• Energy Research
• 7. Clean energy close

Abstract China's mining and quarrying industry is characterized by “high pollution, high energy consumption, and high emissions.” Improving this sector's green total factor productivity (TFP) is of great importance for furthering the sustainable development of China's economy. Using a global data envelopment analysis (DEA), this paper analyzes the green TFP of China's mining and quarrying industry for the period of 1991–2014 with regard to technology, scale, and management. The following results are found. First, during the sample period, the green TFP of China's mining and quarrying industry increased by 71.7%. Technological progress was the most important contributor, and the decline in scale efficiency and management efficiency were two inhibitors. Fortunately, in recent years, management efficiency has gradually improved and become a new impetus for green TFP growth. Second, the characteristics of the green TFPs in the sub-industries vary considerably. During the sample period, the green TFPs of the mining and processing of ferrous metal ores (MPFMO), the mining and processing of non-ferrous metal ores (MPNFMO), and the mining and processing of nonmetal ores (MPNO) grew rapidly and became the benchmarks, whereas those of the mining and washing of coal (MWC) and the extraction of petroleum and natural gas (EPNG) remained very low. Third, the returns to scale of the sub-industries also varied. EPNG, MPNFMO, MPNO were in the stage of increasing returns to scale or constant returns to scale during the entire period, whereas MWC and MPFMO have recently entered the stage of decreasing returns to scale.

Abstract Cities are the main carbon dioxide (CO 2 ) emitters in China, and it is important to explore both the characteristics and reduction potential of their CO 2 emissions. This paper calculates the industrial energy-related CO 2 emissions (IECEs) of 17 cities in China's Yangtze River Delta (YRD) region from 2005 to 2014 and analyses the driving factors of CO 2 emissions using the Logarithmic Mean Divisia Index (LMDI). In addition, this paper predicts the CO 2 reduction potential of this group of cities for the period from 2015 to 2020. The results show that (1) during the sample period, industrial CO 2 emissions in the studied cities increased by a factor of 1.61. Economic output is the greatest contributor, followed by population size. Energy intensity and energy structure are the two main emission mitigation factors; (2) the driving factors of CO 2 emissions in the group of cities exhibit distinct spatial characteristics, indicating that future analyses of cities in this area should have distinctly different foci; and (3) the forecasting results show that under moderate and aggressive scenarios, CO 2 emissions in the studied cities can be reduced by 281.59 Mt and 711.90 Mt, respectively, by 2020.

Abstract Fossil fuel is considered to be the major cause of CO2 emissions, and it flows across countries through the international energy trade. In this paper, we analyse the impact of energy trade patterns on CO2 emissions for a global sample from 2000 to 2014. We construct an international fossil fuel trade network based on emergy theory and calculate some corresponding structural parameters. Then, we systematically evaluate the impact of energy trade on CO2 emissions from the trade volume and trade relationships perspectives. We obtain the following results: (1) Trade strength mainly affects CO2 emissions through the scale effect, composition effect and technique effect. (2) Trade security and trade-centre status of one country will significantly affect CO2 emissions. (3) For high economic-level (HE) countries, concentrating the trade volume on several finite countries will destroy the environment; low economic-level (LE) countries that are proximal to the important countries of the energy market will experience an increase in pollution. This research also discusses some implications for policy makers.

Abstract Using the nonparametric causality-in-quantiles approach, we investigate the causal effects of oil price uncertainty on the returns and volatility of clean energy metal stocks under different market conditions in China. The results suggest that there is a causal relationship between oil price uncertainty and the returns and volatility of Chinese clean energy metal stocks. The effect differs slightly between returns and volatility. Specifically, the causal effect of oil price uncertainty on returns is mainly observed for lower quantiles, whereas the effect on volatility exists for all quantiles. In addition, the effects of change of market environment in China on the causal relationship are tested. The results show that change in market environment has significantly weakened the causal relationship between oil price uncertainty and clean energy metal stocks, suggesting that the structure of the Chinese clean energy metal stock market has undergone major changes.

AbstractIn recent years, increasing attention has been given to the potential supply risks of critical battery materials, such as cobalt, for electric mobility transitions. While battery technology and recycling advancement are two widely acknowledged strategies for addressing such supply risks, the extent to which they will relieve global and regional cobalt demand–supply imbalance remains poorly understood. Here, we address this gap by simulating historical (1998-2019) and future (2020-2050) global cobalt cycles covering both traditional and emerging end uses with regional resolution (China, the U.S., Japan, the EU, and the rest of the world). We show that cobalt-free batteries and recycling progress can indeed significantly alleviate long-term cobalt supply risks. However, the cobalt supply shortage appears inevitable in the short- to medium-term (during 2028-2033), even under the most technologically optimistic scenario. Our results reveal varying cobalt supply security levels by region and indicate the urgency of boosting primary cobalt supply to ensure global e-mobility ambitions.