Considering the undesirable output, this paper adopted the data envelopment analysis (DEA) model with the slack variable and super efficiency improvement, to measure industrial water utilization efficiency in the Yangtze River Economic Belt. The paper also creatively introduces urbanization level and urban primacy into driver factors' estimation by stochastic and fixed Tobit models, exploring how urbanization characteristics affected the water utilization in regional industrial production. The results showed that industrial water efficiency has maintained an upward trend during the whole period, while most central and western provinces have shown a U-shaped trend of decreasing first and then rising. However, the industrial water utilization efficiency of central regions is the lowest, and the eastern regions are the highest, catching up with western regions. Utilization efficiency shows an overall convergence during the research period from 2005 to 2017. Regarding the factors' estimation, both population urbanization and land urbanization negatively affected industrial water utilization efficiency, particularly blind expansion and disorderly development. The urban primacy meant the unbalance of urbanization, which would lead to urban diseases and pollution transfer, while the effects of urban primacy depended on the urbanization level. However, the utilization efficiency of industrial water did not become better automatically along with urbanization development; therefore, the scale and speed of urbanization should be scientifically formulated. The effects of the level of economic development, the advanced industrial structure, and the level of foreign investment are significantly negative. rate has increased from 14.08% in 1978 to 58.28% in 2017. The average rate of water quality qualification was only 73.2% in 2017, while the rate of water quality qualification lower than Class III was 16.1% [2]. The Class III water was mainly suitable for centralized drinking water, fishing and swimming, while the water of Class IV was mainly for industrial production and was not suitable for direct human contact. The built-up urban area was 22,182 square kilometers in 2017 and had been doubled from 12,122 square kilometers in 2005. Urbanization is always accompanied by industrialization and the transfer of rural populations, which also leads to the continuously optimization of the allocation of production factors. However, the industry cluster, the rapid growth of the urban population and the rapid expansion of construction land are also likely to cause irreversible water resources crises and water environment problems [3]. Moreover, water management and allocation, apart from the current competing demands, such as industrial water, urban water supply, agricultural irrigation, and ecosystems preservation, will be further affected, mainly by demographic and climatic changes drivers that increase the stress on water resources [4].

During the COVID-19 pandemic, the Chinese government implemented a “dynamic zero” epidemic prevention policy, which led to an increase in the likelihood of business shutdowns, increased uncertainty about people's income, and changes in people's psychological expectations, which in turn influenced their behavioral choices. This study aims to understand the impact of COVID-19 and other major public health emergencies on household financial asset allocation. To do so, we conducted an online survey of 712 people in China to measure household financial asset allocation behavior during three different time periods: pre-pandemic, mid-pandemic, and post-pandemic. At the same time, we analyzed the impact of sociodemographic characteristics on risk attitudes and the differences in household asset allocation decisions at different pre-pandemic time points among people with different risk attitudes. The results show that household financial asset allocation changed significantly before, during, and after the pandemic, and residents' precautionary savings increased. In addition, gender, education level, occupation, and annual income have significant effects on risk preferences. The pandemic leads to increased uncertainty in economic and social development, people's psychological expectations of economic development play an important role in household financial asset allocation.

To mitigate the adverse effects of climate change, the structure of global energy consumption has changed, and renewable energy consumption has increased rapidly, which may have a new impact on sustainable economic development. Against this backdrop, this paper investigates the direct and indirect effects of renewable energy consumption on economic growth, utilizing panel data from 90 countries along the Belt and Road between 2000 and 2019. Employing Granger causality tests and mediating effect models, we detect a bidirectional causal relationship between renewable energy consumption and economic growth, further affirming the feedback hypothesis. Our findings show that renewable energy consumption directly contributes to economic growth. Additionally, we found that renewable energy consumption has an indirect influence on economic growth via its impact on gross capital formation and trade. Drawing on these findings, we offer practical recommendations for the Belt and Road countries to implement appropriate countermeasures.

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