Water ecology has always been key to environmental protection, and the combination of human activities and natural factors has caused eutrophication in the Yangtze estuary and adjacent waters. Among them, dissolved oxygen (DO) concentration is the key indicator to judge the quality of water. Firstly, using principal component analysis (PCA) to determine the number of parameters affecting dissolved oxygen concentration, the least squares support vector machine (LSSVM) prediction model with improved particle swarm optimization (IPSO) is proposed to be applied to the dissolved oxygen prediction in Shanghai’s Yangtze River basin through the data-driven modeling approach and the regression prediction capability of the neural network. Eight parameters of water temperature (WT), pH, potassium permanganate (KMnO4), ammonia nitrogen (NH4+-N), total phosphorus (TP), total nitrogen (TN), conductivity (Cond), and nephelometric turbidity unit (NTU) are selected as model inputs in the published public data, and the output is the dissolved oxygen concentration. The optimal combination of model parameters is found according to the IPSO algorithm, which effectively overcomes the parameter selection problem of regular support vector machines (SVM). The mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and correlation coefficients of the evaluation indexes of this model (R2) are 0.1702, 0.2221, 0.0267, and 0.9751, respectively. Compared with other similar data driven models, this model has improved model accuracy and stability in predicting DO concentrations in the estuary, and thus it provides technical support for assessing and monitoring offshore water quality.

Chongce ice core, drilled from West Kunlun Mountain, 6350 meters high, provides a unique opportunity to obtain the past atmospheric environmental information. In this paper, the composition and concentration of ions, ions sources in Chongce ice core were analyzed, and the ions variation during last century were reconstructed. Results show that (1) Calcium ion shows the greatest proportion of ions concentration. (2) The major ions are mainly originated from Taklimkan Desert through sandstorm transport and wet deposition process. (3) The major mineral dust ions Ca 2+ , SO 4 2-, Cl-, Na + and Mg 2+ show a decreased trend during the last century, in according with the decreased sandstorm frequency occurring in Taklimkan Desert. (4)The potassium ions show an increased trend during last century, especially after 1950, this related with the increased biomass burning. (5)The nitrite ions show a relatively stable variation during the last century, and there is a remarkable 11-17year period

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