Evidence map›Paper›PMID 41309683›Full record

ArticleScientific reports2025

Sugarcane vinasse remediation through HA-nCaO within a computational sustainability and green SDG framework.

Mahmoud F Mubarak, Ahmed M Saleh

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Mahmoud F MubarakPetroleum Applications Department, Egyptian Petroleum Research Institute (EPRI), Ahmed El-Zomer, Nasr City, Cairo, Egypt.
Ahmed M SalehPharmaceutical Chemistry Department, Faculty of Pharmacy, Horus University, Horus, 34518, Egypt. asaleh@horus.edu.eg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The disposal of sugarcane vinasse, a highly acidic distillery effluent, presents a serious environmental management challenge. In this study, a novel composite adsorbent was developed by integrating green-synthesized nano-calcium oxide (nCaO) with humic acid (HA) via an aqueous co-precipitation method and ultrasonic-assisted stabilization. Characterization (XRD, FTIR, SEM, BET) confirmed the formation of a mesoporous hybrid with a surface area of 112.6 m² g⁻¹, average pore size of 6.3 nm, and enhanced surface basicity due to HA functionalization. Batch adsorption experiments demonstrated that an optimal dosage of 5 g L⁻¹ achieved 82.4% COD removal, 76.1% TOC reduction, and 89.5% color removal within 90 min, surpassing conventional treatments such as lime neutralization, Fenton oxidation, anaerobic digestion, and biochar systems under comparable conditions. The acidic vinasse (pH < 4) was neutralized to 7.6 ± 0.2 without the addition of external alkali. The incorporation of a chalcogel stage further promoted precipitation of suspended solids and volatile fatty acids, reducing residual organic load. Kinetic modeling indicated a pseudo-second-order fit (R² = 0.991), suggesting a chemisorption-dominated mechanism coupled with acid-base neutralization and partial precipitation. Reusability testing confirmed ≥ 68% efficiency retention after four cycles. Sustainability evaluation using the Need Quality Sustainability (NQS) index and Koel's Pyramid metrics indicated favorable environmental and operational performance, aligning with UN SDG 6 (Clean Water and Sanitation) and SDG 12 (Responsible Consumption and Production).

Indexed as

COD reductionHumic acidNano-calcium oxideNeed quality sustainability (NQS) index.Organic pollutant removalUN sustainable development goalsVinasse treatment

Identifiers

PMID41309683
PMCPMC12663415

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.