Integrating Bio-Electrochemical Sensors and Machine Learning to Predict the Efficacy of Biological Nutrient Removal Processes at Water Resource Recovery Facilities-Reference-Cited by-同舟云学术

Integrating Bio-Electrochemical Sensors and Machine Learning to Predict the Efficacy of Biological Nutrient Removal Processes at Water Resource Recovery Facilities

Published:2023-06-30 Issue:46 Volume:57 Page:18372-18381
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Emaminejad Seyed Aryan¹^ORCID,Sparks Jeff²,Cusick Roland D.¹^ORCID

Affiliation:

1. Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States

2. Hampton Roads Sanitation District Nansemond Treatment Plant, Virginia Beach, Virginia 23455, United States

Funder

Water Research Foundation

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.3c00352

Reference49 articles.

1. Nutrients, eutrophication and harmful algal blooms along the freshwater to marine continuum

2. Nutrient Pollution: A Persistent Threat to Waterways

3. Value-Added Products Derived from Waste Activated Sludge: A Biorefinery Perspective

4. Recent developments on biological nutrient removal processes for wastewater treatment

5. Performance and mechanism of modified biological nutrient removal process in treating low carbon-to-nitrogen ratio wastewater

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