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Pollution Indices and Ecological Evaluation for Wastewater in Industrial Areas

2022· article· en· W4283771545 on OpenAlexaboutno aff
Hanan Abdelgawad, Mahar Helal, Sahar Kamal, Maha Abd El-Monhem

Bibliographic record

VenueEgyptian Journal of Chemistry · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
FundersNational Wildlife Research CenterHelwan University
KeywordsPollutionEnvironmental scienceWastewaterIndustrial wastewater treatmentIndustrial pollutionEcologyEnvironmental engineeringBiology

Abstract

fetched live from OpenAlex

Wastewaters from Tenth Ramadan and El-Obour cities and El-Khadrwia drain verify their environmental effects. The study focused to study Wastewater Quality Index (WQI) and their suitability during 2018-2019. The data showed almost of chemical parameters were unacceptable for water irrigation suitability that used to derive criteria and guidelines of hazards ions interactions, FAO for irrigation and Canadian Water Quality Guidelines for aquatic organism. The results indicate that there is no effect of metals in the case of wastewater use for agricultural purposes, whereas for aquatic life, all measured metals except Fe+3, Mn+2, Pb+2, Zn+2 and Cu+2 show different degrees of contamination in wastewaters of investigated areas.The obtained results indicated organic pollution values of examined variables were higher than the recommended standards and they were major waste impacts. They supported by Organic Pollution Index (OPI) evaluation that ranged from 15 to 822 while the maximum Comprehensive Pollution Index (CPI) and OPI values were (16.1 and 822) for cheese whey wastewater at El-Obour City affects aquatic environmental live in this area and producing healthy harms. The study concluded primary treatment removed 50-60% of pollution. So, study recommended use nanoparticles with low cost to acquire positive ecological impacts and increase national goals.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.048
GPT teacher head0.288
Teacher spread0.240 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

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