Rapid economic developments in East Asian countries have inevitably resulted in environmental degradation in the surrounding seas, and concern for both the environment and protection from pollutants is increasing. Identification of sources of contaminants is essential to environmental pollution management. In this study, the provenance of anthropogenic lead (Pb), a major pollutant of Yellow Sea sediments, was determined for river mouth sediments, including those of the Changjiang, Huanghe, Han, and Geum Rivers, and for age-determined shelf core sediments through the measurement of Pb isotope ratios in the HCl-leached fraction using multi-collector inductively coupled plasma-mass spectrometry (MC ICP/MS). Anthropogenic Pb has accumulated in shelf core sediments since 1910, and its isotope ratios were estimated as 0.863–0.866 and 2.119–2.125 for 207Pb/206Pb and 208Pb/206Pb, respectively, from the mixing relationships of the two endmembers. River mouth sediments exhibited enough distinction in anthropogenic Pb isotope ratios to be discriminated: 0.874 (2.144) in the Huanghe, 0.856 (2.129) in the Han, 0.857 (2.122) in the Geum, and 0.854 (2.101) in the Changjiang for 207Pb/206Pb (208Pb/206Pb), respectively. Although isotope ratios of geogenic Pb in sediments dating before 1910 showed narrow ranges (0.842–0.845 and 2.088–2.100 for 207Pb/206Pb and 208Pb/206Pb, respectively), distinct isotope ratios in each core permitted source identification of sediments in the Yellow Sea based on geographic locations and the geogenic Pb of each river. By comparing the isotope ratios of the estimated anthropogenic Pb to source-related materials, the provenances of anthropogenic Pb in Chinese river sediments were presumed to be Chinese coal or ore, which is also a major source of atmospheric particulate Pb. The anthropogenic Pb in the shelf core sediments in the northern Yellow Sea originated from northern Chinese cities such as Beijing and Tianjin through atmospheric pathways. Pb isotope ratios indicated that Pb in Korean river sediments was characteristic of local Korean ores. 相似文献
The knowledge of prey small fish stock, distribution and abundance is necessary to guide stocking of piscivorous fish for the biomanipulation in domestic tap water lakes. This study describes the current status of small fish community in Lake Kuilei (China), and examines the spatial and seasonal variations of the community in relation to key environmental factors. Based on submerged macrophyte cover and water depth, the lake was divided into five major habitats: (1) macrophyte covered shallow habitat of water depth < 2.00 m, (2) uncovered or less-covered shallow habitat (2.00 m–3.50 m), (3) uncovered medium shallow habitat (3.50 m–5.00 m), (4) uncovered medium deep habitat (5.00 m–6.50 m) and (5) uncovered deep habitat (6.50 m–8.50 m). The abundance and composition of small fish were monitored by benthic fykenet sampling from April 2013 to January 2014. A total of 2881 individuals belonging to 5 families and 21 species were collected. Based on their abundance (accounted for 88.96% of the total) and occurrence (more than 33.33%), Acheilognathus chankaensis, Acheilognathus macropterus, Microphysogobio microstomus, Pseudorasbora parva and Rhinogobius giurinus were recognized as dominant small fish species. The results of correlation analysis identified that species richness ( Sr ), Shannon-Wiener diversity index ( H′ ) and Margalef′s richness index ( D ) were significantly negatively correlated with water depth, but positively correlated with biomass of submerged macrophytes.Redundancy analysis (RDA) revealed that the spatial distributions of most small fishes were negatively associated with water depth. The details of these findings are beneficial to understanding the adaptation of the small fishes in degraded environments, and to developing suitable biomanipulation strategies for the management of fish resources and water quality in the lakes along the lower reach of the Changjiang (Yangtze) River basin.
A Hierarchical Parallel simulation framework for spatially-explicit Agent-Based Models (HPABM) is developed to enable computationally intensive agent-based models for the investigation of large-scale geospatial problems. HPABM allows for the utilization of high-performance and parallel computing resources to address computational challenges in agent-based models. Within HPABM, an agent-based model is decomposed into a set of sub-models that function as computational units for parallel computing. Each sub-model is comprised of a sub-set of agents and their spatially-explicit environments. Sub-models are aggregated into a group of super-models that represent computing tasks. HPABM based on the design of super- and sub-models leads to the loose coupling of agent-based models and underlying parallel computing architectures. The utility of HPABM in enabling the development of parallel agent-based models was examined in a case study. Results of computational experiments indicate that HPABM is scalable for developing large-scale agent-based models and, thus, demonstrates efficient support for enhancing the capability of agent-based modeling for large-scale geospatial simulation. 相似文献