| Summary: | After several years of steady decline, carbon emissions began to rise in 2017. If this trend is not curbed as soon as possible, the efforts made for carbon emission reduction will be wasted. Although the effect that the energy consumption structure brought to carbon emissions has been studied in pieces of literature, the limit is that they all take the ratio of coal consumption (CS) as the index of energy consumption structure. With the optimization of energy consumption structure, the index they use is no longer convincing. Shannon–Wiener diversity index (SWI) is an index used to investigate the diversity within the local flora of a plant community, and in this paper, it is innovatively used to reflect the structure of the energy consumption. To test the superiority of the new index in the study of carbon emissions, the Autoregressive Distribution Lag model (ARDL) was used, and we find out the effect of Gross Domestic Product (GDP), Urbanization Rate (UR), Trade Structure (TS) and energy consumption structure on carbon emissions in China through the data from 1985 to 2016. The results show:(1) the R2of the carbon emission model constructed by SWI is as high as 0.9938, which means the model is stable;(2)During the research period, we found the relationship between the environmental quality and the squared term of GDP per capita is a U-shaped curve, so the Environment Kuznets Curve (EKC) hypothesis is not applicable in China;(3)The results also show that the inflexion point of the U-shaped curve is delayed;(4) Urban development and the promotion of trade structure will bring the increase of carbon emissions, while the optimization of energy consumption structure will slow it down. This paper will provide new ideas for studying the impact of energy consumption structure on carbon emissions, and put forward policy suggestions.
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