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利用基于无人机的羽流嗅探微传感器系统实时测定船舶燃料硫含量的方案开发。

Protocol development for real-time ship fuel sulfur content determination using drone based plume sniffing microsensor system.

机构信息

Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong, China.

Sapiens Environmental Technology Co Ltd., Hong Kong, China.

出版信息

Sci Total Environ. 2020 Nov 20;744:140885. doi: 10.1016/j.scitotenv.2020.140885. Epub 2020 Jul 16.

DOI:10.1016/j.scitotenv.2020.140885
PMID:32755779
Abstract

Pollutants from navigation sector are key contributors to emission inventories of most coastal cities with heavy port activities. The use of high fuel sulfur content (FSC) bunker oil by ocean going vessels (OGVs) has been identified as a major source of sulfur dioxide (SO). Government authorities all over the world, including Hong Kong government, have implemented air pollution control regulations to cap FSC of fuel used by OGVs to 0.5%, from the existing 3.5%, to reduce SO emissions. However, the lack of efficient screening tools to identify non-compliant OGVs has prevented effective enforcement. This study developed and evaluated an unmanned aerial vehicle (UAV)-borne lightweight (750 g) microsensor system (MSS), which is capable of measuring ship plume SO, NO, NO, CO, CO, and particulate matter in real-time. Extensive experiments were conducted on the sensor system to evaluate its performance during laboratory and field operations. The effects of cross-sensitivity and meteorological conditions were studied and incorporated to account for the measurement conditions in dispersed ship plumes. The SO to CO concentration ratio-based FSC expression was formulated as per the 2016 European Union Directive and Regulations. Furthermore, the impact of plume dilution on the accuracy of FSC measurement was investigated at different stages using the MSS, with and without the UAV in both simulated conditions and real-world scenarios, maintaining a safe distance from the OGV exhaust stacks. The study demonstrates the robustness of using UAV-borne sensor system for ship emission sniffing and FSC determination. The results will assist in development of a technological framework for effective enforcement of ship emission control regulations.

摘要

航运部门的污染物是大多数港口活动繁忙的沿海城市排放清单的主要贡献者。远洋船舶(OGV)使用高燃料含硫量(FSC)燃料油被确定为二氧化硫(SO)的主要来源。包括香港政府在内的世界各国政府都实施了空气污染控制法规,将 OGV 使用的燃料 FSC 从现有的 3.5% 上限设定为 0.5%,以减少 SO 排放。然而,缺乏有效的筛选工具来识别不合规的 OGV ,使得有效执行受到阻碍。本研究开发并评估了一种基于无人机(UAV)的轻型(750 克)微传感器系统(MSS),该系统能够实时测量船舶羽流中的 SO、NO、NO、CO、CO 和颗粒物。对传感器系统进行了广泛的实验,以评估其在实验室和现场操作期间的性能。研究了交叉灵敏度和气象条件的影响,并将其纳入考虑,以说明分散船舶羽流中的测量条件。根据 2016 年欧盟指令和法规,制定了基于 SO 与 CO 浓度比的 FSC 表达式。此外,还研究了在不同阶段使用 MSS 以及在模拟条件和真实场景中有无无人机时,羽流稀释对 FSC 测量精度的影响,同时保持与 OGV 排气烟囱的安全距离。该研究证明了使用 UAV 搭载的传感器系统进行船舶排放嗅探和 FSC 测定的可靠性。研究结果将有助于为船舶排放控制法规的有效执行开发技术框架。

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