Evaluating Long-Term Treatment Performance and Cost of Nutrient Removal at Water Resource Recovery Facilities under Stochastic Influent Characteristics Using Artificial Neural Networks as Surrogates for Plantwide Modeling-Reference-Cited by-同舟云学术

Evaluating Long-Term Treatment Performance and Cost of Nutrient Removal at Water Resource Recovery Facilities under Stochastic Influent Characteristics Using Artificial Neural Networks as Surrogates for Plantwide Modeling

Published:2021-09-09 Issue:11 Volume:1 Page:1517-1529
ISSN:2690-0645
Container-title:ACS ES&T Engineering
language:en
Short-container-title:ACS EST Eng.

Author:

Li Shaobin¹^ORCID,Emaminejad Seyed Aryan¹,Aguiar Samuel¹,Furneaux Aliza²,Cai Ximing¹,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. WateReuse Association, Alexandria, Virginia 22314, United States

Funder

Division of Earth Sciences

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsestengg.1c00179

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2. Harmful algal blooms and eutrophication along the mexican coast of the Gulf of Mexico large marine ecosystem

3. NOAA. Happening Now: Dead Zone in the Gulf 2020 https://oceantoday.noaa.gov/happenowdeadzone/ (accessed July 25, 2021).

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