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Enregistrement W1574060208 · doi:10.5772/17396

Environmental Impact and Remediation of Residual Lead and Arsenic Pesticides in Soil

2011· book-chapter· en· W1574060208 sur OpenAlexaboutno aff
Eton E. Codling

Notice bibliographique

RevueInTech eBooks · 2011
Typebook-chapter
Langueen
DomaineAgricultural and Biological Sciences
ThématiquePesticide Exposure and Toxicity
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésEnvironmental remediationArsenicPesticideEnvironmental scienceEnvironmental chemistryResidualSoil remediationToxicologyContaminationChemistryAgronomyBiologyEcologyComputer science

Résumé

récupéré en direct d'OpenAlex

Environmental effects of lead arsenate pesticides Occurrence of lead arsenate in the environmentIn the early 1900s, fear and concern arose about the potential for retention of excessive pesticide residues on fruits and vegetables treated with lead arsenate.This concern became a reality in 1919, when western pears were condemned in Boston because of excessive arsenic residues (Klassen & Schwartz, 1983).Arsenate residue was also observed in fruits grown on lead arsenate contaminated soils in Canada.Arsenic concentrations in fruit juice and juice concentrate were higher when prepared from skin and cores.Arsenic concentrations in fruit and fruit products were influenced by the size of fruits at spraying and by spraying frequency (Bishop & Chisholn, 1966).As a result of repeated lead arsenate application, lead and arsenic concentrations increased significantly in orchard soils.In one orchard soil studied, lead concentration ranged from 500 to 1500 mg kg -1 and arsenic concentration ranged from 200 to 500 mg kg -1 , whereas the concentrations found in uncontaminated soil normally range from 2 to 300 mg kg -1 for lead and 0.1 to 20 mg kg -1 for arsenic (Alloway, 1995).In an apple orchard with 70 years of lead arsenate use, Frank et al. (1976) reported lead concentrations in the range of 6.4 to 774 mg kg-1 and arsenic concentrations from 7.4 to 121 mg kg -1 .The extent of contamination is considerable in former fruit growing areas.It has been estimated that approximately five percent of the soils in New Jersey are affected with lead arsenate, for example, while about 188,000 acres in Washington State and 50,000 acres in Wisconsin are contaminated (Focus, 2006).Lead and arsenic concentrations in orchards soils vary depending on the type of orchard (peach, plum, or apple), soil type, organic matter content, rate and frequency of pesticide application, and management practices after old trees are removed.Lower soil lead and arsenic concentrations were observed in peach orchards and vineyards than in apple orchards, due to the infrequency and lower rate of lead arsenate application in the former (Frank et al., 1976).When replanting orchards, some farmers, after removing the old trees, shift the rows when replanting new trees in order to protect them from lead and arsenic toxicity.Under this management practice, there is little disturbance of the surface, and lead and arsenic concentrations will be much higher in the surface soil compared to their levels under management practices in which fields are plowed after removal of old trees and then planted with agronomic crops such as corn, wheat, and soybean for two or three years before being replanted with new trees.Lead and arsenic concentrations in the surface soil under this management will be lower due to the mixing of the surface and subsurface soil.This practice will increase lead and arsenic in subsurface soils, which, in turn, will increase the potential for vertical movement of lead and arsenic to ground water, especially if these soils are sandy.Because lead and arsenic generally do not dissolve, biodegrade, or decay, are not rapidly absorbed by plants, and do not readily move through the soil profile, they remain in the soil long after their use (Wu et al., 2010).When lead arsenate reaches the soil, it undergoes hydrolysis, separating into lead and arsenic, which are bound to soil particles and organic matter and become immobilized.Lead is only slightly soluble and therefore accumulates in the surface soil (0-15 cm depth).Arsenic is slightly more soluble and will move through the soil profile (Focus, 2006).Arsenic mobility is enhanced by addition of phosphorus (Peryea & Kammereck, 1997).Arsenic is more mobile compared to lead regardless of the soil type and texture (Eflving et al., 1994).When lead is applied to soil, it will react with sulfate, www.intechopen.com How to referenceIn order to correctly reference this scholarly work, feel free to copy and paste the following: Eton Codling (2011).Environmental Impact and Remediation of Residual Lead and Arsenic Pesticides in Soil, Pesticides in the Modern World -Risks and Benefits, Dr. Margarita Stoytcheva (Ed.), ISBN: 978-953-307-458-0, InTech, Available from: http://www.intechopen.com/books/pesticides-in-the-modern-world-risks-and-benefits/environmental-impact-and-remediation-of-residual-lead-and-arsenic-pesticides-in-soil

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,006

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,026
Tête enseignante GPT0,218
Écart entre enseignants0,192 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations11
Publié2011
Routes d'admission1
Résumé présentoui

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