| Issue |
E3S Web Conf.
Volume 448, 2023
The 8th International Conference on Energy, Environment, Epidemiology and Information System (ICENIS 2023)
|
|
|---|---|---|
| Article Number | 03004 | |
| Number of page(s) | 10 | |
| Section | Environment Science | |
| DOI | https://doi.org/10.1051/e3sconf/202344803004 | |
| Published online | 17 November 2023 | |
A bibliometric overview of scientific research on phytoremediation of heavy metals and artificial neural network in past two decades
1 Student of Doctor of Environmental Science, School of Postgraduate Diponegoro University, Imam Barjo SH No. 5, Pleburan, Semarang, 50241, Indonesia
2 Environmental Engineering Department, Pelita Bangsa University, Jl Inspeksi Kalimalang No.9, Bekasi, 17530, Indonesia
3 Post Graduate Program of Environmental Science, Diponegoro University, Imam Barjo, SH No. 5, Pleburan, Semarang, 5024, Indonesia
4 Department of Biology, Faculty of Science and Mathematics, Diponegoro University, Semarang, 50241, Indonesia
5 Cluster of Paleolimnology (CPalim), Diponegoro University, Semarang, 50241, Indonesia
* Corresponding author: putrianggunsari@students.undip.ac.id
Numerous pollutants, including organic and toxic pollutants, are currently reaching the sea and land from various sources, including sewage sludge, municipal, industrial, agricultural, and landfill leachate. Heavy metal pollution is the single most pressing environmental issue because metals are so toxic to plants and animals. Additionally, they may be transported to the surrounding area through the production of leachate and migration from waste disposal sites, with the potential increasing risk to the land, the groundwater, and surface water. The remediation of heavy metals pollution by plants has been a hotspot in the research of heavy metals pollution in recent years and model development for heavy metal simulation has progressed rapidly over the past two decade. A bibliometric study of research data from 2003 to 2023 was conducted. Bibliographic data was retrieved from the Scopus database and analyzed using VOS viewer. The hot research topic keywords were “phytoremediation”, “heavy metals” and “artificial neural network”. The main insight from the analysis of the papers are discussed and practical implications for the field of study are provided. The structured information may help understand research trends and locate this topic gaps.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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