Li J.L., 2019. Evaluating green city developments in coastal regions of East China. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 78–82. Coconut Creek (Florida), ISSN 0749-0208.In the face of economic globalization and strained resources, the development of green economies is inevitable. The construction of green cities is an important aspect of green economic development and its connotations. Accelerating the construction of green cities is a growing trend. The construction of a green city is a complex integrated project and requires a comprehensive evaluation index system and a scientific evaluation model. In this study that fully implement the plan for promoting political, economic, social, cultural, and ecological progress. The analytic process and evaluation methods, including the frequency statistics method, theoretical analysis, and expert consultation, were used to construct the evaluation system and the green city multi-level fuzzy comprehensive evaluation model. Taking the coastal city of Shanghai in East China as an example, this paper evaluates the degree of low-carbon green development in Shanghai, carries out empirical research, and promotes the low-carbon green development of coastal cities.

The problem of agricultural surface pollution is becoming increasingly prominent, directly impeding the realization of the goals of “industrial prosperity and ecological livability” in the strategy of rural revitalization. To thoroughly analyze the impact of Digital Rural Construction on agricultural surface pollution and to effectively strengthen the prevention and control measures, the Moran index was used to assess the influence of agricultural surface pollution in 31 provinces and cities across China. The Moran index was employed to conduct global and local spatial autocorrelation analysis of agricultural surface source pollution, and a panel quantile autoregressive model was constructed to explore the effects of Digital Rural Construction on such pollution. The results show the following: (1) agricultural surface pollution in each province and city exhibits spatial spillover effects that are growing stronger; (2) the spatial impact of agricultural surface pollution on neighboring provinces and cities follows an inverted U-shaped pattern at different levels of pollution; (3) the relationship between the degree of agricultural surface pollution and the impact of Digital Rural Construction on it also follows an inverted U-shaped pattern, wherein improvements are observed as the pollution levels deepen. When the level of agricultural surface pollution is located in the quartile point 0.1, the improvement effect of Digital Rural Construction on agricultural surface pollution is small (0.0484), as the quartile point increases, the improvement effect is gradually increased, and it reaches the maximum value at the quartile point 0.5 (0.523), and the coefficient of agricultural surface pollution decreases to the minimum value at the quartile point 0.9 (0.423).

Hu, H.; Li, J.; Jin, Y., and Wu, Y., 2019. Factors influencing information industry development in a coastal economy. In: Li, L.; Wan, X., and Huang, X. (eds.), Recent Developments in Practices and Research on Coastal Regions: Transportation, Environment and Economy. Journal of Coastal Research, Special Issue No. 98, pp. 371–375. Coconut Creek (Florida), ISSN 0749-0208.With the progress of information technology, the proportion of information industry income in China's total high-tech industry income is growing. However, there are obvious regional inequalities in the development of China's information industry. In view of this phenomenon, this paper used the public data released by industry and the National Bureau of Statistics of China to study the factors influencing the information industry, as represented by the development of the telecommunication industry in coastal areas, where the information industry is more developed. Through the construction of a multiple regression model, the main factors affecting the development of the telecommunications industry in coastal areas were found, and other secondary factors were qualitatively studied.

Dai, J.H.; Guo, X.; Chi, J.Y., and Li, J.L., 2020. What are the most influential factors on the development of cultural industry in China's coastal areas? In: Qiu, Y.; Zhu, H., and Fang, X. (eds.), Current Advancements in Marine and Coastal Research for Technological and Sociological Applications. Journal of Coastal Research, Special Issue No. 107, pp. 262-267. Coconut Creek (Florida), ISSN 0749-0208.As a special cultural and economic form, the cultural industry has become an economic pillar of this century. The development of cultural industry in China's coastal areas is influenced and restricted by many factors, which interact with each other and thus affect the value-added of cultural industry. This article analyzes the factors that affect the development of cultural industry in China's coastal areas, takes the analysis of the influence of each factor on the development of cultural industry in coastal areas as the target. According to empirical analysis, the three most important factors affecting cultural industry in China's coastal areas are as patent, consumption, employment. Therefore, to promote cultural technology represented by cultural patents, optimize the industrial structure to increase consumption, encourage cultural innovation and independent entrepreneurship to increase the number of people employed in the cultural industry, will significantly promote the development of cultural industries in China's coastal areas.

Taking Beijing-Tianjin-Hebei as an example, it analyzes the comprehensive competitiveness of Beijing, Tianjin, and Hebei. It selects four dimensions: economic dimension, social dimension, environmental dimension, and technological dimension. From a new perspective, it explores the application of niche theory in regional synergy. Based on the analysis of the ecological niche, the coordination degree model of the composite system is further used to calculate the status quo of the coordinated development of the Beijing-Tianjin-Hebei region from 2013 to 2019. The results show that Beijing has the highest ecological niche, followed by Tianjin, and Hebei is the weakest. In 2019, the Beijing-Tianjin-Hebei region is at a good level of coordination, with the social subsystem having the highest order and the technological subsystem having the lowest order. Based on this, it is proposed that the Beijing-Tianjin-Hebei regions should be scientifically positioned, the overall need to be aligned with international trends, and the internal planning should be integrated to further enhance the level of cooperation in the Beijing-Tianjin-Hebei region.