地球科学进展 doi: 10.11867/j.issn.1001-8166.2025.017

   

大气病原微生物监测预警的研究进展*
黄建平1,连鑫博1,2,王睿1,王丹凤1   
  1. (1. 兰州大学 西部生态安全协同创新中心 大气科学学院,甘肃 兰州 730000; 2. 兰州大学 资源环境学院,甘肃 兰州 730000)
  • 基金资助:
    广州实验室自立项目(编号:SRPG22-007);国家自然科学基金委员会—中国科学院学科发展战略研究联合项目(编号: L2224041/XK2022DXC005);国家资助博士后研究人员计划(编号:GZC20231001)资助.

Monitoring and Early Warning of Atmospheric Pathogenic Microorganisms: A Review of Recent Studies*

HUANG Jianping1, LIAN Xinbo1,2, WANG Rui1, WANG Danfeng1   

  1. (1. Collaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; 2. School of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China)
  • About author:HUANG Jianping, research areas include climate change in semi-arid regions. E-mail: hjp@lzu.edu.cn
  • Supported by:
    Project supported by the Self-supporting Program of Guangzhou Laboratory (Grant No. SRPG22-007); Frontier of Interdisciplinary Research on Monitoring and Prediction of Pathogenic Microorganisms in the Atmosphere (Grant No. L2224041/XK2022DXC005); The National Funded Postdoctoral Researcher Program (Grant Number: GZC20231001).
气候变化正在给公共卫生带来不容忽视的挑战,对病原微生物和传染病的监测预警是预 防大规模公共卫生危机和生物安全风险的重要前提。然而,目前整体缺乏气候与环境变化对病原 微生物传播的监测预警的研究和关注,特别是针对通过空气传播的病原微生物带来的健康威胁。 通过分析病原微生物监测预警的必要性和前瞻性,总结了病原微生物及传染病监测预警领域面临 的关键科学问题,梳理了传染病监测预警的方法和应用的国内外研究基础与条件,包括气候变化 对大气中病原微生物的影响、大气中病原微生物的监测、传染病预测模型与系统等。未来亟需加 强大气病原微生物形成、来源解析、环境演变和传播机制的基础研究;加快推进大气病原微生物的 高精度实时监测技术研发,通过多部门合作建立国家级、省级病原微生物和传染病监测网络;从人 工智能、大数据和基因组学等多个维度切入,强化数据收集与共享,优先发展传染病的预测与预 警,为应对气候危机下的传染病监测预警与生物安全风险防范提供科技支撑。
Abstract:The ongoing public health challenges posed by climate change cannot be ignored. Monitoring and early warning of pathogenic microorganisms and infectious diseases is a key precondition for preventing large-scale public health crisis and biosecurity risks. However, insufficient research and attention have been paid to the monitoring and early warning of pathogenic microorganism spread due to climate and environmental change, especially for the health threats caused by airborne pathogenic microorganisms. By analyzing the necessity and foresight of monitoring and early warning of pathogenic microorganisms, the key scientific problems in the field of monitoring and early warning of pathogenic microorganisms and infectious diseases are summarized, and the research basis and conditions of monitoring and early warning methods and applications of infectious diseases are sorted out. It includes the impact of climate change on pathogenic microorganisms in the atmosphere, the monitoring of pathogenic microorganisms in the atmosphere, and the prediction model and system of infectious diseases. The urgent need to strengthen the basic research on the formation, source analysis, environmental evolution and transmission mechanism of atmospheric pathogenic microorganisms in the future is discussed in this paper. The research and development of high-precision real-time monitoring technology for pathogenic microorganisms in the atmosphere should be accelerated, and national and provincial pathogenic microorganisms and infectious disease monitoring networks should be established through multi-departmental cooperation. Multiple dimensions such as artificial intelligence, big data and genomics should be used as entry points to enhance data collection and sharing. Priority should be given to the development of prediction and early warning of infectious diseases to provide scientific and technological support for infectious disease monitoring and early warning and biosecurity risk prevention under the climate crisis.

中图分类号: 

[1] 姚檀栋, 张太刚, 王伟财, 张国庆, 刘时银, 安宝晟. 亚洲水塔冰湖变化与冰湖溃决灾害风险及应对[J]. 地球科学进展, 2025, 40(3): 221-227.
[2] 吴涛, 徐泽阳, 闫文琦, 费李莹, 刘荷冲, 赵靖舟, 李军, 杜治伟. 准噶尔盆地莫索湾地区侏罗系超压预测技术研究[J]. 地球科学进展, 2024, 39(4): 429-439.
[3] 王一超. 基于多源数据融合的可持续发展目标监测与评估研究进展[J]. 地球科学进展, 2024, 39(2): 181-192.
[4] 李珺, 赵杨, 陈钊州, 张乐乐, 曹欢, 李世昌. 基于地球物理驱动的裂缝性地层三维坍塌压力预测及应用[J]. 地球科学进展, 2024, 39(11): 1196-1209.
[5] 刘金贵, 车助镁, 李尚鲁, 仉天宇. 2019年温州湾藻华期间海洋生态要素演变特征[J]. 地球科学进展, 2023, 38(2): 183-191.
[6] 贾黎黎, 李婷婷, 朱鑫, 易隆科, 罗思亮. 基于改进随机森林模型的多要素层次插值技术在土壤硒元素空间分布上的运用[J]. 地球科学进展, 2023, 38(12): 1259-1270.
[7] 李姜辉, 余凤玲, 牛雄伟, 周天, 张运修, 李雯菱. 海底碳封存监测技术体系研究及未来发展[J]. 地球科学进展, 2023, 38(11): 1121-1144.
[8] 周惜荫, 高晓清, 常毅, 赵素平, 李培都. 城市大气挥发性有机物研究进展[J]. 地球科学进展, 2022, 37(8): 841-850.
[9] 王劲松, 姚玉璧, 王莺, 王素萍, 刘晓云, 周悦, 杜昊霖, 张宇, 任余龙. 青藏高原地区气象干旱研究进展与展望[J]. 地球科学进展, 2022, 37(5): 441-461.
[10] 李一民, 谭振宇, 杨辰, 何峰, 孟迪, 罗菊花, 段洪涛. 基于多源卫星的滇池藻华提取机器学习算法研究[J]. 地球科学进展, 2022, 37(11): 1141-1156.
[11] 王振峰, 蒋宗立, 刘时银, 马致远, 张震. 中帕米尔甘多冰川跃动遥感监测[J]. 地球科学进展, 2022, 37(11): 1181-1193.
[12] 王凯, 张少杰, 马娟, 杨红娟, 刘敦龙, 杨超平. 大数据环境下滑坡宏观位移阶段空间分布规律及预警判据研究[J]. 地球科学进展, 2022, 37(10): 1054-1065.
[13] 摆玉龙, 路亚妮, 刘名得. 基于变分模态分解的机器学习模型择优风速预测系统[J]. 地球科学进展, 2021, 36(9): 937-949.
[14] 王丹,姜亦飞,王先桥,王素芬,何恩业,张蕴斐. 我国马尾藻金潮生态动力学研究进展[J]. 地球科学进展, 2021, 36(7): 753-762.
[15] 汪芋君, 任宏利, 王琳. 第三极地区气温和积雪的季节—年际气候预测研究[J]. 地球科学进展, 2021, 36(2): 198-210.
阅读次数
全文


摘要