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Green finance and environmental regulation can reduce CO2 emissions and promote the sustainability of economic development. Based on panel data of 126 resource-based prefecture-level cities in China from 2005 to 2017, the current study used a dynamic panel data model to empirically determine the CO2 emission reduction effects of different green finance instruments under different environmental regulatory intensities. The results showed that green finance tools had significant negative effects on the intensity of CO2 emissions, and green finance can adapt to environmental regulations of different intensities, which cooperated to promote carbon emission reduction. Moreover, in comparison, the debt-based green finance instrument had a stronger effect than the equity-based green finance instrument, and they did not show a coupling relationship. An administrative adjustment in green finance and environmental regulation is required to reduce environmental emissions and to improve sustainable development.

This study aims to determine the impact of financial development on green ecology to promote cleaner production. Particularly, it estimates the evolution of characteristics of the green-ecology of 37 cities from the Yangtze River Delta and determines the impact of financial development on green-ecology using the projection pursuit model, Moran's Index, and regression model. Results found that the green-ecology index showed an upward trend and the index in the East was higher than the West. The green ecology and its composition indexes were found with significant spatial positive agglomeration characteristics. The Eastern region was mainly distributed as high to high agglomeration while the Western region was distributed as low to low agglomeration. Regarding composition indexes of green ecology, financial development has promoted a positive effect on the green-growth and resource-environment indexes. The study results stress that the enterprises should strengthen the technological innovation for the improvement of resource use efficiency and reduction of pollution.

Agricultural modernization is the most important task of modernization construction. This study used the multi-index comprehensive measurement method to estimate the agricultural modernization level of Shandong Province from 2010 to 2019. Regional differences were analyzed using the ESDA method, and the main obstacles were diagnosed using the obstacle degree model. This paper constructs an index system, including an agricultural production system, a management system, an industrial system, output benefits, rural social development, and agricultural sustainable development. The results showed that the level of agricultural modernization in Shandong Province was divided into three stages: decelerating ascent (2010–2013), accelerating ascent (2014–2016), and high-level fluctuation (2017–2019). Results found that the scores of the agricultural production system, rural development level, and agricultural industrial system peaked in 2017.The regional difference in the agricultural modernization level of Shandong Province is high in the north and low in the south of China. The main obstacles in the rising stage of agricultural modernization in Shandong Province are the proportion of the added value of agriculture, forestry, fishery, and animal husbandry service; the amount of fertilizer and pesticide used per land area; the total power of units farmland machinery; the high-level fluctuation order are shelterbelt construction rate; the proportion of livestock production value; rural per capita electricity consumption; and rural employment rate. The average arable land per household and the employment rate of the rural population are the key obstacles to high levels of agricultural modernization. Therefore, optimizing industrial structure, improving the input of productive factors, cultivating a high-quality rural labor force, improving the efficiency of agricultural funds use, and awareness of the sustainable development of agriculture are all suggested.