港口溢油风险事件统计及应急资源配置数据集
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港口是联通世界经济的重要纽带和综合交通的重要枢纽节点，是国家对外开放的重要门户，绿色港口发展已成为当前世界各国发展绿色经济的重要窗口、建设绿色循环低碳交通运输体系的重要内容和推动港口可持续发展的重要方向，具有十分重要的战略意义和现实意义。本数据依托国家重点研发计划项目《绿色港口建设与生态安全保障技术》课题二《港口污染物动态监测及智能化控制技术研究》，选取某散货港口为示范应用点，对其港口水体中的石油类数据进行监测，对其港口溢油事件进行统计，通过构建基于贝叶斯网络的港口污染风险评估模型，对港口污染风险进行评估。通过构建多目标优化模型，对港口区域应急资源配置进行优化。本数据集中溢油事件统计数据中的监测数据主要为水体中石油类含量数据，数据监测时间为2024年1月至2024年11月，数据集格式为.xls格式；应急资源优化配置数据集为.pdf和.m数据，通过对港口进行溢油风险评估，对其应急资源配布进行优化，实现港口的水质高效应急管理。本数据集的数据量为68.3MB。
Ports are important links connecting the world economy and key hub nodes of comprehensive transportation, as well as important gateways for a country's opening-up. The development of green ports has become a crucial window for countries worldwide to develop green economies, an important component of building a green, circular and low-carbon transportation system, and a key direction for promoting the sustainable development of ports, carrying significant strategic and practical significance. This dataset is developed based on Task 2 "Research on Dynamic Monitoring and Intelligent Control Technologies for Port Pollutants" under the National Key Research and Development Program of China project "Green Port Construction and Ecological Security Guarantee Technologies". A bulk cargo port was selected as the demonstration application site. Petroleum content data in the port's water body were monitored, and port oil spill incidents were statistically recorded. A port pollution risk assessment model based on Bayesian networks was constructed to evaluate port pollution risks. Additionally, a multi-objective optimization model was built to optimize the allocation of emergency resources in the port area. The monitoring data included in the oil spill incident statistics of this dataset mainly refer to the petroleum content data in water bodies, with monitoring conducted from January 2024 to November 2024. The dataset is stored in .xls format. The emergency resource allocation optimization dataset is provided in .pdf and .m formats. By conducting oil spill risk assessment for the port and optimizing its emergency resource deployment, efficient emergency management of port water quality is achieved. The total size of this dataset is 68.3 MB.
