In the context of new industrialization, the energy problem being experienced by the manufacturing industry has aroused social concerns. This paper focuses on the energy use of 27 subindustries in China’s manufacturing industry and it develops an energy consumption index for 1994–2015. Subsequently, the method of grey relational analysis is used, with the full period divided according to years in which change points occur. The empirical analysis indicates that the energy consumption indexes generally exhibit a declining trend. Using the grey model (GM (1,1)) to forecast the index indicates a continued downward trend up to 2025 for energy-intensive industries, which is a more optimistic scenario than the trend forecast for the whole manufacturing sector. Thus, these energy-intensive industries do not drag down the performance of the whole manufacturing industry in regard to energy intensity. In future, more attention should be paid to energy-saving efforts by nontraditional high-energy-consuming industries. Although the results show that energy efficiency is improving in China, total annual consumption is rising rapidly. Therefore, the industry needs to continue to strengthen independent innovation and improve the efficiency of new energy use. The Chinese government should formulate feasible long-term plans to encourage enterprises to save energy.
Air pollution emissions can exceed the environmental self-purification capacity and trigger hazardous meteorological events, which have non negligible impacts on all aspects of society. The aim of this paper is to study the relationship between China's manufacturing industry benefits and air quality, taking into account the role of government policies in the era of big data, and to study the change points in the time series relationship between industry benefits and air quality. First, we apply and analyze big data and estimate values based on the maximum deviation method. Then, gray relational analysis is used to identify change points, which occur in 2005 and 2010 for both industry benefits and air quality. The total study period is divided into three subperiods:
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