A new one-parameter correlation is developed for the evaporation rate (ER) of chemicals as a function of molar mass (M) and vapor pressure (P) that is simpler than existing correlations. It applies only to liquid surfaces that are unaffected by the underlying solid substrate as occurs in the standard ASTM evaporation rate test and to quiescent liquid pools. The relationship has a sounder theoretical basis than previous correlations because ER is correctly correlated with PM rather than P alone. The inclusion of M increases the slope of previous log ER versus log P regressions to a value close to 1.0 and yields a simpler one-parameter correlation, namely, ER (μg m(-1) h(-1)) = 1464P (Pa) × M (g mol(-1)). Applications are discussed for the screening level assessment and ranking of chemicals for evaporation rate, such as pesticides, fumigants, and hydrocarbon carrier fluids used in pesticide formulations, liquid consumer products used indoors, and accidental spills of liquids. The mechanistic significance of the single parameter as a mass-transfer coefficient or velocity is discussed.

A surface drinking water monitoring program for four corn (Zea mays L.) herbicides was conducted during 1995-2001. Stratified random sampling was used to select 175 community water systems (CWSs) within a 12-state area, with an emphasis on the most vulnerable sites, based on corn intensity and watershed size. Finished drinking water was monitored at all sites, and raw water was monitored at many sites using activated carbon, which was shown capable of removing herbicides and their degradates from drinking water. Samples were collected biweekly from mid-March through the end of August, and twice during the off-season. The analytical method had a detection limit of 0.05 microg L(-1) for alachlor [2-chloro-N-(2,6-diethylphenyl)-N-(methoxymethyl)-acetamide] and 0.03 microg L(-1) for acetochlor [2-chloro-N-(ethoxymethyl)-N-(2-ethyl-6-methylphenyl)-acetamide], atrazine [6-chloro-N-ethyl-N'-(1-methylethyl)-1,3,5-triazine-2,4-diamine], and metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)-acetamide]. Of the 16528 drinking water samples analyzed, acetochlor, alachlor, atrazine, and metolachlor were detected in 19, 7, 87, and 53% of the samples, respectively. During 1999-2001, samples were also analyzed for the presence of six major degradates of the chloroacetanilide herbicides, which were detected more frequently than their parent compounds, despite having higher detection limits of 0.1 to 0.2 microg L(-1). Overall detection frequencies were correlated with product use and environmental fate characteristics. Reservoirs were particularly vulnerable to atrazine, which exceeded its 3 microg L(-1) maximum contaminant level at 25 such sites during 1995-1999. Acetochlor annualized mean concentrations (AMCs) did not exceed its mitigation trigger (2 microg L(-1)) at any site, and comparisons of observed levels with standard measures of human and ecological hazards indicate that it poses no significant risk to human health or the environment.

Volatilization of chemicals can be an important form of dissipation in the environment. Rates of evaporative losses from plant and soil surfaces are useful for estimating the potential for food-related dietary residues and operator and bystander exposure, and can be used as source functions for screening models that predict off-site movement of volatile materials. A regression of evaporation on vapor pressure from three datasets containing 82 pesticidal active ingredients and co-formulants, ranging in vapor pressure from 0.0001 to >30,000 Pa was developed for this purpose with a regression correlation coefficient of 0.98.

The Acetochlor Registration Partnership (ARP) conducted a 7-yr ground water monitoring program at a total of 175 sites in seven states: Illinois, Indiana, Iowa, Kansas, Minnesota, Nebraska, and Wisconsin. While acetochlor [2-chloro-N-(ethoxymethyl)-N-(2-ethyl-6-methylphenyl)-acetamide] was the primary focus, the analytical methods also quantified alachlor [2-chloro-N-(2,6-diethylphenyl)-N-(methoxymethyl)-acetamide], atrazine [6-chloro-N-ethyl-N'-(1-methylethyl)-1,3,5-triazine-2,4-diamine], metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)-acetamide], and two classes of soil degradates for acetochlor, alachlor, and metolachlor. Ground water samples were collected monthly for five years and quarterly for two additional years. All samples were analyzed for the presence of parent herbicides, and degradates were monitored during the last three years. Parent acetochlor was detected above 0.1 microg L(-1) in three or more samples at just seven sites. Alachlor and metolachlor were also rarely detected, but atrazine was detected in 36% of all samples analyzed. Even more widespread were the tertiary amide sulfonic acid (ethanesulfonic acid, ESA) degradates of acetochlor, alachlor, and metolachlor, which were detected at 81, 76, and 106 sites, respectively. The other class of monitored soil degradates (oxanilic acid, OXA) was detected less frequently, at 26, 16, and 63 sites for acetochlor OXA, alachlor OXA, and metolachlor OXA, respectively. The geographic distribution of detections did not follow the pattern originally expected when the study began. Rather than being a function primarily of soil texture, the detection of these herbicides in shallow ground water was related to site-specific factors associated with local topography, the occurrence of surface water drainage features, irrigation practices, and the vertical positioning of the well screen.

Growth of corn seedlings during the coleoptile stage was measured using optical flow. The measurement system was comprised of a digital camera, computer, and related software and measured growth in a continuous, noncontact manner. The use of optical flow to measure shoot elongation, i.e., image motion of the elongating seedling, was most easily computed when there were large spatiotemporal variations of the motion of the corn seedling against the background. The sensitivity of the measurement technique was in the micron per second range. Seedling growth did not occur in a smooth even manner, rather, growth was a series of varying bursts or waves of expansion that appeared to be affected by the physical growth or development of the leaves. Spectral analysis techniques were applied to extract the underlying signal from the observed time series of seedling growth rate and angle.