Machine Learning Modeling Based on Microbial Community for Prediction of Natural Attenuation in Groundwater-Reference-Cited by-同舟云学术

Machine Learning Modeling Based on Microbial Community for Prediction of Natural Attenuation in Groundwater

Published:2023-12-08 Issue:50 Volume:57 Page:21212-21223
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Zhang Xiaodong¹²,Long Tao¹,Deng Shaopo¹,Chen Qiang¹,Chen Sheng³,Luo Moye¹²,Yu Ran²^ORCID,Zhu Xin¹

Affiliation:

1. State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment of China, Nanjing 210042, Jiangsu, China

2. Department of Environmental Science and Engineering, School of Energy and Environment, Southeast University, Nanjing 210096, Jiangsu, China

3. Geo-engineering Investigation Institute of Jiangsu Province, Nanjing 210041, Jiangsu, China

Funder

National Key Research and Development Program of China

Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment

Foundation Program of Jiangsu Geological Engineering Survey Institute

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.3c05667

Reference65 articles.

1. Assessing of Natural Attenuation and Intrinsic Bioremediation Rates at a Petroleum-Hydrocarbon Spill Site: Laboratory and Field Studies

2. A Case Study of Natural Attenuation of Chlorinated Solvents Under Unstable Groundwater Conditions in Takahata, Japan

3. Diversity of bacteria and archaea in the groundwater contaminated by chlorinated solvents undergoing natural attenuation

4. Application of natural attenuation for the control of petroleum hydrocarbon plume: Mechanisms and effectiveness evaluation

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