Diseño de metodológico de la investigación

6.1. Analysis of pesticides in water and sediment

Before the monitoring program could begin, the extraction methods and analytical procedures of the pesticides in the water and sediment samples had to be established. Generally, physicochemical properties such as polarity, solubility in water and/or octanol- water partition coefficient (Kow), volatility, and stability are important aspects to be considered

in pesticide analysis. In multi-residue analysis, however, determining pesticides with a wide range of properties at the same time typically results in more problems. Several extraction methods for single groups of pesticides, i.e. polar or non-polar compounds, may be best suited. However, in a routine studies it is commonly not possible due to increased efforts and costs. To reduce constraints in the analysis compromises are necessary, while an acceptable result should still be achievable. Not all analysts will have 100 % recovery for detection at low levels in all matrices. In general, for the multi-residue analysis of pesticides, a recovery ranging between 70 % and 120 % and relative standard deviation (RSD) less than 20 % are sufficient.

From the bed sediment, five of the seven investigated pesticides, but not dichlorvos and dimethoate, were recovered at acceptable ranges. With the suspended sediment, only dimethoate was outside of the upper acceptable range. The low recovery of dichlorvos is most probably due to the high volatility of this insecticide. Dimethoate recoveries of above 120 % were found in both sediment matrices. A matrix-induced chromatographic enhancement was suspected to increase the analytical signal of extracted samples, particularly with the GC-NPD system.

Additional information on how the extraction and analytical methods for the water samples were set up was presented in Chapters 4 and 5. The recoveries of the seven investigated pesticides ranged between 58 % and 117 % with high repeatability (RSD<20 %), except for chlorothalonil. Dichlorvos, chlorothalonil, and cypermethrin were troublesome pesticides with recoveries below the lower acceptable range of 70 %. Dichlorvos is a highly volatile pesticide. Evaporation is reported to be the main reason for low recoveries (Anyusheva et al., 2012). In contrast, the low extraction efficiency (58 %) and high variation (RSD=27 %) of chlorothalonil can be explained by the strong retention of chlorothalonil by the graphitized carbon black (GCB) sorbent. The high affinity of the planar molecule

chlorothalonil can provoke effects of chemisorption for particular adsorbents. In order to eliminate this undesirable effect, the sorbent was deactivated by washing the cartridge with ascorbic acid (Di Corcia et al., 1993). In our study, however, the recovery of chlorothalonil was high compared to literature values (0-46 %, Tolosa et al., 1999). The recovery of cypermethrin (69 %) was slightly below the acceptable range, because of the strong sorption of the pesticide (Log Koc 4.9) in the cartridge (Tolosa et al., 1999).

6.2. Comparison of pesticide losses during single runoff events versus long- term monitoring data

Pesticide monitoring was conducted on two different time scales: on the scale of a runoff event and on a seasonal time scale. The results from both monitoring regimes supplement each other. Short-term monitoring during the single runoff events allows for a comprehensive investigation of the input patterns of pesticides in the watershed. Additionally it uncovers occasional extremely high runoff concentrations. The long-term monitoring provides the seasonal variation and spatial distribution of the pesticides depending on the climate, pesticide use, and agricultural practices used within the watershed.

During the single runoff events, our results showed that some high mobility pesticides (log Koc<2.5), such as atrazine and dimethoate, were characterized by a close relationship between

the peak concentration and peak flow at the early part of the runoff hydrograph, indicating transport by fast flow components. However, other strongly sorbing pesticides, such as chlorpyrifos, chlorothalonil, (α, β) endosulfan, and cypermethrin, behaved inconsistently. These pesticides were sporadically detected in high concentrations during the falling limb of the runoff peak, indicating a fast and sporadic sub-surface flow component. After recession, many pesticide concentrations remained low and fairly constant on a baseline level until the end of the sampling course. Similar findings were reported by many studies. Pedersen et al. (2006) found that the maximum concentration of some organophosphorus insecticides occurred sometimes near the beginning of an event (e.g. malathion and diazinon) but chlorpyrifos remained fairly constant throughout the hydrograph. Oliver et al. (2012) reported that during the runoff event the concentration of chlorpyrifos increased with increasing peak flow, but did not decrease with the descending limb of the hydrograph.

In the long-term monitoring study, pesticide concentrations and loads in surface water show a marked increase during the rainy season (May to October when the use of insecticides (e.g., chlorpyrifos and cypermethrin) and fungicides (e.g. chlorothalonil) is typically high (Schreinemachers and Sirijinda, 2008). The pesticide load monitored at the outlet station

during the rainy season was more than 10 times higher than during the dry season (Chapter 5). In general, mean and maximum concentrations of pesticides obtained from the long-term monitoring, were lower than pesticide concentrations determined during single rainfall events. During one single runoff event in August 2008, chlorpyrifos concentration reached up to 9.7 μg L-1 at the headwater catchment of Mae Sa River. This concentration is clearly higher than the limit of EU (>0.03 μg L-1) for chlorpyrifos in surface water and it is much higher than the Canadian limit (>0.0035 μg L-1). Nevertheless, although the short-term monitoring scheme provides a better picture of maximum concentration and load of pesticides due to high resolution sampling, it runs the risk of not detecting the pesticides that show up only sporadically in river waters. For example, dichlorvos was detected in none of the three single rainfall events in May, August and September 2008. However, with long term monitoring, dichlorvos was detected several times during the rainy season in 2007 and 2008. The maximum concentration of dichlorvos at the MSN station was as high as 1.1 μg L-1.