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The mechanism between financial agglomeration and environmental pollution is an important concern for both academia and policymaking. The main objective of this paper is to study the nonlinear impacts of financial agglomeration on environmental pollution. A theoretical framework was first constructed based on the scale effect, structure effect, and technology innovation effect of financial agglomeration and a Copeland-Taylor endogenous growth model. Using the panel data of 281 Chinese prefectural-level cities from 2003 to 2019, a panel threshold regression model was introduced to estimate the nonlinear association between financial agglomeration and environmental pollution. Industrial smoke (dust) emissions and industrial wastewater discharge were adopted to quantify current environmental pollution in China. The results show that financial agglomeration had a significant effect on improving the environment characterized by gradient thresholds; also notable is that 68.64% of the cities crossed the threshold value, entering the decelerating phase of financial agglomeration inhibiting environmental pollution. Both upgrading industrial structure and enhancing marketization could reduce environmental pollution, whereas increasing human capital, environmental regulation, and energy consumption had a deteriorating effect. The three channels for financial agglomeration to reduce environmental pollution were revealed to be financial scale, financial structure, and financial technology innovation. Our findings provide strong evidence for policymaking in sustainable development. [Display omitted] • Financial agglomeration (FA) is a crucial way to improve environment pollution (EP). • We built the theoretical framework of FA and EP based on the Copeland-Taylor model. • We tested the nonlinear impacts of FA on EP using the panel threshold model. • We revealed the transmission mechanism between FA and EP. [ABSTRACT FROM AUTHOR]

In recent days, many emerging nations facing severe environmental pollution problems. In order to overcome the environmental problems, many new methods and strategies have been built and some advance sources of energies were also utilized in order to overcome such issues but by using such sources, many challenges were faced. In order to find best possible solutions of such issues, this paper was aimed to minimize the gap of research by examining the effect on economic development of energy expenditure and environmental pollution and by means of finding the casual relationship between them because it has been observed that with development of economy, environmental issues always increase. Effects of both traditional and modern energies was analyzed in this research. Several explanatory variables will be used: Renewable energy consumption, CO 2 emission, economic GDP. Environmental pollution will be taken as the mediating factor that influence this association between energy utilization as well as economic development. Present study was based on the economy of China. ARDL regression model was applied in this research to increase the time series econometrics when non-stationary value demonstrated the co-integration and it is also effective for both stationary and non-stationary time series. At the end, some advanced methods of production were discussed that can be used in this era of industry 4.0. By proper implementation of such processes, many economic and environmental benefits can be achieved. • Effects of both traditional and modern energies was analyzed in this research. • Some advanced methods of production were discussed that can be used in this era of industry 4.0. • By proper implementation of such processes, many economic and environmental benefits can be achieved. [ABSTRACT FROM AUTHOR]