A novel approach to predict CO2 emission in the agriculture sector of Iran based on Inclusive Multiple Model

Shabani, Edris; Hayati, B; Pishbahar, Esmaeil; Ghorbani, Mohammad Ali; Ghahremanzadeh, Mohammad

doi:10.1016/j.jclepro.2020.123708

Cited by 77 publications

(24 citation statements)

References 40 publications

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“…Consistent with JRC, climate change 2020’s reports, and World Bank data, this study adopts two main regressor’s, notably: C-EM and C-LF are the CEM (metric tonnes per capita) although C-LF considered due to liquid consumption in individual developing and developed economies. Based on similar studies, regressors of CEM have chosen [5, 16, 36, 41–43] and individually analyzed. Due to data limitations, 25 years period consider in 22 developing and developed countries.…”

Section: Methodsmentioning

confidence: 99%

“…Fig.4 shows CEM (C-EM and C-LF), where China captured 23% of C-LF and 2% of C-EM and recorded as the highest carbon emitter, as well as Qatar, shows 28% C-EM in developing countries [15]. Germany and France trapped 9 and 6% in C-LF and, also Canada and Australia are 9 and 4% in C-EM in developed countries [5,[16][17][18]. The EKC development methodology developed presently besides of spotless afterward as well as ample serious resources besides colossal natural fetched and developing nations ought to take after the development way than that of EKC [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

“…Agricultural practice and modification can naturally reduce CO2 emissions in the environment by soil organic compounds of the land cultivation [4]. Developing and developed the country’s investment in sustainable development will help to reduce building climate resilience and GHG emissions [5–7]. Fig.1 indicated that CO2 emissions approach of developing and developed countries by total CO2 emission and liquid fuel consumption.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Agricultural production and CO2 emissions causes in the developing and developed countries: New insights from quantile regression and decomposition analysis

Khan

2020

Preprint

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Agriculture is the dominant economic activity of the economies. The developing and developed countries are responsible for the most greenhouse gasses emitted in the developing areas. Are there heterogeneous determinants of environmental degradation and CO2 emitters in developing and developed countries? and estimating the significance of agricultural production, renewable energy consumption, the industrial revolution, and economic growth. In this study, 22 countries’ environmental degradation analyze by two (per-capita and liquid) sources of CO2 emissions and using panel data from 1991 through 2016. This study adopts a panel regression (non-additive effects) and quantile regression techniques to explore the connection between agriculture and economic factors. And the extent of the CO2 emitter gap between developing and developed countries. The outcome of agriculture has a positive and significant influence on CO2 emission from liquid with a 36.75% increase in environmental degradation and a negative impact on CO2 emission in the total emissions by 19.12%. The agriculture-related activities negatively influence the environment, such as deforestation for feed cropping, burning of biomass, and deep soil cropping in the developing countries. Furthermore, the quantiles decomposition procedure in agriculture production is signifying heterogeneity of the determinants of environmental degradation, low and high CO2 emitters.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Agricultural production and CO2 emissions causes in the developing and developed countries: New insights from quantile regression and decomposition analysis

Khan

2020

Preprint

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“…The use of chemical fertilizers [ 14 ], agricultural irrigation [ 15 ], agricultural machinery [ 16 ], and agricultural diesel [ 17 ] are all major causes of carbon emissions in the process of crop production. Therefore, agricultural production activities are also an important source of greenhouse gases [ 18 ]. Many studies have shown that greenhouse gas emissions mainly caused by agricultural production should be reduced [ 19 ].…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of Planting Industry Structural Changes on Carbon Emissions in the Three Northeast Provinces of China

Guo

Xie

Pan

2021

IJERPH

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This paper focuses on the impact of changes in planting industry structure on carbon emissions. Based on the statistical data of the planting industry in three provinces in Northeast China from 1999 to 2018, the study calculated the carbon emissions, carbon absorptions and net carbon sinks of the planting industry by using crop parameter estimation and carbon emissions inventory estimation methods. In addition, the multiple linear regression model and panel data model were used to analyze and test the carbon emissions and net carbon sinks of the planting industry. The results show that: (1). The increase of the planting area of rice, corn, and peanuts in the three northeastern provinces of China will promote carbon emissions, while the increase of the planting area of wheat, sorghum, soybeans, and vegetables will reduce carbon emissions; (2). Fertilizer application, technological progress, and planting structure factors have a significant positive effect on net carbon sinks, among which the changes in the planting industry structure have the greatest impact on net carbon sinks. Based on the comprehensive analysis, it is suggested that, under the guidance of the government, resource endowment and location advantages should be given full play to, and the internal planting structure of crops should be reasonably adjusted so as to promote the development of low-carbon agriculture and accelerate the development process of agricultural modernization.

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Predicting Silicon Dioxide Grade

Ehteram¹,

Khozani²,

Soltani-Mohammadi³

et al. 2023

Estimating Ore Grade Using Evolutionary Machine Learning Models

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A novel approach to predict CO2 emission in the agriculture sector of Iran based on Inclusive Multiple Model

Cited by 77 publications

References 40 publications

Agricultural production and CO2 emissions causes in the developing and developed countries: New insights from quantile regression and decomposition analysis

Agricultural production and CO2 emissions causes in the developing and developed countries: New insights from quantile regression and decomposition analysis

The Impact of Planting Industry Structural Changes on Carbon Emissions in the Three Northeast Provinces of China

Predicting Silicon Dioxide Grade

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