The drivers of GHG emissions: A novel approach to estimate emissions using nonparametric analysis

被引:17
作者
Magazzino, Cosimo [1 ]
Cerulli, Giovanni [2 ]
Haouas, Ilham [3 ]
Unuofin, John Onolame [4 ]
Samuel Asumadu, Sarkodie [5 ]
机构
[1] Roma Tre Univ, Dept Polit Sci, Rome, Italy
[2] Natl Res Council Italy, Rome, Italy
[3] Abu Dhabi Univ, Coll Business, Abu Dhabi, U Arab Emirates
[4] Univ Pretoria, Dept Chem Engn, Pretoria, South Africa
[5] Nord Univ Business Sch, Bode, Norway
基金
新加坡国家研究基金会;
关键词
Lasso regression; Climate change mitigation; GHG emissions; Land use; Forestry; GREENHOUSE-GAS EMISSIONS; CLIMATE-CHANGE; CO2; EMISSIONS; ENERGY-CONSUMPTION; ECONOMIC-GROWTH; URBANIZATION; PRODUCTIVITY; CONSEQUENCES; IMPACT;
D O I
10.1016/j.gr.2023.10.004
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The rising levels of global GHG emissions underpin climate change, hence, taking an appropriate inventory of the drivers and patterns of anthropogenic emissions remains crucial to mitigating global climate effects. However, there are conflicting views in the literature on the relationship between respective drivers and GHG emissions due to the lack of robust analysis that accommodates the interaction of all significant drivers. We use novel estimation techniques to decipher the 26-year inventory of GHG occurrences and simultaneous assessment of interactions in 50 countries stratified based on socioeconomic developments over the period 1990-2018. This study highlights different drivers of GHG emissions under broader categories such as population, economic development, forest density, and agricultural practices. Non-parametric estimations roughly confirm the magnitude of the influence of forests, agriculture, and land-use intensity on GHG emissions, ultimately tracking the most significant emission sinks. (c) 2023 The Author(s). Published by Elsevier B.V. on behalf of International Association for Gondwana Research. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/ 4.0/).
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页码:4 / 21
页数:18
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