Search

As a significant energy consumer, China is under tremendous pressure from the international community to address climate change issues by reducing carbon emissions, thus, the use of clean energy is imperative. Wind power is an essential source of renewable energy, and improving the efficiency of wind power generation will contribute substantially to China’s ability to achieve its energy-saving and emission reduction goals. This paper measured the wind power efficiency of 30 provinces in China from 2012 to 2017 using the data envelopment analysis (DEA) method. Moran’s I index and the spatial Durbin model were applied to analyse the spatial distribution of the wind power efficiency and the spatial effects of influencing factors. The results show obvious differences in the spatial distribution of wind power efficiency in China, specifically, the wind power efficiency in the eastern and western regions is higher than that in the central areas. Moreover, wind power efficiency has a significant positive spatial correlation between regions: the eastern and western regions show certain high-high clustering characteristics, and the central area shows certain low-low clustering characteristics. Among the influencing factors, the fixed asset investment and carbon emission intensity of the wind power property have a negative impact on the efficiency of regional wind power production, while the urbanization process and carbon emission intensity have significant spatial spillover effects. The optimization of the economic structure, technological innovation and the construction of energy infrastructure are expected to improve the regional wind power efficiency. The results present a new approach for accurately identifying the spatial characteristics of wind power efficiency and the spatial effects of the influencing factors, thus providing a reference for policymakers.

Based on the monthly observation data of major surface meteorological observatories in Northwest China from 1960 to 2019, this paper uses the temperature and humidity index (THI), wind efficiency index (WEI), and clothing index (ICL) to construct a comprehensive climate comfort index evaluation model. This model was used to quantitatively evaluate the change characteristics of climate comfort in Northwest China against the background of climate warming. The results show that the overall climate comfort index in Northwest China is on the rise. In terms of space, an increase in the climate comfort index means an increase in the comfort zone, with the largest increase in the southeastern part of Gansu Province and the southern part of Shaanxi Province. The trend of change is that the increase in the north is greater than that in the south, and the higher the latitude, the greater the change. The space range of the comfort zone and the sub-comfort zone is generally expanding, and the climate is gradually becoming more comfortable. In terms of time, an increase in the climate comfort index means an increase in the climate comfort period, and the annual comfort index shows an increasing trend. The comfort period is mostly distributed in summer, with the most suitable cities in May and September, followed by June.