pesticide aquatic risk indicators
TRANSCRIPT
Pesticide Aquatic Risk Indicators
- an examination of the OECD indicators REXTOX, ADSCOR and theDanish indicators FA and LI based on Danish sales data from 1992-2000
by Flemming Møhlenberg DHI, Water & EnvironmentKim Gustavson DHI, Water & EnvironmentPeter B. Sørensen, National Environmental Research InstituteDenmark
2
3
Index1 Background.............................................................................................................................................................42 Introduction ............................................................................................................................................................53 Description of Indicators ........................................................................................................................................6
3.1 Frequency of Application ................................................................................................................................63.3 REXTOX.........................................................................................................................................................83.4 ADSCOR .........................................................................................................................................................8
4. Quantitative evaluation of pesticide indicators ......................................................................................................94.1 Data sources.....................................................................................................................................................94.2 Principles of indicator calculation .................................................................................................................104.3 Temporal variation in Indicators....................................................................................................................114.4 Pesticides dominating Indicators ...................................................................................................................134.5 Quantification of input variability..................................................................................................................15
5. Qualitative analysis..............................................................................................................................................185.1 REXTOX.......................................................................................................................................................185.1.2 A simpler version of REXTOX ..................................................................................................................195.1.3 Effect of buffer zones in reducing pesticide transport to streams ...............................................................215.2 ADSCOR .......................................................................................................................................................235.3 FA – Frequency of Application .....................................................................................................................245.4 LI – Load Index .............................................................................................................................................26
6. Conclusion ...........................................................................................................................................................27Annex A. Sale of pesticides in Denmark .................................................................................................................29Annex B. Standard dosages of pesticides. Kg ha-1..................................................................................................31Annex B. Standard dosages of pesticides. Kg ha-1..................................................................................................32Annex C. Calculated Sprayed area (1000 ha) using standard dosage levels............................................................33Annex D No-spray zones (m) required for risk mitigation ......................................................................................35Annex E. Data availability and gaps........................................................................................................................37Annex E. Data availability and gaps (continued) ....................................................................................................38Annex F. Fate data DT50 (days)..............................................................................................................................39Annex F. DT50 Continued.......................................................................................................................................41Annex G. Fate data Kd .............................................................................................................................................42Annex F. Kd Continued............................................................................................................................................44Annex H. Acute Toxicity. Fish96hrLC50 (mg l-1)...................................................................................................45Annex I. Acute Toxicity. Daphnia 48hrEC50(mg l-1)..............................................................................................48Annex J. Acute & Chronic Toxicity. Algae96hrEC50 ............................................................................................50Annex K. Chronic Toxicity. Fish21dayNOEC ........................................................................................................53Annex L. Chronic Toxicity. Daphnia 21day NOEC................................................................................................54Annex L. Chronic Toxicity. Daphnia 21day NOEC................................................................................................55Annex M. Fraction of missing data for acute indicators. .........................................................................................56Annex N. Fraction of missing data for acute indicators...........................................................................................56Annex O. Example of random selection of input data of acute fish toxicity. ..........................................................57Annex P. Min - Max risk indices for fungicides......................................................................................................58Annex Q. Min - Max risk indices for growth regulators..........................................................................................59Annex R. Min - Max risk indices for herbicides......................................................................................................60Annex S. Min - Max risk indices for insecticides....................................................................................................61Annex T. Scaled risk indices for Insecticides & Herbicides....................................................................................62Annex U. Scaled risk indices for Fungicides & Growth regulators.........................................................................63Annex X. Indicator agreement on trends. ................................................................................................................64Annex Y. Trend analysis for Indicators during the period 1992-2000. ...................................................................65Annex Z. Exposure estimation of REXTOX in field studies...................................................................................66Annex AA. Effect of buffer zone width on spray drift and run-off .........................................................................67Annex BB. Modelling relation between FA and Pesticide Effects on Aquatic life. ................................................68Annex DD. Toxicity function in Indicators .............................................................................................................69 Annex EE. Calculation of FA.................................................................................................................................71Annex FF: Calculation of LI....................................................................................................................................72
4
1 Background
As a respond to the recommendation, that OECD develop “systems to measure progress in riskreduction”, made by the OECD/FAO workshop on pesticide risk reduction in Sweden 1995, aworkshop on pesticide risk indicators was held in Copenhagen in 1997.
The workshop recommended that the Pesticide Forum should undertake work to facilitatedevelopment of pesticide risk indicators. It was estimated that the indicators could help nationalgovernments to obtain baseline information about pesticide use and risk and then track risktrends over time.
The workshop did also recommend that it would be better to have a set of indicators dealingseparately with risks to human health and to different compartments of the environment, ratherthan to have one single indicator of pesticide risk.
OECD Pesticide Forum did on that background initiated the Aquatic Risk Indicator Pilot Projectin spring 1998 as a effort to help OECD countries to monitor risk trends over time and evaluatethe effectiveness of risk reduction policies. In Phase 1 of the pilot project an Expert Groupdefined 3 indicators to be tested for consistency using real data of pesticide use in Phase 2. Twoindicators (REXTOX and ADSCOR) were developed in 4 versions allowing to calculate acute orlong-term risks indices associated with single crops (unscaled versions) and at a regional- orcountry wise level of aggregation taking account of pesticide use on single crops and the areacontribution of various crops (scaled indicators). Acute and long-term risks could be calculatedusing corresponding acute or chronic input data for fate and toxicity. The third indicatorSYSCOR was constructed in a scaled version, only.
Phase 2 included a thorough testing of the Indicators using data on actual pesticide use in arableand orchard crops in England and Wales for the period 1977 – 1996 (Report Phase 2).
This report constitutes the Danish contribution to Phase 4 of the Pilot Project on aquatic riskindicators. The Danish testing has included the OECD indicators REXTOX, ADSCOR and theDanish indicators FA (Frequency of Application) and LI (Load Index). The revised SYSCORIndicator was however released too late to be included in the project. Denmark has focused onexamining and comparing the temporal variation in the different indicators for the period 1992-2000 as well as on the indicator sensitivity to variability in input data.
The indicators has been calculated using available information on sale of individual pesticides,area of different crops, buffer zones and recommended doses. The indicators were calculatedseparately for different groups of pesticides and for all pesticides, and risks calculated separatelyfor algae, daphnia and fish. The sensitivity to input data variability was also quantified as part ofan evaluation of the overall robustness of the indicators with respect to describing changes intime trends.
5
2 IntroductionPesticides are used in agriculture to control weed (herbicides), pests, including insects(insecticides), and plant diseases (fungicides). An other type of pesticide applied to fields insignificant amounts includes growth regulators. Different groups of pesticides have differenttypes of effects on aquatic organisms thus making generalisation rather difficult. Most pesticidesare targeted to interfere with specific metabolic processes such as inhibition of electron transport,synthesis of aminoacids, lipid metabolism or mitochondrial respiration. Effects at thebiochemical and cellular level are translated into various effects at the organismic level (cancer,immune and hormonal system) which reduce fitness of the individual and eventually causemortality.
The ecological effects of pesticides are varied, inter-related and often act in concert with otherstressors such as other contaminants, eutrophication and pathogens. In combination differentstresses can be simple additive or effects can be synergistic. An important issue is that many ofthese effects are chronic and non-lethal, i.e. exposures may not result in immediate death butsubtle effects may later reduce reproductive output affecting the long-term survival of thepopulation. Other non-lethal effects include changes in behaviour, e.g. several insecticidesinduce drift in populations of insect larvae and crustaceans. Because of trophic interactionseffects of pesticides usually extend beyond populations to ecosystems, e.g. reduction ofsubmerged plant and algal biomass by herbicides may indirectly affect insect larvae and fish byreducing food availability and deterioration of habitats, and insecticides can indirectly affect fishpopulations by removing their food.
Even though our knowledge is incomplete there exist a wealth of information on how pesticidesare transported from the field to surface waters, how they are distributed and degraded and howthey affect aquatic life. However, detailed understanding and quantification of all processesinvariably will narrow the applicability and make our predictions rather specific for particularsites. On the other hand to evaluate risk trends policy makers do need simple tools or indicatorsTo develop easy to use indicators that extract the critical information of complex natural systemsis a serious challenge that has previously been pursued by the European Union in the CAPERProject, various EPA workshops and extended by the OECD in the Aquatic Risk Indicator PilotProject. It is the intent through different phases of development and validation to compare andimprove different indicators, so they can be applied for policy use and analysis by governmentsand other stakeholders. Such indicators will eventually provide a series of key benchmarks tomonitor changes in risks.
Given the complexity of natural systems and the diverse action of pesticides the limitations ofsimple indicators should be recognised. Indicators are built on information on direct effects, andcalculated risks will not include any information related to interaction in the aquatic system.Indicators provide estimates of risk trends and not absolute measures of actual risks andindicators ultimately rely on the quality of input data. Hence, insufficient data on use, fate andeffects will translate into poor or unreliable estimates of risk trends.
6
3 Description of IndicatorsThe indicators evaluated include the two Danish indicators: Frequency of Application (FA) andLoad Index (LI), (Clausen 1998) and the two OECD Indicators REXTOX and ADSCOR. Theindicators differ in complexity and especially in the amount of input data needed to calculateindicator values with low data requirements by the Danish Indicators while the OECD indicatorsrequiring much more input data (Table 3.1)
Table 3.1 Data requirements of indicators.
LI REXTOX ADSCORParameter FAAcute Chronic Acute Chronic Acute Chronic
Total usage + + + +Sprayed area1 + + +Dosage + +Spray zone length + + + +Run off zone + + + +Kd + + +DT50 + +Fish96hrLC50 + + +Fish21dayNOEC + + +Daphnia48hrEC50 + + +Daphnia21dayNOEC50 + + +Algae96hrEC50 + + +Algae96hrNOEC + + +
1: Calculated as Dosage
saleTotalareaSprayed =
A description of the mathematical equations of the indicators REXTOX and ADSCOR havebeen described in detail in the Report of Phase 2 (ref ). In this report the general form ofindicators are outlined in order to show similarities and dissimilarities between indicators.
3.1 Frequency of Application
The Frequency of Application is the calculated average number of pesticide applications peryear.
FA and LI was the key indicator of the first Danish Pesticide Action Plan from 1986 where thegoals were a re-evaluation of all pesticides and a 50-percentage reduction of FA. (Status of theMinister for the Environment’s Action Plan for reducing the Consumption of Pesticides). FAconstitutes the key indicator of Pesticide Action Plan II from 1999.The indicator Frequency of Application (FA) was developed in the mid-eighties because it wasrealised that the increasing use of low dose products was not reflected in the Danish statistics onsold amount of active ingredients. Thus a drop in sales of active ingredient can easily take placeat the same time as the number of application - and pesticide load on the environment - increases.The indicator considers the quantities of each active ingredient sold, the standard dose of eachactive ingredient in each crop/crop type and the area of arable land in Denmark:
7
∑
=singredientactiveall year
croptype
edientactiveingr
AGRA
SD
SA
FA , (3.1)
where,SA denotes Sold amount of individual active ingredients per yearSD denotes a defined standard dose for each individual active ingredients in each crop/crop typeandAGRA is the area of arable land in Denmark.
More details on the calculation of FA can be found in annex EEThe indicator is regarded as an indicator for the spraying intensity as well as an overall indicatorof the environmental impact of pesticides. Because FA is based on a standard dose that relates tothe biologically active field dose it is assumed to reflect the direct effect on target organisms aswell as the indirect impact on ecosystems, which results from changes in the quantities andspecies found in the food chain. In chapter 5 it is discussed to what extend the standard fielddose varies inversely with toxicity to non-target organisms as fish, daphnia’s and algae. Inaddition, an example is presented on predicted changes in effects on aquatic life following 4different pesticide reduction scenarios.
3.2 Load IndexThe Load Index (LI) is the calculated number of toxic doses in the sold amount ofpesticides.
The indicator Load Index (LI) has been used to track changes in potential pesticide impact onenvironment and health as a result of the Danish re-evaluation of pesticides and the plan toreduce the use of pesticides. The indicator calculates the ratio between Total sale of differentpesticides:Toxicity summed for all active ingredients to follow if number of toxic doses haschanges as a result of either changes in sales and/or toxicity
∑ ⋅=
singredientactiveall year
ingridienteachactive
AGRATOX
SalesLI , (3.2)
where TOX represents acute or long-term LC50 or LD50values.
More details on the calculation of LI can be found in annex FF
The indicator is calculated separately for mammals, birds, earthworms, fish, crustaceans andalgae using a value (average, min or max) for toxicity of individual pesticides. The calculatedvalues are designated "load indices for mammals", "load indices for fish", etc. The LI provides arelative measure of environmental load concerning specific type of toxicity. In line with theOECD indicators LI is not a measure of actual effects on populations or ecosystems in the fieldbut calculates a relative risk that can be compared between years. LI does not includeinformation on exposure risks or buffer zones required for risk mitigation. Such buffer zones caneasily be implemented though by imposing scaled reductions on total sales of pesticide accordingto buffer zone widths.
8
3.3 REXTOX
REXTOX is a mechanistic OECD indicator based on national indicators developed in theNetherlands and Germany. Among the 4 indicators tested REXTOX is the only indicator thatcalculates the amounts of pesticides that are likely to end up in surface waters due to spray driftand surface run-off, while drainage is ignored. The calculated pesticide exposure estimate isdivided by toxicity to obtain a risk index aquatic organisms.
∑ +⋅=singredientactiveall
runoffspraydrift LLTOX
usageTotalREXTOX )%%( , (3.3)
where L%spraydrift is the percentage of the applied amount entering the surface water by spray driftand L%runoff is the percentage of the applied amount entering the surface water by run off.
Calculation of exposure (L%spraydrift + L%runoff) is very detailed even in the acute version as ittakes account of slope, precipitation, soil type, width of buffer zones required for risk mitigationand pesticide characteristics (Kd and half-life) to arrive at pesticide concentrations in waters(Report Phase 2). In testing REXTOX with Danish data default value of slope, C content in soil,water index and precipitation were used throughout in the calculation of pesticide loss inREXTOX. In chapter 5 several assumptions of the exposure calculations of REXTOX arecritically discussed. In addition, accepting the relative importance of spray drift and surface run-off as calculated by REXTOX a simpler expression of exposure is derived.
3.4 ADSCOR
ADSCOR is a hybrid indicator that uses additive scores for exposure (Dosage, Spray (buffer)zones, frequency of treatment, Application Method) that subsequently is multiplied by the ratioTotal area sprayed:Toxicity to calculate a risk estimate for aquatic organisms (Report Phase 2):
∑ ∑
⋅=
singredientactiveall scoring
ApplMzoneoffRunzoneSprayDosageTOX
areaSprayedADSCOR ,,, (3.4)
Using the Danish data frequency of treatments per season of individual pesticides could only becalculated from 1997 onwards, hence the scoring for this variable was set to 0 throughout theperiod in the ADSCOR calculations. In chapter 5 several issues of ADSCOR such as a lowresolution in several scores is discussed in the context of currently used pesticides in Denmark.
Both REXTOX and ADSCOR exist in unscaled and scaled versions. Unscaled versions calculatethe risks associated with pesticides applied to a single field and subsequently average risks toobtain an overall measure. The scaled version provide a measure of total risk taking account ofboth local severity of risk and the area treated with each pesticide. The present examination willfocus on the scaled versions only, because they are more related to the impact measure calculatedby FA and LI than the unscaled versions and because the most important use of the indicatorswill be to indicate the countrywide environmental impact.
9
4. Quantitative evaluation of pesticide indicators
4.1 Data sources
Actual data of pesticide use on Danish arable land is currently not available. Therefore, use datawas calculated from sales data, area of different crops and recommended dosage of activeingredients (Annex A-C). For pesticide products with more than one active ingredient the areatreated was calculated based on the main ingredient. Laboratory data on toxicity and fate ofpesticides were extracted from a database established by the Danish EPA in connection with thepesticide approval procedure and supplemented when necessary with data from US EPAdatabase “Acquire” and data collections carried out by Clausen (1998) and Hansen (2000).Data/results presented as larger than or smaller than a given value are not included in calculationof the indicators.
Figure 4.1. Availability of data for fateparameters (Kd and DT50) and toxicity ofpesticides to Fish, Daphnia and Algae.Average values of arable area representedcalculated for the period 1992-2000. Totalnumber of pesticides =106.
Table 4.1. Data gapsVariable Number of substances with
data gapsPercentage of the total number(106)
DT50 6 6Kd 12 11Acute Fish 9 8Acute Daphnia 13 12Acute Algae 15 14Chronic Fish 83 78Chronic Daphnia 68 65Chronic Algae 80 76
0
20
40
60
80
100
Kd DT50
Missing
Avail.
Dis
t. of
fate
dat
a -
%
0
20
40
60
80
100
Fish Daphnia Algae
Dis
t. of
acu
te to
x da
ta -
%
0
20
40
60
80
100
Fish Daphnia Algae
Dis
t. of
chr
onic
tox
data
- %
10
Data availability for acute toxicity and fate of pesticides was almost complete with more than 95% of the arable area represented (Fig. 4.1). On the other hand, data for chronic toxicity was farfrom complete especially for long-term toxicity to fish and daphnia with more than half of thearable area not represented. Such large fraction not accounted for is likely to produce unreliableresults and accordingly chronic indicators were not included in this test. A detailed enumerationof data availability distributed among years and indicators is shown in Annex E.
4.2 Principles of indicator calculation
The usage of pesticides was calculated from sales data, recommended dose levels and using theyearly statistics on area coverage of different crops. Hence, for each pesticide two numberscharacterise the area treated and amount dosed on this area. In contrast, for every parameterdescribing the fate and toxicity to fish, daphnia and algae several alternative values exist. Thespecific choice of property values will influence the indicator value and this influence needs tobe quantified in order to evaluate the indicators. The effect of varying parameter values on RiskIndicator values and calculated time trends is discussed in section 4.5.
In the quantitative test of indicators four different selection approaches were used:1) averaging all available values of each input parameter,2) selecting the maximum value of toxicity, Kd and minimum value of LD50 to produce the
lowest indicator value,3) selecting the minimum value of toxicity, Kd and the maximum value of LD50 to produce the
highest indicator value and4) random selection of sets of parameter values, but using these sets throughout the whole
period. An example of the random selection procedure for a single pesticide is shown inAnnex O.
By combining results from random selections for all pesticides the variation in risk indices canbe calculated (Fig. 4.2 ).
Figure 4.2. Fifty alternative time series of LI values for fish (thin lines ) and the maximal andminimal possible value time series as (thick lines)
Despite an almost 5 fold variation in absolute values of LI the time trend seemingly is ratherconsistent irrespective of set of parameter values chosen. Therefore, a large variability as shownin Fig. 4.2 does not necessary mean a high uncertainty in the ability to make time trendpredictions. This is further discussed in section 4.5.
Fish all pesticides
0
5
10
15
20
25
30
1992 1993 1994 1995 1996 1997 1998 1999 2000
LI v
alue
11
4.3 Temporal variation in Indicators
In the time trend analysis indicator values were calculated for the period 1992-2000 using datafor pesticide sale, area of different crops, dosage of pesticide, width of buffer zone (that waschanged for several insecticides during the period) and averaged data for toxicity and fate.Indicator values and trends were calculated separately for fish, daphnia and algae both for allpesticides and for each pesticide group. Figure 4.3 shows the temporal variation in indicatorscalculated for all pesticides. Temporal variation in indicators calculated for insecticides,fungicides, herbicides and growth regulators are shown in Annex P - U.
Figure 4.3. Temporal variation of riskindicators calculated for all pesticides.Calculations were based on averaged inputvalues. Two versions of REXTOX areshown – with and without no spray bufferzones required for risk mitigation.Indicator values are scaled to a time meanvalue of unity for each specific indicator.
Among the 4 indicators REXTOX generally showed the strongest temporal variation followed byADSCOR and FA or LI. With one exception (LI algae) risk indicators calculated for allpesticides showed significant decreasing trends for fish, daphnia and algae when the wholeperiod was included (Fig. 4.3 and Table 4.1; temporal trends calculated separately for pesticidegroups are shown in Annex T & U). Most indicators showed a peak in 1995 followed by aminimum in 1996 due to stockpiling in anticipation of a substantial increase of the rate of tax onpesticides in 1996. Such biases are to be expected when pesticide use is derived from sales data.The pattern with local minima and maxima overriding a monotonous trend illustrate thattemporal trends must be calculated based on several years information otherwise erraticconclusions may result. For the most responsive indicator REXTOX 4-5 years’ data was neededto obtain a significant trend, while 9 years’ data was required to obtain a significant trend for theindicator FA using raw sales data for individual years (Fig. 4.4). However, the average value forsales in 1995 and 1996 is properly a reasonable estimate for use in 1995 and 1996. Using theaverage value for indicators 1995-95 significant trend is obtained using 5 years’ of data.Alternatively, using a 3 year running average a significant trend in FA is obtained using 4 years’data only (Fig. 4.4).
Fish
0
0.5
1.0
1.5
2.0
2.5
1992 1994 1996 1998 2000
FTLIREXTOXREXTOX - bufferADSCOR
Daphnia
012345678
1992 1994 1996 1998 2000
Algae
0
1
2
3
4
5
6
1992 1994 1996 1998 2000
12
Table 4.2. Trend analysis for Indicators during the period 1992-2000. Calculated indicators forthe different years were log transformed causing indicators to be normally distributed. Residualswere then calculated by subtracting from each year’s value the corresponding average value forthe period 1992-2000. Residuals were subsequently tested for temporal trends using Kendall’s τ.
Indicator Kendall’s τ ProbabilityFish FA -0.556 0.0371 LI -0.500 0.0606 REXTOX -0.722 0.0067 ADSCOR -0.500 0.0218Daphnia FA -0.556 0.0371 LI -0.556 0.0371 REXTOX -0.778 0.0035 ADSCOR -0.611 0.0218Algae FA -0.556 0.0371 LI 0.000 1 REXTOX -0.833 0.0018 ADSCOR -0.778 0.0035
Figure 4.4. P-value of temporal trend of indicators REXTOX-Fish and FA as a function ofnumber of consecutive years included in analysis. Trend of FA calculated using raw sales data(FA), data averaged for 1995-1996 (95&96) and using a running 3 year average (3 yr. Avr.).Stipulated line indicates p-level of 0.05. Data analysed from year 2000 and back in time.
The agreement between indicators was evaluated by comparing the direction of change (upward“+”or downward “-“) through progressing pair of years (1992,1993), (1993,1994), etc. Theresults for indicators calculated for all pesticides are shown in Table 4.2, where the numbers of“+” and “-“ are summed in the columns at right. For several years the agreement between
REXTOX - Fish
0.00
0.020.04
0.06
0.08
0.100.12
0.14
9876543
p-va
lue
of tr
end
Number of consecutive years
FA
0.0
0.2
0.4
0.6
0.8
1.0
1.2
9876543
p-va
lue
of tr
end
Number of consecutive years
FA (95&96 avr.)
p-va
lue
of tr
end
Number of consecutive years
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
9876543 0
0.02
0.04
0.06
0.08
0.10
0.12
0.14
9876543
FA (3 yr. avr.)
p-va
lue
of tr
end
Number of consecutive years
13
Indicators was good (e.g. 1994-1995, 1997-1998), however ADSCOR indicator calculated foralgae was quite often in conflict with the other indicators. The analysis is further detailed inAnnex X.
Table 4.3 Direction of change in indicator values (calculated for all pesticides) betweenprogressing pair of years. + = values increasing (+); - = values decreasing. Two versions ofREXTOX are included, i.e. taking account and not taking (excl. zone) account of buffer zonesrequired for risk mitigation.
LI REXTOX REXTOXexcl. zone
ADSCOR SumYear
FA
Fish Daphn Algae Fish Daphn Algae Fish Daphn Algae Fish Daphn Algae + -
1992 1993 - + + - - - - + - - - - - 3 101993 1994 - - - + - - - - - + - + - 3 101994 1995 + + + + + + + + + + + + - 12 11995 1996 - - - - - - - - - - - - + 1 121996 1997 + + + + + + - + + + + + - 11 21997 1998 - - - - - - - - - - - - - 0 131998 1999 + + + - - - - + + - - + - 6 71999 2000 - - - - - - - - - - - - - 0 13
4.4 Pesticides dominating Indicators
Pyretroid insecticides (esfenvalerate, lambda-cyhalothrin, alpha-cypermethrin, cypermethrin)were the most influential pesticides for fish and daphnia indicator values and accordinglyspecific indicators calculated for insecticides showed almost identical trends as indicatorscalculated for all pesticides (see Annex T). However, also the herbicide pendimethalin and thefungicides mancozeb and azoxystrobin were among the top 5 pesticides in several indicators(Table 4.2)
14
Table 4.4. Pesticides dominating Indicator values calculated for Fish, Daphnia and Algae. N =number of years (within the period 1992-2000) a specific pesticide was among the mostimportant 5 pesticides contributing to Indicator value. Letters in brackets I: insecticide; H:herbicide; F: fungicide.
LI REXTOX ADSCORFish
Pesticide N Pesticide N Pesticide NEsfenvalerate (I) 9 Esfenvalerate (I) 8 alpha-cypermethrin (I) 9
lambda-cyhalothrin (I) 9 lambda-cyhalothrin (I) 8 Esfenvalerate (I) 9Cypermethrin (I) 7 alpha-cypermethrin (I) 7 lambda-cyhalothrin (I) 9
alpha-cypermethrin (I) 5 Cypermethrin (I) 5 Cypermethrin (I) 7Pendimethalin (H) 4 delta-methrin (I) 5 delta-methrin (I) 6Bromoxynil (H) 3 Mancozeb (F) 4 Tau-fluvalinate (I) 4delta-methrin (I) 3 Azoxystrobin (F) 3 Bromoxynil (H) 1
Triflusulfuron methyl (H) 3 Tau-fluvalinate (I) 2Tau-fluvalinate (I) 2 Bromoxynil (H) 1
Chlorothalonil (F) 1Pendimethalin (H) 1
Daphniaalpha-cypermethrin (I) 9 Esfenvalerate (I) 9 alpha-cypermethrin (I) 9
Esfenvalerate (I) 9 alpha-cypermethrin (I) 8 Esfenvalerate (I) 9Pendimethalin (H) 8 Cypermethrin (I) 7 Cypermethrin (I) 7Cypermethrin (I) 7 Pendimethalin (H) 6 Pirimicarb (I) 6
Malathion (I) 4 Azoxystrobin (F) 3 delta-methrin (I) 5Chlorfenvinfor (I) 3 Pyrazophos (F) 3 Pendimethalin (H) 5
Pyrazophos (F) 3 Linuron (H) 2 Azoxystrobin (F) 2Azoxystrobin (F) 1 Malathion (I) 2 Chlorfenvinfos (I) 2
Pirimicarb (I) 1 Pirimicarb (I) 2Chlorothalonil (F) 1
Glyphosat (H) 1Maneb (F) 1
AlgaeIsoproturon (H) 8 Mancozeb (F) 9 Pendimethalin (H) 9Mancozeb (F) 8 Diquat (H) 8 Isoproturon (H) 8
Propiconazol (F) 8 Isoproturon (H) 8 Propiconazol (F) 7Pendimethalin (H) 7 Propiconazol (F) 5 Diquat (H) 6
Diquat (H) 6 Azoxystrobin (F) 3 Mancozeb (F) 5Cyanazin (H) 3 Cyanazin (H) 3 Azoxystrobin (F) 3
Terbuthylazine (H) 2 Metamitron (H) 3 Cyanazin (H) 3Azoxystrobin (F) 1 Metribuzin (H) 2 Fenpropidin (F) 2Fenpropidin (F) 1 Aclonifen (H) 1 Metribuzin (H) 2Prosulfocarb (H) 1 Fenpropidin (F) 1
Pendimethalin (H) 1Terbuthylazine (H) 1
15
Figure 4.5. Scaled risk indices for Algaecalculated for herbicides, fungicides andinsecticides. Calculations were based onaveraged input values. Indices have beenscaled to allow comparisons withinindices but not between different indices.
Growth regulators, though not contributing significantly to the overall indicator values showeddecreasing trends (but not significant) for indicators calculated for fish and daphnia, but not foralgae (Annex U).
4.5 Quantification of input variability
Absolute values of REXTOX, ADSCOR and LI indicators were very sensitive to variability ininput values. Hence, by consequently selecting minimum or maximum values of toxicity,physico-chemical properties and fate, indicators varied between 1 and 5 orders of magnitude, butwhat was more important: the temporal trends were almost identical irrespective of min or maxinput values were used. The large variation due to the input variability is illustrated in theFigures 4.6-4.8 (and Annex P – S). A similar robustness of indicators to quantify trends was alsodemonstrated, if input values were randomly selected (but selected data sets used throughout the1992-2000 period).
Figure 4.6. Scaled risk indices for Fishcalculated for all pesticides using theminimum and maximum possible inputvalues for toxicity and fate. Notice thatindices have been scaled to allowcomparisons within indices but notbetween different indices.
FTLIREXTOXADSCOR
Herbicides
00.20.40.60.81.01.21.41.6
1992 1994 1996 1998 2000
Fungicides
0
0.5
1.0
1.5
2.0
2.5
1992 1994 1996 1998 2000
Insecticides
0
0.5
1.0
1.5
2.0
2.5
3.0
1992 1994 1996 1998 2000
LI Fish
0
1
2
3
4
5
1992 1994 1996 1998 2000
MinMax
REXTOX Fish
0
1
2
3
4
5
1992 1994 1996 1998 2000
ADSCOR Fish
0
1
2
3
4
5
1992 1994 1996 1998 2000
16
Figure 4.7. Scaled risk indices forDaphnia calculated for all pesticidesusing the minimum and maximumpossible input values for toxicity andfate. Notice that indices have beenscaled to allow comparisons withinindices but not between different indices.
Figure 4.8. Scaled risk indices for Algaecalculated for all pesticides using theminimum and maximum possible inputvalues for toxicity and fate. Indices havebeen scaled to allow comparisons withinindices but not between different indices.
Despite such extreme test conditions the trends calculated with min or max input values with fewexceptions were similar to temporal trends of indicators calculated with averaged input values(Figs 4.6-4.8). This analysis is further detailed in Table 4.4. Using either min or max inputvalues REXTOX disagreed in one instance only (1994-1995 Fish). ADSCOR disagreed in 3 andLI in 4 instances. Therefore the indicators must be regarded as rather robust to demonstrate timetrends.
REXTOX Daphnia
0
1
2
3
4
5
6
1992 1994 1996 1998 2000
ADSCOR Daphnia
0
1
2
3
4
5
6
1992 1994 1996 1998 2000
LI Daphnia
0
1
2
3
4
5
1992 1994 1996 1998 2000
Min
Max
REXTOX algae
0
1
2
3
4
1992 1994 1996 1998 2000
ADSCOR Algae
0
1
2
3
4
1992 1994 1996 1998 2000
LI Algae
0
1
2
3
1992 1994 1996 1998 2000
minmax
17
Table 4.5. Analysis of indicator robustness to predict consistent trends between progressing pairof years using min or max values of fate and toxicity. A “+” denotes that both min and maxvalues of input data result in same direction of change between years (i.e. no indicatoruncertainty due to input uncertainty), while “-“ sign denotes opposite sign of change using minor max input values (i.e. a possible uncertainty in indicator prediction).
LI REXTOX ADSCORYears Fish Daphnia Algae Fish Daphnia Algae Fish Daphnia Algae1992 1993 - + - + + + + + +1993 1994 + + - + + + + - +1994 1995 + + + - + + + + +1995 1996 + + + + + + + + -1996 1997 + + + + + + + + -1997 1998 + + + + + + + + +1998 1999 + - + + + + + + +
1999 2000 + + + + + + + + +
Changes in availability of input data may bias temporal trends. New pesticides will usually bebacked up by fewer data for toxicity and fate than “old pesticides” introduced earlier in theperiod analysed. If so, variability in risk indicator values invariably will increase towards the endof the period examined. To illustrate this, a random sampling of 2, 5 and 10 LC50 values out of atotal of 18 LC50 values for toxicity of α-cypermethrin to fish was carried out (Fig. 4.9). If onlytwo set were sampled the average LC50 varied between 0.0008 and 0.181 mg l-1. The rangedecreased with increasing number of data sets sampled (5 sets: 0.0017 to 0.126; 10 sets: 0.054 to0.098 mg l-1). Assuming the average LC50 of 18 individual values (0.057 mg l-1) represent the“correct” average value of toxicity under-sampling (e.g. representing pesticides with 2 dataavailable) may result in gross under- and overestimates of the “true” average toxicity value (0.3and 71 times). At increasing availability of toxicity data the average value approaches the“correct” average value (Fig. 4.9). However, as trends were rather consistent across indicatorsthe bias probably was more theoretical than real.
Figure 4.9. Range in averageEC50 values for Fish exposed to α-cypermethrin. Out of a total of 18individual EC50 values 2. 5 and 10and 18 (all) values were randomlysampled and averaged. Thesampling was carried out 20 timesresulting in a range of averagedEC50. Single species data wereobtained from the Danish EPAdata base and Aquire (see AnnexH).
0.0001
0.0010
0.0100
0.1000
1.0000
0 5 10 15 20Number of data sets sampled out of 18
Ave
rage
EC
50 v
alue
(m
g l-1
)
18
5. Qualitative analysis
This chapter focuses on the suite assumptions behind the different indicators. REXTOX as themost complex, detailed and ‘data-demanding’ indicator naturally will receive the most attentionespecially what concerns the calculations of exposure. Further, selected breakpoints of theADSCOR are discussed and an example of the applicability of the Danish indicator FA ispresented.
The indicators differ primarily in how exposure risk is calculated, while the toxic effects more orless uniformly relate to the pesticide dose/exposure divided by some measure of toxicity. For thatreason the toxic equations of indicators are discussed separately.
5.1 REXTOX
The basic form of the scaled REXTOX indicator is:
∑ +⋅⋅=singredientactiveall
runoffspraydrift LLTOX
CATADRREXTOX )%%( (5.1)
where ADR (kg/ha) is the dose rate, CAT the accumulated sprayed area (ha), TOX is themeasure for toxicity, L%spraydrift the percentage of the applied amount entering the surface waterby spray drift and Lrunoff is the percentage of the applied amount entering the surface water byrun off.
5.1.1 Exposure calculationSpray drift, edge-of-field runoff, subsurface transport through transient inter-flow in the normalunsaturated zone and drainage constitute the major routes of nonpoint-source pesticide input intoaquatic surface waters. In Europe current regulatory risk assessment focus largely on spray driftand this priority is also reflected in the REXTOX indicator. This is in contrast to reported seriousincidents of fish kills in streams and rivers associated with non-point pesticide sources. They allrelate to surface run-off events in connection with heavy rainfall and not to spray drift duringground pesticide application. Therefore, focussing on spray drift the effect of buffer zonesrequired for risk mitigation to protect aquatic life probably will be underestimated as the effect ofbuffer zones probably is more important for run-off than for spray drift.
REXTOX considers spray drift and surface run-off only. Spray drift is calculated usingderivatives of the Ganzelmeier Tables (Report of Phase 2; 12.1.2.1). In Annex Y is shown acomparison of measured concentration of pesticides as a result of spray drift and surface run-off(and drainage) and calculated concentrations according to the indicator REXTOX. Theinformation has been collected from various literature sources that contain sufficient informationon environmental characteristics, mode and intensity of application to satisfy the input needs ofREXTOX. In some studies information on one or two environmental characteristics was missing.In these cases default values of REXTOX was assumed (see Annex Y).
As shown in Fig 5.1 REXTOX generally underestimate concentrations in streams resulting fromrun-off of pesticides, while spray drift is estimated correctly.
19
Figure 5.1 Comparison of pesticideconcentrations estimated byREXTOX and actual concentrationsmeasured in streams. Data fromAnnex BB.
Pesticides in surface run-off are either in soluble form or associated with particles. Due to highermobility (i.e. low Kd) and thus propensity to loss by surface run-off most studies haveconsidered herbicides, while studies on insecticides with high particle affinities are few, becausethese pesticides are not expected to run-off in significant amounts and if so then primarilyassociated with particles. These considerations are also reflected in REXTOX. But insecticidesdo enter streams by run-off, they appear in the water phase and even though not in true solutionthey are as toxic as expected if in solution (Baughman et al. 1989, Mathiessen et al. 1995, Schulz& Liess 1999a, Schulz & Liess 1999b).
The inherent dominance of spray drift over surface run-off in REXTOX is further illustratedbelow. The values of L%spraydrift and L%runoff were calculated for all pesticides using the non-spray zone for year 2000. The year 2000 represents the most restrictive (widest) spray zone forthe most pesticides (see Annex D). Hence, this analysis favours for the run-off zone influence asthe spray drift is at a minimum value. The L%spraydrift values differs only between substances as aresult of different non spray zones, so the input uncertainty as due to varying fate values (Kd andDT50) will not influence L%spraydrift. On the contrary, Lrunoff is affected by the uncertainty relatedto the fate parameters Kd and DT50, will create uncertainty in the having Kd as the mostimportant parameter to induce uncertainty. In order to evaluate the dominance of the L%spraydrift
the maximum possible influence from L%runoff compared to L%spraydrift is evaluated simply byusing the maximum possible estimates of the L%runoff values based on the databases yielding thefollowing result:
13.0)%(
%
=∑
∑
singredientactiveallspraydrift
singredientactiveallrunoff
LMAX
L
(5.2)
This clearly indicates that the Spray drift is assumed to be the dominating route of entry to thesurface waters in REXTOX.
5.1.2 A simpler version of REXTOX
If the run-off is neglected and the spray drift is assumed to be dominating or in other words if theREXTOX indicator is assumed “valid” in the present form using the present data, then it ispossible to derive a simpler version of the indicator.
0.001
0.01
0.1
1
10
100
0.001 0.01 0.1 1 10 100
REXTOX - µg l-1
Mea
sure
d - µ
g l-1
Run-off
Spray drift
20
The equation for L%spraydrift in early season (i.e. herbicides) is
2)1
(%x
baL spraydrift +
+= (5.3)
where a and b are empirical coefficients and x the spray zone width. The spray zone width isadded by 1 in order not to make infinite vales for x = 0 (this of cause will decrease the actualestimates of spray-drift). The loss of other pesticides applied later in season (with vegetatedbuffer zone) is described by the equation:
)1ln(% +⋅−= xbaspraydrift eL (5.4)
where the x is added by 1 as in Eq. 5.3.
Only 3 spray zones (0, 10 and 20m, see Annex D) are used in the data set so the pesticide inputto a stream can attain the following 3 values (% of application):
Table 5.2. The percentage of applied amount, which enters the surfaceby spray drift according to REXTOX.
Buffer Zonewidth
Herbicides Others Average
0 (+1) 4.08 4.95 4.510 0.22 0.2820 0.16 0.13 0.2
The results in Table 5.2 shows that the spray buffer zone do have a dramatic influence on thespray drift. Thus the exposure due to spray drift calculated by REXTOX roughly splits thepesticides into two groups: those with no buffer (spray) zone and those with buffer zone. In thisway it is possible to write an approximate version of Eq. 5.1 using the Table 5.2 coefficients as:
∑∑ ⋅⋅+⋅⋅≈zonesprayhavingallzonesprayhavingnotall TOX
CATADR
TOX
CATADRREXTOX 2.05.4 (5.5)
Therefore, the RETOX indicator splits up in two sums of tox-weighted usage very much similarto the Load index (LI):
∑ ⋅⋅=
singredientactiveall yearAGRATOX
CATADRLI (5.6)
where AGRAyear is the total agricultural area for the specific year.
Combining Eqs. 5.5 and 5.6 yields:
)2.05.4( zonessprayhavingzonespraynohaving LILIAGRAREXTOX ⋅+⋅⋅≈ (5.7)
21
The conclusion of this analysis is that RETOX in reality represents a weighed sum of the simpleLI between the two categories of pesticides: those with a spray buffer zone and those withoutspray buffer zone. Thus the simple version of REXTOX in form of Eq. 5.7 can replace theoriginal version (Eq. 2.3) for the data used.
This can also be illustrated by a correlation analysis, where the REXTOX and LI are linearlycorrelated as shown in Fig. 5.2.
Figure 5.2. Correlation between REXTOX and LI.
5.1.3 Effect of buffer zones in reducing pesticide transport to streams
Buffer zones along streams, lakes and ponds can reduce the input of pollutants entering theadjacent water body either by intercepting spray drift or surface run-off. Buffer zones andespecially if densely vegetated may act as a physical barrier for suspended solids and associatedcontaminants. Numerous studies have shown a huge variability in the effectiveness of thebuffers, because of different width of buffers, ratio of crop field to buffer area, type of vegetationin buffer zone, soil texture and slope of field and buffer zone. In Figure 5.3 is shown acomparison of measured reductions of pesticides through buffer zones of various widths alongwith calculations carried out according to REXTOX. The reported values on environmentalcharacteristics and information on pesticide data (Kd, DT50, see Annex F & G) has been used tocalculate pesticide entry into streams with and without buffer zones.
Generally, the reduction of pesticide run-off through buffer zone is adequately calculated usingREXTOX when buffer width is large, but REXTOX seem to underestimate the effect of narrowbuffer zones (Fig. 5.3).
0,0E+00
2,0E+06
4,0E+06
6,0E+06
8,0E+06
1,0E+07
1,2E+07
1,4E+07
0 1 2 3 4Load index
RE
XT
OX
with bufferzone
With out bufferzone
22
Fig. 5.3 Effect of buffer zone widthon run-off (% reduction throughbuffer zone) to streams. Calculatedreductions according to REXTOXand actual reductions measuredthrough buffer zones shown (SeeAnnex AA for references).
In conclusion:• the role of spray drift in the REXTOX indicator invariably dominate over run-off• accepting a major role of spray drift a simpler version of REXTOX can be calculated• based on a brief literature survey the role of run-off in the REXTOX indicator seemingly is
too small especially for insecticides with high particle affinities• the role of buffer zone width (especially if the zone is vegetated) is underestimated as both
spray drift and run-off of pesticides show greater reduction than estimated by the REXTOXindicator.
0
20
40
60
80
100
120
0 5 10 15 20 25Buffer width (m)
Red
uctio
n of
pes
t co
nc (
%)
REXTOX
OBSERVED
23
5.2 ADSCOR
The basic form of the scaled ADSCOR indicator is:
∑ ∑
⋅=
singredientactiveall scoring
ApplMzoneoffRunzoneSprayDosageTOX
areaSprayedADSCOR ,,, (5.8)
where Sprayed area is the area treated, TOX is the measure for toxicity, Dosage is the score forDose Rate, Spray zone is the score for Spray drift Buffer zone, Run-off zone is the score forRun-off Buffer zone and ApplM is the score for Method of Application. All input data exceptSprayed area and TOX (-icity) are entered as scores.
5.2.1 Exposure calculationIn the equation for ADSCOR the exposure is included in a scoring system (see Table 5.3).
Table 5.3. The scoring system used in ADSCOR to calculate exposure risk.
Parameter Single value Minimum value Maximum value Score0.1 0
0.1 1 11 3 23 10 3
Average dose rate Kg/ha
10 4Method of application Seed treatment 0
Granular incorporated 1Soil sterilant 1Granular broadcast 2Ground spray 3Air blast 4
Spray drift buffer zone For ground spray -1Runoff buffer zone -1
The average dose rate and method of application encompass the largest range in scores from 0 to4, while presence or absence of buffer zones required for risk mitigation shows the lowest range(0 or –1). ADSCOR in the default form does not discriminate between different buffer widths.
Common to most scoring systems ADSCOR may not be applicable to all countries withoutresetting breakpoints and scores. If not ADSCOR may be too insensitive, e.g. 60% of thepesticides currently used in Denmark will only obtain score 0 or 1, and less than 2% will obtainthe maximum score value on 4 for Average dose rate.
The influence of the different exposure scores on the indicator values was evaluated bycalculating the contribution of the different exposure variables to the overall exposure score forthe period 1992-2000 (see Table 5.4). A noticeable changes within this period was a moreextended requirement for no spray buffer zones for several pesticides in 1997 (see Annex D).
24
Table 5.4. The total exposure scoring in ADSCOR for each year during the period 1992-2000.
1992 1993 1994 1995 1996 1997 1998 1999 2000Average dose rate 103 105 103 70 72 73 76 88 71Method of application 318 318 318 318 318 318 318 318 318Spray drift buffer zone -6 -13 -17 -22 -27 -35 -39 -46 -47Runoff buffer zone 0 0 0 0 0 0 0 -106 -106Total: 415 410 404 366 363 356 355 254 236
Overall ADSCOR is driven by the ratio Tox
areaSprayed, however, the temporal variation in the
total scoring as well as the contribution of the individual exposure variables highlights theinfluence from the spray and run-off zone (Table 5.4). Generally, buffer zones do influence thecontribution from run-off to a much higher extent than contribution from spray drift, which seemto be consistent with literature values (see Annex Z & AA). This is in contrast to REXTOX,where the spray drift was dominating.
Conclusion:Like other scoring indicators ADSCOR offer several strengths including• easy of use and easy to adapt to specific environmental or management needs• scores allow to include all routes of exposure without calculating precise levels for each
variable
However, ADSCOR (and other scoring systems)• inherently suffers from low sensitivity to react on even large changes in inputs because of
few breakpoints for important variables• is rather subjective in determining break points and coefficients, making it difficult to make a
general and objective evaluation of the scoring results in relation to other indicators such asREXTOX which is based on a deterministic approach
5.3 FA – Frequency of Application
Among the indicators evaluated FA is by far the simplest as it does not include explicit estimatesfor exposure or toxicity.
∑
=singredientactiveall year
croptypescrop
edientsactiveingrindividual
AGRA
SD
SA
FA/
, where
SA is the amount sold of individual active ingredients per year, SD the standard dose for eachingredient in each crop/crop type and AGRA the area of arable land in Denmark
Because FA is based on a standard dose that relates to the biologically active field dose it isimplicitly assumed to reflect the direct effect on target organisms as well as the indirect impacton ecosystems, which results from changes in the quantities and species found in the food chain.This assumption probably is valid for target organisms in the field, but FA has also been shownto be a valid indicator for several bird species other terrestrial non-target organisms. Briefly, thepopulations of several bird species have been shown to correlate negatively with the number of
25
herbicide-, insecticide- and fungicide applications, i.e. FA (Pest Res. No. 34). In another studythe preliminary results indicates that diversity of flora and fauna was increased followingreductions in FA by 50% and 75% (Esbjerg et al. to be publicised in 2002). In addition, amodelling exercise demonstrated a close correlation between FA and the probability ofsignificant reductions in populations of daphnia and algae in model ponds (Fig. 5.4, Annex BB).However, an examination on the most frequently used pesticides in Denmark indicates that aninverse relationship between applied dose and toxicity of pesticides may not be universallywarranted for all non target aquatic organisms. It should be noted that the examination includesrelatively few pesticides and that this may have biased the outcome significantly. (Annex CC).
Figure 5.4. Relation between probability for significant effects on populations of algae(♦ ) and daphnia (■ ) and FA index (from Møhlenberg & Gustavson 1998).
Conclusion:FA only considers sales of pesticides and the sprayed area. Therefor FA is the easiest to useindicator and by not relying on data on toxicity and fate FA inherently is objective (e.g. nochoices how to select input data have to be made) and the most conservative among indicatorstested.• FA produce risk trends very similar to those produced by more complex and data-intensive
indicators like REXTOX (albeit less responsive and requiring longer periods to obtainsignificant trends).
• Several studies (experimental and modelling exercises) have indicated that FA is areasonable risk indicator for terrestrial and aquatic ecosystems.
However,• By not including no spray buffer zones required for risk mitigation FA will not be able to
predict temporal variations in risks associated with adoption of new buffer zone widths, and• There are indications that suggest that an inverse relationship between applied dose and
toxicity of pesticides may not be universally warranted for all non-target organisms in theaquatic environment. It should however be noted that the examination includes relatively fewpesticides and that this may have biased the outcome significantly.
0%
20%
40%
60%
80%
100%
0 0.5 1 1.5 2 2.5 Frequency of application
Pro
babi
lity
of d
etec
ting
sign
ifica
nt r
educ
tions
inpo
pula
tions
26
5.4 LI – Load Index
Load Index is used as a supplement to FA in Denmark and does take account of the toxicity ofdifferent pesticides:
∑ ⋅=
singredientactiveall yearAGRATOX
usageTotalLI ,
LI is closely related to REXTOX (see 5.1.2) and is driven by the toxicity of individual pesticides.In accordance, LI produce risk trends almost similar to REXTOX. However, LI does not takeaccount of varying buffer zone widths and therefore LI will not be able to predict temporalvariations in risks associated with adoption of new buffer zone widths. This was the sole reasonwhy LI was less responsive than REXTOX.
27
6. ConclusionThe pesticide risk indicators tested REXTOX, ADSCOR, FA and LI differ markedly incomplexity and amount of input data required. However, regardless of their complexity it ismainly use/sales data and toxicity of pesticides that drives the indicators. Thus very simpleindicators such as FA and LI produce risk trends very similar to risk trends produced by the morecomplex and data-intensive indicators REXTOX and ADSCOR.
The indicators FA and LI do not take account of requirements for no-spray bufferzones.Therefore, FA and LI will not be able to predict temporal variations in risks associated withchanges in requirement for no-spray buffer zones. This was the main reason why FA and LI wereless responsive than e.g. REXTOX and a longer period was needed to obtain significant risktrends. However, by not including buffer zone issues related to farmers’ compliance withrequirements for no spray buffer zones calculated risk trends inherently will be moreconservative that indicators including buffer zones.
Data on pesticide fate and toxicity are highly variable and the indicators LI, REXTOX andADSCOR were very sensitive to variation in input data with a maximal variation in valuesranging 1-5 orders of magnitude. This did not affect risk trends as long as the same rules werefollowed each year for selecting values (e.g. so that minimum, maximum or average values isconsistently selected). This shows that the indicators are very robust.
Depending on choice of input data the values of a single indicator occasionally showedcontradictory year-to-year trends without this affecting risk trend over longer time, and differentindicators (calculated on the basis of the same input data) did also show contradictory trends agiven year without this affecting risk trend over longer time. These facts emphasise that severalyears are needed for calculating trends over time.
Data on pesticide sales was used as a substitute for data on actual use of pesticides. Thisintroduced a bias in the indicators in 1995-1996 due to stockpiling caused by tax imposition.However, because several years’ data were available the bias introduced by using sales was ofminor importance. Therefore, sales data provide an adequate substitute for actual use when broadnational risk trends are requested.
Overall, simple indicators such as FA and LI proved to be adequate for estimating pesticide risktrends in Denmark. To make indicators more responsive to e.g. new requirements for buffer zoneas a mean of risk mitigation minor modifications of FA and LI can be included.
Given the complexity of natural systems and the diverse action of pesticides the limitations ofsimple indicators should be recognised. Indicators are built on information on direct effects, andcalculated risk trends will not include information related to interactions in the aquaticenvironment. Indicators provide estimates of risk trends and not absolute measures of actual risksand indicators ultimately rely on the quality of input data. Hence, insufficient data on use, fateand effects will translate into poor or unreliable estimates of risk trends.
Major gaps were identified with respect to chronic toxicity data for fish, daphnia and algae. Asthis is likely to bias the risk trends significantly chronic indicators were not included in this test.
28
Annexes
29
Annex A. Sale of pesticides in DenmarkAgricultural usage (kg)
1992 1993 1994 1995 1996 1997 1998 1999 2000Fungicides
Azoxystrobin 0 0 0 0 0 0 69651 93458 68775Benomyl 2598 488 401 0 0 0 0 0 0Carbenazim 19481 6975 3900 10708 0 0 0 0 0Chlorothalonil 17428 6017 5951 5490 6194 19442 21310 9852 5872Cuprihydroxidchlorid 26136 11951 0 0 0 0 0 0 0Cyprodinil 0 0 0 0 0 0 0 20770 22564Dimethomorph 0 0 0 0 0 0 0 0 1878Fenpropidin 0 0 0 0 0 0 7275 39698 5235Fenpropimorph 365228 332306 317870 286611 196565 278496 219280 132881 118649Fluazinam 0 0 0 0 0 0 12540 14147 10482Iprodion 2114 1489 1530 1611 2441 3413 0 0 0Kresoxim-methyl 0 0 0 0 0 0 0 22767 2117Mancozeb 181565 201360 164018 258269 282411 270307 294482 333211 311455Maneb 433650 273700 243694 246488 0 97500 64800 0 0Metalaxyl 3724 4441 4150 4606 0 0 0 0 0Prochloraz 90700 57085 26903 27293 29435 16520 11615 3537 1386Propamocarb 0 0 0 16095 13536 12286 4404 5476 1300Propiconazole 109511 88403 84053 97501 66847 85522 40545 18412 21195Propineb 9464 6877 7819 2237 2854 2658 0 0 0Pyrazophos 553 669 846 0 0 0 0 0 0Tebuconazol 0 0 0 0 0 0 22141 14535 40025Thiabendazol 161 288 212 0 0 0 0 0 0Thiophanat methyl 1794 0 0 0 0 0 0 0 0Triadimenol 22256 12120 7708 6685 0 0 0 0 0Tridemorph 15357 0 0 0 0 0 0 0 0Vinclozolin 1011 0 705 728 1909 3129 0 0 0
Growth regulatorsChlormequat Chloride 250389 317876 237736 289415 71008 84366 151188 207385 193867Ethephon 18940 7877 4769 16455 10020 15341 17416 12110 8234Maleinhydrazid 663 1105 1069 1253 1467 378 288 0 536Mepiquat-chlorid 11175 4365 3666 3337 4270 3788 3398 1366 1495Trinexapac-ethyl 0 0 0 0 0 0 2270 292 40
Herbicides2,4-D 40970 29951 33036 15717 5673 0 0 0 0Aclonifen 0 0 0 0 0 0 15648 14304 5748Asulam 0 1366 2522 2652 1630 1882 1726 2388 2498Atrazin 16687 42594 665 0 0 0 0 0 0Benazolin 3630 1720 4144 3786 5376 0 0 0 0Bentazon 70496 82329 69352 93326 80577 79317 68918 54081 47773Bromoxynil 35427 22287 20601 29816 33142 96181 80192 56463 42327Carbetamid 10706 2890 4605 0 0 0 0 0 0Chloridazon 16640 21057 23195 11765 11037 0 0 0 0Chlorsulforon 92 32 68 0 0 0 0 0 0Clopyralid 16682 14727 15089 22587 11592 10725 12224 9917 7128Cyaniazin 53208 51129 45968 0 1405 0 0 0 0Desmedipham 4004 3831 4466 3175 1798 1035 912 1196 1686Dicamba 2127 1058 1144 1372 464 29 2810 591 2553Dichlorprop-P 240977 171073 139955 129338 49473 3261 2908 1451 1693Difenzoquat methyl sulfat 25016 18080 11883 11581 29842 17469 16731 13999 0Diflufenican 0 0 0 0 0 0 0 15735 1456Diquat 52793 58879 44353 51659 42341 74883 7190 17403 15092Ethofumesate 57578 50761 35107 52906 31408 22575 21629 15594 15273Fenoxaprop-P-ethyl 0 0 0 0 0 2444 5728 4522 3872Flamprop-M-isopropyl 18582 13157 7704 13877 12327 13384 12272 6800 10110Fluazifop-P-butyl 12089 14139 12636 15321 10845 10704 6222 6684 5030Fluroxypyr 9130 10368 11206 22378 17790 28270 30852 40191 18389Glufosinate ammonium 541 709 547 838 661 523 1342 2074 3443Glyphosate 350944 300017 392549 472763 447788 554373 618496 513398 671731Glyphosate-Trimesium 0 159390 155368 198526 204650 248278 203283 179203 206442Haloxyfop ethoxyethylester 2573 4305 4211 7241 3592 6525 5465 3856 3320Ioxynil 97654 74475 73075 93093 86102 92130 80937 71430 39468Isoproturon 300876 249235 346767 453168 523547 541365 433725 247525 10275Isoxaben 1977 930 2602 4107 3926 3942 3427 3563 0Linuron 11146 3544 4104 11255 10643 9603 8019 6228 7002MCPA 348206 281516 285793 387396 257543 72903 153215 112380 142113MCPB 17113 0 0 0 0 0 0 0 0
30
Annex A. Agricultural usage (kg), continued
1992 1993 1994 1995 1996 1997 1998 1999 2000Herbicides (continued)
Mechlorprop-P 472092 369034 332545 380565 229469 11703 19237 12217 11594Metamitron 285390 273210 245112 248896 220097 207298 189382 58436 100065Methabenzthiazuron 10466 12712 12726 17910 19712 10917 7672 9142 11200Metribuzin 17814 17133 10452 12670 9317 12389 5334 5691 6676Metsulfuron methyl 766 692 661 768 223 384 790 1128 753Napropamide 3845 417 5400 8280 7524 9009 4491 17208 4000Paraquat 0 993 265 0 0 0 0 0 0Pendimethalin 110078 118712 132926 233726 267328 357928 374158 185438 243256Phenmedipham 54823 58554 61857 63479 42398 34282 30844 27875 29998Propachlor 6325 6172 7111 0 25 6 0 0 0Propaquizafop 0 0 0 2394 1253 1436 2049 1932 482Propyzamid 26644 27537 30580 29709 19883 19170 19050 13182 8867Prosulfocarb 0 24986 22928 47984 149568 74512 113224 85184 247664Pyridate 0 3240 19260 0 17991 4841 13383 12717 14768Terbacil 67 0 0 0 0 0 0 0 0Terbuthylazine 2182 4068 14121 51488 34671 52849 42270 57273 32473Thifensulfuron-methyl 17 158 123 138 0 632 746 165 200Tri-allat 2403 136 32 0 0 320 580 700 0Triasulfuron 0 0 0 283 24 72 255 69 322Tribenuron methyl 3015 2592 2192 5146 1160 5060 1548 2816 4785Trifluralin 10248 25957 33936 67475 8654 30505 0 0 581Triflusulfuron methyl 0 0 0 0 175 768 269 325 389
Insecticidesalpha-cypermethrin 3115 3146 1263 4722 1303 609 659 1287 602Carbofuran 1512 1674 1425 1612 563 1139 286 274 725Chlorfenvinphos 1572 897 753 629 908 26 89 101 130Cypermethrin 4524 5152 5040 9360 0 2016 2394 3323 0Deltamethrin 808 718 370 544 29 73 0 0 0Diazinon 1820 1860 1725 2135 295 0 0 0 0Dimethoate 62790 51538 37250 64378 19540 32718 36996 21852 24610Endosulfan 579 456 495 0 0 0 0 0 0Esfenvalerate 5924 5213 4741 7678 1189 2965 751 1985 759Fenitrothion 121 0 0 0 0 0 0 0 0Lambda-cyhalothrin 767 1184 1194 1548 1020 1000 1171 790 645Malathion 2688 3219 1850 2945 2466 3576 1434 2275 0Mercaptodimethur 21 0 19 24 0 0 0 0 0Metaldehyd 76 84 39 220 395 530 3684 3697 7987Mevinphos 188 151 104 198 0 0 0 0 0Oxydemeton-methyl 264 227 214 28 0 0 0 0 0Phosphamidon 640 0 0 0 0 0 0 0 0Phoxim 919 816 587 336 188 216 0 0 0Pirimicarb 39675 30988 37910 66245 6435 5024 5787 5579 1000Tau-fluvalinate 0 0 0 0 1190 850 2040 4370 4994
31
Annex B. Standard dosages of pesticides. Kg ha-1.1992 1993 1994 1995 1996 1997 1998 1999 2000
FungicidesAzoxystrobin 0.250 0.250 0.272Benomyl 0.999 0.244 0.251Carbenazim 0.770 0.734 0.684 0.878Chlorothalonil 1.254 1.254 1.240 1.248 1.239 1.246 1.254 1.247 1.249Cuprihydroxidchlorid 3.788 6.639Cyprodinil 0.400 0.400DimethomorphFenpropidin 0.750 0.750 0.748Fenpropimorph 0.865 1.029 1.022 0.383 0.397 0.409 0.483 0.286 0.477Fluazinam 0.200 0.200 0.200Iprodion 0.571 0.573 0.588 0.597 0.581 0.588Kresoxim-methylMancozeb 1.889 1.914 1.974 2.022 1.698 1.694 1.635 1.633 1.591Maneb 1.998 2.001 1.500 1.500 1.500 1.500Metalaxyl 0.199 0.200 0.200 0.200Prochloraz 0.573 0.665 0.621 0.571 0.829 0.601 0.624 0.431 0.433Propamocarb 1.000 1.003 0.999 1.001 0.996 1.000Propiconazole 0.175 0.161 0.170 0.919 0.446 0.758 1.229 0.829 6.837Propineb 1.753 1.763 1.738 1.721 1.784 1.772Pyrazophos 0.614 0.608 0.604Tebuconazol 0.272 0.263 0.259Thiabendazol 0.537 0.576 0.530Thiophanat methyl 0.352Triadimenol 0.125 0.125 0.125 0.125Tridemorph 0.844Vinclozolin 0.532 0.504 0.520 0.502 0.497
Growth regulatorsChlormequat Chloride 0.932 0.929 0.931 0.927 0.933 1.139 1.005 0.976 0.980Ethephon 0.607 0.579 0.691 0.478 0.533 0.478 0.463 0.648 0.664Maleinhydrazid 2.210 1.842 2.138 2.088 2.096 1.890 2.880 1.787Mepiquat-chlorid 0.601 0.598 0.601 0.596 0.601 0.601 0.596 0.594 0.598Trinexapac-ethyl 0.125 0.127 0.133
Herbicides2.4-D 0.703 0.722 0.923 1.455 2.364Aclonifen 1.505 1.460 1.474Asulam 1.518 1.484 1.473 1.482 1.448 1.569 1.493 0.806Atrazin 0.987 1.954 0.739Benazolin 0.190 0.307 0.309 0.310 0.311Bentazon 2.797 0.858 0.817 0.801 0.668 0.499 0.492 0.510 0.523Bromoxynil 4.542 3.377 1.703 3.923 5.814 1.289 1.001 564.630 0.383Carbetamid 2.099 2.064 2.093Chloridazon 2.600 2.600 2.606 2.614 2.628Chlorsulforon 0.004 0.004 0.004Clopyralid 0.116 0.129 0.131 0.134 0.156 0.113 0.176 0.215 0.141Cyaniazin 0.378 0.382 0.342 0.343DesmediphamDicamba 0.073Dichlorprop-P 1.844 1.659 1.449 1.010 1.008 0.836 0.831 0.854 0.847Difenzoquat methyl sulfat 1.117 1.116 1.111 1.114 1.114 1.113 1.115 1.111Diflufenican 0.094 0.102Diquat 0.909 0.904 0.905 0.906 0.907 0.905 0.910 1.360 1.360Ethofumesate 0.749 0.653 0.919 0.590 0.635 0.640 0.562 0.600 0.491Fenoxaprop-P-ethyl 0.069 0.069 0.069 0.069Flamprop-M-isopropyl 0.599 0.598 0.602 0.601 0.601 0.600 0.602 0.602 0.598Fluazifop-P-butyl 0.316 0.314 0.315 0.315 0.315 0.315 0.314 0.331 0.340Fluroxypyr 0.188 0.222 0.346 0.321 0.242 0.150 0.183 0.144 0.159Glufosinate ammonium 0.541 0.591 0.608 0.599 0.601 0.581 0.610 0.593 0.604Glyphosate 0.873 0.939 1.057 1.058 0.971 1.050 1.101 1.120 1.172Glyphosate-Trimesium 1.440 1.440 1.440 1.358 1.311 1.256 1.896 1.887Haloxyfop ethoxyethylester 0.250 0.192 0.192 0.192 0.192 0.192 0.192 0.192 0.169Ioxynil 0.245 0.239 0.261 0.272 0.233 0.222 0.246 0.252 0.349Isoproturon 1.224 1.225 1.229 1.227 1.234 1.250 1.250 1.250Isoxaben 0.080 0.080 0.112 0.095 0.081 0.106 0.200 0.313Linuron 0.995 0.984 1.001 0.996 1.004 1.000 1.002 1.005 1.000MCPA 1.481 2.028 1.706 1.577 1.233 1.288 0.892 1.243 1.410MCPB 1.347
32
Annex B. Standard dosages of pesticides. Kg ha-1
1992 1993 1994 1995 1996 1997 1998 1999 2000Herbicides (continued)
Mechlorprop-P 7.164 7.208 8.549 9.397 23.179Metamitron 3.502 3.498 3.502 3.501 3.499 3.502 3.501 2.102 2.098Methabenzthiazuron 2.093 2.119 2.086 2.107 2.097 2.099 2.074 2.126 2.113Metribuzin 0.500 0.500 0.500 0.501 0.250 0.250 0.250 0.250 0.250Metsulfuron methyl 0.006 0.006 0.005 0.005 0.005 0.005 0.005 0.005 0.005Napropamide 0.610 0.596 0.478 0.521 0.485 0.479 0.478 0.479 0.482Paraquat 0.828 0.883Pendimethalin 1.101 1.099 1.356 1.357 1.356 1.323 1.323 1.323 1.368Phenmedipham 0.653 0.711 0.595 0.829 0.833 0.790 0.771 0.845 0.761Propachlor 4.518 4.748 4.741Propaquizafop 0.122 0.123 0.123 0.123 0.125 0.118Propyzamid 0.645 0.645 0.645 0.646 0.646 0.645 0.646 0.499 0.501Prosulfocarb 2.807 2.796 2.806 2.854 2.801 2.803 2.802 2.798Pyridate 1.906 0.900 0.900 0.896 0.898 0.480 0.479Terbacil 0.335Terbuthylazine 1.148 1.162 0.759 1.195 1.313 1.106 0.899 1.176 27.061Thifensulfuron-methyl 0.007 0.007 0.008 0.008 0.007 0.008 0.008 0.008Tri-allat 24.030 1.360 1.600 1.600 1.450 1.750Triasulfuron 0.004 0.004 0.004 0.004 0.003 0.004Tribenuron methyl 0.006 0.006 0.007 0.008 0.007 0.008 0.010 0.008 0.008Trifluralin 1.708 0.868 0.853 0.872 0.874 0.820 0.830Triflusulfuron methyl 0.045 0.045 0.041 0.045 0.045
Insecticidesalpha-cypermethrin 0.013 0.013 0.013 0.012 0.013 0.013 0.015 0.012 0.012Carbofuran 0.687 0.644 0.679 0.672 0.704 0.670 0.715 0.685 0.659Chlorfenvinphos 0.983 0.997 2.510 3.145 1.009 0.890 1.010 1.300Cypermethrin 0.040 0.040 0.040 0.040 0.040 0.040 0.040Deltamethrin 0.007 0.007 0.007 0.006 0.006 0.007Diazinon 3.640 3.720 4.313 4.270 2.950Dimethoate 0.301 0.299 0.307 0.298 0.304 0.292 0.295 0.306 0.304Endosulfan 0.526 0.570 0.550Esfenvalerate 0.013 0.014 0.010 0.010 0.010 0.010 0.010 0.010 0.010Fenitrothion 0.605Lambda-cyhalothrin 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008Malathion 0.584 0.555 0.561 0.566 0.560 0.559 0.896 0.910Mercaptodimethur 0.105 0.000 0.095 0.120Metaldehyd 0.760 0.840 0.390 0.550 0.494 0.482 0.505 0.500 0.499Mevinphos 0.145 0.151 0.149 0.152Oxydemeton-methyl 0.126 0.119 0.126 0.140Phosphamidon 0.256Phoxim 4.595 4.080 5.870 3.360Pirimicarb 0.136 0.135 0.136 0.136 0.136 0.136 0.134 0.134 0.135Tau-fluvalinate 0.060 0.060 0.060 0.060 0.060
33
Annex C. Calculated Sprayed area (1000 ha) using standard dosage levels1992 1993 1994 1995 1996 1997 1998 1999 2000
FungicidesAzoxystrobin 278.6 373.8 252.9Benomyl 2.6 2.0 1.6Carbenazim 25.3 9.5 5.7 12.2Chlorothalonil 13.9 4.8 4.8 4.4 5.0 15.6 17.0 7.9 4.7Cuprihydroxidchlorid 6.9 1.8Cyprodinil 51.9 56.4DimethomorphFenpropidin 9.7 52.9 7.0Fenpropimorph 422.3 322.9 311.0 748.4 495.4 681.0 454.0 463.9 248.7Fluazinam 62.7 70.7 52.4Iprodion 3.7 2.6 2.6 2.7 4.2 5.8Kresoxim-methylMancozeb 96.1 105.2 83.1 127.7 166.3 159.6 180.1 204.1 195.8Maneb 217.0 136.8 162.5 164.3 65.0 43.2Metalaxyl 18.7 22.2 20.8 23.0Prochloraz 158.2 85.8 43.3 47.8 35.5 27.5 18.6 8.2 3.2Propamocarb 16.1 13.5 12.3 4.4 5.5 1.3Propiconazole 626.2 547.6 494.8 106.1 149.9 112.8 33.0 22.2 3.1Propineb 5.4 3.9 4.5 1.3 1.6 1.5Pyrazophos 0.9 1.1 1.4Tebuconazol 81.3 55.2 154.8Thiabendazol 0.3 0.5 0.4Thiophanat methyl 5.1Triadimenol 178.0 96.9 61.7 53.5Tridemorph 18.2Vinclozolin 1.9 1.4 1.4 3.8 6.3
Growth regulatorsChlormequat Chloride 268.7 342.3 255.4 312.1 76.1 74.1 150.4 212.5 197.9Ethephon 31.2 13.6 6.9 34.4 18.8 32.1 37.6 18.7 12.4Maleinhydrazid 0.3 0.6 0.5 0.6 0.7 0.2 0.1 0.3Mepiquat-chlorid 18.6 7.3 6.1 5.6 7.1 6.3 5.7 2.3 2.5Trinexapac-ethyl 18.2 2.3 0.3
Herbicides2.4-D 58.3 41.5 35.8 10.8 2.4Aclonifen 10.4 9.8 3.9Asulam 0.9 1.7 1.8 1.1 1.3 1.1 1.6 3.1Atrazin 16.9 21.8 0.9Benazolin 19.1 5.6 13.4 12.2 17.3Bentazon 25.2 95.9 84.9 116.5 120.7 158.8 140.1 106.0 91.3Bromoxynil 7.8 6.6 12.1 7.6 5.7 74.6 80.1 0.1 110.4Carbetamid 5.1 1.4 2.2Chloridazon 6.4 8.1 8.9 4.5 4.2Chlorsulforon 23.0 8.0 17.0Clopyralid 143.7 114.5 114.9 169.0 74.4 95.1 69.4 46.1 50.5Cyaniazin 140.8 134.0 134.4 4.1DesmediphamDicamba 0.4Dichlorprop-P 130.7 103.1 96.6 128.1 49.1 3.9 3.5 1.7 2.0Difenzoquat methyl sulfat 22.4 16.2 10.7 10.4 26.8 15.7 15.0 12.6Diflufenican 167.8 14.3Diquat 58.1 65.1 49.0 57.0 46.7 82.7 7.9 12.8 11.1Ethofumesate 76.9 77.7 38.2 89.6 49.5 35.3 38.5 26.0 31.1Fenoxaprop-P-ethyl 35.4 83.0 65.5 56.1Flamprop-M-isopropyl 31.0 22.0 12.8 23.1 20.5 22.3 20.4 11.3 16.9Fluazifop-P-butyl 38.2 45.0 40.1 48.6 34.4 34.0 19.8 20.2 14.8Fluroxypyr 48.5 46.8 32.4 69.7 73.6 187.9 168.9 278.7 115.6Glufosinate ammonium 1.0 1.2 0.9 1.4 1.1 0.9 2.2 3.5 5.7Glyphosate 402.0 319.5 371.3 447.0 461.2 528.2 561.7 458.5 573.1Glyphosate-Trimesium 110.7 107.9 137.9 150.7 189.4 161.9 94.5 109.4Haloxyfop ethoxyethylester 10.3 22.4 21.9 37.7 18.7 33.9 28.4 20.1 19.6Ioxynil 399.1 311.3 280.1 342.4 369.4 414.6 329.6 282.9 113.2Isoproturon 245.9 203.4 282.1 369.2 424.3 433.1 347.0 198.0Isoxaben 24.7 11.6 23.2 43.3 48.3 37.1 17.1 11.4Linuron 11.2 3.6 4.1 11.3 10.6 9.6 8.0 6.2 7.0MCPA 235.1 138.8 167.5 245.7 208.9 56.6 171.8 90.4 100.8MCPB 12.7
34
Annex C. Calculated Sprayed area (1000 ha), continued1992 1993 1994 1995 1996 1997 1998 1999 2000
Herbicides (continued)Mechlorprop-P 65.9 51.2 38.9 40.5 9.9Metamitron 81.5 78.1 70.0 71.1 62.9 59.2 54.1 27.8 47.7Methabenzthiazuron 5.0 6.0 6.1 8.5 9.4 5.2 3.7 4.3 5.3Metribuzin 35.6 34.3 20.9 25.3 37.3 49.6 21.3 22.8 26.7Metsulfuron methyl 130.9 115.3 132.0 153.6 44.6 76.8 158.0 225.6 150.6Napropamide 6.3 0.7 11.3 15.9 15.5 18.8 9.4 35.9 8.3Paraquat 1.2 0.3Pendimethalin 100.0 108.0 98.0 172.3 197.1 270.6 282.9 140.2 177.8Phenmedipham 84.0 82.4 104.0 76.6 50.9 43.4 40.0 33.0 39.4Propachlor 1.4 1.3 1.5Propaquizafop 19.6 10.2 11.7 16.7 15.4 4.1Propyzamid 41.3 42.7 47.4 46.0 30.8 29.7 29.5 26.4 17.7Prosulfocarb 8.9 8.2 17.1 52.4 26.6 40.4 30.4 88.5Pyridate 1.7 21.4 20.0 5.4 14.9 26.5 30.8Terbacil 0.2Terbuthylazine 1.9 3.5 18.6 43.1 26.4 47.8 47.0 48.7 1.2Thifensulfuron-methyl 2.3 21.1 16.4 18.4 84.3 91.2 20.2 24.4Tri-allat 0.1 0.1 0.0 0.2 0.4 0.4Triasulfuron 70.8 6.0 18.0 63.8 19.8 91.2Tribenuron methyl 482.4 402.1 320.1 686.1 154.7 633.7 156.5 364.4 624.7Trifluralin 6.0 29.9 39.8 77.4 9.9 37.2 0.7Triflusulfuron methyl 3.9 17.1 6.6 7.2 8.6
Insecticidesalpha-cypermethrin 249.2 251.6 101.0 377.8 104.2 48.7 43.7 103.0 48.2Carbofuran 2.2 2.6 2.1 2.4 0.8 1.7 0.4 0.4 1.1Chlorfenvinphos 1.6 0.9 0.3 0.2 0.9 0.1 0.1 0.1Cypermethrin 112.9 129.1 126.0 234.0 50.4 59.9 83.1Deltamethrin 124.1 110.4 56.9 83.7 4.5 11.2Diazinon 0.5 0.5 0.4 0.5 0.1Dimethoate 208.9 172.6 121.3 215.8 64.2 111.9 125.2 71.5 81.0Endosulfan 1.1 0.8 0.9Esfenvalerate 455.0 373.1 463.6 767.8 118.9 296.5 75.1 198.5 75.9Fenitrothion 0.2Lambda-cyhalothrin 96.1 147.3 149.3 193.5 127.5 125.0 146.4 98.8 80.6Malathion 4.6 5.8 3.3 5.2 4.4 6.4 1.6 2.5Mercaptodimethur 0.2 0.1 0.2 0.2Metaldehyd 0.1 0.1 0.1 0.4 0.8 1.1 7.3 7.4 16.0Mevinphos 1.3 1.0 0.7 1.3Oxydemeton-methyl 2.1 1.9 1.7 0.2Phosphamidon 2.5Phoxim 0.2 0.2 0.1 0.1Pirimicarb 292.6 228.7 279.5 488.4 47.4 37.0 43.2 41.7 7.4Tau-fluvalinate 19.8 14.2 34.0 72.8 83.2
35
Annex D No-spray zones (m) required for risk mitigation1992 1993 1994 1995 1996 1997 1998 1999 2000
FungicidesAzoxystrobin 0 0 0 0 0 0 0 0 0Benomyl 0 0 0 0 0 0 0 0 0Carbenazim 0 0 0 0 0 0 0 0 0Chlorothalonil 0 0 0 0 0 10 10 10 10Cuprihydroxidchlorid 0 0 0 0 0 0 0 0 0Cyprodinil 0 0 0 0 0 0 0 10 10Dimethomorph 0 0 0 0 0 0 0 0 20Fenpropidin 0 0 0 0 0 0 0 20 20Fenpropimorph 0 0 0 0 0 20 20 20 20Fluazinam 0 0 0 0 0 0 0 20 20Iprodion 0 0 0 0 0 0 0 0 0Kresoxim-methyl 0 0 0 0 0 0 0 0 20Mancozeb 0 0 0 0 0 0 0 0 0Maneb 0 0 0 10 10 10 10 10 10Metalaxyl 0 0 0 0 0 0 0 0 0Prochloraz 0 0 10 10 10 10 10 10 10Propamocarb 0 0 0 10 10 10 10 10 10Propiconazole 0 0 0 0 0 20 20 20 20Propineb 0 0 0 0 0 0 0 0 0Pyrazophos 0 0 0 0 0 0 0 0 0Tebuconazol 0 0 0 0 0 0 10 10 10Thiabendazol 0 0 0 0 0 0 0 0 0Thiophanat methyl 0 0 0 0 0 0 0 0 0Triadimenol 0 0 0 0 0 0 0 0 0Tridemorph 0 0 0 0 0 0 0 0 0Vinclozolin 0 0 0 0 0 0 0 0 0
Growth regulatorsChlormequat Chloride 0 0 0 0 10 10 10 10 10Ethephon 0 0 0 0 0 0 0 0 0Maleinhydrazid 0 0 0 0 0 0 0 0 0Mepiquat-chlorid 0 0 0 0 10 10 10 10 10Trinexapac-ethyl 0 0 0 0 0 0 2 0 0
Herbicides2.4-D 0 0 0 0 0 0 0 0 0Aclonifen 0 0 0 0 0 0 0 20 20Asulam 0 0 0 0 0 0 0 0 0Atrazin 10 10 10 10 10 10 10 10 10Benazolin 0 0 0 0 0 0 0 0 0Bentazon 0 0 0 0 10 10 10 10 10Bromoxynil 0 0 0 0 10 20 20 20 20Carbetamid 0 0 0 0 0 0 0 0 0Chloridazon 0 10 10 10 10 10 10 10 10Chlorsulforon 0 0 0 0 0 0 0 0 0Clopyralid 0 0 0 0 0 0 0 0 0Cyaniazin 0 0 0 0 0 0 0 0 0Desmedipham 10 10 10 10 10 10 10 10 10Dicamba 0 0 0 0 0 0 0 0 0Dichlorprop-P 0 0 0 0 0 0 0 0 0Difenzoquat methyl sulfat 0 10 10 10 10 10 10 10 10Diflufenican 0 0 0 0 0 0 0 10 0Diquat 0 0 0 0 0 0 0 0 0Ethofumesate 10 10 10 10 10 10 10 10 10Fenoxaprop-P-ethyl 0 0 0 0 0 10 10 10 10Flamprop-M-isopropyl 0 10 10 10 10 10 10 10 10Fluazifop-P-butyl 0 0 0 0 0 0 0 10 10Fluroxypyr 0 0 0 0 0 0 0 0 0Glufosinate ammonium 0 0 0 0 0 0 0 0 0Glyphosate 0 0 0 0 0 0 0 0 0Glyphosate-Trimesium 0 0 0 0 0 0 0 0 0Haloxyfop ethoxyethylester 0 0 0 10 10 10 10 10 10Ioxynil 0 0 0 0 10 10 10 10 10Isoproturon 0 0 0 0 0 0 0 0 0Isoxaben 0 0 0 0 0 0 0 0 0Linuron 0 0 0 0 0 0 0 0 0MCPA 0 0 0 0 0 0 0 0 0MCPB 0 0 0 0 0 0 0 0 0
36
Annex D. No-spray zones required for risk mitigation (m), continued1992 1993 1994 1995 1996 1997 1998 1999 2000
Herbicides (continued)Mechlorprop-P 0 0 0 0 0 0 0 0 0Metamitron 0 0 0 0 0 0 0 0 0Methabenzthiazuron 0 0 0 0 0 0 0 0 0Metribuzin 0 0 0 0 0 0 10 10 10Metsulfuron methyl 0 0 0 0 0 20 20 20 20Napropamide 0 0 0 0 0 0 0 0 0Paraquat 0 0 0 0 0 0 0 0 0Pendimethalin 10 10 10 10 10 10 10 10 10Phenmedipham 10 10 10 10 10 10 10 10 10Propachlor 0 0 0 0 0 0 0 0 0Propaquizafop 0 0 0 0 0 0 10 10 10Propyzamid 0 0 0 0 0 0 0 0 0Prosulfocarb 0 0 10 10 10 10 10 10 10Pyridate 0 0 0 0 0 0 0 0 0Terbacil 0 0 0 0 0 0 0 0 0Terbuthylazine 10 10 10 10 10 10 10 10 10Thifensulfuron-methyl 0 0 0 0 0 0 0 0 0Tri-allat 0 0 0 0 0 0 0 0 0Triasulfuron 0 0 0 10 10 10 10 10 10Tribenuron methyl 0 0 0 0 0 0 0 0 0Trifluralin 0 10 10 10 10 10 10 10 10Triflusulfuron methyl 0 0 0 0 0 10 10 10 10
Insecticidesalpha-cypermethrin 0 0 0 0 0 0 0 20 20Carbofuran 0 10 10 10 10 10 10 10 10Chlorfenvinphos 0 0 0 0 0 0 0 0 0Cypermethrin 0 0 0 0 0 20 20 20 20Deltamethrin 0 0 0 0 0 0 0 0 0Diazinon 0 0 0 0 0 0 0 0 0Dimethoate 0 0 10 10 10 10 10 10 10Endosulfan 0 0 0 0 0 0 0 0 0Esfenvalerate 0 0 0 0 0 0 0 20 20Fenitrothion 0 0 0 0 0 0 0 0 0Lambda-cyhalothrin 0 0 0 10 10 10 10 10 10Malathion 0 0 10 10 10 10 10 10 10Mercaptodimethur 0 0 0 0 0 0 0 0 0Metaldehyd 0 0 0 0 0 0 0 0 0Mevinphos 0 0 0 0 0 0 0 0 0Oxydemeton-methyl 0 10 10 10 10 10 10 10 10Phosphamidon 0 0 0 0 0 0 0 0 0Phoxim 0 0 0 0 0 0 0 0 0Pirimicarb 0 10 10 10 10 10 10 10 10Tau-fluvalinate 0 0 0 0 0 20 20 20 20
37
Annex E. Data availability and gaps
Fate Acute Toxicity Chronic ToxicityPesticide
DT50 KdFish96hr
LC50Daphnia48hr
EC50Algae96hr
EC50Fish21day
NOECDaphnia21d
NOEC50Algae96hr
NOEC
FungiciderAzoxystrobin + + + + + + + +Benomyl + + + + + - - -Carbenazim + - + + + - - -Chlorothalonil + + + + + - + -Cuprihydroxidchlorid - - - - - - - -Cyprodinil + + + + + + - -Dimethomorph - - - - - - - -Fenpropidin + + + + + + - +Fenpropimorph + + + + + + + +Fluazinam + + + + + - + -Iprodion + + + + + - - -Kresoxim-methyl + + + + + + + -Mancozeb + + + + + - + -Maneb + + + + + - - -Metalaxyl - - - + + - - -Prochloraz + + + + + - + +Propamocarb + + + + + - + -Propiconazole + + + + + - - -Propineb + - + + + - - -Pyrazophos + + + + + - - -Tebuconazol + + + + + - - -Thiabendazol + + + + + - - -Thiophanat methyl + - + + - - - -Triadimenol + + + + + - - -Tridemorph + + + + + - - -Vinclozolin + + - + + - - -
Growth regulatorChlormequat Chloride + + + + + + + +Ethephon + + + + + - + +Maleinhydrazid + + + - + - - -Mepiquat-chlorid + + + + + - - -Trinexapac-ethyl + + + + + - - +
Herbicides2,4-D + + + + + - - -Aclonifen + + + + + + - +Asulam + + + + + - - -Atrazin + + + + + - - -Benazolin + + + + + - - -Bentazon + + + + + - - +Bromoxynil + + + + + - - +Carbetamid + + + + + - - -Chloridazon + + + + + - - -Chlorsulforon + + - + - - - -Clopyralid + + + + + - - +Cyaniazin + + + + + - - -Desmedipham + + + + + + + -Dicamba + + + + + + - -Dichlorprop-P + + + + + + + +Difenzoquat methyl sulfat + + + + + - - -Diflufenican + + + - + + + -Diquat + + + + + + + -Ethofumesate + + + + + - + -Fenoxaprop-P-ethyl + + + + + - + +Flamprop-M-isopropyl + + + + + - + -Fluazifop-P-butyl + + + + - + + +Fluroxypyr + + + + + + + +Glufosinate ammonium + - + + + - - -Glyphosate + + + + + + + +Glyphosate-Trimesium + + + + + + - +Haloxyfopethoxyethylester
+ + + + + - - -
Ioxynil + + + + + - - -Isoproturon + + + + + - - -
38
Annex E. Data availability and gaps (continued)
Fate Acute Toxicity Chronic ToxicityPesticide
DT50 KdFish96hr
LC50Daphnia48hr
EC50Algae96hr
EC50Fish21day
NOECDaphnia21d
NOEC50Algae96hr
NOEC
Herbicides (continued)Isoxaben + + - + + - + -Linuron + + + + - - - -MCPA + + + + + + + -MCPB - - + - - - - -Mechlorprop-P + + + + + + + -Metamitron + + + + + - + -Methabenzthiazuron + + + + + - + -Metribuzin + + + + + + + -Metsulfuron methyl + + + + + - - +Napropamide + + + + + - - -Paraquat + + + - - - - -Pendimethalin + + + + + - - -Phenmedipham + + + + + - + +Propachlor + + + + - - - -Propaquizafop + + + - - + + +Propyzamid + + + - + - - -Prosulfocarb + + + + + - + -Pyridate + + + + + - - -Terbacil + + + + + - - -Terbuthylazine + + + + + + + +Thifensulfuron-methyl + + - + + - + -Tri-allat + + + + + - - -Triasulfuron + + - - + - - -Tribenuron methyl + + - + + - - -Trifluralin + + + + + - - -Triflusulfuron methyl + + + + + + + +
Insecticidesalpha-cypermethrin + + + + - - + -Carbofuran + + + + + - + -Chlorfenvinphos + - + + + - - -Cypermethrin + + + + - - - +Deltamethrin + + + + - - - -Diazinon + + + + + - - -Dimethoate + + + + + + + +Endosulfan + + + + + - - -Esfenvalerate + + + + + - + -Fenitrothion + + + + + - - -Lambda-cyhalothrin + + + - + - - +Malathion + + + + + - - -Mercaptodimethur + + + - + - - -Metaldehyd + + + - + - - -Mevinphos + - + + - - - -Oxydemeton-methyl + + + + + - - -Phosphamidon - - + + + - - -Phoxim - - + + + - - -Pirimicarb + + + + + - + +Tau-fluvalinate + + + - - - + -
Annex F. Fate data DT50 (days)Pesticide
FunigicidesAzoxystrobin 279.00 54.00 164.00 85.00 94.00 57.00 60.00Benomyl 0.79Carbenazim 30.87 30.18 42.64 46.16 25.15 52.87 41.99 41.09 28.17 35.29Chlorothalonil 7.97 9.12 10.34 5.77 6.66 0.06 0.04Cyprodinil 21.40 23.70 122.00 44.00 40.00 33.00 24.20 50.70 79.80 13.00 41.70 19.00 22.10 106.00 165.00 125.50 177.70Fenpropidin 96.00 97.00 50.00 94.00 93.00 59.00 141.00 187.00 233.00 65.00 21.00Fenpropimorph 36.00 13.25 5.06 20.00Fluazinam 55.00Iprodion 52.07 14.66 37.81 53.54 43.14 48.16 32.65 46.57 39.48 21.79Kresoxim-methyl 44.00 511.00 25.00 22.00 294.00 24.00 129.00 22.00 23.00 1.30 0.90 1.20 0.80Mancozeb 6.35 6.32 8.12 11.05 6.53 6.74 6.55 7.36 11.06 6.81Maneb 6.46 13.71 10.83 13.93 4.90 12.41 13.21 18.01 17.88 10.04Prochloraz 228.00 92.00 171.00 155.00 115.00 21.00Propamocarb 10.00 18.00 58.00 12.00 23.00 44.00 14.00 22.00 24.00Propiconazole 43.00 47.00 70.00 309.00 255.00 41.00 56.00 128.00 316.00 42.00 430.00 72.00 70.00 426.80Propineb 11.07 4.74 9.00 0.63 1.35 3.97 4.76 2.46 2.26 2.47Pyrazophos 24.17 15.07 33.14 40.18 12.13 29.79 43.86 31.35 33.07 35.86Tebuconazol 489.00 129.00 17.57 21.00Thiabendazol 672.95 623.18 576.53 567.97 595.84 711.61 553.52 693.72 629.69 582.32Thiophanat methyl 2.56 3.46 3.88 4.17 3.35 3.80 3.97 3.46 2.49 4.28Triadimenol 192.57 345.92 199.07 332.37 243.35 257.36 206.12 282.71 253.30 277.69Tridemorph 48.78 28.79 38.49 40.16 25.84 20.72 41.56 39.89 35.11 39.78Vinclozolin 10.89 14.11 10.68 33.10 6.73 2.71 22.35 25.19 0.00 25.42
Growth regulatorChlormequat Chloride 10.50 8.00 2.38 3.28 2.64Ethephon 4.00 8.00 10.00 25.00 22.00 7.10 7.00 7.50Maleinhydrazid 0.46Mepiquat-chlorid 11.00 10.00 2.72 21.06Trinexapac-ethyl 0.22 0.22 0.09 0.17 3.30 2.10 3.40 5.20 3.90 5.50
Herbicides2.4-D 210.62 166.47 143.99 116.50 67.21 72.63 46.05 252.85 10.77 110.91Aclonifen 91.80 40.00 217.00 217.00 84.00 49.00 70.00 76.00 82.00 15.40 16.10Asulam 28Atrazin 39Benazolin 3Bentazon 17.00 17.00 38.00 38.00 73.00 24.00 31.00 65.00Bromoxynil 0.75 0.75 0.63 0.63 2.40 2.10 2.40 1.80 0.78 0.30 0.84 0.44 1.42 0.63 1.19 0.78Carbetamid 12.10 17.72 9.85 12.83 6.70 6.53 9.78 14.40 14.30 17.76Chloridazon 27.33 4.27 11.53 22.66 4.01 24.33 18.53 34.14 34.27 12.33Chlorsulforon 39.31 38.79 30.93 40.72 34.77 34.81 37.07 34.47 36.11 33.23Clopyralid 62.00 12.00 178.00 226.00 23.00 48.00 11.00 30.00 350.00 285.00 102.00 68.00 44.00 28.00 24.00 17.00 157.00 82.00Cyaniazin 52.29 56.55 59.77 44.30 61.04 44.82 77.31 49.45 69.34 25.93Desmedipham 5.30 12.40 5.50 20.50 8.00 3.40 0.80Dicamba 2,90 6,00 39,80 45,50 20,20
40
Annex F. DT50 ContinuedPesticide
Herbicides (continued)Dichlorprop-P 21.00 25.00 20.45 9.00 14.00 21.00 20.00Difenzoquat methyl sulfat 30.00Diflufenican 168.00 294.00 875.00 728.00 72.00 82.00Diquat 1308.7 1098.3 1282.0 1159.5 1181.7 1257.0 1295.7 1246.0 1226.1 1286.0Ethofumesate 50.00 125.00 147.00 140.00 105.00Fenoxaprop-P-ethyl 3.00 6.00 0.60 0.60 0.70 0.70Flamprop-M-isopropyl 68.80 87.20 233.60 56.00 217.00 112.00Fluazifop-P-butyl 3Fluroxypyr 2.38 2.28 3.19 5.05 7.20 4.29 30.00 832.00 45.00 55.00 12.00 12.00 23.00 7.00 15.00 12.00 7.00 70.00Glufosinate ammonium 42.00 32.00 15.00 23.00 21.00 22.00 15.00Glyphosate 25.40 15.40 11.20 14.00 25.90 25.20 25.90 7.50 8.50 3.60 1.40 27.40 3.70 146.30 14.40Glyphosate-Trimesium 3.00 3.00 12.00 9.00 67.00 20.00 5.00 6.00 70.00 6.00 1.00 24.00 46.00 58.00 62.00 3.00 8.00 11.00 15.00 35.00Haloxyfopethoxyethylester
47.00 51.00 100.00 27.00 56.00 47.00 1.00 1.00 1.00 98.00 105.00 113.00 230.00
Ioxynil 1.50 2.00 3.50 6.50 7.50 75.00 2.50 15.50Isoproturon 52.93 64.50 6.76 26.02 23.25 48.51 37.39 42.32 39.67 29.80Isoxaben 131.15 179.95 323.30 521.00 29.60 989.90 16.80 4466.0 11.30Linuron 291.90 87.50 275.80 64.40 187.60 56.00 91.00 136.50 73.90 74.10 35.20 86.00 77.80 68.00 76.00 82.40 50.80 69.80 81.20 57.40
66.70 49.30 24.90 22.30 56.20 23.70 10.00 19.00 16.00 28.00MCPA 32.03 11.52 35.60 18.41 44.48 43.70 0.00 45.51 24.97 29.65Mechlorprop-P 13.30 11.73 12.23 5.91 18.50 11.50Metamitron 3.00 3.20 3.50Methabenzthiazuron 26.25 65.71 31.00Metribuzin 106.00 70.00 50.00 50.00 21.00 42.00 20.00 56.00 58.00Metsulfuron methyl 11.00 10.00Napropamide 56.00 84.00 670.00 230.00Paraquat 2750.7 6542.2 3701.7 5943.2 5171.8 4890.7 4374.4 7006.9 6098.6 5808.4Pendimethalin 72.00 87.00 132.00 127.00 172.00Phenmedipham 43.78 21.46 41.12 32.61 24.92 32.27 23.64 35.85 31.76 39.13Propachlor 121.31 132.16 115.71 125.85 123.21 147.66 151.71 145.01 164.87 133.32Propaquizafop 28.00 47.00 22.00 42.00 32.00 39.00 10.00 4.00 17.00 139.00 110.00 20.00 20.00Propyzamid 23.83 25.50 28.45 32.57 24.39 31.14 19.66 18.70 23.88 13.84Prosulfocarb 13.00 13.00Pyridate 87.00 0.82 14.00 23.00 23.00 26.00 60.00 10.00 20.00 22.00 27.00Terbacil 266.16 181.01 375.67 222.47 298.57 206.01 292.13 225.68 232.99 195.97Terbuthylazine 77.00 63.00 121.00 108.00 94.00 66.00 169.00 79.00 252.00 272.00 456.00 133.00 138.00 73.00 149.80 74.20 6.10 79.80 6.50 33.10
32.30 246.40 19.30 137.10 61.00 55.00 78.70 137.80 60.90 6.00 6.00 73.00 33.00 18.00 9.00 167.00 88.00Thifensulfuron-methyl 2.00 6.00 1.67 3.39Tri-allat 12.00 4.00 12.00 5.00 10.00 4.00 12.00 3.00 20.00Triasulfuron 325.50 66.50 105.00 121.50 52.80 44.90 38.60 70.90 73.50 193.90 205.10 189.00 247.10 38.00Tribenuron methyl 19.20 20.90 29.70 30.10 3.00 12.00Trifluralin 122.61 83.06 159.78 14.04 145.84 169.58 305.91 164.98 205.61 0.00Triflusulfuron methyl 6.00 6.30 5.50 14.40 6.10 8.40 7.70 17.20 30.00 39.00 18.00 21.00
41
Annex F. DT50 Continued
PesticideInsecticides
alpha-cypermethrin 189.00 91.00Carbofuran 25.00 160.00 3.50 4.50Chlorfenvinphos 58.00 55.00 28.00Cypermethrin 7.00 14.00 21.00 14.00 7.00 21.00 49.00 56.00Deltamethrin 37.27 19.30 19.70 33.74 40.63 46.94 28.90 45.30 24.59 31.44Diazinon 31.11 36.10 47.00 38.83 32.47 27.58 50.70 38.36 32.46 31.38Dimethoate 2.40 2.40 2.00 4.10Endosulfan 45.82 39.88 56.17 67.82 67.20 65.47 50.04 48.61 37.69 56.56Esfenvalerate 15.00 91.50 46.00 39.20 178.80 61.20 26.90 67.80Fenitrothion 18.04 24.62 25.22 17.37 24.12 21.15 19.49 17.81 16.61 22.45Lambda-cyhalothrin 22.00 82.00 42.00 56.00 74.00Malathion 1.00 0.21Mercaptodimethur 40.02 32.19 32.75 37.96 34.07 40.92 35.61 34.39 35.40 30.59Metaldehyd 0.00 46.47 124.09 36.15 12.06 39.64 79.39 108.67 90.45 92.54Mevinphos 0.92 1.37 1.23 1.48 1.48 0.55 0.82 0.88 0.42 1.19Oxydemeton-methyl 3.57 1.31 2.22 3.09 3.92 2.36 3.34 1.76 2.36 2.65Pirimicarb 121.06 3.46 67.97 21.11 75.09 0.00 73.29 157.96 74.24 0.00Tau-fluvalinate 6.00 6.00 8.00 8.30 14.90
42
Annex G. Fate data KdPesticide
FunigicidesAzoxystrobin 7.90 9.50 1.50 4.00 6.20 15.00Benomyl 24.72 25.56 12.97 23.65 16.51 18.45 19.05 29.85 27.55 21.27Chlorothalonil 0.00 23.46 0.00 0.00 22.17 32.60 113.29 44.23 57.70 74.56Cyprodinil 12.30 18.89 25.41 74.91 355.55 16.30 14.20 31.20 24.30Fenpropidin 117.10 64.20 43.50 40.30 24.10 17.40Fenpropimorph 34.47 73.73 22.62Fluazinam 11.12 43.48 27.19 37.88Iprodion 21.68 8.61 11.21 9.56 13.41 16.13 11.92 20.45 8.66 13.61Kresoxim-methyl 26.01 77.38 36.16 59.19Mancozeb 11.67 9.89 7.26 10.13Maneb 0.47 0.09 0.08 0.14Prochloraz 86.80 101.70Propamocarb 5.83 1.26 0.67 0.85 5.20Propiconazole 13.00 12.75 11.97 12.24 12.40 16.15 8.70 12.46 11.44 9.77Propyzamid 8.05 10.10 3.47 4.85 3.15 5.16Pyrazophos 63.56 66.00 68.99 69.30 61.90 69.36 72.76 64.75 67.23 65.24Tebuconazol 18.77 22.27 11.83 23.76 12.70 10.84Thiabendazol 43.11 53.95 58.66 31.65 32.86 50.61 52.87 23.31 39.00 29.88Thifensulfuron-methyl 0.08 0.19 1.38 1.25Triadimenol 3.6Tridemorph 87.34 134.97 69.19 145.89 149.56 126.24 101.87 60.43 68.49 52.35Vinclozolin 2.52 4.94 2.48 4.73 5.11 2.95 2.58 1.71 5.12 1.59
Growth regulatorChlormequat Chloride 24.35Ethephon 57.33 53.13 29.77 2.37 7.17 5.93 6.55 17.10 8.85Maleinhydrazid 1.15 1.04 1.05 0.66 1.05 0.72 0.99 0.90 0.81 0.72Mepiquat-chlorid 133.65 17.06 5.74 74.07 3.90 51.70Trinexapac-ethyl 17.77 1.50 0.66 0.67
Herbicides2.4-D 210.62 166.47 143.99 116.50 67.21 72.63 46.05 252.85 10.77 110.91Aclonifen 91.80 40.00 217.00 217.00 84.00 49.00 70.00 76.00 82.00 15.40 16.10Asulam 28Atrazin 39Benazolin 3Bentazon 17.00 17.00 38.00 38.00 73.00 24.00 31.00 65.00Bromoxynil 0.75 0.75 0.63 0.63 2.40 2.10 2.40 1.80 0.78 0.30 0.84 0.44 1.42 0.63 1.19 0.78Carbetamid 12.10 17.72 9.85 12.83 6.70 6.53 9.78 14.40 14.30 17.76Chloridazon 27.33 4.27 11.53 22.66 4.01 24.33 18.53 34.14 34.27 12.33Chlorsulforon 39.31 38.79 30.93 40.72 34.77 34.81 37.07 34.47 36.11 33.23Clopyralid 62.00 12.00 178.00 226.00 23.00 48.00 11.00 30.00 350.00 285.00 102.00 68.00 44.00 28.00 24.00 17.00 157.00 82.00Cyaniazin 52.29 56.55 59.77 44.30 61.04 44.82 77.31 49.45 69.34 25.93Desmedipham 5.30 12.40 5.50 20.50 8.00 3.40 0.80
43
Annex F. Kd ContinuedPesticide
Herbicides (continued)Dicamba 0.16 0.10 0.53 0.07 0.21Dichlorprop-P 0.48 0.22 0.10 0.24Difenzoquat methyl sulfat 181.00 636.00 1093 2680Diflufenican 33.90 13.50 39.80 48.90Diquat 5000 1200 17000 85.00 16000 3500 5000 4500 42000 22000 2000 7000 27000 38000 37000 31000 43000 14000 12000 6000
25000 16000 92000 53000 14000 28000 47000 43000 57000 49000 25000 25000Ethofumesate 1.13 0.73 2346 5315 6155 3.14 1.11 21.70Fenoxaprop-P-ethyl 104.00 57.00 82.00 149.00Flamprop-M-isopropyl 0.94 5.05 1.74Fluazifop-P-butyl 0.26 0.17 0.23 0.14Fluroxypyr 0.29 0.17 0.00 0.00 0.00 0.00Glyphosate 90.00 70.00 62.00 22.00 175.00 115.00 80.00 68.00 30.00 205.00Glyphosate-Trimesium 20.51 11.98 8.09 22.06 376.00 55.70 31.50 2060Haloxyfopethoxyethylester
0.79 1.80 3.30 0.10 0.73 0.25 0.60 0.41 0.73 3.76 1.81
Ioxynil 3.50 5.10 6.00 182.00Isoproturon 0.72 0.80 0.84 0.85 0.81 0.75 0.88 0.87 0.83 0.82Isoxaben 5.70 0.81 2.48 4.41 6.63 2.18Linuron 8.25MCPA 0.75Mechlorprop-P 4.50 3.50 3.30 0.30 0.69 0.43 0.20Metamitron 1.43 2.36 1.20 1.07 1.66 0.68 1.82 1.04 1.54 0.36 1.49 5.88 1.23 0.70 22.51Methabenzthiazuron 7.47 7.88Metribuzin 1.10 0.93 1.75 1.85 1.99 2.33 1.15 1.55 2.26 1.29Metsulfuron methyl 0.35 0.47 0.21 0.57 0.46 0.36 0.50 0.36 0.45 0.24Napropamide 3.38 5.12 8.63 14.80 6.44Paraquat 45.00Pendimethalin 30.00 110.00Phenmedipham 36.00Propachlor 0.70 0.90 0.58 0.98 0.95 1.28 0.55 0.92 0.92 1.24Propaquizafop 2.36 6.24 9.29 5.27Prosulfocarb 11.70 24.70 32.80Pyridate 0.37 2.30 0.30Terbacil 0.51 0.83 0.57 0.28 1.18 0.59 0.69 0.24 0.00 0.63Terbuthylazine 2.27 1.11 2.36 5.94 25.18 4.93 1.43 0.31Thifensulfuron-methyl 0.21 0.21 0.21 0.20 0.22 0.20 0.20 0.20 0.20 0.20Tri-allat 36.78 32.53 26.43 27.66 29.92 35.53 37.19 21.71 22.35 28.19Triasulfuron 2.18 2.26 2.86 3.16 0.86 1.78 1.45 2.23 2.01 3.00Tribenuron methyl 0.19 0.45 2.00 1.70Trifluralin 96.52 178.32 146.82 116.06 197.50 157.25 130.72 128.95 127.88 122.75Triflusulfuron methyl 0.36 0.50 1.28 0.41 0.67
44
Annex F. Kd Continued
PesticideInsecticides
alpha-cypermethrin 821 1042 868Carbofuran 0.10 0.56 0.31 1.23 1.08Cypermethrin 1014 1491 1910Deltamethrin 24814 4413 22361 26663 12090 33724 28136 36790 21320 30123Diazinon 8.97 7.49 9.32 11.40 9.19 9.04 10.79 9.15 9.30 11.77Dimethoate 0.37 0.52 0.43 0.41 0.25 0.10 0.53 0.41 0.44 0.42Endosulfan 169.74 51.00 72.86 200.01 130.14 169.52 265.84 236.93 133.84 241.13Esfenvalerate 4.41 6.36 71.32 104.83Fenitrothion 4.94 4.45 4.84 4.65 5.65 4.60 3.77 5.57 5.38 3.78Lambda-cyhalothrin 1290 464 1470 5350Malathion 0.83 1.23 1.76 2.47 1.60Mercaptodimethur 2.61Metaldehyd 0.45 0.30 0.31 0.26 0.47 0.27 0.59 0.33 0.52 0.43Oxydemeton-methyl 0.18 0.34 0.39 0.05 0.27 0.39 0.29 0.15 0.36 0.31Pirimicarb 0.19 6.05 5.20 7.98 3.40 4.04 1.70 3.84 5.34 0.00Tau-fluvalinate 2614 8679 19668 17151 2540 16163 16853 13008 14732 23603
45
Annex H. Acute Toxicity. Fish96hrLC50 (mg l-1)Pesticide
FungicidesAzoxystrobin 0.4700 2.8000Benomyl 0.4100 0.1700Carbenazim 0.3600Chlorothalonil 0.0560 0.0560 0.0470 0.0600 0.0600 0.0550 0.0430 0.0870 0.0840 0.0320 0.1950 0.0440Cyprodinil 0.9800 1.0400 1.3300 1.1700 1.1700 1.0300 1.2500 1.4000 1.0700 1.1000 1.4300 2.1700 2.4100Fenpropidin 2.8900 2.5700 2.1600 1.9300 4.3800 3.6800 3.5500 1.9300Fenpropimorph 9.5000 3.4300 3.2000 3.1600Fluazinam 0.1700 0.1400 0.1100 0.1500 0.1500Iprodion 3.1000Kresoxim-methyl 3.2000 0.4140 0.1900Mancozeb 1.5000 1.5000 1.5000 4.8000 4.4000 4.2000 2.5100 2.5100 2.5100 4.6000Maneb 3.0500 0.4600 0.2200Prochloraz 2.2000 2.2000 2.8000Propamocarb 163.00
00Propiconazole 20.000 6.4000 5.1000 5.1000 6.3000 6.3000 5.3000 6.8000 5.1000 6.8000 6.4000 3.1300 3.0100 2.6000Propineb 0.5000Pyrazophos 0.0160Tebuconazol 6.4000 8.7000 6.1000 5.7000 4.4000 3.7400
Thiabendazol 0.5600Thiophanat methyl 7.8000Triadimenol 14.000 15.000Tridemorph 3.5000
Growth regulatorsChlormequat Chloride 465.00Ethephon 720.00 720.00 311.00 357.00 300.00Maleinhydrazid 1608.2Mepiquat-chlorid 3300.0 3300.0 3500.0 2500.0 5036.0 4320.0Trinexapac-ethyl 92.000 82.400 68.000 57.000 38.000 36.000 35.000 32.500
Herbicides2.4-D 1.1000Aclonifen 1.2000 1.1000 0.6700 1.5000 1.4000 1.3000 0.6250Asulam 3000.0Atrazin 4.3000Benazolin 2.8000 27.000Bentazon 255.00 1500.0 780.00 180.00Bromoxynil 0.0600 23.000Carbetamid 354.00Chloridazon 20.000Clopyralid 103.50 125.40 500.00Cyaniazin 4.8000
46
Annex H. Fish96hrLC50 ContinuedPesticide
Herbicides (continued)Desmedipham 1.7000 6.3000 6.0000Dicamba 135.00Dichlorprop-P 428.00 100.00Difenzoquat methyl sulfat 891.90 788.00 696.00 694.00Diflufenican 77.000 75.000 70.000Diquat 27.000 23.000 21.000 143.00 91.000 67.000 6.1000Ethofumesate 25.000 64.100 11.900 12.650 12.400 14.510 17.350 15.000Fenoxaprop-P-ethyl 4.2000 4.2000 1.5000 1.3000 0.6100 0.5800 0.5800 0.6900 0.5700 0.5200 0.5000 0.4600Flamprop-M-isopropyl 2.4000Fluazifop-P-butyl 1.4500 1.3700 1.3700 1.3200 1.3100 1.3100 117.00 1.0700Fluroxypyr 14.300 24.500 4.6000 4.2000 3.5000Glufosinate ammonium 39.900 26.700 28.100 320.00Glyphosate 38.000Glyphosate-Trimesium 1800.0 3100.0 4800.0 664.00 541.00 517.00 441.00 441.00 441.00Haloxyfopethoxyethylester
0.0035 548.00 0.2900 0.5380 0.2900 0.2900 0.2840 0.7430 0.6590 0.6380 1.6700 1.3400 1.1800
Ioxynil 0.7500 0.6400 9.5000 8.5000 8.4000Isoproturon 9.0000Linuron 16.200 30.600 16.400 0.8900MCPA 748.00 97.000MCPB 5.6000Mechlorprop-P 100.00Metamitron 326.00 443.00 222.00 222.00 225.00Methabenzthiazuron 15.900 29.000 48.700 20.000Metribuzin 80.000 131.00 76.000 147.00 85.000 64.000 59.000Metsulfuron methyl 981.00Napropamide 32.000 30.000 15.000 13.500 16.600 10.700Paraquat 2.5000Pendimethalin 0.1400 0.1380 1.0000 0.5200 86.600 72.440Phenmedipham 3.0000 1.4100 3.9800Propachlor 0.1700Propaquizafop 1.1880 0.2000 0.1900 0.1900 0.4500 0.3700 0.3400Propyzamid 350.00 150.00 72.000Prosulfocarb 3.7000 3.0000 4.2000 7.0000 1.8600 1.6500 1.6500Pyridate 81.000 48.000 145.00 124.00 118.00 20.000 12.000 10.000Terbacil 46.000Terbuthylazine 3.8000 3.8000 7.0000 7.0000 6.2000 19.000 15.000 55.000 15.000 24.800 26.000 29.000 18.000 18.000 19.000 3.3000 3.4000 3.9000 9.4000 4.6000Tri-allat 1,2000 1,3000Trifluralin 0.0100 0.0200 0.1900 0.6600 0.0450 0.4170 2.2000 0.2100 0.1520 0.0420 0.0100 0.0860 0.0410 0.1050 0.1050 0.6730 0.0540 0.0166Triflusulfuron methyl 530.00 420.00 150.00 730.00 860.00 750.00 870.00 760.00 760.00
47
Annex H. Fish96hrLC50 ContinuedPesticide
Insecticidesalpha-cypermethrin 0.0056 0.3500 0.0650 0.1200 0.2200 0.0028 0.0009 0.0010 0.0011 0.0008 0.0110 0.0600 0.0004 0.0032 0.0220 0.011 0.0008 0.0028 0.24 5Carbofuran 0.2800 0.2100 0.2400 0.0073Chlorfenvinphos 0.5500 0.9000 0.7700 0.0570 0.0510 0.0390Cypermethrin 0.0011 0.0010 0.0009 0.0022 0.0019 0.0018 0.0023 0.0020 0.0016 0.0007 0.0007 0.0007 0.0009 0.0011 0.0099 0.011 0.0008 0.0021 0.0091 0.0005
0.0071 0.0028 0.24 0.005 0.0047 0.0009 0.0133 0.013 0.0009 0.0012Deltamethrin 0.0006Diazinon 0.2100Dimethoate 30.200 694.00 6.2000Endosulfan 0.0020Esfenvalerate 0.0003 0.0013 0.0013 0.0012 0.0028 0.0028 0.0027 0.0018 0.0018 0.0018 0.0056 0.0056 0.0056 0.0019 0.0019 0.0019 0.0046 0.0045 0.0044 0.0156
0.0003Fenitrothion 1.700Lambda-cyhalothrin 0.0002 0.0005 0.0112 0.0002Malathion 0.0400Mercaptodimethur 0.44Metaldehyd 7.3000Mevinphos 0.0120Oxydemeton-methyl 1.9000Phosphamidon 1.4100 3.2000
00048Phoxim 0.81 0.2200Pirimicarb 40.000 32.000 180.00 124.00 60.000 36.000 380.00 315.00 156.00 141.00 129.00 132.00 95.000 78.000 34.000 30.000 29.000 130.00 89.000 55.000Tau-fluvalinate 0.0053 0.0043 0.0042 0.0110 0.0110 0.0110 0.0032 0.0028 0.0027 0.0075 0.0070 0.0062
48
Annex I. Acute Toxicity. Daphnia 48hrEC50(mg l-1)Pesticide
FungicidesAzoxystrobin 0.2800 0.1100Benomyl 0.5500Carbenazim 0.1300Chlorothalonil 0.0700Cyprodinil 0.1000 0.3900Fenpropidin 3.3000 0.5400Fenpropimorph 3.5000 2.3900Fluazinam 0.3600 0.1900Iprodion 0.2500Kresoxim-methyl 0.1860 1.5100 0.6000 0.3500Mancozeb 13.6000 13.6000Maneb 3.4000 1.0200 0.5200Metalaxyl 610.0000Prochloraz 2.6000Propamocarb 284.0000Propiconazole 11.5000 1.7000Propineb 4.7000Pyrazophos 0.0002Tebuconazol 11.8000 5.9000 3.2000Thiabendazol 0.4500Thiophanat methyl 12.7000Triadimenol 2.5000Tridemorph 1.3000Vinclozolin 4.0000
Growth regulatorsChlormequat Chloride 59.0000 16.0000 16.9000 100.0000 7.4000Ethephon 31.7000 78.0900 78.0900Mepiquat-chlorid 68.5000Trinexapac-ethyl 142.0000
Herbicides2.4-D 1.4000Aclonifen 2.0000 1.2000 2.5000Asulam 63.4000Atrazin 3.6000Benazolin 233.4000Bentazon 170.7600 125.0000Bromoxynil 21.0000 12.5000Carbetamid 54.0000Chloridazon 50.1000Chlorsulforon 370.0000Clopyralid 225.0000Cyaniazin 42.0000Desmedipham 0.5900Dicamba 400.0000 110.0000Dichlorprop-P 1300.0000Difenzoquat methyl sulfat 20.0000 44.0000Diquat 2.5000Ethofumesate 34.0000 22.0000 33.0000 295.0000Fenoxaprop-P-ethyl 2.7000Flamprop-M-isopropyl 10.0000 18.6000Fluazifop-P-butyl 3.0000 2.1000 5.8000 6.1000Fluroxypyr 3.8000 1.1000 1.2000Glufosinate ammonium 560.0000Glyphosate 2.2500 84.0000 281.0000Glyphosate-Trimesium 27.0000 4.2000 12.0000Haloxyfop ethoxyethylester 4.6400Ioxynil 5.6000 3.9000Isoproturon 507.0000Isoxaben 544.0000Linuron 0.1200MCPA 123.0000 78.0000 160.0000Mechlorprop-P 420.0000Metamitron 101.7000 167.6000 111.9000Methabenzthiazuron 30.6000Metribuzin 100.0000 35.0000 4.5000Metsulfuron methyl 971.0000Napropamide 14.3000Pendimethalin 0.0400Phenmedipham 3.2000
49
Annex I. Daphnia 48hrEC50 continuedPesticide
Herbicides (continued)Propachlor 7.8000Prosulfocarb 1.3000Pyridate 0.8300Terbacil 68.0000Terbuthylazine 21.2000Thifensulfuron-methyl 970.0000Tri-allat 0.4300Tribenuron methyl 720.0000Trifluralin 0.2400Triflusulfuron methyl 1200.0000 280.0000 460.0000 490.0000
Insecticidesalpha-cypermethrin 0.0011 0.0003Carbofuran 0.0150Chlorfenvinphos 0.0012 0.0003 0.0003Cypermethrin 0.0012 0.0002Deltamethrin 0.0035Diazinon 0.9900Dimethoate 0.4600Endosulfan 0.0750Esfenvalerate 0.0009 0.0008 0.0010 0.0001 0.0002Fenitrothion 0.0016Malathion 0.0022Mevinphos 0.0002Oxydemeton-methyl 0.1100Phosphamidon 0.0200Phoxim 0.0006Pirimicarb 0.0220 0.0190 0.0190 0.0140
50
Annex J. Acute & Chronic Toxicity. Algae96hrEC50
PesticideFungicides
Azoxystrobin 0.0540Benomyl 2.0000Carbenazim 1.3000Chlorothalonil 0.5210 0.5250 0.2100Cyprodinil 0.7500 1.9700 1.7500 1.7800 2.8400 2.2200 2.1100 2.2500 3.8100 3.7600 2.8900 2.8200 2.6000Fenpropidin 0.0025 4.4000 0.0057Fenpropimorph 0.1700 2.2100 0.2900Fluazinam 0.1600Iprodion 0.0480 1.9Kresoxim-methyl 0.0630 0.0710 0.5320Mancozeb 2.8000 0.0110 1.1600 2.2000 1.1000Maneb 0.2610 0.4300Metalaxyl 42.0000Prochloraz 0.0730Propamocarb 301.000Propiconazole 0.0034 0.6800 0.0008 6.5000 2.2000 1.0000 6.3000 5.0000 1.5000 0.7200 1.6000Propineb 0.4900Pyrazophos 65.5000Tebuconazol 1.9600 1.6400 5.3000 4.0100Thiabendazol 9.0000Triadimenol 3.7000Tridemorph 0.2600Vinclozolin 10.0000 16.0000
Growth regulatorsChlormequat Chloride 5656.00 5747.00 1998.00Ethephon 29.0000 32.0000 16.5000 25.0000 21.0000Maleinhydrazid 8.0000Mepiquat-chlorid 267.984Trinexapac-ethyl 0.4000 0.7300 9.4000 12.0000 21.0000 16.0000 18.0000 19.0000 55.0000 26.0000 11.0000
Herbicides2.4-D 243.682 48.0358 385.415 256.257 346.703 2.7963 382.763 17.1773 301.917 90.5628Aclonifen 0.0067 0.0069 0.0290Asulam 11.0000 13.5000Atrazin 0.0440Benazolin 16.0000Bentazon 47.3580 279.262 34.8000Bromoxynil 1.7700 44.0000Carbetamid 210.000Chloridazon 1.9000Clopyralid 6.9000 7.3000 730.000 449.000
51
Annex J. Algae96hrEC50. Continued.Pesticide
Herbicides (continued)Diquat 0.0110 0.0190Ethofumesate 3.9000 0.0600Fenoxaprop-P-ethyl 1.3000 0.5100Flamprop-M-isopropyl 6.8000Fluroxypyr 3.8500 3.8000 49.8000Glufosinate ammonium 1000.00Glyphosate 326.900 117.800 485.000 1.3000 166.000 72.9000 1.0000Glyphosate-Trimesium 19.0000 14.0000 30.0000Haloxyfop ethoxyethylester 106.500 80.7200Ioxynil 24.0000 10.0000Isoproturon 0.0300 0.0225 0.0210 0.0135 0.0770Isoxaben 60.3300 60.2100MCPA 115.000 220.000Mechlorprop-P 270.000 220.000Metamitron 0.2200Methabenzthiazuron 0.0420 0.1190Metribuzin 0.0078 0.0069 0.0220 0.0210 0.0430Metsulfuron methyl 64.0000 63.0000 62.0000 73.0000 70.0000 69.0000 2.9000Napropamide 4.5000Pendimethalin 0.0550 1.6000 5.0700 0.4677 5.8200 0.0220 0.0054 15.4000 72.4400Phenmedipham 0.1302Propyzamid 5.8000 2.9000Prosulfocarb 0.1090 202.000 0.0900Pyridate 82.0000Terbacil 0.3000Terbuthylazine 0.0200 0.0390 0.0730 0.0160 0.0190 0.0460Thifensulfuron-methyl 14.5000 15.0000Tri-allat 0.1200Triasulfuron 0.7700Tribenuron methyl 7.0000 4.5000Trifluralin 0.0850Triflusulfuron methyl 0.5000 0.6200
52
Annex J. Algae96hrEC50. Continued.Pesticide
InsecticidesCarbofuran 7.0000 19.9000Chlorfenvinphos 1.6000Diazinon 6.4000Dimethoate 282.290 90.4300Endosulfan 1.4400Esfenvalerate 1.0000Fenitrothion 3.9000Lambda-cyhalothrin 27.0000 31.0000Malathion 100.000 1.0000Mercaptodimethur 1.2000Metaldehyd 73.0000Oxydemeton-methyl 100.000Phosphamidon 240.000Phoxim 0.6500Pirimicarb 140.000 180.000
53
Annex K. Chronic Toxicity. Fish21dayNOECPesticide
Fungicides
Azoxystrobin 0.1470
Cyprodinil 0.0830
Fenpropidin 0.3200
Fenpropimorph 0.1000
Kresoxim-methyl 0.0200
Growth regulator
Chlormequat Chloride 1000000
Herbicides
Aclonifen 0.0100
Desmedipham 16000
Dicamba 1800000
Dichlorprop-P 1000000
Diflufenican 0.0500
Diquat 14000
Fluazifop-P-butyl 0.2500
Fluroxypyr 0.3200 0.5600
Glyphosate 520000
Glyphosate-Trimesium 1800000
MCPA 800000
Mechlorprop-P 500000
Metribuzin 56000
Propaquizafop 0.0710
Terbuthylazine 0.2380
Triflusulfuron methyl 1000000 2100000
Insecticide
Dimethoate 0.4000
54
Annex L. Chronic Toxicity. Daphnia 21day NOECPesticide
FungicidesAzoxystrobin 0.0440Chlorothalonil 0.1800Fenpropimorph 0.0710Fluazinam 0.0125Kresoxim-methyl 0.0320 0.1500Mancozeb 0.0290Prochloraz 0.0222Propamocarb 88900
Growth regulatorsChlormequat Chloride 156000Ethephon 156000 625000 670000 0.0980
HerbicidesDesmedipham 0.0100Dichlorprop-P 1000000Diflufenican 0.1630Diquat 0.1250Ethofumesate 63200 0.6400 0.3200Fenoxaprop-P-ethyl 0.1000 0.2200Flamprop-M-isopropyl 0.8370 0.1670Fluazifop-P-butyl 0.2500Fluroxypyr 0.1000 560000Glyphosate 300000 1000000Isoxaben 0.6900MCPA 500000 500000Mechlorprop-P 500000Metamitron 320000 320000Methabenzthiazuron 20000Metribuzin 15000Phenmedipham 0.0320Propaquizafop 0.4400Prosulfocarb 0.0470Terbuthylazine 0.2100Thifensulfuron-methyl 1000000Triflusulfuron methyl 320000 110000
Insecticidesalpha-cypermethrin 0.00003Carbofuran 0.00980 0.00020Dimethoate 0.04000Esfenvalerate 0.00000Pirimicarb 0.00200 0.00100Tau-fluvalinate 0.00010
55
Annex L. Chronic Toxicity. Daphnia 21day NOECPesticidealpha-cypermethrin 0.0000
Azoxystrobin 0.0440
Carbofuran 0.0098 0.0002
Chlormequat Chloride 15.6000
Chlorothalonil 0.1800
Desmedipham 0.0100
Dichlorprop-P 100.0000
Diflufenican 0.1630
Dimethoate 0.0400
Diquat 0.1250
Esfenvalerate 0.0000
Ethephon 15.6000 62.5000 67.0000 0.0980
Ethofumesate 6.3200 0.6400 0.3200
Fenoxaprop-P-ethyl 0.1000 0.2200
Fenpropimorph 0.0710
Flamprop-M-isopropyl 0.8370 0.1670
Fluazifop-P-butyl 0.2500
Fluazinam 0.0125
Fluroxypyr 0.1000 56.0000
Glyphosate 30.0000 100.0000
Isoxaben 0.6900
Kresoxim-methyl 0.0320 0.1500
Mancozeb 0.0290
MCPA 50.0000 50.0000
Mechlorprop-P 50.0000
Metamitron 32.0000 32.0000
Methabenzthiazuron 2.0000
Metribuzin 1.5000
Phenmedipham 0.0320
Pirimicarb 0.0020 0.0010
Prochloraz 0.0222
Propamocarb 8.8900
Propaquizafop 0.4400
Prosulfocarb 0.0470
Tau-fluvalinate 0.0001
Terbuthylazine 0.2100
Thifensulfuron-methyl 100.0000
Triflusulfuron methyl 32.0000 11.0000
56
Annex M. Fraction of missing data for acute indicators.Fractions were calculated in relation to total area treated. (Acute toxicity, Kd and DT50)
LI REXTOX ADSCORYearFish Daph Algae Fish Daph Algae Fish Daph Algae
1992 0.008 0.016 0.018 0.019 0.024 0.026 0.008 0.016 0.0181993 0.005 0.011 0.011 0.009 0.016 0.016 0.005 0.011 0.0111994 0.003 0.009 0.008 0.006 0.013 0.013 0.003 0.009 0.0081995 0.003 0.008 0.009 0.006 0.012 0.013 0.003 0.008 0.0091996 0.002 0.007 0.007 0.003 0.008 0.008 0.002 0.007 0.0071997 0.003 0.006 0.007 0.004 0.007 0.008 0.004 0.006 0.0071998 0.002 0.008 0.006 0.002 0.008 0.006 0.002 0.008 0.0061999 0.002 0.014 0.008 0.003 0.015 0.009 0.002 0.014 0.0082000 0.003 0.010 0.007 0.003 0.010 0.008 0.002 0.009 0.006
Annex N. Fraction of missing data for acute indicators.Fractions were calculated in relation to total area treated. Fractions identical across indicatorsbecause data on chronic toxicity sets the lower limit. (Chronic toxicity, Kd and DT50).
LI REXTOX ADSCORYearFish Daph Algae Fish Daph Algae Fish Daph Algae
1992 0.483 0.656 0.358 0.483 0.656 0.358 0.483 0.656 0.3581993 0.513 0.658 0.403 0.513 0.658 0.403 0.513 0.658 0.4031994 0.513 0.635 0.401 0.513 0.635 0.401 0.513 0.635 0.4011995 0.517 0.662 0.409 0.517 0.662 0.409 0.517 0.662 0.4091996 0.450 0.626 0.361 0.450 0.626 0.361 0.450 0.626 0.3611997 0.428 0.563 0.429 0.428 0.563 0.429 0.428 0.563 0.4291998 0.441 0.587 0.455 0.441 0.587 0.455 0.441 0.587 0.4551999 0.528 0.678 0.516 0.528 0.678 0.516 0.528 0.678 0.5162000 0.549 0.733 0.527 0.549 0.733 0.527 0.549 0.733 0.527
57
Annex O. Example of random selection of input data of acute fish toxicity.Example is calculated for Alpha-cypermethrin and illustrates how the selection affects LI. Thetoxicity values (mg/l) is listed in Appendix E and the usage data is seen in Appendix C. The LIindicator is defined by Eq. 2.2. A large variation in the magnitude of 105 mainly due to thevariability of the TOX values.
Year: 1992 1993 1994 1995 1996 1997 1998 1999 2000Total usage (kg): 3115 3146 1263 4722 1303 609 659 1287 602AGRAyea (1000ha):
2532 2351 2272 2289 2319 2326 2321 2233 2188
TOXFish96hrLC50(mg/l)
0.0056 0.21969 0.23896 0.09927 0.36838 0.10034 0.04675 0.05070 0.10292 0.049130.3500 0.00352 0.00382 0.00159 0.00589 0.00161 0.00075 0.00081 0.00165 0.000790.0650 0.01893 0.02059 0.00855 0.03174 0.00864 0.00403 0.00437 0.00887 0.004230.1200 0.01025 0.01115 0.00463 0.01719 0.00468 0.00218 0.00237 0.00480 0.002290.2200 0.00559 0.00608 0.00253 0.00938 0.00255 0.00119 0.00129 0.00262 0.001250.0028 0.43938 0.47791 0.19853 0.73675 0.20067 0.09351 0.10140 0.20584 0.098260.0009 1.32285 1.43888 0.59774 2.21818 0.60417 0.28153 0.30530 0.61974 0.295850.0010 1.23025 1.33815 0.55590 2.06291 0.56188 0.26182 0.28393 0.57635 0.275140.0011 1.11841 1.21650 0.50536 1.87537 0.51080 0.23802 0.25812 0.52396 0.250120.0008 1.53782 1.67269 0.69487 2.57864 0.70235 0.32728 0.35491 0.72044 0.343920.0110 0.11184 0.12165 0.05054 0.18754 0.05108 0.02380 0.02581 0.05240 0.025010.0600 0.02050 0.02230 0.00926 0.03438 0.00936 0.00436 0.00473 0.00961 0.004590.0004 3.07563 3.34538 1.38974 5.15727 1.40470 0.65456 0.70982 1.44089 0.687840.0032 0.38445 0.41817 0.17372 0.64466 0.17559 0.08182 0.08873 0.18011 0.085980.0220 0.05592 0.06083 0.02527 0.09377 0.02554 0.01190 0.01291 0.02620 0.012510.011 0.11184 0.12165 0.05054 0.18754 0.05108 0.02380 0.02581 0.05240 0.02501
0.0008 1.53782 1.67269 0.69487 2.57864 0.70235 0.32728 0.35491 0.72044 0.343920.0028 0.43938 0.47791 0.19853 0.73675 0.20067 0.09351 0.10140 0.20584 0.09826
0.24 0.00513 0.00558 0.00232 0.00860 0.00234 0.00109 0.00118 0.00240 0.001155 0.00025 0.00027 0.00011 0.00041 0.00011 0.00005 0.00006 0.00012 0.00006
58
Annex P. Min - Max risk indices for fungicidesCalculated using the minimum and maximum possible input values for toxicity and fate. Notice that indices have been scaled to allowcomparisons within indices but not between different indices.
LI Fish
0.00.51.01.52.02.53.03.5
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
MinMax
Rextox Fish
0.0
1.0
2.0
3.0
4.0
5.0
6.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
ADSCOR Fish
0.00.51.01.52.02.53.03.5
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
LI Daphnia
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
REXTOX Daphnia
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
ADSCOR Daphnia
0.0
1.0
2.0
3.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
LI algae
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue REXTOX algae
0.00.5
1.01.5
2.02.5
3.03.5
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
ADSCOR algae
0.0
1.02.0
3.0
4.0
5.06.0
7.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
59
Annex Q. Min - Max risk indices for growth regulatorsCalculated using the minimum and maximum possible input values for toxicity and fate. Notice that indices have been scaled to allowcomparisons within indices but not between different indices.
LI Fish
0.0
0.5
1.0
1.5
2.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
MinMax
REXTOX Fish
0.0
0.5
1.0
1.5
2.0
2.5
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
ADSCOR Fish
0.2
0.6
1.0
1.4
1.8
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
LI Daphnia
0.0
0.51.0
1.52.0
2.53.0
3.5
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
REXTOX Daphnia
0.0
1.0
2.0
3.0
4.0
5.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
ADSCOR Daphnia
0.0
1.0
2.0
3.0
4.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
LI algae
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
REXTOX algae
0.0
1.0
2.0
3.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
ADSCOR algae
0.0
2.0
4.0
6.0
8.0
10.0
12.0
1992 1994 1996 1998 2000S
cale
d in
dica
tor
valu
e
60
Annex R. Min - Max risk indices for herbicidesCalculated using the minimum and maximum possible input values for toxicity and fate. Notice that indices have been scaled to allow comparisons within indices but notbetween different indices.
LI Fish
0.0
1.0
2.0
3.0
4.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
MinMax
REXTOX Fish
0.0
1.0
2.0
3.0
4.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
ADSCOR Fish
0.0
1.0
2.0
3.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
LI Daphnia
0.0
0.4
0.8
1.2
1.6
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
REXTOX Daphnia
0.0
0.4
0.8
1.2
1.6
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
ADSCOR Daphnia
0.0
1.0
2.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
LI algae
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
REXTOX algae
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
ADSCOR algae
0.0
0.5
1.0
1.5
2.0
2.5
1992 1994 1996 1998 2000S
cale
d in
dica
tor
valu
e
61
Annex S. Min - Max risk indices for insecticidesCalculated using the minimum and maximum possible input values for toxicity and fate. Notice that indices have been scaled to allow comparisons within indices but notbetween different indices.
REXTOX Fish
0,0
1,0
2,0
3,0
4,0
5,0
6,0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue ADSCOR Fish
0,0
1,0
2,0
3,0
4,0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lueLI Fish
0,0
1,0
2,0
3,0
4,0
5,0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
MinMax
LI Daphnia
0.0
1.0
2.0
3.0
4.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue REXTOX Daphnia
0.0
1.0
2.0
3.0
4.0
5.0
6.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue ADSCOR Daphnia
0.0
1.0
2.0
3.0
4.0
5.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
LI algae
0.0
0.5
1.0
1.5
2.0
2.5
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue
REXTOX algae
0.0
1.0
2.0
3.0
4.0
1992 1994 1996 1998 2000
Sca
led
indi
cato
r va
lue ADSCOR algae
0.0
0.5
1.0
1.5
2.0
2.5
1992 1994 1996 1998 2000S
cale
d in
dica
tor
valu
e
62
Annex T. Scaled risk indices for Insecticides & HerbicidesScaled risk indices for Fish, Daphnia and Algae calculated for insecticides and herbicides. Calculations were based on averaged input values.Indices have been scaled to allow comparisons within indices but not between different indices.
Inse
ctic
ides
Her
bici
des
Fish
0
0.5
1
1.5
2
2.5
1992 1994 1996 1998 2000
FTLIREXTOXADSCOR
Daphnia
0
0.5
1
1.5
2
2.5
3
1992 1994 1996 1998 2000
Algae
0
0.5
1
1.5
2
2.5
1992 1994 1996 1998 2000
Fish
0
0.5
1
1.5
2
2.5
1992 1994 1996 1998 2000
FALIREXTOXADSCOR
Daphnia
00.2
0.6
1
1.4
1.8
1992 1994 1996 1998 2000
Algae
00.2
0.6
1
1.4
1992 1994 1996 1998 2000
63
Annex U. Scaled risk indices for Fungicides & Growth regulatorsScaled risk indices for Fish, Daphnia and Algae calculated for fungicides and growth regulators. Calculations were based on averaged inputvalues. Indices have been scaled to allow comparisons within indices but not between different indices.
Fung
icid
esG
row
th r
edul
ator
s
Fish
0
0.5
1
1.5
2
2.5
3
1992 1994 1996 1998 2000
FALIREXTOXADSCOR
Daphnia
00.5
11.5
2
2.53
3.5
1992 1994 1996 1998 2000
Algae
0
0.5
1
1.5
2
2.5
3
1992 1994 1996 1998 2000
Fish
0
0.5
1
1.5
2
2.5
1992 1994 1996 1998 2000
FALIREXTOXADSCOR
Daphnia
0
0.5
1
1.5
2
2.5
3
1992 1994 1996 1998 2000
Algae
0
1
2
3
4
1992 1994 1996 1998 2000
64
Annex X. Indicator agreement on trends.Analysis includes every type of pesticide. Increasing values (+) and decreasing values (-)between progressing pair of years.
LI REXTOX ADSCOR ∑Years
FA
Fish Daphni Algae Fish Daphni Algae Fish Daphni Algae + -
Fungicides1992 1993 - - + - - + - - - - 2 81993 1994 - - + - - + - + + - 4 61994 1995 + - - + - - + - - - 3 71995 1996 - - - - - - - - - + 1 91996 1997 + + + + - - - + + - 6 41997 1998 + + + - + + + + + + 9 11998 1999 + - + + - + - - + + 6 41999 2000 - - - - - - - - - - 0 10
Growth regulators1992 1993 - + + - + + - - - - 4 61993 1994 - - - - - - - - - - 0 101994 1995 + + + + + + + + + + 10 01995 1996 - - - - - - - - - - 0 101996 1997 + + + + + + + + + + 10 01997 1998 + + + + + + + + + + 10 01998 1999 + + + - - + - - + - 5 51999 2000 - - - - - - - - - - 0 10
Herbicides1992 1993 - + + + - - - + - - 4 61993 1994 - + + + + + + + - + 8 21994 1995 + + + + + + + + + - 9 11995 1996 - - + + - + + - + + 6 41996 1997 + + + + + + + + + + 10 01997 1998 + - + - - + - - + - 4 61998 1999 + - - - - - - - - - 1 91999 2000 - + + - - + - + + - 5 5
Insecticides1992 1993 - + + - + - - - - - 3 71993 1994 - - - - - - - - + + 2 81994 1995 + + + + + + + + + + 10 01995 1996 - - - - - - - - - - 0 101996 1997 + + + + + + + + + + 10 01997 1998 + - - - - - - - - - 1 91998 1999 + + + + - - - - + + 6 41999 2000 - - - - - - - - - - 0 10
65
Annex Y. Trend analysis for Indicators during the period 1992-2000.Calculated indicators for the different years were log transformed causing indicators to benormally distributed. Residuals were then calculated by subtracting from each year’s value thecorresponding average value for the period 1992-2000. Residuals were subsequently tested fortemporal trends using Kendall’s τ. FA calculated for all pesticides. Significant trends are shownin bold.Pesticide Indicator Kendall’s τ ProbabilityAll groups FA -0.556 0.0371
Fish LI -0.444 0.0953 REXTOX -0.722 0.0067 ADSCOR -0.500 0.0035Daphnia LI -0.500 0.0606 REXTOX -0.778 0.0035 ADSCOR -0.611 0.0218Algae LI 0.667 0.0123 REXTOX -0.833 0.0018
Insecticides
ADSCOR -0.611 0.0218Fish LI 0.056 0.8348 REXTOX -0.722 0.0067 ADSCOR 0 1Daphnia LI 0.611 0.0218 REXTOX 0.444 0.0953 ADSCOR 0.389 0.1444Algae LI 0 1 REXTOX -0.333 0.2109
Herbicides
ADSCOR -0.500 0.0606Fish LI -0.722 0.0067 REXTOX -0.778 0.0035 ADSCOR -0.167 0.5316Daphnia LI -0.222 0.4042 REXTOX -0.278 0.2971 ADSCOR -0.278 0.2971Algae LI -0.333 0.2109 REXTOX -0.722 0.0067
Fungicides
ADSCOR -0.722 0.0067Fish LI -0.333 0.2109 REXTOX -0.500 0.0606 ADSCOR -0.500 0.0606Daphnia LI -0.278 0.2971 REXTOX -0.389 0.1444 ADSCOR -0.500 0.0606Algae LI 0.056 0.8348 REXTOX -0.056 0.8348
Growthregulators
ADSCOR 0.056 0.8348
66
Annex Z. Exposure estimation of REXTOX in field studies Measured and estimated pesticide concentration in streams in connection with spray drift and surface run-off events. Predicted concentrations instreams were calculated according to REXTOX using available information on depth of stream, characteristics of pesticide (T½, Koc), application(dose, interval), water index, area treated, slope, precipitation and buffer width. In case of missing information slope was assumed to 2.3 %, bufferzone set to 0 and soil assumed to be sandy (carbon % of 1.3), covered with vegetation and dry.Pesticide Pesticide conc. in stream Precipita.
(mm d-1)Stream Q(m3 s-1)
Remark Ref.
Spray-drift(µg l-1)
Run-off(µg l-1)
Predicted(REXTOX)
Azinphos-M 0.04±0.01 (within 95% ofpredicted)
0 0.28
Azinphos-M 0.26 0.15 6.8 7.5Azinphos-M 1.5 1.4 28.8 22.4Endosulfan 0.07±0.02 (within 95% of
predicted)0
Endosulfan 0.13 0.003 6.8 7.5Endosulfan 2.9 0.06 28.8 22.4
OrchardArial spray
Schulz 2001
Fenvalerate - 6.2 0.30 15 0.02Parathion - 6.0 1.7 8 0.03
Field spray Liess et al.
Carbofuran - 26run-off + drainage
2.6 >15 - Granules; drainconc. 264 µg/l
Mathiessen et al. 1995
Cypermethrin 0.03 0.01-0.09 Field spray Shires & Bennett 1985
Fenvalerate 0.11 0.01-0.04 Field spray Baughman et al. 1989
67
Annex AA. Effect of buffer zone width on spray drift and run-offEffect of buffer zone width on spray drift (% of dose applied on field) and run-off (% reduction through buffer zone) to streams (and ditch). Forspray drift calculated percentages of field dose (according to REXTOX) are shown in brackets. For run-off calculated reductions according toREXTOX are shown in brackets.
0 m 1 m 2m 3 m 5 m 6 m 10 m 20 m ReferenceSpray driftDitch bank 4-25
(-)0-0.08(0.82)
0(0.38)
Ditch 0.6-2.2(-)
0-0.07(0.82)
0(0.38)
De Snoo & deWit
Run offLindane 0 72 (68) 100
(96)Atrazine 0 44 (68) 100
(96)
Gril et al. 1997
Metribuzin 0 51 (31) Webster &Shaw 1996
Norflurazon 0 50(25)*
Fluometuron 0 48(24)*
Murphy & Shaw1998
* seasonal average for 0.5 and 1 m buffer width
68
Annex BB. Modelling relation between FA and Pesticide Effects on Aquaticlife.The effect of different Frequency of Treatment of pesticides in Danish agriculture on non-targetorganisms in ponds has previously been evaluated using a dynamic exposure-effect model(Møhlenberg & Gustavsson 1998). Briefly, the model considers wind drift and surface run-offfrom a “standard” field surrounding a small pond. Depending on the crop various pesticides areapplied according to recommended date of application and doses. Wind drift is calculatedaccording to Ganzelmeier functions taking account of buffer zones required for risk mitigationfor the different insecticides. Pesticides on the field and vegetation are degraded according topublished DT50 and modified by a temperature function. Surface run-off occurs only in case ofheavy rainfall (>10 mm during 3 h) that is modelled by 3 Monte-Carlo functions to simulateactual rainfall during different seasons. During run-off events 0.2 % of pesticides remaining(after degradation) on 2 ha closest to the pond are transferred to the pond. In the pond pesticidesdissipates due to degradation and sedimentation and affects populations of plankton algae,daphnia and macrophytes that are modelled using generic population models. Only direct(mortality) effects are considered using concentration-mortality relations obtained fromliterature. Effect of pesticides are calculated as deviations from control run (without pesticideapplication) in average biomass/numbers of plankton algae, daphnia and macrophytes during thegrowth season. Each field/pesticide combination was run 40-50 times, population biomassaveraged and compared to control. Data was the averaged for different crops according to theirrelative coverage to arrive at an overall impact (Table V).
Table V. Probabilities of detecting significant effects on algae and daphnia at different LoadIndex. Data based on deterministic exposure-effect model. See text for further details.
Application Scenario Probability of significanteffects (>10 % reduction)on algae
Probability of significanteffects (> 10 %reduction) on daphnia
FT = 2.34 (Year 1997) 1) 85 % 55 %FT = 1.17 2) 45 % 25 %FT = 0.59 3) 20 % 15 %FT = 0.40 4) 10 % 10 %1. Actual average application rate in 1997 based on distribution of crops and using pesticides at recommended
frequency and dose.2. Actual average application rate in 1997 divided by 2 (i.e. halving the frequency but maintaining doses).3. Only grain and grass grown and pesticides applied at recommended dose and frequency.4. As 3) but winter grain exchanged with spring grain. Pesticides applied at recommended dose and frequency.
In the study four different load scenarios were considered (see Table V). The scenarios includedboth changes in pesticides applied (scenarios 3 and 4), frequency of application (scenarios 2, 3and 4) and season of application (scenario 3 and 4). The effects on algae and daphnia quantifiedas probabilities for observing reductions larger than10 % in populations decreased monotonicallyand almost linear with decreases in FA index from 85 % to 10 % in algae and from 55 % to 10 %in daphnia. Hence, based on these examples the simple FA index as used by the Danish Agencyof Environmental Protection does represent a reliable measure of risk estimate. However, itshould be noted that the effect of buffer zones required for risk mitigation was not quantified.
69
Annex DD. Toxicity function in IndicatorsAll indicators discussed except FA include a function describing the toxicity relative to thesprayed area (ADSCOR), the Total use (LI) or both (REXTOX). ADSCOR however alsoincludes an element for dosage, but this is entered as a score (0 – 4). By not including numeric orscoring values for toxicity FA implicitly assume that the standard dose varies inversely with theactive ingredients’ toxicity towards target organisms, i.e. pesticides dosed at high rates areexpected to show a low toxicity and visa versa. The validity of this assumption with respect tonon-target organisms was examined by plotting the single species toxicity against the dose ratefor those pesticides with the highest influence in the REXTOX indicator (Figure DD). For fishLC50 increased significantly with recommended dose rate of pesticides (all pesticides: r2 = 0.26,p < 0.01; insecticides only: r2 = 0.52, p < 0.01), but for daphnia and algae no relations was foundirrespective of pesticide type considered. This indicates that, an inverse relationship between theapplied dose of pesticides and the toxic concentrations may not be generally valid for all aquaticorganisms. It should however be noted that the examination includes relatively few pesticidesand that this may have biased the outcome significantly.
Figure DD. Scatter plots between dose rateand toxicity (expressed as LC50) ofpesticides to Daphnia, Fish and Algae.Pesticides included those with the highestADR/ToxA ratios in REXTOX indicatorand applied during the period 1992-2000 inDenmark.
Relation between EC50 for daphnia and dose on field
0.000
0.001
0.010
0.100
1.000
0.001 0.010 0.100 1.000 10.000Dose (Kg/ha)
EC
50(m
g/l)
Insecticides
Fungicide
Herbicide
Relation between EC50 for fish og dose on field
0.0001
0.0010
0.0100
0.1000
1.0000
10.0000
0.001 0.010 0.100 1.000 10.000
Dose (Kg/ha)
EC
50 (m
g/l)
Insecticide
Fungicide
Herbicide
Relation between EC50 for algae and dose on field
0.001
0.010
0.100
1.000
10.000
0.1 1.0 10.0Dose (Kg/ha)
EC
50 (
mg/
l)
Herbicide
Fungicide
71
Annex EE. Calculation of FA
Product Sales Crop Dose Area Area FAkg/year kg/ha treated ha in rotation ha
Herbicide 1: 1.000 Winter cereals 75% 0,50 1.500Spring cereals 25% 0,25 1.000
Herbicide 2: . . . . . . . . . . . . . . All herbicides: Winter cereals 921.192 804.198 1,15
Spring cereals 723.348 768.704 0,94
. . . . . . . .
All herbicides All crops 2.809.074 2.188.213 1,28
All growth regulators All crops 219.321 2.188.213 0,10
All fungicides All crops 1.085.111 2.188.213 0,50
All insecticides All crops 407.017 2.188.213 0,19
All pesticides All crops 4.520.522 2.188.213 2,07
72
Annex FF: Calculation of LI
Sales Organism Toxicity Number of Area Load Indexkg/year LC50 etc. toxicity doses in rotation ha
Herbicide 1: 1.000 Fish 1 mg/l 1.000.000
Herbicide 2: . . . . . . . . . . . . All herbicides: Fish 5.903,00 x 106 2.361.233 2.500,0
All growth regulators Fish 0,71 x 106 2.361.223 0,3
All fungicides Fish 2.007,00 x 106 2.361.223 850,0
All insecticides Fish 35.417,00 x 106 2.361.223 15.000,0
All pesticides Fish 43.328,00 x 106 2.361.223 18.350,3
73