Your browser doesn't support javascript.
loading
Spatiotemporal assessment of marine environmental monitoring programme based on DIN concentration in the Yangtze River estuary and its adjacent sea.
Fan, Haimei; Wang, Jiaxin; Hu, Maogui; Li, Zhien; Jiang, Xiaoshan; Wang, Jinfeng.
Affiliation
  • Fan H; East China Sea Environmental Monitoring Center, State Oceanic Administration, Shanghai 201206, China.
  • Wang J; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Hu M; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China. Electronic address: humg@lreis.ac.cn.
  • Li Z; East China Sea Environmental Monitoring Center, State Oceanic Administration, Shanghai 201206, China.
  • Jiang X; East China Sea Environmental Monitoring Center, State Oceanic Administration, Shanghai 201206, China.
  • Wang J; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Sci Total Environ ; 707: 135527, 2020 Mar 10.
Article in En | MEDLINE | ID: mdl-31784161
ABSTRACT
The marine environment is rigorously protected in the Yangtze River Estuary (YRE) and its adjacent sea, and routine monitoring is constantly upgraded. Therefore, scientific and efficient monitoring programmes are needed. Nitrogen is one of the most serious pollutants in the YRE. Obtaining the precise pollution areas of water quality grades (WQGs) are a scientific and management issue that requires optimization of monitoring programmes and interpolation methods. Based on spatiotemporal regression point means of surface with non-homogeneity (STR-PMSN), dissolved inorganic nitrogen (DIN) concentrations were estimated in a stratified heterogeneous estuary. The annual average areas of DIN Grades I and II were classified by interpolating the concentrations; the values were 3145 km2, 1626 km2, 2320 km2 and 3758 km2 for February, May, August and November, respectively. This means that November had the best water condition, and May had the worst. Meanwhile, DIN area changes showed that the water condition changed due to removal of data much more in August and May than in February and November. The descending order of importance was August, May, February and November. Every month represented different runoff periods. Monitoring frequency should not be reduced. Removal of sampling data for the third stratum had a significant effect on the area. When the sampling data for outer boundary meshes of the third stratum were removed, the water condition became worse. However, when the sampling data for inner boundary meshes were removed, the water condition improved. New sites should be added to the outer boundary region to avoid interpolation instability and reduce the sensitivity of the existing sites. This study assesses the spatiotemporal effect of the marine environmental monitoring programmes on pollutant distribution by STR-PMSN, and it offers guidance for more precise data acquisition and processing methods in the YRE and its adjacent sea.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Total Environ Year: 2020 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Total Environ Year: 2020 Document type: Article Affiliation country: