Optimal operations for groundwater denitrification of drinking water using heterotrophic biological denitrification process

反硝化 硝酸盐 地下水 环境科学 异养 化学 环境化学 氮气 环境工程 制浆造纸工业 细菌 生物 遗传学 工程类 有机化学 岩土工程
作者
Ching‐Hsia Hung,Kuo-Sheng Tsai,Y. Su,Chih-Wei Liang,Meizhong Su,S.-J. Horng
出处
期刊:Water Science & Technology: Water Supply [IWA Publishing]
卷期号:6 (2): 125-130
标识
DOI:10.2166/ws.2006.060
摘要

Due to the extensive application of artificial nitrogen-based fertilizers on land, groundwater from the central part of Taiwan faces problems of increasing concentrations of nitrate, which were measured to be well above 30 mg/L all year round. For meeting the 10 mg/L nitrate standard, optimal operations for a heterotrophic denitrification pilot plant designed for drinking water treatment was investigated. Ethanol and phosphate were added for bacteria growing on anthracite to convert nitrate to nitrogen gas. Results showed that presence of high dissolved oxygen (around 4 mg/L) in the source water did not have a significantly negative effect on nitrogen removal. When operated under a C/N ratio of 1.88, which was recommended in the literature, nitrate removal efficiency was measured to be around 70%, sometimes up to 90%. However, the reactor often underwent severe clogging problems. When operated under C/N ratio of 1.0, denitrification efficiency decreased significantly to 30%. Finally, when operated under C/N ratio of 1.5, the nitrate content of the influent was almost completely reduced at the first one-third part of the bioreactor with an overall removal efficiency of 89–91%. Another advantage for operating with a C/N ratio of 1.5 is that only one-third of the biosolids was produced compared to a C/N value of 1.88.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Lucas应助Accept采纳,获得10
1秒前
李爱国应助xr采纳,获得10
2秒前
3秒前
cdercder应助魏伯安采纳,获得10
4秒前
5秒前
嘻嘻完成签到,获得积分10
5秒前
巴巴bow发布了新的文献求助10
7秒前
Ava应助taozi采纳,获得10
7秒前
crystal119发布了新的文献求助30
8秒前
8秒前
冷酷的可乐完成签到,获得积分10
8秒前
杨怂怂发布了新的文献求助10
9秒前
hu完成签到 ,获得积分20
10秒前
10秒前
晴晴完成签到,获得积分10
11秒前
11秒前
12秒前
13秒前
打打应助姜汁采纳,获得10
13秒前
13秒前
无花果应助CQ采纳,获得10
13秒前
完美傲柔完成签到 ,获得积分10
14秒前
Linly发布了新的文献求助10
14秒前
典雅的静发布了新的文献求助10
17秒前
dddddd发布了新的文献求助10
17秒前
Accept完成签到,获得积分10
17秒前
魏伯安完成签到,获得积分10
17秒前
科研通AI5应助ziz采纳,获得10
17秒前
刻苦大叔发布了新的文献求助10
19秒前
英俊的铭应助陈帅帅采纳,获得10
20秒前
科研通AI5应助dddddd采纳,获得10
21秒前
crystal119完成签到,获得积分10
22秒前
23秒前
24秒前
XX完成签到,获得积分10
25秒前
勿念完成签到,获得积分20
26秒前
26秒前
Linly完成签到,获得积分10
26秒前
26秒前
李健应助lt1014采纳,获得10
28秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Mapping the Stars: Celebrity, Metonymy, and the Networked Politics of Identity 400
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
The Spatio-Temporal Stock Prediction Method Based on End-to-End Learning with Attention Mechanism 200
Stock price prediction in Chinese stock markets based on CNN-GRU-attention model 200
The phrasal lexicon 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3836233
求助须知:如何正确求助?哪些是违规求助? 3378583
关于积分的说明 10504968
捐赠科研通 3098204
什么是DOI,文献DOI怎么找? 1706318
邀请新用户注册赠送积分活动 820958
科研通“疑难数据库(出版商)”最低求助积分说明 772349