Search

It is widely acknowledged that greenhouse gases (GHG) like carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) play a key role in the development of global climate change. 17% of China's GHG came from the agricultural industry. For China's future development, it is essential to investigate low-carbon emission paths in planting fields, as one of the key components of agriculture. In this study, the IPCC method was used to estimate the total carbon emission from cultivation in Eastern China. The Tapio decoupling model was used to study the relationship between economic growth and carbon emission. An extended STIRPAT stimulus model was established to predict the carbon emission of the planting industry in East China with three development paths. The results show that carbon emission in East China has shown a fluctuating downward trend with a peak in 1999, which has strong decoupling characteristics with economic growth. Adjusting agricultural structure and raising the mechanization rate can remarkably reduce agricultural carbon emission. Compared to 2020, carbon emission in 2035 will decrease by 12.50%, 13.68%, and 14.32% with Baseline, Low-carbon, and Enhanced Low-carbon scenarios, respectively. Effective measures such as optimizing planting structure by adjusting rice area, promoting intensive mechanization, and improving fertilizer use efficiency can reduce carbon emission actively. [ABSTRACT FROM AUTHOR]

This research aims to find out effective approaches to improve the low carbon economy efficiency of China and to promote its low carbon economy development. This paper utilizes two kinds of data envelopment analysis models to estimate the economic efficiency and low carbon economy efficiency of China. It takes carbon dioxide emissions as an undesirable output and compares them to find out the different performances of economic growth in various regions in China in the context of low carbon economy development, and then explores the potential determinants of low carbon economy efficiency for different regions in different periods. The results show that low carbon economy efficiency is much lower than economy efficiency in most areas in China. Additionally, both low carbon economy efficiency and economy efficiency show a slow downward trend in most provinces in China from 2000 to 2011, which was followed by a slight increase in 2012. Moreover, low carbon economy efficiency and economy efficiency show obvious geographic characters. We propose some policy implications. Several policy implications are also provided for various areas to improve low carbon economy efficiency. [ABSTRACT FROM AUTHOR]

Agriculture has become an important source of greenhouse gas emissions. This paper calculates the agricultural GHGs emissions of 30 provinces in China from 1997 to 2016, and analyzes the emission intensity of GDP of carbon dioxide, methane and nitrous oxide by club convergence. After using the DEA CCR model to divide the club, the absolute β-convergence analysis method is used to verify the emission trends of various greenhouse gases. The results showed that the carbon dioxide emission intensity showed obvious absolute β convergence in all three clubs. Methane and nitrous oxide only have absolute β convergence in one of the clubs, respectively, and there is divergence in other clubs. Since the emission trends of the three greenhouse gases in the clubs are different, the formulation of reasonable reduction target allocation plan should be more detailed and targeted, and more stringent emission reduction targets should be set for provinces with high GHGs intensity of GDP in order to reduce it rapidly. [ABSTRACT FROM AUTHOR]