Machine Learning and Hyperspectral Imaging-Aided Forecast for the Share of Biogenic and Fossil Carbon in Solid Waste-Reference-Cited by-同舟云学术

Machine Learning and Hyperspectral Imaging-Aided Forecast for the Share of Biogenic and Fossil Carbon in Solid Waste

Published:2023-02-28 Issue:10 Volume:11 Page:4020-4029
ISSN:2168-0485
Container-title:ACS Sustainable Chemistry & Engineering
language:en
Short-container-title:ACS Sustainable Chem. Eng.

Author:

Lan Dong-Ying¹,He Pin-Jing¹²^ORCID,Qi Ya-Ping¹,Wu Ting-Wei¹,Xian Hao-Yang¹,Wang Rui-Heng¹,Lü Fan¹²^ORCID,Zhang Hua¹²^ORCID,Long Ji-Sheng³

Affiliation:

1. Institute of Waste Treatment & Reclamation, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China

2. Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China

3. Shanghai SUS Environment Co., LTD, Shanghai 201703, China

Funder

Ministry of Science and Technology of the People's Republic of China

Shanghai's Municipal State-owned Assets Supervision and Administration Commission

Publisher

American Chemical Society (ACS)

Subject

Renewable Energy, Sustainability and the Environment,General Chemical Engineering,Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acssuschemeng.2c05104

Reference52 articles.

1. Toxicological Risk by Inhalation Exposure of Air Pollution Emitted from China’s Municipal Solid Waste Incineration

2. International Organization for Standardization (ISO). Solid recovered fuels – Methods for the determination of biomass content. ISO 21644:2021, https://www.iso.org/standard/71313.html (accessed February 2, 2023).

3. International Organization for Standardization (ISO). Stationary source emissions – Determination of the biogenic fraction in CO2in stacks gas using the balance method. ISO 18466:2016, https://www.iso.org/standard/62513.html (accessed February 2, 2023).

4. Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review

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