Evidence map›Paper›PMID 39150422›Full record

ArticleWater science and technology : a journal of the International Association on Water Pollution Research2024

Pollutant removal efficiency of bare and planted rain gardens with diverse planting mixtures.

Sandeep Kumar, Krishna Kumar Singh

Abstract read
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In one paragraph

Article in Water science and technology : a journal of the International Association on Water Pollution Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Sandeep KumarCivil Engineering Department, NIT Kurukshetra, Kurukshetra, Haryana, India E-mail: balwan.verma74@gmail.com.ORCID https://orcid.org/0000-0002-4820-1624
Krishna Kumar SinghCivil Engineering Department, NIT Kurukshetra, Kurukshetra, Haryana, India.

Funding

ministry of education (MOE), GOI 2K19/NITK/PHD/61900082
6 · The paper itself

Abstract

This study examines the influence of planting mixture variations on the quality of the percolated water of the rain garden with and without plants. Six planting mixtures in experimental rain gardens have been used. It has been noted that pollutant removal efficiency of RG can exhibit variations based on specific parameters. Notably, RG6, utilizing a planting mix of 75% topsoil and 25% compost, demonstrated the highest performance. These results draw attention to the critical role of the specific planting mixtures in influencing the performance of vital parameters related to pollutant removal. The observation shows that RG5 exhibits exceptional removal efficiency in pH, Total Suspended Solids (TSS), Biological Oxygen Demand (BOD), and Chemical Oxygen Demand (COD), and RG6 performs best in electrical conductivity (EC), Total Dissolved Solids (TDS), Total Nitrogen (TN), and Total Phosphorus (TP) removal. In particular, when analyzing pollutant removal on a surface with Madagascar periwinkle plants, RG6 emerges as the most effective, achieving an impressive efficiency of approximately 49%. For the bare surface, pollutant removal efficiency is 40%. The study outcome will be useful in deciding the composition of the planting mixture, which will keep the rain garden to improve quality and quantitatively hydrological performance, lowering urban flooding magnitude.

Indexed as

RainBiological Oxygen Demand AnalysisNitrogenPhosphorusSoilWater Pollutants, ChemicalNitrogenPhosphorusSoilWater Pollutants, Chemicalinfiltration rateMadagascar Periwinkle plantplanting mixturepollutant removal efficiencyrain gardenwastewater quality index

Identifiers

PMID39150422

What OpenQuestion holds

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Registered trials

None linked

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.