Research on the potential for China to achieve carbon neutrality: A hybrid prediction model integrated with elman neural network and sparrow search algorithm

Yang, Meng; Liu, Yi‐Sheng

doi:10.1016/j.jenvman.2022.117081

Cited by 38 publications

(8 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Chen et al [ 57 ] investigated a BP neural network learning algorithm-based carbon emission management and prediction method for electric cars to achieve pre-mass production prediction and in-use vehicle carbon emission analysis, which serves as a crucial reference for the precise management of vehicle carbon emissions. Yang and Liu [ 58 ] suggested a hybrid projection to examine China’s potential to become carbon neutral in the years 2020–2060, this projection combines the Elman Neural Network (ENN) and Sparrow Search Algorithm (SSA). With the development and application of AI, future studies in the domain of carbon neutrality should focus on the intricate integration of AI with carbon neutrality, which is a significant and popular research area.…”

Section: Finding and Discussionmentioning

confidence: 99%

A bibliometric analysis of carbon neutrality: Research hotspots and future directions

Gou

Zhang

et al. 2023

Heliyon

View full text Add to dashboard Cite

Section: Finding and Discussionmentioning

confidence: 99%

A bibliometric analysis of carbon neutrality: Research hotspots and future directions

Gou

Zhang

et al. 2023

Heliyon

View full text Add to dashboard Cite

“…Yang et al [27] even suggest that China's path to carbon neutrality is a game changer for counteracting climate change, since this country alone can reduce global anthropogenic warming up to 0.3 • C. At the same time, because of the improving air quality, 1.8 million people could be saved from death due to high levels of pollutants in the air. The possible ways to achieve carbon neutrality are presented in the paper written by Meng et al [28], where renewables are reported as the key factor.…”

Section: Literature Review On the Covid-19 Pandemic And Its Influence...mentioning

confidence: 99%

Challenges and Opportunities for the Energy Sector in the Face of Threats Such as Climate Change and the COVID-19 Pandemic—An International Perspective

Pawłowski

Rydzewski

2023

Energies

View full text Add to dashboard Cite

New threats such the COVID-19 pandemic have brought forth not only threats to human health but also changes to many other sectors of the global economy. Despite strict lockdowns, the highest annual number of global renewable energy installations were completed in 2020, including onshore wind power stations and PV power stations. The development of these two types of renewables is increasingly rapidly. Transformations in terms of renewable energy require both governmental and public support; thus, it is important to note that the pandemic did not weaken the public commitment to fight climate change. This article aims to evaluate the actual level of support for renewable energy sources in different countries of the world and how the pandemic has affected public opinion regarding this issue. Our analysis suggests that, regardless of the pandemic, public support for renewable energy remains strong in different regions of the world.

show abstract

“…Countries and regions have adopted corresponding emission reduction plans and formulated main emission reduction goals to reduce greenhouse gas emissions and avoid extreme disasters [1][2][3]. Currently, carbon peaking and carbon neutrality have become hot research topics among scholars worldwide [4,5]. Agriculture is the second largest source of greenhouse gas emissions [6], with livestock being the main source of agricultural greenhouse Sustainability 2023, 15, 11994 2 of 14 gas emissions, mainly of CH 4 and N 2 O [7].…”

Section: Introductionmentioning

confidence: 99%

Simulation and Prediction of Greenhouse Gas Emissions from Beef Cattle

et al. 2023

View full text Add to dashboard Cite

Greenhouse gas emission is a key issue in the sustainable development of agriculture. To effectively predict the greenhouse gas emissions of beef cattle, a model is proposed based on system dynamics and greenhouse gas emission calculation methods, and a scenario is set as a ‘Straw to Beef’ project in Jilin Province. The model was built on a baseline emission scenario (feed precision: 60%, breeding environment: dry fattening farm, corn straw utilization: burning straw), with single- and comprehensive emission reduction scenarios considered, predicting trends and reduction potentials in greenhouse gas emissions from cattle breeding and straw burning in Jilin Province from 2013 to 2028, measured in CO2-eq (CO2 equivalent). The model also explored the impact of 11 controllable variables on greenhouse gas emissions. Results showed that (1) From 2013 to 2022, greenhouse gas emissions from straw burning and cattle breeding in Jilin Province increased significantly and had an annual growth rate of 6.51% in 2020. (2) Single emission reduction scenarios showed an increasing trend in greenhouse gas emissions, while comprehensive emission reduction scenarios showed a decreasing trend. Among them, the S2.2.1 scenario (feed precision: 80%, breeding environment: livestock barn manure pit, corn straw utilization: burning straw) had the strongest emission reduction ability in the single reduction scenario, the S3.2.2 scenario (feed precision: 80%, breeding environment: livestock barn manure pit, corn straw utilization: Feed-processing straw) had the strongest emission reduction ability in the comprehensive reduction scenario, reducing emissions by 5.10% and 69.24%, respectively, compared to the baseline scenario. This suggests that the comprehensive emission reduction scenarios which utilized straw resources reasonably can greatly reduce agricultural greenhouse gas emissions. (3) The optimal emission reduction scenario indicated that the higher the proportion of digestible energy in beef cattle’s total energy intake, the more perfect the fecal treatment process, and the higher the utilization rate of straw feed, the lower the greenhouse gas emissions. Therefore, to effectively reduce greenhouse gas emissions from cattle breeding and straw burning in Jilin Province, it is important to implement comprehensive emission reduction scenarios prioritizing the efficient utilization of straw resources and improving beef cattle management practices.

show abstract

Research on the potential for China to achieve carbon neutrality: A hybrid prediction model integrated with elman neural network and sparrow search algorithm

Cited by 38 publications

References 51 publications

A bibliometric analysis of carbon neutrality: Research hotspots and future directions

A bibliometric analysis of carbon neutrality: Research hotspots and future directions

Challenges and Opportunities for the Energy Sector in the Face of Threats Such as Climate Change and the COVID-19 Pandemic—An International Perspective

Simulation and Prediction of Greenhouse Gas Emissions from Beef Cattle

Contact Info

Product

Resources

About