四川盆地由于风小、潮湿、多云等不利气象条件，冬季持续气溶胶污染频发。基于2015-2021年的长期观测数据分析发现，四川盆地4个代表性站点经常同时出现PM2.5污染，并伴随着850hPa以上气象条件的变化，这表明四川盆地区域性冬季空气污染与大尺度的同步模式存在联系。利用T模式主成分分析法，将南亚局地冬季主要的850hPa 天气模式划分为六种模式。\n
本数据集包括4个代表性站点2015-2021年冬季时间(12月、1月和2月)PM2.5浓度的逐日变化，以及18个城市站点2017年1月1-7日PM2.5浓度的逐时变化。气象资料(xls)覆盖了4个代表性站点2015-2021年冬季时位势温度和2017年1月1-7日露点温度的日变化。", "ds_source": "
空气质量监测数据来自中国生态环境部在南海建立的空气质量监测点。", "ds_process_way": "
实地监测记录。", "ds_quality": "
数据质量较好。", "ds_acq_start_time": "2015-12-01 00:00:00", "ds_acq_end_time": "2021-02-28 00:00:00", "ds_acq_place": "重庆,成都,绵阳,德阳,乐山,眉山,雅安,资阳,自贡,宜宾,泸州,内江,广安,南充,遂宁,广元,达州,巴中", "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": "login-access", "ds_total_size": 136119, "ds_files_count": 2, "ds_format": "excel", "ds_space_res": "", "ds_time_res": "日", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "5e482169-c98d-4b3e-8921-c51cccc23a5a.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "a3ce23a2-c353-4383-a544-65c8f218579f", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.15" ], "quality_level": 3, "publish_time": "2024-06-20 15:38:33", "last_updated": "2026-01-14 10:52:51", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.DVN.DB6526.2024", "i18n": { "en": { "title": "Dataset on Significant Inhibition of Aerosol Radiation Effects by Clouds under Typical Pollution Weather Patterns in Sichuan Basin (2015-2021)", "ds_format": "excel", "ds_source": "
The air quality monitoring data comes from the air quality monitoring point established by the Ministry of Ecology and Environment of China in the South China Sea.", "ds_quality": "
The data quality is good.", "ds_ref_way": "", "ds_abstract": "
This dataset includes the daily variation of PM2.5 concentration at four representative sites during the winter period of 2015-2021 (December, January, and February), as well as the hourly variation of PM2.5 concentration at 18 urban sites from January 1-7, 2017. The meteorological data (xls) covers the daily variations of winter potential temperature from 2015 to 2021 and dew point temperature from January 1-7, 2017 at four representative stations.
", "ds_time_res": "日", "ds_acq_place": "Chongqing, Chengdu, Mianyang, Deyang, Leshan, Meishan, Ya'an, Ziyang, Zigong, Yibin, Luzhou, Neijiang, Guang'an, Nanchong, Suining, Guangyuan, Dazhou, Bazhong", "ds_space_res": "", "ds_projection": "", "ds_process_way": "On site monitoring records.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "四川盆地", "气溶胶污染", "长期观测", "主成分分析法", "云辐射" ], "ds_subject_tags": [ "大气科学" ], "ds_class_tags": [], "ds_locus_tags": [ "重庆", "成都", "绵阳", "德阳", "乐山", "雅安", "资阳", "自贡", "宜宾", "泸州", "内江", "广安", "南充", "遂宁", "广元", "达州", "巴中", "眉山" ], "ds_time_tags": [ 2015, 2016, 2017, 2018, 2019, 2020, 2021 ], "ds_contributors": [ { "true_name": "谢旻", "email": "minxie@nju.edu.cn", "work_for": "南京大学大气科学学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "谢旻", "email": "minxie@nju.edu.cn", "work_for": "南京大学大气科学学院", "country": "中国" } ], "ds_managers": [ { "true_name": "谢旻", "email": "minxie@nju.edu.cn", "work_for": "南京大学大气科学学院", "country": "中国" } ], "category": "大气本底" }