Abstract:The contents, speciation, source factors and potential ecological risks of the selected metals (Cr, Ni, Cu, Pb, Zn, Cd and As) were analyzed in surface sediments from Daya Bay (DYB). The results show that, with the exception of Pb, metal concentrations have decreased at all sites over the past decade. The distribution features of these concentrations represent a ring shape that descends from shore to bay by varying degrees. Speciation analysis showed that Cr, Ni, Cu, Zn and As exist mainly in the residual fraction and, thus, are of low bioavailability, while Cd and Pb were found to be abundant in the non-residual fraction and, thus, have high potential mobility. The ratio of heavy metals in non-residual form in descending order is Pb (78.83%), Cd (78.65%), Cu (48.54%), Zn (48.10%), Ni (38.31%), Cr (28.43%) and As (27.76%). The ratio of Pb content is the highest, meaning the highest mobility of Pb. The metals' potential ecological risks to the environment were also assessed using the methods of the mean effect range-median quotient and the criteria of OPEN ACCESS Sustainability 2014, 6 9097 risk assessment code. The results showed that Cd presents the highest risk, and Pb and Cu are generally considered to be medium risks in the sub-basins of Daya Bay. The principal component analysis (PCA) revealed that natural coastal weathering and erosion of rock caused the highest input, followed by mariculture and industrial wastewater and, finally, domestic sewage discharge.

Sediments in estuary areas are recognized as the ultimate reservoirs for numerous contaminants, e.g., toxic metals. Multivariate analyses by chemometric evaluation were performed to classify metal ions (Cu, Zn, As, Cr, Pb, Ni and Cd) in superficial sediments from Lingdingyang Bay and to determine whether or not there were potential contamination risks based on the BCR sequential extraction scheme. The results revealed that Cd was mainly in acid-soluble form with an average of 75.99% of its total contents and thus of high potential availability, indicating significant anthropogenic sources, while Cr, As, Ni were enriched in the residual fraction which could be considered as the safest ingredients to the environment. According to the proportion of secondary to primary phases (KRSP), Cd had the highest bioavailable fraction and represented high or very high risk, followed by Pb and Cu with medium risks in most of samples. The combined evaluation of the Pollution Load Index (PLI) and the mean Effect Range Median Quotient (mERM-Q) highlighted that the greatest OPEN ACCESSSustainability 2015, 7 4939 potential environmental risk area was in the northwest of Lingdingyang Bay. Almost all of the sediments had a 21% probability of toxicity. Additionally, Principal Component Analysis (PCA) revealed that the survey region was significantly affected by two main sources of anthropogenic contributions: PC1 showed increased loadings of variables in acid-soluble and reducible fractions that were consistent with the input from industrial wastes (such as manufacturing, metallurgy, chemical industry) and domestic sewages; PC2 was characterized by increased loadings of variables in residual fraction that could be attributed to leaching and weathering of parent rocks. The results obtained demonstrated the need for appropriate remediation measures to alleviate soil pollution problem due to the more aggregation of potentially risky metals. Therefore, it is of crucial significance to implement the targeted strategies to tackle the contaminated sediments in Lingdingyang Bay.

This paper proposes a new method to classify remote sensing data by using Particle Swarm Optimization (PSO). This method is to generate classification rules through simulating the behaviors of bird flocking. Optimized intervals of each band are found by particles in multi-dimension space, linked with land use types for forming classification rules. Compared with other rule induction techniques (e.g. See5.0), PSO can efficiently find optimized cut points of each band, and have good convergence in the search process. This method has been applied to the classification of remote sensing data in Panyu district of Guangzhou with satisfactory results. It can produce higher accuracy in the classification than the See5.0 decision tree model. swarm intelligence, particle swarm optimization (PSO), remote sensing

In this study, the spatiotemporal distributions, potential sources, and ecological risks of Hg, Cr, and As in seawater, and Hg, As, Zn, Cd, Pb, and Cu in sediments from Daya Bay were investigated. The five-year average concentrations of Hg, Cr, and As in seawater were 0.020 μg/L, 0.79 μg/L, and 2.08 μg/L, respectively. The five-year average concentrations of Hg, As, Zn, Cd, Pb, and Cu in surface sediments were 0.04 mg/kg, 7.34 mg/kg, 63.81 mg/kg, 0.23 mg/kg, 25.60 mg/kg, and 11.78 mg/kg, respectively. Annual variations in Hg, Cr, and As in seawater exhibited different trends. HMs in sediments, such as As, Zn, Pb, and Cu, exhibited similar annual variations, whereas Hg and Cd exhibited different annual variations. The spatial distribution of metal species in seawater and sediments showed significant variability, and the concentrations decreased gradually from the coast to the open sea. The comprehensive potential ecological hazard index (RI) of HMs in sediments indicated a relatively high risk, especially for Hg and Cd contamination. The geoaccumulation indices (Igeo) of As, Zn, Pb, and Cu suggested that these metals did not pollute Daya Bay, whereas those of Cd and Hg indicated mild and moderate pollution. The environmental fates of HMs were discussed based on Pearson correlation analysis, revealing that concentrations of HMs were greatly affected by parameters, such as pH, salinity, dissolved oxygen (DO), and total organic carbon (TOC). Principal component and factor analyses indicated that Hg, Cr, As, and dissolved inorganic nitrogen (DIN) in water originated from similar sources, including domestic sewage and wastewater from fishing ports, runoffs, and outlets. For sediments, it was proposed that Cu, Zn, As, Pb, and TOC exhibited similar sources, including cage culture and waste discharge from outlets. Meanwhile, Hg and Cd originated from other point sources, such as a harbor. The study suggests that sustainable management and economic development be integrated to control pollutant emissions in Daya Bay.

This study concerns the distribution and potential sources of elevated heavy metal concentrations (Cu, Zn, Pb, Cd, As) in surface sediments of the Dongzhai Harbor, Hainan Island,a national important mangrove ecosystem protection area.It was found that the pollution of As may occur occasional biological effect by numerical Sediment Quality Guidelines. Further, Geoaccumulation indices (Igeo) suggest there are serious pollution levels of As at all five stations. Spatial distribution of ecotoxicological index and pollution load index suggested that most of the surface sediments have a 9% probability of being toxic and the potential ecological risk zone appear in northern and southern of Dongzhai Harbor. Correlation analysis, principal component analysis, and cluster analysis showed that these metals primarily originate from natural sources. As and Pb resulted primarily from aquaculture, and combustion of gasoline and diesel fuel by ships. The present study provides a baseline record of heavy metals in mangrove surface sediments on the Dongzhai Harbor, and provide a useful aid for sustainable marine management in this region.