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Based on the data analysis of economic development and the water environmental quality from 2002 to 2012 in the Nansi Lake Basin in China, the correlation between economic development and the water environmental quality was researched. Analysis shows that the GDP of the Nansi Lake Basin had an average annual growth of 7.3% in 2012, and the COD and CODMn had the average annual decrease of 7.69% and 6.79%, respectively, compared to 2002. Basin water environmental quality overall improved, reaching Class III of the “Environmental quality standards for surface water (GB3838-2002).” The pollution of the water environment was analyzed from three aspects: agricultural fertilizers and pesticides, livestock, and aquaculture. Results indicated that the water pollution of the Nansi Lake Basin mainly came from nonpoint source pollution, accounting for more than 80% of the overall pollution. The contributions of both agricultural fertilizers and pesticides account for more than 85% of the overall nonpoint source, followed by livestock and aquaculture. According to the water pollution characteristics of the Nansi Lake Basin, the basin pollution treatment strategy and prevention and treatment system were dissected, to solve the pollution problem of the Nansi Lake Basin. [ABSTRACT FROM AUTHOR]

This paper revealed the spatial and temporal distribution characteristics of Chinese marine environmental quality and driving factors during 2003–2021. [Display omitted] • Spatial distribution: South China Sea > East China Sea > Yellow Sea > Bohai Sea. • Shanghai, Zhejiang, Fujian and Hainan maintain high-pollution-low-investment model. • Jiangsu maintains low-pollution-low-investment model. • Typical correlation between Environmental Quality and Socioeconomic is 0.960. • GOP and Per Capita GDP show significant correlation with excellent water quality. As land and sea integration continues to accelerate, it will inevitably have an effect on the marine ecological environment. However, the study on spatial and temporal distribution characteristics of Chinese marine environmental quality and its driving factors was lacking. This paper employs Regression Analysis, Spearman Correlation Analysis, Canonical Correlation Analysis, Boston Consulting Group Matrix and Environmental Kuznets Curve to examine the spatial–temporal distribution characteristics and correlation factors of Chinese jurisdictional sea areas environmental quality. The environmental quality of the waters under China's jurisdiction improved on average from 2003 to 2021, the area of sea with excellent water quality increased by 7.21 × 104 km2. The spatial distribution showed "South superior, North inferior" trend. The accumulated red tide area is 2.01 × 105 km2, and the green tide has the average maximum area of distribution is 3.13 × 104 km2. The marine dumping area's volume of waste has a three stages of slow rise (2003–2007), steady (2008–2014) and rapid rise (2015–2021). The average percentage of seawater bathing areas with good water quality is 82.10 %. Urban Environmental Infrastructure Investment and Urban Drainage Construction Investments are positively correlated with excellent water quality and negatively correlated with light-sewage water quality. The typical correlation for the group "Environmental Quality/Environmental Governance" is 0.911, and the strongest correlation is between excellent water quality and urban drainage construction investment. The typical correlation coefficient for the "Environmental Quality/Socioeconomic" group is 0.960, and the strongest correlation is between excellent water quality and per capita GDP. The Gross Ocean Product, Per Capita GDP, Proportion of Non-agricultural Industries, Year-end Resident Population, and excellent water quality are positively correlated whereas light-sewage water quality is negatively correlated. Liaoning, Tianjin, Shandong and Guangdong shift from high-pollution-low-investment to low-pollution-low-investment model. Shanghai, Zhejiang, Fujian and Hainan maintain high-pollution-low-investment model, Hainan maintains high-pollution-high-investment model. Jiangsu maintains low-pollution-low-investment model. Hebei and Guangxi shift from low-pollution-low-investment to low-pollution-high-investment model. Liaoning, Hebei, Tianjin, Shandong, Guangxi and Shanghai show inverted "N" shape, Jiangsu shows positive "N" shape, Zhejiang and Fujian show monotonic decline shape, Guangdong and Hainan show positive "U" shape. The results could provide valuable suggestions for coastal provinces to accomplish economic development and environmental improvement, which to prevent the old way of "pollution first and treatment later". [ABSTRACT FROM AUTHOR]