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An overview for monitoring and prediction of pathogenic microorganisms in the atmosphere

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Fundamental Research 2024年第3期4卷 430-441页

作者： Jianping Huang Danfeng Wang Yongguan Zhu Zifeng Yang Maosheng Yao Xiaoming Shi Taicheng An Qiang Zhang Cunrui Huang Xinhui Bi Jiang Li Zifa Wang Yongqin Liu Guibing Zhu Siyu Chen Jian Hang Xinghua qiu Weiwei Deng Huaiyu Tian Tengfei Zhang Tianmu Chen Sijin Liu Xinbo Lian Bin Chen Beidou Zhang Yingjie Zhao Rui Wang Han Li Collaborative Innovation Center for Western Ecological Safety College of Atmospheric SciencesLanzhou UniversityLanzhou 730000China Research Center for Eco-Environmental sciences Chinese Academy of SciencesBeijing 100085China National Clinical Research Center for Respiratory Disease Guangzhou Institute of Respiratory HealthFirst Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease(Guangzhou Medical University)Guangzhou 510230China College of Environmental sciences and Engineering Peking UniversityBeijing 100871China china CDC Key Laboratory of Environment and Population Health National Institute of Environmental HealthChinese Center for Disease Control and PreventionBeijing 100021China Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health School of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China Vanke School of Public Health Tsinghua UniversityBeijing 100084China State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization Guangzhou Institute of GeochemistryChinese Academy of SciencesGuangzhou 510640China National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China State Key Laboratory of atmospheric Boundary Layer physics and atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Center for Pan-third Pole Environment Lanzhou UniversityLanzhou 730000China College of atmospheric sciences Lanzhou UniversityLanzhou 730000China School of atmospheric sciences Sun Yat-sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 510640

Corona virus disease 2019(COVID-19)has exerted a profound adverse impact on human *** have demonstrated that aerosol transmission is one of the major transmission routes of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Pathogenic microorganisms such as SARS-CoV-2 can survive in the air and cause widespread infection among *** monitoring of pathogenic microorganism transmission in the atmosphere and accurate epidemic prediction are the frontier guarantee for preventing large-scale epidemic *** of pathogenic microorganisms in the air,especially in densely populated areas,may raise the possibility to detect viruses before people are widely infected and contain the epidemic at an earlier *** multi-scale coupled accurate epidemic prediction system can provide support for governments to analyze the epidemic situation,allocate health resources,and formulate epidemic response *** review first elaborates on the effects of the atmospheric environment on pathogenic microorganism transmission,which lays a theoretical foundation for the monitoring and prediction of epidemic ***,the monitoring technique development and the necessity of monitoring pathogenic microorganisms in the atmosphere are summarized and ***,this review introduces the major epidemic prediction methods and highlights the significance to realize a multi-scale coupled epidemic prediction system by strengthening the multidisciplinary cooperation of epidemiology,atmospheric sciences,environmental sciences,sociology,demography,*** summarizing the achievements and challenges in monitoring and prediction of pathogenic microorganism transmission in the atmosphere,this review proposes suggestions for epidemic response,namely,the establishment of an integrated monitoring and prediction platform for pathogenic microorganism transmission in the atmosphere.

关键词： Aerosol transmission Epidemic monitoring methods Epidemic prediction modelsEpidemic response Multidisciplinary cooperation

BCC-CSM2模式耦合同化对北极海冰次季节预测的影响

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气象学报 2024年第3期82卷 340-355页

作者：邱孙俊杰刘向文姚隽琛中国气象科学研究院北京100081 中国气象局地球系统数值预报中心北京100081

近年来北极海冰的加速融化对北半球天气和气候的影响逐渐加剧,开展准确的海冰次季节预测已成为迫切需求。基于北京气候中心气候系统模式(BCC-CSM2),采用多种耦合同化方案(大气同化、海洋-大气同化、海洋-海冰-大气同化)产生模式初值,开... 详细信息

近年来北极海冰的加速融化对北半球天气和气候的影响逐渐加剧,开展准确的海冰次季节预测已成为迫切需求。基于北京气候中心气候系统模式(BCC-CSM2),采用多种耦合同化方案(大气同化、海洋-大气同化、海洋-海冰-大气同化)产生模式初值,开展大气(FST-A)、海洋-大气(FST-AO)、海洋-海冰-大气(FST-AOI)预测试验,进而探讨了多圈层耦合同化对北极海冰次季节预测的影响。结果表明,随着耦合同化分量的增加,模式对海冰密集度气候态和变率的预测技巧逐渐提高,其中FSTAOI在所有试验中表现最优。海洋-海冰-大气同化对预测的影响存在明显的季节性差异,其在大多数月份(尤其是少冰期(9—10月))能够明显降低海冰密集度预测误差,但在快速融冰期(6—7月),若干海冰边缘区(波弗特海、东西伯利亚海、拉普捷夫海、喀拉海附近)的密集度误差随预测时间延长而快速增大。因此,多圈层耦合同化在总体上能够有效改善北极海冰次季节预测,但其在快速融冰阶段对预测的影响存在较大不确定性。进一步诊断表明,在快速融冰期,采用海洋-海冰-大气同化初值的试验在预报开始阶段(主要指第1周)低估了海冰边缘区的密集度。在海冰-反照率正反馈机制影响下,这可能导致模拟地表短波辐射吸收增加,引起海水升温和海冰融化加快,进而导致海冰误差快速增长。未来研究将致力于继续提升海洋-海冰-大气多分量耦合同化的协调,以持续改进北极海冰次季节—季节预测能力。

关键词： BCC-CSM2 耦合同化北极海冰次季节预测

不同气候变化情景下中国北方苹果花期霜冻风险研究

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中国农业气象 2024年第1期45卷 33-44页

作者：邱星霖林泽全李璨俞海洋王瑛北京师范大学环境演变与自然灾害教育部重点实验室北京100875 应急管理部−教育部减灾与应急管理研究院北京100875 河北雄安新区气象局河北071700 中国气象局雄安大气边界层重点开放实验室河北071700

中国北方苹果主产区位于华北平原和黄土高原,苹果花期霜冻灾害事件对果农收入和产区经济造成严重影响。未来气候变化会加剧极端天气气候事件的发生频率和强度。本研究基于NEX-GDDP共享的气候模式数据,利用泰勒图选取对苹果花期最低气温... 详细信息

中国北方苹果主产区位于华北平原和黄土高原,苹果花期霜冻灾害事件对果农收入和产区经济造成严重影响。未来气候变化会加剧极端天气气候事件的发生频率和强度。本研究基于NEX-GDDP共享的气候模式数据,利用泰勒图选取对苹果花期最低气温拟合能力最优的7个模式,计算未来苹果花期最低气温年遇值,采用极值分布传递函数校正方法对其订正,预估气候变化下中国北方苹果霜冻灾害及减产风险。以研究区各地遭遇30a一遇的苹果花期霜冻灾害强度为例,RCP4.5情景下未来近期和远期,河南、山西、陕西北部、宁夏北部区域为主要受灾区域,以最低气温−3~−2℃为主,减产率最高的为河南、宁夏、山西、陕西省北部地区,中国北方苹果总减产率在2.47%~5.22%。RCP8.5情景下,最低气温−3℃以下霜冻灾害区扩大至河南全境、山东中部等地,中国北方苹果总减产率在4.57%~12.39%。未来这些地区苹果种植需加强对霜冻灾害风险的防范。

关键词：霜冻灾害风险评估减产气候模式苹果

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一次极端暴雨过程低空急流变化机制分析

大气科学 2024年第4期48卷 1608-1626页

作者：田利庆李舒文邱晓滨冉令坤申冬冬刘宇琛河北省气象与生态环境重点实验室石家庄050021 中国气象局雄安大气边界层重点开放实验室雄安新区071800 河北省气象科学研究所石家庄050021 中国科学院大气物理研究所北京100029 天津市海洋气象重点实验室天津300074 中国科学院大学北京100049 云南省大湄公河次区域气象灾害与气候资源重点实验室云南大学昆明650500

2021年7月19~21日河南极端暴雨伴有显著的低空急流活动。本文利用ERA5(Fifth Generation of ECMWF Reanalyses)数据,采用等压坐标系水平运动方程、动能方程和位势高度梯度方程分析影响低空急流发展的关键物理因素。分析表明,低空急流中... 详细信息

2021年7月19~21日河南极端暴雨伴有显著的低空急流活动。本文利用ERA5(Fifth Generation of ECMWF Reanalyses)数据,采用等压坐标系水平运动方程、动能方程和位势高度梯度方程分析影响低空急流发展的关键物理因素。分析表明,低空急流中心首先从郑州附近925 hPa发展起来,然后垂直倾斜地向西北方向发展增强,中心位置先后抬升到850 hPa和700 hPa。低空急流纬向风和经向风局地变化主要受位势高度水平梯度的影响。郑州西侧山区存在位势高度低值系统,郑州东北侧平原地区为位势高度高值区,二者在郑州附近产生显著的纬向梯度力,与纬向东风耦合做功,驱动低空急流动能增长。位势高度这种异常分布主要与地表位势高度和近地层虚位温垂直积分有关。位势高度纬向梯度方程计算表明,垂直速度纬向梯度引起的位温垂直平流和非绝热加热纬向梯度项是导致位势高度纬向梯度局地变化的主要强迫项。总体上,近地面层山区相对低温区和平原地区相对高温区对低空急流发展演变有重要影响。

关键词：极端暴雨低空急流动能位势高度梯度

Must mercury enriched substrate be atmospheric mercury sources?

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Acta Geochimica 2006年第S1期 27-27页

作者： Shaofeng WANG1,2, Xinbin FENG1, Guangle qiu1, Lihai SHANG1,2, Ping LI1,2, Zhongqing WEI1,2 1 State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, chinese academy of sciences, Guiyang 550002, china 2 Graduate School of chinese academy of sciences, beijing 100039, china

Possible triggering relationship of six Mw > 6 earthquakes in 2018–2019 at Philippine archipelago

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Acta Oceanologica Sinica 2021年第7期40卷 142-158页

作者： qiu Zhong Yangfan Deng Zhigang Peng Lingyuan Meng Key Laboratory of Ocean and Marginal Sea Geology South China Sea Institute of OceanologyInnovation Academy of South China Sea Ecology and Environmental EngineeringChinese Academy of SciencesGuangzhou 510301China Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) Guangzhou 511458China School of Earth and atmospheric sciences Georgia Institute of TechnologyAtlantaGA 30332USA State Key Laboratory of Isotope Geochemistry Guangzhou Institute of GeochemistryChinese Academy of SciencesGuangzhou 510640China china Earthquake Networks Center(CENC) Beijing 100045China

Philippine archipelago (PA) has strong background seismicity,but there is no systematic study of earthquake triggering in this region. There are six earthquakes (M_(w) > 6) occurred between 2018/12/29 and 2019/09/29 in PA,which provides an excellent opportunity to investigate the triggering relationship among these events. We calculate the static Coulomb stress changes of the first five events,and find that the local seismicity after the 2018/12/29 M_(w) 7.0 earthquake is mostly associated with positive Coulomb stress changes,including the 2019/05/31 M_(w) 6.1 event,suggesting a possible triggering relationship. However,we cannot rule out the dynamic triggering mechanism,due to increased microseismicity in both positive and negative stress change regions,and an incomplete local catalog,especially right after the first M_(w) 7.0 mainshock. The dynamic stresses from these M_(w) > 6 events are large enough (from 5 kPa to 3532 kPa) to trigger subsequent events,but a lack of seismicity and waveform evidence does not support delayed dynamic triggering among these events,even the shortest time interval is less than 24 hours. In the past 45 years,the released seismic energy shows certain peaks every 5–10 years. However,earthquakes with M_(w) > 6.0 were relatively infrequent between 2004 and 2018 at PA. Hence,it is possible that several regions are relatively late in their earthquake cycles,which would enhance their susceptibility of being triggered by earthquakes at nearby and regional distances.

关键词： static triggering dynamic triggering seismicity ETAS model Philippine archipelago

High-resolution Projection Dataset of Agroclimatic Indicators over Central Asia

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Advances in atmospheric sciences 2022年第10期39卷 1734-1745页

作者： Yuan qiu Jinming FENG Zhongwei YAN Jun WANG Key Laboratory of Regional Climate-Environment for Temperate East Asia(RCE-TEA) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

To understand the potential impacts of projected climate change on the vulnerable agriculture in Central Asia(CA),six agroclimatic indicators are calculated based on the 9-km-resolution dynamical downscaled results of three different global climate models from Phase 5 of the Coupled Model Intercomparison Project(CMIP5),and their changes in the near-term future(2031-50)are assessed relative to the reference period(1986-2005).The quantile mapping(QM)method is applied to correct the model data before calculating the *** show the QM method largely reduces the biases in all the *** season length(GSL,day),summer days(SU,day),warm spell duration index(WSDI,day),and tropical nights(TR,day)are projected to significantly increase over CA,and frost days(FD,day)are projected to ***,changes in biologically effective degree days(BEDD,°C)are spatially *** high-resolution projection dataset of agroclimatic indicators over CA can serve as a scientific basis for assessing the future risks to local agriculture from climate change and will be beneficial in planning adaption and mitigation actions for food security in this region.

关键词： agroclimatic indicators Central Asia near-term future agriculture quantile mapping

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全格陵兰冰盖表面融水卫星遥感观测

自然资源遥感 2024年第1期36卷 110-117页

作者：张闻松朱雨欣邱玉宝王裕涵刘金昱杨康南京大学地理与海洋科学学院南京210023 江苏省地理信息技术重点实验室南京210023 中国南海研究协同创新中心南京210023 中国科学院空天信息创新研究院中国科学院数字地球重点实验室北京100094 中国科学院空天信息创新研究院和芬兰气象研究所北极观测联合研究中心索丹屈莱999018

每年夏季,格陵兰冰盖表面消融产生大量融水。冰面融水由冰面河输送,存储在冰面湖或注水冰裂隙中,形成了规模庞大、结构复杂的水文系统。然而,目前研究对全格陵兰冰面融水空间分布的理解十分有限。文章利用134景10 m空间分辨率的Sentine... 详细信息

每年夏季,格陵兰冰盖表面消融产生大量融水。冰面融水由冰面河输送,存储在冰面湖或注水冰裂隙中,形成了规模庞大、结构复杂的水文系统。然而,目前研究对全格陵兰冰面融水空间分布的理解十分有限。文章利用134景10 m空间分辨率的Sentinel-2遥感影像,提取了2019年消融旺盛期格陵兰冰面融水遥感信息;进一步,对比分析了遥感观测的冰面融水分布与区域大气气候模型(regional atmospheric climate model,RACMO)模拟的冰面融水径流量。结果表明:①2019年消融旺盛期,格陵兰冰面融水面积为9900.9 km^(2),融水体积为6.8 km^(3);②格陵兰冰面融水的空间分布差异较大,呈现明显的“西多东少”“北多南少”的态势;③格陵兰冰面融水主要由冰面河组成,冰面河占冰面融水总体积的57.1%,其次是注水冰裂隙(25.6%)和冰面湖(17.3%);④RACMO在多数流域准确模拟了冰面融水径流区域。研究反映了高分辨率遥感在格陵兰冰面水文研究中的应用潜力,提升了对冰面融水输送与存储等关键水文过程的理解。

关键词：冰面河冰面湖注水冰裂隙 Sentinel-2 格陵兰冰盖

Projection of weather potential for winter haze episodes in beijing by 1.5℃ and 2.0℃ global warming

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Advances in Climate Change Research 2020年第3期11卷 218-226页

作者： qiu Liang YUE Xu HUA Wei LEI Ya-Dong School of atmospheric sciences Chengdu University of Information and TechnologyChengdu610225China Jiangsu Key Laboratory of atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environment Science and EngineeringNanjing University of Information Science&TechnologyNanjing210044China Climate Change Research Center Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China University of chinese academy of sciences Beijing100049China

Haze episodes become very frequent in beijing over the past decade,and such trend is related to favorable weather ***,we project the changes of weather conditions conducive to winter haze episodes in beijing by 1.5℃ and 2.0℃ global warming using Haze Weather Index(HWI)and data of ensemble simulations from the Community Earth System Model(CESM)low-warming *** to present day(2006–2015),the frequency in winter season is projected to increase by 14% for regular haze episodes(HWI>0)and 21% for severe haze episodes(HWI>1)at the 1.5℃ global *** shows larger increases of 27% for regular and 18%for severe haze events at the 2℃ global *** additional warming of 0.5℃ largely enhances the persistence of weather conditions conducive to haze *** increased temperature contrast between near-surface and mid-troposphere in eastern Asia accounts for 57% and 81% of the change in HWI by 1.5℃ and 2℃ warming,*** increased haze weather potential caused by climate warming,we suggest that additional efforts in emission reductions of carbon dioxide and air pollution are necessary to mitigate haze episodes in beijing.

关键词： Haze 1.5℃global warming 2℃global warming china Community earth system model(CESM)