Water pollution remediation in Kazakhstan: evaluating bacterial consortiums for organic pollutant decomposition

IF 2.1 4区 环境科学与生态学 Q2 ENGINEERING, CIVIL AQUA-Water Infrastructure Ecosystems and Society Pub Date : 2023-10-06 DOI:10.2166/aqua.2023.203
Zinigul Sarmurzina, Gulmira Bissenova, Aslan Temirkhanov, Zhanar Tekebayeva, Kunsulu Zakarya
{"title":"Water pollution remediation in Kazakhstan: evaluating bacterial consortiums for organic pollutant decomposition","authors":"Zinigul Sarmurzina, Gulmira Bissenova, Aslan Temirkhanov, Zhanar Tekebayeva, Kunsulu Zakarya","doi":"10.2166/aqua.2023.203","DOIUrl":null,"url":null,"abstract":"Abstract Wastewater treatment is one of the key problems that has to be solved by environmental biotechnology. Wastewater bioremediation is one of the most efficient and safest methods to replenish water resources. The aim of this study is to investigate the potential of using bacterial consortiums for reducing the organic load in wastewater, specifically focusing on water samples collected from three water bodies in central and northern Kazakhstan, which are known for their high levels of organic pollution. This study utilized bacterial strains from a microorganism collection to create consortiums. These consortiums were used to treat wastewater from polluted water bodies in Kazakhstan, focusing on parameters like COD, BOD5, ammonia, and phosphate. The methodology involved culturing strains, collecting water samples, and analyzing various parameters. Statistical analysis was performed to assess the results. The study found that two bacterial consortiums, 7BLB and 7BLPA, were the most effective in reducing COD, ammonia, and ammonia nitrogen in wastewater. The consortium 6BLP was highly effective at reducing phosphate levels, surpassing acceptable standards. Hydrogen levels met regulatory requirements in all cases. The study recommends further investigation of these consortiums’ impact on other water quality indicators and suggests conducting field experiments in natural water ponds.","PeriodicalId":34693,"journal":{"name":"AQUA-Water Infrastructure Ecosystems and Society","volume":"36 1","pages":"0"},"PeriodicalIF":2.1000,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AQUA-Water Infrastructure Ecosystems and Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/aqua.2023.203","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0

Abstract

Abstract Wastewater treatment is one of the key problems that has to be solved by environmental biotechnology. Wastewater bioremediation is one of the most efficient and safest methods to replenish water resources. The aim of this study is to investigate the potential of using bacterial consortiums for reducing the organic load in wastewater, specifically focusing on water samples collected from three water bodies in central and northern Kazakhstan, which are known for their high levels of organic pollution. This study utilized bacterial strains from a microorganism collection to create consortiums. These consortiums were used to treat wastewater from polluted water bodies in Kazakhstan, focusing on parameters like COD, BOD5, ammonia, and phosphate. The methodology involved culturing strains, collecting water samples, and analyzing various parameters. Statistical analysis was performed to assess the results. The study found that two bacterial consortiums, 7BLB and 7BLPA, were the most effective in reducing COD, ammonia, and ammonia nitrogen in wastewater. The consortium 6BLP was highly effective at reducing phosphate levels, surpassing acceptable standards. Hydrogen levels met regulatory requirements in all cases. The study recommends further investigation of these consortiums’ impact on other water quality indicators and suggests conducting field experiments in natural water ponds.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
哈萨克斯坦水污染修复:评价细菌群落对有机污染物分解的影响
废水处理是环境生物技术必须解决的关键问题之一。废水生物修复是最有效、最安全的水资源补充方法之一。本研究的目的是调查使用细菌联合体减少废水中有机负荷的潜力,特别关注从哈萨克斯坦中部和北部三个水体收集的水样,这些水体以其高水平的有机污染而闻名。本研究利用微生物收集的细菌菌株创建联合体。这些联合体用于处理哈萨克斯坦受污染水体的废水,重点关注COD、BOD5、氨和磷酸盐等参数。方法包括培养菌株、收集水样和分析各种参数。对结果进行统计分析。研究发现,7BLB和7BLPA两个菌群对废水中COD、氨和氨氮的还原效果最好。6BLP在降低磷酸盐水平方面非常有效,超过了可接受的标准。在所有情况下,氢含量都符合监管要求。该研究建议进一步调查这些财团对其他水质指标的影响,并建议在天然池塘中进行实地试验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
4.10
自引率
21.10%
发文量
0
审稿时长
20 weeks
期刊最新文献
Biogas production from water lilies, food waste, and sludge: substrate characterization and process performance How suitable is the gold-labelling method for the quantification of nanoplastics in natural water? Corrigendum: AQUA – Water Infrastructure, Ecosystems and Society 72 (7), 1115–1129: Application of system dynamics model for reservoir performance under future climatic scenarios in Gelevard Dam, Iran, Ali Babolhakami, Mohammad Ali Gholami Sefidkouhi and Alireza Emadi, https://dx.doi.org/10.2166/aqua.2023.193 Exploring the rise of AI-based smart water management systems Unraveling air–water two-phase flow patterns in water pipelines based on multiple signals and convolutional neural networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1