Carbon emission factor decomposition and carbon peak prediction based on multi-objective decision and information fusion processing

Abstract

Global warming caused by excessive carbon dioxide emissions has seriously threatened the sustainable development of human society. How to reduce carbon dioxide emissions has become a common problem faced by the international community. This article aims to study the decomposition of carbon emission factors and the prediction of carbon peaks from the perspective of multi-objective decision-making and information fusion processing. The sample collection method and statistical analysis method are used to collect samples and simplify the algorithm. A collection experiment of carbon emission factors based on the industry of City A is designed. The experimental data collection takes into account the conversion of coal and oil products into standard coal and carbon dioxide the resulting emissions impact. The experimental results in this paper show that the simulated and real values of my country’s petroleum carbon emissions have both increased from 2000 to 2015, and the decline will be controlled in 2017. Both the simulated value and the real value of my country's coal carbon emissions have been on the rise from 2000 to 2015, and the decline will be controlled in 2017. The carbon emissions of coal are far greater than those of petroleum. The research on carbon emission factor decomposition and carbon peak prediction based on multi-objective decision-making and information fusion processing has been completed well. The research results can be used for industrial carbon emission factor decomposition and carbon peak prediction in other cities across the country.

Calculation and prediction of carbon emissions in construction industry based on LMDI

“…Calculations were conducted for each year according to equations ( 4) to (7), and the LMDI decomposition results of the carbon emission influencing factors in the construction industry in China from 2011 to 2020 are shown in Table 3. Based on the LMDI decomposition results in Table 3, the degree of influence for each year was calculated and listed in Table 4.…”

“…Estimation methods vary depending on the research object and include lifecycle analysis, emission factor analysis [3] , and input-output analysis [4] . Effective prediction of carbon dioxide emissions [5][6][7] and determining the peak carbon time [8] have become widely discussed topics among many researchers, aiming to predict future carbon dioxide emissions and develop corresponding emission reduction plans in advance. In-depth analysis of factors influencing regional carbon dioxide emissions is crucial for scientifically formulating carbon dioxide reduction plans.…”

A comparative study on LinkedIn and Sina Weibo users’ perceptions of the carbon-neutral city

“…It affects almost all natural processes and threatens the species and biodiversity (Demirhan, 2020). Driven by excessive carbon dioxide emissions, global warming has seriously threatened human society's sustainable development (Shi and Feng, 2021). Carbon dioxide remains in the atmosphere for hundreds of years, longer than typical air pollutants, typically hours to days (Dryden et al, 2018).…”

“…Reducing greenhouse gas emissions, especially carbon dioxide emissions from fossil fuel combustion, is an effective way to minimise climate change and avoid global temperature increases (Zhang et al, 2017;Moomaw et al, 2020). Reducing carbon dioxide emissions has become a common goal in the global community (Shi and Feng, 2021). Some scholars have explored the impact of climate change due to carbon emissions from fossil fuel combustion, cement production, land-use change emissions, and land and ocean carbon sinks (Redlin and Gries, 2021).…”