Water pesticide determination

The solubility of methyl parathion is not sufficient to pose a problem in runoff water as determined by an empirical model of Wauchope and Leonard (1980). Some recent monitoring data, however, indicate that methyl parathion has been detected in surface waters (Senseman et al. 1997). In a study to determine the residue levels of pesticides in shallow groundwater of the United States, water samples from 1,012 wells and 22 springs were analyzed for methyl parathion. No methyl parathion was detected in any of the water samples (Kolpin et al. 1998). In a study of water from near-surface aquifers in the Midwest, no methyl parathion was detected in any of the water samples from 94 wells that were analyzed for pesticide levels (Kolpin et al. 1995). Leaching to groundwater does not appear to be a significant fate process. 

A monitoring system has been established to determine 90 pesticides including anilides and 10 related degradation products in river water. Pesticide residues in the water sample are collected on a PS-2 cartridge (265-mg) at a flow rate of 10 mL min, eluted with 3 mL of acetone, 3 mL of n-hexane and 3 mL of ethyl acetate successively, and determined by GC/MS. Overall recoveries ranged from 72 to 118%. Recoveries of mepronil, naproanilide, propanil and flutolanil at fortification levels of 0.1 and 2 mg kg Mn water by this method were 80-112%. The LODs were 0.01 -0.1 pg L ... 

M.A. Sirvent, A. Merkoci, and S. Alegret, Pesticide determination in tap water and juice samples using disposable amperometric biosensors made using thick-film technology. Anal. Chim. Acta 442, 35-44 (2001). 

E. Mallat, D. Barcel6, C. Barzen, G. Gauglitz, and R. Abuknesha, Immunosensors for pesticide determination in natural waters. Trac-Trends Anal. Chem. 20, 124-132 (2001). 

Effects assessment, by, as in the case of risk assessment for chemicals and pesticides, determining a set of marker organisms (including algae, zebrafish, insect larvae, benthic worm, water flea, etc.) that represent ecosystem components and food networks and are used to indicate acute and chronic effects. This step is also used to define the predicted no-effect concentrations (PNECs). 

Surface water was determined to be more vulnerable than groundwater for most contaminants. SOCs were more common in surface waters, and most of the contaminants that exceeded the MCLs were in surface waters. For VOCs, however, no signihcant difference was found in the number of contaminants exceeding MCLs in ground or surface waters. lOCs were found to be equally common in both ground and surface waters. Many SOCs (pesticides, in particular) were seasonally present. 

A bibliographic search has shown that the majority of the HPLC techniques for determining OPPs and OCPs have been applied to the determination of residues in surface, ground- and drinking water. Table 5 lists pesticides determined, extraction and cleanup methods used, HPLC conditions, contaminated matrix and analyte detection limits taken from the literature for water, animal tissues, milk, fruit and vegetables, and cereals. The majority of the studies were done on spiked samples, and in the best of cases there were few real samples analyzed. 

Hydrolysis can explain the attenuation of contaminant plumes in aquifers where the ratio of rate constant to flow rate is sufficiently high. Thus 1,1,1-trichloroethane (TCA) has been observed to disappear from a mixed halocarbon plume over time, while trichlo-roethene and its biodegradation product 1,2-dichloroethene persist. The hydrolytic loss of organophosphate pesticides in sea water, as determined from both laboratory and field studies, suggests that these compounds will not be long-term contaminants despite runoff into streams and, eventually, the sea (Cotham and Bidleman, 1989). The oceans also can provide a major sink for atmospheric species ranging from carbon tetrachloride to methyl bromide. Loss of methyl bromide in the oceans by a combination of hydrolysis... 

The general environmental situation in the coastal regions of the Black Sea is very complicated and is close to critical [3]. The recent decades have witnessed growing pollution of waters with total phosphorus and nitrogen (Danube seaside), petroleum products (nearby Sebastopol and the Georgian coast), detergents and phenols (the southern coast of Crimea), phenols and pesticides (Odessa coast). Here the quality of coastal waters is determined not so much by the source of the pollutants and the width of the continental shelf, but by the nature and intensity of currents in the particular regions. 

The basic principles of modeling the physical, chemical and biological processes that determine pesticide fate in unsaturated soil are reviewed. The mathematical approaches taken to integrate diffusion, convection, sorption, degradation and volatilization are presented. Deterministic and stochastic models formulated to describe these processes in a soil-water pesticide system are contrasted and evaluated. The use of pesticide models for research or management purposes dictates the degree of resolution with thich these processes are modeled. 

The analytical solution to Equation 2 for a range of boundary conditions is a model of pesticide fate that has been used under a variety of laboratory situations to study the basic principles of soil-water-pesticide interaction. It is in fact limited to such laboratory cases, as steady state water flow is an assumption used in deriving the equation. As a modeling approach it is useful in those research studies in which careful control of water and solute fluxes can be used to study degradation and adsorption. For example, Zhong et al. (11) present a study of aldicarb in which the adsorption and degradation of aldicarb, aldicarb sulfone and aldicarb-sulfoxide were simultaneously determined from laboratory soil column effluent data. The solution to a set of equations of the form of Equation 2 was used. A number of similar studies for other chemicals could be cited that have provided useful basic information on pesticide behavior in soil (4,12,13). Yet, these equations are not useful in the field unless re-formulated to describe transient water and solute fluxes rather than steady ones. Early models of pesticide fate based upon Equation 2 (14) were constrained by such assumptions, but were... 

Fernandez, M. J., Garcia, C., Garcia-Villanova, R. J., and Gomez, J. A., Evaluation of liquid-solid extraction with a new sorbent and LEE for multiresidue pesticides. Determination in raw and finished drinking waters, J. Agric. Food Chem., 44, 1790-1795, 1996. 

The determination of pesticide contents in water, organic substrates,. sediments, and animal tissues depends on the chemical methods. The solid materials of plant and animal tissues are homogenized and extracted with acetone or hexane, evaporated to a small volume for microdetermi-nation by various chromatographic methods. The concept of in situ bioassays is mainly based on exposure of test animals In the contaminated water and determination of... 

ESI, triazines) [537]. Recoveries observed were > 80% except for carbendazim, bu-tocarboxim, aldicarb and molinate, all better than 67% [500]. An aoTOF-MS interfaced by ESI was used to screen and identify unknown compounds and pesticides in water samples by MS and MS/MS. Structures for compounds observed besides pesticides were proposed [538]. Traces of the phenylurea pesticides Hnuron and monolinuron in water were determined quantitatively. Calibration graphs obtained after Supelclean ENVI-18 SEE were Hnear with detection limits < 25 pg [511]. Large numbers of phenylurea herbicide analyses led to the elaboration of on-line preconcentration techniques coupled to ESI-LC-MS. The procedure was demonstrated and validated with several pesticides using 10 ml of sample, resulting in detection Hmits of about 10 ng [539]. ESI-LC-MS and MS/MS were applied to quantify and to confirm 16 different herbicides of sulfonylurea [527] type in surface water samples. Surface water samples were extracted by SPE (Spe-ed RP-102). As confirmation criteria RT, molecular ion and two fragment ions besides ion abundance ratios were defined. Quantitation at 0.1 and 1.0 ppb level was demonstrated [540]. 

In a study covering a wide range of polar and acidic pesticides deethylatrazine and atrazine besides anilide, phenoxy acid, phenylurea, carbamates and other types of specific pesticides in river water were determined by ESI-LC-MS and MS/MS. Recoveries, depending on preconcentration steps, obtained with different SPE materials (PLRS-S, Hyshere-1, LiChrolut EN and Isolute ENV -i-) and at different pH values were reported [502]. Sixteen of the most widely used pesticides in Southern Italy were monitored in surface water samples taken in the Calabria region. Triazines were determined quantitatively by LC-UV and ESI-LC-MS(-i-) and were confirmed by MS [537]. In another study the simultaneous determination of 26 non-acidic (base and neutral e.g. triazine, carbamate, anilide, N-substituted amine, urea and organophosphorus type) and 13 acidic (sulfuron and phenoxy acid type) pesticides in natural waters was performed using ESI-LC-MS. Recoveries... 

In order to be certain that no substances are present which may influence the pesticide determination, it is necessary to test the purity of the reagents before use. This is required in order to utilize the lower gas-chromatographic detection limit when analyzing concentrated water extracts. 

Mallat E and Barcelo D (2001) Immunosensors for pesticide determination in natural waters. Trends in Analytical Chemistry 20 124—132. 

This publication provides several examples of the use of solid-phase extractions for separating analytes from their matrices. Some of the examples included are caffeine from coffee, polyaromatic hydrocarbons from water, parabens from cosmetics, chlorinated pesticides from water, and steroids from hydrocortisone creams. Extracted analytes maybe determined quantitatively by gas (GC) or liquid chromatography (LG). 

U.S. EPA, Metliod SIS.1-Determination of Chlorinated Pesticide in Water hyGCjECD, draft, Apr. 15, 1988 available from U.S. EPA Environmental Monitoring and Support Laboratory, Cincinnati, Ohio, 1988. 

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