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Record W2031861972 · doi:10.4236/jep.2012.35054

Disposal and Treatment Methods for Pesticide Containing Wastewaters: Critical Review and Comparative Analysis

2012· article· en· W2031861972 on OpenAlexafffund
Mariam T. Al hattab, A. E. Ghaly

Bibliographic record

VenueJournal of Environmental Protection · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPesticideEnvironmental scienceWastewaterPesticide applicationWaste managementEnvironmental protectionEnvironmental engineeringAgronomyBiologyEngineering

Abstract

fetched live from OpenAlex

Pesticides provide the primary means for controlling organisms that compete with man for food and fibre or cause injury to man, livestock and crops. They played a vital role in the economic production of wide ranges of vegetable, fruit, cereal, forage, fibre and oil crops which now constitute a large part of successful agricultural industry in many countries. After application to the target areas, pesticide residues are removed from applicators by rinsing with water which results in the formation of a toxic wastewater that represents a disposal problem for many farmers. Pesticides can adversely affect people, pets, livestock and wildlife in addition to the pests they are intended to destroy. The phenomenon of biomagnification of some pesticides has resulted in reproductive failure of some fish species and egg shell thinning of birds such as peregrine falcons, sparrow hawk and eagle owls. Pesticide toxicity to humans include skin and eye irritation and skin cancer. Therefore, care must be exercised in the application, disposal and treatment of pesticides. Currently, disposal of pesticide wastewater is carried out by: 1) land cultivation, 2) dumping in soil pits, plastic pits and concrete pits or on land and in extreme cases in streams near the rinsing operation, 3) use of evaporation beds and 4) land filling. These methods of disposal are unsafe as the surface run off will reach streams, rivers and lakes and the infiltration of the wastewater into the local soil will eventually reach ground water. The treatment methods currently used for pesticide wastewater include: 1) incineration (incinerators and open burning), 2) chemical treatments (O3/UV, hydrolysis, Fenton oxidation and KPEG), 3) physical treatments (inorganic, organic absorbents and activated carbon) and 4) biological treatments (composting, bioaugmentation and phytoremediation). Therefore, the choice of safe, on farm disposal techniques for agricultural pesticides is very important. A comparative analysis was performed on 18 methods of pesticide disposal/treatment using six criteria: containment, detoxification ability, cost, time, suitability for on farm use, size and evaporation efficiency. The results indicated that of the 18 methods evaluated, 9 scored above 80/100 and can be used on farm. They were organic absorbents (97), composting (94), bioaugmentation (92), inorganic absorbents (90), Fenton oxidation (86), O3/UV (83), activated carbon (82), hydrolysis (82), and land cultivation (80). The other methods are not suitable for on farm use as they suffered from containment problems, high cost and variability of effectiveness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.006
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.356
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations60
Published2012
Admission routes2
Has abstractyes

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