本数据集提供冰冻圈内陆水体（湖泊、池塘、水库、河流及溪流）时空分辨率温室气体（CO₂、CH₄、N₂O）观测数据。数据集通过数据整合汇编流程构建而成。\n
数据集汇编过程中，系统检索了期刊论文、学位论文、公共数据仓库等多类数据源；检索平台涵盖：科学引文索引（Web of Science）、谷歌学术（Google Scholar）、ProQuest 全球博硕士论文库、中国知网（CNKI）、北极数据中心、Zenodo、环境数据倡议平台（EDI）及 PANGAEA 地球科学数据平台。\n
本研究采用统一筛选标准：纳入冻土/冰川影响下溪流、河流、池塘、湖泊、水库等内陆水体的温室气体浓度与通量观测数据；研究范围严格限定在冰冻圈空间边界内，剔除冰冻圈范围外站点。同时剔除无冰川、无冻土背景的寒区湿地生态系统及内陆水体；与河道连通的洪泛区湖泊予以排除，仅高封闭度、微弱连通的水体按湖泊站点收录。常年冰封水体的气体浓度数据不纳入本库。此外，尽可能同步收集了水体理化特征、气候、土地覆盖等辅助环境数据。\n
数据集分为两个独立文件：CryoLake.xlsx：收录湖泊、池塘、水库数据；CryoRiver.xlsx：收录河流、溪流数据。每个文件均包含 4 个子表：文献来源表、站点信息表、浓度数据表、通量数据表。所有子表通过唯一文献编号关联，站点表、浓度表、通量表再通过唯一站点编号联动匹配。数据时间分辨率不等，最短为日尺度；日内高频观测均值整合为日数据，同时收录月、季节、年尺度观测结果。鉴于冰冻圈温室气体数据稀缺，本库收录所有可获取的有效观测记录。空间分辨率以样点尺度为主，同时纳入部分站点聚合数据；数据表完整记录观测时空信息，可供后续深度分析。受区域异质性影响，未设置统一季节划分标准，季节归属依据各原始文献的站点描述进行界定。\n
附带的 R 脚本为内陆水体温室气体排放升尺度多级自助抽样算法；压缩文件包含自助抽样结果，可进一步用于分区、分月温室气体排放量核算。", "ds_source": "", "ds_process_way": "", "ds_quality": "", "ds_acq_start_time": null, "ds_acq_end_time": null, "ds_acq_place": "冰冻圈", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "open-access", "ds_total_size": 3071109, "ds_files_count": 0, "ds_format": "*.xlsx,*.R", "ds_space_res": "", "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "9ae28db8-117a-4e0e-9948-6792e6107af3.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0a4269e1-65f4-45f1-aeba-88ea3068eebf", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.15" ], "quality_level": 0, "publish_time": "2026-05-11 15:04:48", "last_updated": "2026-05-14 16:55:17", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.cryosphere.db7321.2026", "i18n": { "en": { "title": "Cryosphere Inland Water Greenhouse Gases Database (CIWD-GHG)", "ds_format": "*.xlsx,*.R", "ds_source": "", "ds_quality": "", "ds_ref_way": "", "ds_abstract": "
This is a database called Cryosphere Inland Water Greenhouse Gases Database (CIWD-GHG), which provides spatial-temporally resolved greenhouse gases (CO2, CH4, and N2O) data from cryosphere inland waters (lakes, ponds, reservoirs, rivers, and streams). The dataset was created through a synthesis procedure.\r\n
To compile the dataset, we conducted searches in various sources including peer-reviewed papers, dissertations, theses, and public data repositories. The searches were conducted using platforms such as Web of Science, Google Scholar, ProQuest Dissertations & Theses Global, China National Knowledge Infrastructure, Arctic Data Center, Zenodo, Environmental Data Initiative, and PANGAEA. The search string is: (methane OR CH4 OR carbon dioxide OR CO2 OR nitrous oxide OR N2O OR greenhouse*) AND (river OR stream OR lake OR pond OR reservoir) AND (Arctic* OR Tibet* OR Greenland OR Antarctic OR glacier* OR permafrost). We ensured completeness by conducting multiple searches before April 2023.\r\n
We applied a consistent criterion for screening and selecting the searched results. Specifically, we included data on greenhouse gas concentrations or fluxes measured in inland water systems such as streams, rivers, ponds, lakes, and reservoirs that are associated with permafrost or glaciers. The study focused on the cryosphere extent, excluding sites outside this extent. Wetland ecosystems and inland waters in cold regions without glaciers or permafrost were also excluded. Additionally, floodplain lakes connected with river channels were excluded, except for those barely connected with high-closure river channels, which were included as lake sites. Gas concentration data in permanently ice-covered water bodies were not included. We also collected auxiliary data on waterbody physical and chemical characteristics, climate, and land cover to the extent possible.\r\n
The dataset was divided into two separate files: CryoLake.xlsx and CryoRiver.xlsx. CryoLake.xlsx contained data on lakes, ponds, and reservoirs, while CryoRiver.xlsx contained data on rivers and streams. Each file consisted of four sub-tables: source table (data sources), sites table (sites information), concentration table (concentration data), and flux table (flux data). All sub-tables were linked using unique source IDs, and the sites, concentration, and flux tables were further linked using unique site IDs. The temporal resolution varied, with daily data being the shortest resolution. Sub-daily measurements were averaged to daily data, and data reported in monthly, seasonal, and annual scales were also included. Considering the difficulty in obtaining cryosphere-related GHG data, we included all available data. The spatial resolution primarily focused on the plot scale, although aggregated sites were also included. Detailed spatiotemporal information of the measured data was recorded in the data table for further analysis. Due to regional heterogeneity, we did not have a uniform standard for dividing seasons. Instead, seasons were assigned based on the site descriptions provided in each study.\r\n
The R script file is the multilevel bootstrap method used for Inland water greenhouse gas emissions upscaling. The ziped file contains bootstrap results for further calculating zonal and monthly GHG emissions.", "ds_time_res": "", "ds_acq_place": "Cryosphere", "ds_space_res": "", "ds_projection": "", "ds_process_way": "", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "belong_to_nieer": false, "ds_topic_tags": [ "冰冻圈", "温室气体", "陆地碳汇" ], "ds_subject_tags": [ "大气科学" ], "ds_class_tags": [], "ds_locus_tags": [ "冰冻圈" ], "ds_time_tags": [ 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 ], "ds_contributors": [ { "true_name": "宋春林", "email": "songchunlin@scu.edu.cn", "work_for": "四川大学", "country": "中国" }, { "true_name": "王根绪", "email": "wanggx@scu.edu.cn", "work_for": "四川大学水利水电学院", "country": "中国" }, { "true_name": "刘少达", "email": "liushaoda@bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "宋春林", "email": "songchunlin@scu.edu.cn", "work_for": "四川大学", "country": "中国" }, { "true_name": "王根绪", "email": "wanggx@scu.edu.cn", "work_for": "四川大学水利水电学院", "country": "中国" }, { "true_name": "刘少达", "email": "liushaoda@bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" } ], "ds_managers": [ { "true_name": "宋春林", "email": "songchunlin@scu.edu.cn", "work_for": "四川大学", "country": "中国" } ], "category": "极地" }