The increasing marine pollution in China’s coastal areas has seriously affected the sustainable development of the economy and the living standards of residents. It is of great significance to explore the relationship between urbanization and marine pollution in coastal areas for the sustainable development of coastal cities. Based on the marine pollution data and nighttime light (NTL) data of 46 coastal cities from 2006 to 2015, the paper discusses the impact of urbanization on marine pollution by using the generalized spatial two-stage least square method (GS2SlS), and analyzes the role of technological innovation, financial development, and human capital in the impact of urbanization on marine pollution by using the three-stage least square method (3SLS). Results show that China’s coastal marine pollution has a strong spatial spillover effect, and a U-shaped relationship exists between urbanization and marine pollution. Regional heterogeneity analysis shows that an inverted U-shaped relationship was found between coastal urbanization and marine pollution in the northern marine economic circle, while the eastern and southern marine economic circles have a U-shaped correlation. The heterogeneity of the urbanization pattern indicates that the relationship between different urbanization patterns and marine pollution in coastal areas is generally in a positive correlation stage, but the depth of urbanization occupies a dominant position. Further mechanism tests show that urbanization can effectively reduce coastal marine pollution and improve the marine environment through the technological innovation effect, financial development effect, and human capital effect.

By developing an industrial structure change model, this paper investigates the role of the information technology in explaining the process of industrial structure optimization and upgrading in China from 2001 to 2019. Then, we put forward and discuss the substitution effect and the pervasiveness effect of information technology, and deduce the theoretical propositions from the model. We use the Malmquist index method to estimate the rate of information technology progress, and then choose the genetic algorithm to calibrate the parameters of the model. The research conclusions innovatively explain how the information technology can promote the industrial structure optimization and upgrading in China based on the substitution effect and the pervasiveness effect of information technology in detail. The results point out that when the contribution of information technology to total factor productivity of the tertiary industry is higher than that of the secondary industry, the pervasiveness effect of information technology can promote the upgrading of the industrial structure. Under the comprehensive effect of the pervasiveness effect and substitution effect of information technology, the industrial structure tends to be more optimized. The further heterogeneity analysis shows that the driving effect of information technology on the optimization and upgrading of industrial structure in regions with “servitization” characteristics is more significant. It highlights policy suggestions designed to adopt innovation-driven and technology development strategy, regional industrial structure transformation and economy development strategy.