Shuying Bai
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Shuying Bai has a total of 11 co-authors. Here are the top co-authors by number of shared publications:
- Chao Wang
School of Electronics and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
1 shared publication - Jian Li
School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
1 shared publication Li Yu
Environmental Monitoring Centre of Jilin Province
1 shared publication- Qiufen Li
Yellow Sea Fisheries Research Institute, CAFS
1 shared publication - Tao Xie
School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
1 shared publication - Xia Wang
Environmental Monitoring Centre of Jilin Province
1 shared publication
Latest Publications
- Open Access
Seasonal Variations and Drivers of Total Nitrogen and Phosphorus in China’s Surface Waters
Total nitrogen (TN) and total phosphorus (TP) are essential indicators for assessing water quality. This study systematically analyzes the spatial and temporal distribution of TN and TP in China’s surface waters and examines the influence of natural factors and human activities on their concentrations. Utilizing data from 1387 monitoring sites (2020–2021) and employing K-means clustering and geographically weighted regression (GWR), we found that the national average concentrations were 3.89 mg/L for TN and 0.096 mg/L for TP. Spatially, higher TN and TP levels were observed in northern regions, coastal areas, and plains compared with southern, inland, and mountainous areas. Notably, TN concentrations reached up to 29.49 mg/L in the Haihe River basin and related plains, while TP peaked at 0.497 mg/L in the southeastern Shandong and northern Jiangsu coastal zones. Temporally, TN levels were approximately 50% higher in winter than summer, whereas TP levels were about 40% higher in summer. Key influencing factors included rainfall, elevation, fertilizer use, and population density, with spatial heterogeneity observed. Rainfall was the primary factor for TN change and the secondary factor for TP change. Soil type positively correlates with TN and TP changes, affecting non-point source pollution. Human activities such as land use, fertilizer application and population density had a significant effect on the nitrogen and phosphorus concentrations, while woodland had a significant impact on the improvement of water quality. The geographically weighted regression analysis showed spatial heterogeneity in the effects of each factor on TN and TP concentrations, and the best fit was at the watershed scale. The findings highlight the need for enhanced control of agricultural runoff, improved sewage treatment, and region-specific management strategies to inform effective water environment policies in China.
Open AccessSeasonal Variations and Drivers of Total Nitrogen and Phosphorus in China’s Surface Waters
Total nitrogen (TN) and total phosphorus (TP) are essential indicators for assessing water quality. This study systematically analyzes the spatial and temporal distribution of TN and TP in China’s surface waters and examines the influence of natural factors and human activities on their concentrations. Utilizing data from 1387 monitoring sites (2020–2021) and employing K-means clustering and geographically weighted regression (GWR), we found that the national average concentrations were 3.89 mg/L for TN and 0.096 mg/L for TP. Spatially, higher TN and TP levels were observed in northern regions, coastal areas, and plains compared with southern, inland, and mountainous areas. Notably, TN concentrations reached up to 29.49 mg/L in the Haihe River basin and related plains, while TP peaked at 0.497 mg/L in the southeastern Shandong and northern Jiangsu coastal zones. Temporally, TN levels were approximately 50% higher in winter than summer, whereas TP levels were about 40% higher in summer. Key influencing factors included rainfall, elevation, fertilizer use, and population density, with spatial heterogeneity observed. Rainfall was the primary factor for TN change and the secondary factor for TP change. Soil type positively correlates with TN and TP changes, affecting non-point source pollution. Human activities such as land use, fertilizer application and population density had a significant effect on the nitrogen and phosphorus concentrations, while woodland had a significant impact on the improvement of water quality. The geographically weighted regression analysis showed spatial heterogeneity in the effects of each factor on TN and TP concentrations, and the best fit was at the watershed scale. The findings highlight the need for enhanced control of agricultural runoff, improved sewage treatment, and region-specific management strategies to inform effective water environment policies in China.
- 15 May 2007
- Published by Springer Nature in Stochastic Environmental Research and Risk Assessment
- Vol. 22 (4) , 477-486
Ecological risk assessment of eutrophication in Songhua Lake, China
- 15 May 2007
- Published by Springer Nature in Stochastic Environmental Research and Risk Assessment
- Vol. 22 (4) , 477-486
Ecological risk assessment of eutrophication in Songhua Lake, China