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1.
Environ Toxicol Chem ; 36(9): 2465-2475, 2017 09.
Artículo en Inglés | MEDLINE | ID: mdl-28262983

RESUMEN

Nature of exposure is a fundamental driver in nontarget terrestrial plant risk assessment for pesticides; consequently a novel study was designed to generate field-based drift exposure and evaluate corresponding biological effects of the herbicide mesotrione. The approach used a combination of US guideline drift reduction technology and vegetative vigor approaches. In each of 3 independent replicate spray application trials, 10 pots each of lettuce and tomato were placed at distances of 10, 20, 30, 40, and 50 ft (∼3, 6, 9, 12, and 15 m) from the downwind edge of the spray boom. Each application was conducted using a commercial 60-ft (18-m) boom sprayer fitted with TeeJet® Technologies TTI110025 nozzles, with a nominal application rate of 0.2 lb a.i./A (224 g a.i./ha). The environmental conditions required by the protocol (air temperature 10-30 °C and wind perpendicular to the swath (±30°) blowing toward the plants at a mean wind speed of ≥10 mph [≥4.5 m/s] measured at 2.0 m above the ground) were met for each application. Following exposure, plants were transferred to a greenhouse for the 21-d vegetative vigor phase of the study. Symptoms of phytotoxicity and plant height were assessed at 7, 14, and 21 d after treatment. On completion of the 21-d after treatment assessment, all plants were harvested and dried in an oven to determine shoot dry weight. The biological data indicated that no statistically significant effects were observed at a distance of 30 ft (∼9 m) from mesotrione drift at wind speeds of ≥10 mph (10.9-12.4 mph); this endpoint (30 ft) is defined as the no observed effects distance (NOED). Environ Toxicol Chem 2017;36:2465-2475. © 2017 SETAC.


Asunto(s)
Ciclohexanonas/toxicidad , Herbicidas/toxicidad , Plantas/efectos de los fármacos , Monitoreo del Ambiente , Medición de Riesgo , Viento
2.
Integr Environ Assess Manag ; 11(1): 102-17, 2015 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-25091316

RESUMEN

Simple, deterministic screening-level assessments that are highly conservative by design facilitate a rapid initial screening to determine whether a pesticide active ingredient has the potential to adversely affect threatened or endangered species. If a worst-case estimate of pesticide exposure is below a very conservative effects metric (e.g., the no observed effects concentration of the most sensitive tested surrogate species) then the potential risks are considered de minimis and unlikely to jeopardize the existence of a threatened or endangered species. Thus by design, such compounded layers of conservatism are intended to minimize potential Type II errors (failure to reject a false null hypothesis of de minimus risk), but correspondingly increase Type I errors (falsely reject a null hypothesis of de minimus risk). Because of the conservatism inherent in screening-level risk assessments, higher-tier scientific information and analyses that provide additional environmental realism can be applied in cases where a potential risk has been identified. This information includes community-level effects data, environmental fate and exposure data, monitoring data, geospatial location and proximity data, species biology data, and probabilistic exposure and population models. Given that the definition of "risk" includes likelihood and magnitude of effect, higher-tier risk assessments should use probabilistic techniques that more accurately and realistically characterize risk. Moreover, where possible and appropriate, risk assessments should focus on effects at the population and community levels of organization rather than the more traditional focus on the organism level. This document provides a review of some types of higher-tier data and assessment refinements available to more accurately and realistically evaluate potential risks of pesticide use to threatened and endangered species.


Asunto(s)
Especies en Peligro de Extinción , Contaminantes Ambientales/toxicidad , Plaguicidas/toxicidad , Animales , Monitoreo del Ambiente , Modelos Teóricos , Medición de Riesgo
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