
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82-256
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cannot have three risk points = 5
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"present"
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257-400
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"large"
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>400
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"very large"
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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 :
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Symbol
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Description & Units
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AC
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soil air content (%)
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b
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width of ditch bottom (m)
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BD
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soil bulk density (kg/m3)
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C
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concentration of air at 1.5 m (g/m3)
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Csa
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soil-air concentration (kg/m3)
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d
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thickness boundary layer (m)
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Da
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diffusion coefficient in free air (m2/h)
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Depth
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mixing depth of soil (m)
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Dr
|
runoff depth (mm)
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Faq
|
pesticide fraction dissolved in runoff
water (kg*mm/m3)
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FC
|
soil field capacity
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fdrift
|
fraction of pesticide lost to drift
during application (%)
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fint
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crop interception (%)
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Fr
|
rainfall factor
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Fs
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slope factor
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Fst
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soil type factor
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h
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ditch depth (m)
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HF
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soil half-life (days)
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i
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days between applications
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Jo
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boundary layer flux (m2/h)
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Kh
|
henry's constant (unitless)
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Koc
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sorption coefficient (m3/kg)
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L
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groundwater level (m)
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MW
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molecular weight of the pesticide's
active ingredient (g/mol)
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n
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number of applications
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OC
|
soil organic carbon content (%)
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P
|
soil porosity (unitless)
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Pa
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mass fraction in air (unitless)
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PD
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particle density (kg/m3)
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PECair
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predicted environmental concentration
in air (g/m3)
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PECdrift
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predicted environmental concentration
in surface water due to drift (g/m3)
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PECgw
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predicted environmental concentration
in groundwater (mg/L)
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PECrunoff
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predicted environmental concentration
in surface water due to runoff (g/ha*m3)
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PECsoil
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predicted environmental concentration
in soil (g/m)
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Pr
|
fraction of pesticide lost by runoff
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q
|
net recharge of groundwater (m/year)
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rate
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pesticide active ingredient application
rate (g/m2)
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S
|
water solubility (mol/m3)
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SL
|
slope of the ground (%)
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R
|
gas constant (L*atm/K*mol)
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Rate3d
|
quantity of applied pesticide remaining
after 3 days on soil (g/ha)
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RE
|
rain amount in excess (mm)
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Rmax
|
average maximum daily rainfall (mm)
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Runoff
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quantity of water loss (mm/year)
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T
|
temperature in Kelvin
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V
|
volume of water in a ditch (m)
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Va
|
volume fraction of air
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Vs
|
volume fraction of soil
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Vw
|
volume fraction of water
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Vf
|
dilution velocity (m/h)
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Za
|
fugacity in air compartment (mol/L*atm)
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Zw
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fugacity in water compartment (mol/L*atm)
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Zs
|
fugacity in soil compartment (mol/L*atm)
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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.
