Environment occurrence of perfluoroalkyl acids and associated human health risks near a major fluorochemical manufacturing park in southwest of China.

Despite China being the largest global manufacturer of perfluoroalkyl acids (PFAAs), few studies have been carried out on the environmental occurrence and associated human health risks of PFAAs emitted from manufacturing sites in China. Here, river water, tap water, soil and leaf samples were collected around a major fluorochemical manufacturing park (FMP) in the southwest of China in 2019. High ΣPFAA concentrations (sum of 12 PFAAs) of 3817 ng/L, 3254 ng/L, 322-476 ng/g dw and 23401-33749 ng/g dw were measured near the FMP in river water, tap water, soil and leaves, respectively, indicating that the FMP is a point source of PFAAs. PFOA was the predominant PFAA in all samples (58.5-98.6 %) indicating the production or use of PFOA at the FMP. PFOA concentrations in most tap water samples (> 300 ng/L in 31 of 38 samples) exceeded the U.S. EPA health advisory. Proportions of branched PFOA isomers in all samples were in 5.9-47.4 %, suggesting the production or use of PFOA manufactured by electrochemical fluorination at the FMP. It is recommended to focus more attention on branched PFOA isomers in the future because otherwise health risks may be underestimated due to their relatively high proportions in China.

Energy-Efficient Spatial Query-Centric Geographic Routing Protocol in Wireless Sensor Networks.

In data-centric wireless sensor networks (WSNs), sensing data have a high time-space correlation. Most queries are spatial and used to obtain data in a defined region. Geographic routing (GR) protocols are the optimal choice for routing spatial queries. However, several drawbacks still exist in GRs, and these the include premature death of nodes and communication latency, which result in reduced network life and query efficiency. A new clustering GR protocol called quadtree grid (QTGrid) was proposed in this study to save energy and improve spatial query efficiency. First, the monitoring area was logically divided into clusters by a quadtree structure, and each grid's location was encoded to reduce the memory overhead. Second, cluster head (CH) nodes were selected based on several metrics, such as distance from the candidate node to the grid center and adjacent CHs and residual energy. Third, the next-hop routing node was selected depending on the residual energy of the candidate node and its distance to the sink node. Lastly, a lossless data aggregation algorithm and a flexible spatial query algorithm were adopted to reduce the transmission of redundant data and meet the application requirements, respectively. Simulation results showed that compared with three related protocols, QTGrid has lower energy consumption and higher spatial query efficiency and is more suitable for large-scale WSN spatial query application scenarios.