大气组分垂直廓线观测是厘清区域大气污染形成、演变与输送过程的重要基础。受现有技术条件与观测成本限制，当前大气垂直廓线观测数据较为匮乏。\n
本研究依托被动遥感技术，在中国七大重点区域32个观测站点开展气溶胶、二氧化氮（NO₂）及甲醛（HCHO）连续观测，构建了一套2019-2023 年间高时间分辨率（约 15 分钟）大气组分垂直廓线观测数据集。系统刻画了三类污染物的垂直分布特征、季节变化规律与日变化特征，揭示了我国不同区域大气组分的长期演变趋势。\n
该数据集可为区域环境治理与政策制定提供重要科学依据；数据开放共享有助于科研学界深入探究大气污染源汇响应关系，阐明大气组分对区域及全球气候系统的影响与反馈作用机制。", "ds_source": "", "ds_process_way": "", "ds_quality": "", "ds_acq_start_time": "2019-01-01 00:00:00", "ds_acq_end_time": "2023-12-31 00:00:00", "ds_acq_place": "中国", "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": 392390469, "ds_files_count": 0, "ds_format": "", "ds_space_res": "", "ds_time_res": "15min", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "abe1b9c9-5712-40b4-a517-436d568a982c.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": "2026-05-19 10:38:06", "last_updated": "2026-05-19 10:38:06", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.atmosphere.db7324.2026", "i18n": { "en": { "title": "A dataset of ground-based vertical profile observations of aerosol, NO2, and HCHO from the hyperspectral vertical remote sensing network in China (2019-2023)", "ds_format": "", "ds_source": "", "ds_quality": "", "ds_ref_way": "", "ds_abstract": "
Vertical profile observations of atmospheric composition are crucial for understanding the generation, evolution, and transport of regional air pollution. However, existing technological limitations and costs have resulted in a scarcity of vertical profile data. This study introduces a high-time-resolution (approximately 15 minutes) dataset of vertical profile observations of atmospheric composition (aerosols, NO2, and HCHO) conducted using passive remote sensing technology across 32 sites in seven major regions of China from 2019 to 2023. The study meticulously documents the vertical distribution, seasonal variations and diurnal pattern of these pollutants, revealing long-term trends in atmospheric composition across various regions of China. This dataset provides essential scientific evidence for regional environmental management and policy-making. Its sharing would facilitate the scientific community in exploring of source-receptor relationships, investigating the impacts of atmospheric composition on regional and global climate and feedback mechanisms.", "ds_time_res": "", "ds_acq_place": "China", "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, "ds_topic_tags": [ "气溶胶", "二氧化氮", "甲醛", "被动遥感技术", "大气垂直廓线" ], "ds_subject_tags": [ "大气科学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 2019, 2020, 2021, 2022, 2023 ], "ds_contributors": [ { "true_name": "邢成志", "email": "xingcz@aiofm.ac.cn", "work_for": "中国科学院合肥物质科学研究院安徽光学精密机械研究所", "country": "中国" }, { "true_name": "刘诚", "email": "chliu81@ustc.edu.cn", "work_for": "中国科学技术大学精密机械与精密仪器系", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "邢成志", "email": "xingcz@aiofm.ac.cn", "work_for": "中国科学院合肥物质科学研究院安徽光学精密机械研究所", "country": "中国" }, { "true_name": "刘诚", "email": "chliu81@ustc.edu.cn", "work_for": "中国科学技术大学精密机械与精密仪器系", "country": "中国" } ], "ds_managers": [ { "true_name": "邢成志", "email": "xingcz@aiofm.ac.cn", "work_for": "中国科学院合肥物质科学研究院安徽光学精密机械研究所", "country": "中国" } ], "category": "气象" }