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With the development of China's economy, more and more energy consumption has led to serious environmental problems. Faced with the enormous pressure of large amounts of carbon dioxide ( C O 2 ) emissions, China is now actively implementing the development strategy of low-carbon and emission reduction. Through the analysis of the influencing factors of C O 2 emissions in China, five key influencing factors are selected: urbanization level, gross domestic product (GDP) of secondary industry, thermal power generation, real GDP per capital and energy consumption per unit of GDP. This paper applies the Elman neural network optimized by the Firefly Algorithm (FA) to forecast the C O 2 emissions in China. And the results show that the performance of the FA–Elman is better than the Elman neural network and Back Propagation Neural Network (BPNN), verifying the effectiveness of the FA–Elman model for the C O 2 emissions prediction. Finally, we make some suggestions for low-carbon and emission reduction in China by analysing key influencing factors and forecasting C O 2 emissions using the FA–Elman model from 2017 to 2020. [ABSTRACT FROM AUTHOR]

In 2019, New York State passed aggressive new climate legislation to reduce greenhouse gas (GHG) emissions and laid out major changes for how emissions are reported. One change is the inclusion of emissions from outside of the boundaries of the State if they are associated with energy use within NY; the traditional inventory considered emissions only within the State. The new legislation also mandated that methane emissions be compared with carbon dioxide over a 20-year time frame rather than the 100-year time frame previously used by NY and still used by virtually all other governments globally. This reflected the desire of NY's policymakers for a tool that evaluates emissions from the standpoint of energy consumption and that more heavily weighs the role of methane as an agent of warming over the next few decades. This paper compares emissions based on the new approach for GHG reporting with the traditional inventory. The traditional inventory is driven almost entirely by carbon dioxide emissions. As of 2015, these carbon dioxide emissions had declined by 15% since 1990 due to an 88% decrease in coal consumption and a 27% decrease in consumption of petroleum products, although consumption of natural gas had increased by 57%. Methane emissions increased by almost 30% between 1990 and 2015, largely due to the increased consumption of natural gas. According to the new GHG reporting rules, methane contributed 28% of all fossil-fuel emissions in 1990 and 37% in 2015. Total GHG emissions remained virtually unchanged from 1990 to 2015. [ABSTRACT FROM AUTHOR]