Insomnia is a prevalent sleep disorder that causes serious harm to individuals and society. It is closely linked to not only personal factors but also social, economic and other factors. This study explores the influencing factors and spatial differentiation of insomnia from the perspective of social media. This paper chose China's largest social media platform, Sina Weibo, as its data source. Then, based on the collected relevant data of 288 Chinese cities from 2013 to 2017, it explored the impact of economic, social, and environmental factors and an educated population on insomnia. Additionally, the importance and interaction of each influencing factor were analyzed. According to the results, the gross domestic product (GDP), proportion of households connected to the Internet and number of students in regular institutions of higher education are the major factors that influence insomnia, and their influences show obvious spatial nonstationarity. Rapid GDP growth has increased the probability of insomnia, and the positive correlation between the proportion of households connected to the internet and insomnia has strengthened annually. Although the impact of insomnia on college students decreased in some regions, the overall impact was still increasing annually, and spatial nonstationarity was obvious. Properly controlling GDP growth and unnecessary time spent online and guiding people to develop healthy Internet surfing habits and lifestyles will help improve their sleep quality. Our research results will help relevant professionals better understand the distribution of regional insomnia and provide a reference for related departments to formulate regional insomnia prevention and treatment policies.

Fast urbanization in developing countries contributes to heavier pollution in urban water environments, as urbanization enhances land development and even requires lake filling to meet urban land needs, which produces significant water runoff pollution. Centralized construction brings heavier non-point source pollution, which is one of the most crucial types of pollution in urban areas. However, the pollution caused by urbanization in infilled lake areas is lack of attention. To reduce the negative impact of pollution brought on by urbanization, it is important to monitor the characteristics of runoff water qualities and their relationship with rainfall features. In this study, runoff water quality was monitored from 10 rainfall events, totaling 157 samples in the Wuhan Shahu area, an infilled lake area, to characterize the pollutant event mean concentrations (EMCs) and to explore the different effects of land-use types. COD (chemical oxygen demand), TN (total nitrogen), and TP (total phosphorus) were selected as water quality indicators. The results show that the pollutants have a significant spatial variation. Residential runoff had the largest COD (averaged EMC = 54.02 (mg/L)) and TN (averaged EMC = 2.69 (mg/L)) pollution, while road runoff had the second largest COD (averaged EMC = 48.05 (mg/L)) and TN (2.572 (mg/L)) pollution. The TP pollution level is opposite to COD and TN, as commercial and green spaces have heavier pollution, while the differences in TP pollution levels between the four types of land are not significant. The release of organic matter and nitrogen is closely related to human activities on land types, while phosphorus emission is relatively stable, indicating that it is not easily affected or controlled. In addition, the variation in pollutants between land types is also related to a certain extent. The correlation analysis shows that parameters like antecedent dry days (ADDs), rainfall intensity, and rainfall duration most significantly affect the EMCs of commercial and green spaces. Phosphorus pollutants on roads are harder to reduce. These results may help researchers to identify the specific pollutant source and find an effective method to reduce pollution in infilled lake areas and other areas.