Input data for the selected test cases and description of calculations

Eleven substances fit in the selected positive and negative cases. Their physico-chemical properties were collected, if possible from their List of endpoints available at http://europa.eu.int/comm/food/plant/protection/evaluation/exist_subs_en.htm and otherwise by making use of data procured by the Dutch Ctgb. The data were critically reviewed, e.g. with respect to sorption coefficient in relation to pH. Table 4.3 lists the physico-chemical properties used for the Tier I PEC calculations. MCPA was included, although we know that its use on hard surfaces may contribute to its measured presence in surface waters. (Glyphosate is included in this table, but, as stated before, it was not included in the Tier I calculations in this report as this substance is known to enter surface water mainly by its use on hard surfaces and not by its use on agricultural crops.)

So, the original list of 18 substances, mentioned in chapter 2.2 was reduced to the 11 substances (including glyphosate) mentioned in Table 4.3.

Table 4.3. Overview of physico-chemical properties of the 10 substances used for calibration of Tier I plus glyphosate * Summary of used pesticide property data

* (version 24/11/2006) *

* DT50-w = half-life time for water from water-sediment study [d]

* DT50-s & T_s = half-life time for water-sediment system [d] & temperature [K] from water-sediment study

* DT50-b & T_b = half-life time for soil [d] & temperature [K] from soil study

* Kom_mn = arithmetic mean Kom value [L/kg]

* Kom_pH = median Kom value in pH 7-8 range for pesticides with pH dependent sorption [L/kg];

* for pesticides with pH dependent sorption Kom_pH is given;

* if the sorption is not pH dependent the value is -999

* Freund = Freundlich coefficient [-]; DEFAULT = 0.9

* Solub & T_sol = Solubility [g/L] & temperature at which this is determined [K]

* M_mass = Molar mass of pesticide [g]

* Psat & T_vap = Saturated vapour pressure [Pa] & temperature at which this is determined [K]

*

* NB: - default for missing data = -999

* - for calculations the worst case Kom is used, i.e. the Kom in pH range 7-8, where this value is available

*

* id# pesticide source_data DT50-w DT50-s T_s DT50-b T_b Kom_mn Kom_pH Freund Solub T_sol M_mass Psat T_vap

* [d] [d] [K] [d] [K] [L/kg] [L/kg] [-] [g/L] [K] [g/mol] [Pa] [K]

01 Isoproturon DAR 42 133 293 11.9 293 60.3 -999 0.9 0.0702 293 260.3 2.8e-6 293

02 Metribuzin draft_DAR 41 48.5 293 11 293 21.5 -999 1.1 1.28 298 214.3 1.21e-4 293

03 MCPA DAR 13.5 16.9 293 24 298 43 24.5 0.9 0.395 298 200.6 4e-4 305

04 MCPP DAR -999 -999 -999 12 283 16.6 12.9 0.9 6.6 293 214.6 1.6e-3 298

05 MCPP-P DAR 36.5 45 293 7.2 293 -999 12.9 0.9 0.86 293 214.65 2.3e-4 293

06 Metolachlor draft_DAR 9 48 293 14.5 293 133 -999 0.9 0.48 298 283.8 3.7e-3 298

07 Dicamba Ctgb 34 45 293 5 293 5 5 0.9 4.51 293 221 2.21e-3 293

08 Terbutylazin Ctgb 18.5 56.5 293 111 293 130 -999 0.9 0.0085 293 229.7 4.68e-5 293

09 Bentazone DAR -999 716 293 45 293 30 15 0.9 0.57 293 240.3 1.7e-4 293

10 Metoxuron(†) Ctgb -999 73 293 8 293 73 -999 0.9 0.678 293 228.7 4.3e-3 293

11 Metazachlor Ctgb -999 33 293 18 293 49 48.5 0.9 0.030 293 277.8 4.7e-5 293

12 Glyphosate DAR -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999

For the 10 substances we calculated the PECTier I by first simulating the FOCUS

scenario for Dutch drift deposition numbers and next feeding the selected edge-of- field PEC into a Fortran program for the Tier I calculation as described in chapter 4.1. All calculations were performed for the D1 and D3 FOCUS ditch scenarios as initially, they were judged to represent the Dutch situation best.

Detailed description of calculations

The so-called GAP sheets were collected to establish the registered use of the 10 selected substances on crops in the Netherlands (Appendix 27 – 36). The D1 and D3 FOCUS surface water scenarios contain a limited number of crop groupings, for D1 these are only winter or spring cereals, spring oil seed rape and grass/alfalfa, while for D3 possible crop groupings are winter and spring cereals and oil seed rape, field beans, legumes, maize, potatoes, sugar beets, bulb, leafy and root vegetables, grass/alfalfa and pome/stone fruit. So all crops mentioned in the GAP sheets were categorized into these FOCUS surface water crops groupings in order to be able to calculate concentrations for the D1 and D3 ditches. Appendix 37 gives an overview of the relationship between the Ctgb crops (mentioned in the registration application forms) and the crop groupings existing in the D1 and D3 FOCUS surface water scenarios. We selected the worst case application pattern of all crops mentioned in the GAP sheet that were combined into one FOCUS crop grouping. These data were introduced in SWASH. They are presented in Appendices 38 to 47. Next the FOCUS_MACRO model was run for all selected crop-substance combinations to simulate drainage entries into surface water. Spray drift entries were determined with the aid of the Dutch drift table (Ctgb, 2006) and next PEC and TWA7d values for the D1 and D3 ditch scenarios were calculated by the FOCUS_TOXSWA_2.2.1 model (Beltman et al., 2006). TWA7d concentrations represent the maximal time- weighted average concentrations calculated with a moving time window for the entire FOCUS simulation period. The results of these simulations are presented in Appendix 48 up to 57. They present details about (i) the crops for which the simulations were executed (ii) the peak and time weighted average concentrations over a period of 7 d, TWA7d, and (iii) their main contributing entry route (spray drift deposition or drainage). These Appendices are input files for the Fortran program, which calculates the concentrations at the nine abstraction points on the basis of the edge-of-field concentrations.

Furthermore the crops of the GAP sheets were categorized into the GeoPEARL crop groupings, presented in Appendix 37, to be able to calculate their relative crop areas. Appendix 58 presents the f_use_intensity and the RCA (Relative Cropped Area) factors are presented in Appendix 59. The data of Appendix 59 show that ‘Grass’ covers the largest surface areas, followed by ‘Cereals’, ‘Sugar beets ’ and ‘Potatoes’ in most intake areas. The fadd_dilution factor was not included in all

calculations. Only for the evaluation of the six negative cases in the Andijk abstraction point it was considered, so after having finalized all calculations.

Appendices 60 up to 69 present the final calculation results, the estimated concen- trations in the nine abstraction points. The results show that the edge-of-field

concentrations may be diluted by a factor of 2 to 3 up to a factor of 30 or more, on their way towards the abstraction points.