A machine learning approach for country-level deployment of greenhouse gas removal technologies-Reference-Cited by-同舟云学术

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A machine learning approach for country-level deployment of greenhouse gas removal technologies

Published:2023-12 Issue: Volume:130 Page:103995
ISSN:1750-5836
Container-title:International Journal of Greenhouse Gas Control
language:en
Short-container-title:International Journal of Greenhouse Gas Control

Author:

Asibor Jude O.^ORCID,Clough Peter T.^ORCID,Nabavi Seyed Ali,Manovic Vasilije

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Industrial and Manufacturing Engineering,General Energy,Pollution

Reference78 articles.

1. Agroforestry: a sustainable environmental practice for carbon sequestration under the climate change scenarios—A review;Abbas;Environ. Sci. Pollut. Res.,2017

2. Machine learning to predict biochar and bio-oil yields from co-pyrolysis of biomass and plastics;Alabdrabalnabi;Fuel,2022

3. The potential for implementation of Negative Emission Technologies in Scotland;Alcalde;Int. J. Greenh. Gas Control,2018

4. A review of developments in carbon dioxide storage;Aminu;Appl. Energy,2017

5. Combating climate change through enhanced weathering of agricultural soils;Andrews;Elements,2019

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1. Road transportation emission prediction and policy formulation: Machine learning model analysis;Transportation Research Part D: Transport and Environment;2024-10

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