Modeling Indirect Greenhouse Gas Emissions Sources from Urban Wastewater Treatment Plants: Integrating Machine Learning Models to Compensate for Sparse Parameters with Abundant Observations-Reference-Cited by-同舟云学术

Modeling Indirect Greenhouse Gas Emissions Sources from Urban Wastewater Treatment Plants: Integrating Machine Learning Models to Compensate for Sparse Parameters with Abundant Observations

Published:2023-11-17 Issue:48 Volume:57 Page:19860-19870
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Huang Yujun¹^ORCID,Xie Yifan¹^ORCID,Wu Yipeng¹,Meng Fanlin¹,He Chengyu¹,Zou Hao²,Wang Xiaoting³,Shui Ailun¹,Liu Shuming¹

Affiliation:

1. School of Environment, Tsinghua University, 1 Qinghuayuan, Beijing 100084, China

2. Department of Computer Science and Technology, Tsinghua University, 1 Qinghuayuan, Beijing 100084, China

3. Intelligent Cities Research, JD Technology, 11 Kechuang Street, Beijing 100176, China

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.3c06482

Reference58 articles.

1. Municipal wastewater treatment in China: Development history and future perspectives

2. An evaluation of the environmental benefit and energy footprint of China's stricter wastewater standards: Can benefit be increased?

3. Environmental and economic profile of six typologies of wastewater treatment plants

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