BGC-05 Coastal biogeochemical processes in a climatically sensitive ocean
Baseline assessment of the heavy metals influencing factors in surface sediments of the Cross River Estuary and surrounding environments, South East Nigeria, using a Bayesian Network Model
Solomon Felix Dan* , Guangxi Key Laboratory of Marine Disaster in the Beibu Gulf, Beibu Gulf University, Qinzhou 535011, China
Enobong Charles Udoh, State Key Laboratory of Marine Geology, Tongji University, Shanghai 200092, China
Jiaodi Zhou, Guangxi Key Laboratory of Marine Disaster in the Beibu Gulf, Beibu Gulf University, Qinzhou 535011, China
Buddhi Wijesiri, School of Civil and Environmental Engineering, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland 4001, Australia
Shuai Ding, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
Bin Yang, Guangxi Key Laboratory of Marine Disaster in the Beibu Gulf, Beibu Gulf University, Qinzhou 535011, China
Dongliang Lu, Guangxi Key Laboratory of Marine Disaster in the Beibu Gulf, Beibu Gulf University, Qinzhou 535011, China
Qianqian Wang, State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China

Heavy metals (Ni, Cu, Cr, Zn, Pb, and Cd) are persistent widespread pollutants in different environmental compartments. The bioavailability and toxicity potentials of heavy metals depend on their chemical speciation. In this study, chemical speciation of heavy metals using the Community Bureau of Reference (BCR) extraction scheme was studied in surface sediments of the Cross River Estuary (CRE) and surrounding environment, Gulf of Guinea, South East Nigeria. Sources of sedimentary organic carbon (OC) also were quantified using a Monte Carlo mixing model utilizing the stable isotope of OC (δ13C) and OC/TN molar ratio as endmember values for OC derived from terrestrial soil, C3 plants from mangrove wetland, and marine phytoplankton to determine its influence on heavy metals contents. A Bayesian Network (BN) model was developed and applied to study the interdependency of heavy metals on factors such as sedimentary OC sources, total nitrogen (TN), pH, salinity, and sediment granulometry. Results showed that the contents of Ni and Cu in terrestrial soil, mangrove and estuarine sediments were dominated by residual fraction, suggesting that Ni and Cu are immobilized in aluminosilicate minerals. Pb (~56%), Cd (~71%), Zn (~67%), and Cr (~76%) were mainly available in non-residual phases, suggesting potential bioavailability. Cd was the most polluted (CF >3) heavy metal with the highest bioavailability risk (RAC = 4.76~46.34) in the study area. According to the BN model results, sediment granulometry did not exert any dominant control over the spatial distributions of OC and heavy metals in the study area. However, the model results revealed that sedimentary OC of C3 plants from mangrove wetland played a key influencing role on the contents and variability of Pb and Zn, while the input of terrestrial soil OC strongly influenced Cu and Ni contents. In the estuarine sediments, Cd and Cr were sensitive to changes in sediment pH, while Ni was sensitive to salinity variation. Strong interdependency between Cd and TN suggested that nitrogen has the potential to increase Cd bioavailability upon release from sediments. This study has important implications for the ecological health of coastal marine systems where the surrounding environments are degraded and, at the same time, significantly perturbed by human activities.