Global Marine LNG Terminals, Tankers & Trade (LNG-T3): A High-Resolution AIS-Based Dataset of LNG Trade Dynamics (2020-2024)
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The LNG-T3 dataset provides the first open-access, daily-resolution dataset of global liquefied natural gas (LNG) maritime trade flows between 2020 and 2024. It integrates three core components: (1) a global LNG tanker fleet inventory (406 vessels), (2) a harmonized LNG terminal inventory (545 terminals), and (3) AIS-derived daily records of LNG tanker voyages, terminal throughput, and country-to-country trade flows. The dataset is constructed from Automatic Identification System (AIS) vessel position and draught reports, port call records, and open infrastructure sources. A robust voyage detection framework identifies loading and unloading events at LNG terminals and reconstructs tanker voyages, enabling the estimation of daily LNG volumes transported, processed, and traded globally. Validation against multiple independent references—including Gas Infrastructure Europe (GIE), U.S. EIA, Eurostat, and GIIGNL—demonstrates high consistency at the terminal, country, and regional scales. LNG-T3 captures the dramatic shifts in LNG trade following the 2022 Russian invasion of Ukraine, including Europe’s surge in LNG imports, the expansion of U.S. exports, continued Russian LNG shipments despite pipeline sanctions, and the diversification of Europe’s suppliers to include smaller exporters such as Cameroon, Turkmenistan, and Peru. Files included: LNG_tanker.csv – global LNG tanker fleet inventory (2020–2024) LNG_tanker_voyage.csv - Individual LNG tanker export/return voyage events (2020-2024). LNG_terminal.csv – LNG export/import terminal inventory LNG_terminal_daily.csv – daily LNG terminal-level throughput LNG_trade_daily.csv – daily country-to-country LNG trade flows AIS_feed.zip - code for obtaining real-time AIS data with AIShub (your API key is required) code.zip - code for generating visualizations and validations Table 2. Key Attributes of LNG Tankers, Terminals, and Trade Records in the LNG-T3 Dataset. Dataset Attribute Description Tankers IMO International Maritime Organization number MMSI Maritime Mobile Service Identity number ship_name Name of the LNG tanker built_year The year the vessel was built tanker_class Classification of tankers by size/type (e.g., Q-Flex, Q-Max, Conventional) capacity_cbm ** LNG carrying capacity in cubic meters (m³) registered_country The country where the tanker is registered is_capacity_estimated ** Flag indicating if capacity is estimated (1 = Yes) is_active_tanker Flag indicating if the tanker has AIS or port call record during the study period total_LNG * Total LNG volume transported by the vessel (m³) delivery_counts The number of LNG deliveries made by the tanker total_distance * Total vessel travel distance (in kilometers) first_delivery_record Date of the earliest recorded LNG delivery last_delivery_record Date of the most recent recorded LNG delivery Tanker Voyages start_date, end_date Voyage date of departure and arrival IMO International Maritime Organization number voyage Voyage type, export or return from_terminal, to_terminal LNG terminal of departure and arrival amount_cmb Delivered LNG cargo volume (m³) from_country, to_country Country of departure and arrival confidence_score Confidence level of detected voyage (1–5, with 5 being highest) voyage_distance Estimated voyage distance from origin to destination (in kilometers) Terminals name Name of the LNG terminal UN_LOCODE UN/LOCODE code of the nearest port to the terminal port_distance_km The distance between the terminal and the port status Operational status (e.g., proposed, idle, operating) unit_count Number of processing units/trains at the terminal capacity_mtpa LNG processing capacity in million tonnes per annum (MTPA) terminal_type Import or export classification start_year Planned or actual start year of terminal operations region Geographical region where the terminal is located areas Country or locality of the terminal lat, lon Geocoordinate of the terminal total_processed_cbm * Total LNG volume processed at the (cbm) first_record Earliest record of terminal activity last_record Most recent record of terminal activity Terminals name LNG terminal name date Date of the activity processed_cbm Total LNG volume processed at the (m³) Trade date Date of LNG trade activity type Type of activity (e.g., arrival or departure) from_country Country of departure to_country Country of arrival amount_cbm Traded LNG cargo volume (m³) voyage_distance Estimated voyage distance from origin to destination (in kilometers) confidence_score Confidence level of the estimated trade event (1–5, with 5 being highest) * “Total” values in the LNG-T3 dataset (e.g., total_LNG, delivery_counts, total_distance, total_processed_cbm) represent aggregated values over the period from 2020-01 to 2024-12, based on available and validated data records. ** The fields capacity_cbm and is_capacity_estimated are derived from a DWT-to-capacity regression model (r2 = 0.75, see Methods). The model was applied exclusively in cases where official capacity data were not available, and the flag is_capacity_estimated will be set 1.
LNG-T3数据集提供了2020年至2024年间全球液化天然气(liquefied natural gas, LNG)海运贸易流量的首个开源每日分辨率数据集。其整合了三大核心组成部分:(1) 全球LNG油轮船队清单(共406艘船舶);(2) 统一标准化的LNG终端清单(共545个终端);(3) 源自自动识别系统(Automatic Identification System, AIS)的LNG油轮航行、终端吞吐量以及国家间双边贸易流量的每日记录。 本数据集基于船舶自动识别系统(AIS)的船位与吃水报告、港口停靠记录以及开放基础设施数据源构建。通过一套稳健的航行检测框架,可识别LNG终端的装卸作业事件并重构油轮航行路径,进而估算全球范围内每日运输、处理与交易的LNG体量。 通过与欧洲天然气基础设施协会(Gas Infrastructure Europe, GIE)、美国能源信息署(U.S. EIA)、欧盟统计局(Eurostat)以及GIIGNL等多个独立参考源开展验证,结果表明该数据集在终端、国家及区域尺度上均具备高度一致性。LNG-T3完整捕捉了2022年俄罗斯入侵乌克兰后LNG贸易格局的剧烈转变,包括欧洲LNG进口量激增、美国LNG出口规模扩张、即便面临管道制裁俄罗斯LNG出货量仍持续,以及欧洲LNG进口供应商的多元化——新增喀麦隆、土库曼斯坦与秘鲁等小型出口国。 ### 包含文件 - LNG_tanker.csv:2020-2024年全球LNG油轮船队清单 - LNG_tanker_voyage.csv:2020-2024年单艘LNG油轮出口/返程航行事件记录 - LNG_terminal.csv:LNG进出口终端清单 - LNG_terminal_daily.csv:分终端的每日LNG吞吐量数据 - LNG_trade_daily.csv:分国家的每日LNG双边贸易流量数据 - AIS_feed.zip:基于AIShub获取实时AIS数据的代码(需使用个人API密钥) - code.zip:用于生成可视化图表与开展验证的代码 ## 表2 LNG-T3数据集中LNG油轮、终端及贸易记录的关键属性 | 数据类别 | 属性字段 | 说明 | | --- | --- | --- | | 油轮 | IMO | 国际海事组织(International Maritime Organization, IMO)编号 | | | MMSI | 海上移动通信业务标识(Maritime Mobile Service Identity)编号 | | | ship_name | LNG油轮名称 | | | built_year | 船舶建造年份 | | | tanker_class | 按尺寸/类型划分的油轮分类(例如"Q-Flex"、"Q-Max"、常规型) | | | capacity_cbm ** | LNG载货容量,单位为立方米(m³) | | | registered_country | 油轮注册国籍 | | | is_capacity_estimated ** | 容量估算标记(1=已估算) | | | is_active_tanker | 标记该油轮在研究期内是否存在AIS或港口停靠记录 | | | total_LNG * | 该船舶累计运输的LNG总体量(单位:m³) | | | delivery_counts | 该油轮完成的LNG卸货次数 | | | total_distance * | 该船舶累计航行总距离(单位:千米) | | | first_delivery_record | 有记录以来最早的LNG卸货日期 | | | last_delivery_record | 有记录以来最晚的LNG卸货日期 | | 油轮航行 | start_date、end_date | 船舶航行的出发与到达日期 | | | IMO | 国际海事组织编号 | | | voyage | 航行类型,分为出口或返程 | | | from_terminal、to_terminal | 出发与抵达的LNG终端 | | | amount_cmb | 交付的LNG货物体量(单位:m³) | | | from_country、to_country | 出发与抵达的国家 | | | confidence_score | 检测到的航行的置信度等级(1~5,5为最高置信度) | | | voyage_distance | 出发港至目的港的估算航行距离(单位:千米) | | 终端清单 | name | LNG终端名称 | | | UN_LOCODE | 终端最近港口的联合国/货物装卸港口代码(UN/LOCODE) | | | port_distance_km | 终端与所属港口的距离(单位:千米) | | | status | 运营状态(例如拟建、闲置、运营中) | | | unit_count | 终端的处理单元/生产线数量 | | | capacity_mtpa | LNG年处理能力,单位为百万吨/年(MTPA) | | | terminal_type | 终端的进出口分类(进口型/出口型) | | | start_year | 终端运营的计划或实际启动年份 | | | region | 终端所在的地理区域 | | | areas | 终端所属国家或地区 | | | lat、lon | 终端的地理坐标 | | | total_processed_cbm * | 该终端累计处理的LNG总体量(单位:m³) | | | first_record | 该终端有记录以来最早的活动日期 | | | last_record | 该终端有记录以来最晚的活动日期 | | 每日终端吞吐量 | name | LNG终端名称 | | | date | 活动日期 | | | processed_cbm | 当日该终端处理的LNG体量(单位:m³) | | 贸易记录 | date | LNG贸易活动日期 | | | type | 活动类型(例如抵达或离港) | | | from_country | 出发国 | | | to_country | 抵达国 | | | amount_cbm | 交易的LNG货物体量(单位:m³) | | | voyage_distance | 出发地至目的地的估算航行距离(单位:千米) | | | confidence_score | 估算贸易事件的置信度等级(1~5,5为最高置信度) | --- * 注:LNG-T3数据集中的"累计"类字段(如total_LNG、delivery_counts、total_distance、total_processed_cbm)均基于2020年1月至2024年12月期间的有效经验证数据记录汇总得到。 ** 注:字段capacity_cbm与is_capacity_estimated源自载重吨(DWT)与载货容量的回归模型(决定系数r²=0.75,详见研究方法部分)。仅在官方容量数据缺失时应用该模型,此时is_capacity_estimated标记将被设为1。



