Characterizing the role of hydraulic retention time on nitrate removal indices in denitrifying bioreactors by nonlinear models

Yuchuan Fan, Jie Zhuang, Michael Essington, Xi Zhang, Guanghui Hua, Jehangir Bhadha, Shaopan Xia, Xuanyu Lu, Jaehoon Lee
{"title":"Characterizing the role of hydraulic retention time on nitrate removal indices in denitrifying bioreactors by nonlinear models","authors":"Yuchuan Fan, Jie Zhuang, Michael Essington, Xi Zhang, Guanghui Hua, Jehangir Bhadha, Shaopan Xia, Xuanyu Lu, Jaehoon Lee","doi":"10.1016/j.eti.2023.103431","DOIUrl":null,"url":null,"abstract":"Denitrifying bioreactors (DNBRs) are a sustainable and cost-effective practice commonly used at the edge of fields to reduce nitrate from agricultural runoff. The hydraulic retention time (HRT) is a crucial variable that affects nitrate removal rate (NRR, g N m-3 d-1), nitrate removal efficiency (NRE, %), and nitrate concentration reduction per length (Nrd, mg N L-1 m-1). In this study, two nonlinear models, the developed Michaelis-Menten (MM) model and the Mitscherlich (MT) model, were developed to characterize the relationship between nitrate removal indices (NRR, NRE, and Nrd) and HRT. This study first utilizes nonlinear models to quantitatively understand the relationship between NRR, NRE, Nrd, and HRT. To verify the models, eight experiments were conducted under different conditions, including different scales (laboratory and field), media (woodchip, woodchip+biochar, woodchip+silage leachate, woodchip+biochar+silage leachate), and influent nitrate concentrations (6.8-70 mg N L-1). The results showed that the MT model outperformed the MM model and MT could accurately characterize the nitrate removal changes with HRT and provide the optimal HRT (HRTO). Overall, the model could be beneficial for designers and practitioners to optimize nitrate removal.","PeriodicalId":11899,"journal":{"name":"Environmental Technology and Innovation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Technology and Innovation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.eti.2023.103431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Denitrifying bioreactors (DNBRs) are a sustainable and cost-effective practice commonly used at the edge of fields to reduce nitrate from agricultural runoff. The hydraulic retention time (HRT) is a crucial variable that affects nitrate removal rate (NRR, g N m-3 d-1), nitrate removal efficiency (NRE, %), and nitrate concentration reduction per length (Nrd, mg N L-1 m-1). In this study, two nonlinear models, the developed Michaelis-Menten (MM) model and the Mitscherlich (MT) model, were developed to characterize the relationship between nitrate removal indices (NRR, NRE, and Nrd) and HRT. This study first utilizes nonlinear models to quantitatively understand the relationship between NRR, NRE, Nrd, and HRT. To verify the models, eight experiments were conducted under different conditions, including different scales (laboratory and field), media (woodchip, woodchip+biochar, woodchip+silage leachate, woodchip+biochar+silage leachate), and influent nitrate concentrations (6.8-70 mg N L-1). The results showed that the MT model outperformed the MM model and MT could accurately characterize the nitrate removal changes with HRT and provide the optimal HRT (HRTO). Overall, the model could be beneficial for designers and practitioners to optimize nitrate removal.

Abstract Image

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
用非线性模型表征水力停留时间对反硝化生物反应器中硝酸盐去除指标的影响
反硝化生物反应器(dnbr)是一种可持续的、具有成本效益的做法,通常用于农田边缘,以减少农业径流中的硝酸盐。水力停留时间(HRT)是影响硝酸盐去除率(NRR, g N m-3 d-1)、硝酸盐去除率(NRE, %)和每长度硝酸盐还原浓度(Nrd, mg N L-1 m-1)的关键变量。本文建立了两种非线性模型,分别为Michaelis-Menten (MM)模型和Mitscherlich (MT)模型,用于表征硝酸盐去除指标(NRR、NRE和Nrd)与HRT之间的关系。本研究首先利用非线性模型定量理解了NRR、NRE、Nrd和HRT之间的关系。为了验证模型,在不同规模(实验室和现场)、不同介质(木片、木片+生物炭、木片+青贮渗滤液、木片+生物炭+青贮渗滤液)和进水硝酸盐浓度(6.8 ~ 70 mg N L-1)下进行了8项实验。结果表明,MT模型优于MM模型,MT能准确表征HRT对硝酸盐去除的影响,并提供最佳HRT (HRTO)。综上所述,该模型可为设计师和实践者优化硝酸盐去除提供参考。
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
自引率
0.00%
发文量
0
期刊最新文献
Emission characteristics of typical gas pollutants during oxygen-enriched waste incineration process Assessing the ecological impact and microbial restoration of quinclorac-contaminated paddy fields through high-throughput sequencing technology Enhancing biofilm growth in an integrated fixed-film activated sludge process through modification of polypropylene carriers Curcumin-loaded hydroxyapatite nanoparticles for enriched removal of organic pollutants and inhibition of dual-species biofilm formation Influences of lithium on soil microbial biomass, bacterial community structure, diversity, and function potential
×
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