太湖表层沉积物多环芳烃的空间分布、来源及其风险

随着太湖流域社会与经济的发展,多环芳烃(PAHs)在各种环境介质中逐渐累积,污染日益严重,可能对太湖生态环境及周边人体健康构成威胁。为探究太湖沉积物PAHs的来源及生态风险,于2021年12月在太湖采集30个表层沉积物样品,利用气相色谱-质谱联用仪(GC-MS)检测样品中16种PAHs含量;利用受体模型和苯并[a]芘(BaP)毒性当量法进行来源解析及生态风险评估,并将各来源贡献与毒性当量浓度相结合,量化源风险。结果表明,太湖表层沉积物中16种PAHs总含量介于124~592 ng/g之间,平均值为294 ng/g,中值为279 ng/g;高环多环芳烃(HMW PAHs)为主要组分,占∑PAHs的67%。高含量区域位于竺山湾、梅梁湾、贡湖湾和西太湖,与国内外其他湖泊沉积物相比,太湖沉积物PAHs含量处于较低水平。源解析的结果表明,太湖表层沉积物中PAHs交通排放源贡献率为29.1%、煤炭燃烧源贡献率为26.7%、生物质燃烧源贡献率为28.7%、石油源贡献率为15.6%。生态风险评价结果表明,交通排放源、生物质燃烧源、煤炭燃烧源和石油源的BaP毒性当量含量(TEQ_BaP)均值分别为19.34、17.81、16.33和9.1 ng/g,均小于70 ng/g,几乎处于无风险水平。西太湖、贡湖湾和梅梁湾的部分区域ΣTEQ_BaP大于70 ng/g属于潜在风险区,具有一定潜在毒性。在后续的污染治理中应重点关注太湖西北部地区污染物的排放。本研究可为沉积物中PAHs污染的研究提供数据支撑,为地方政府精准、高效地管控PAHs污染提供理论依据。     

极端洪水导致的湖泊水位抬升和氮磷输入增加对苦草(Vallisneria natans)的复合影响

据全球气候变化模型预测,未来极端洪水事件将呈现增多和加剧态势。极端洪水对沉水植物功能性状、生长发育状况及整个生态系统均有深远的影响,研究极端洪水对沉水植物生长发育的影响对理解和预测气候变化过程中水生态系统的变化具有重要意义。本文针对极端洪水事件引起的水位急剧上升和营养负荷量增加双重效应,在实验周期90 d内设置对照(水位保持75 cm)、2种极端洪水条件(水位在第1天从75 cm快速上升至150 cm + NP输入、水位从75 cm逐步上升至150 cm + NP输入)以及水位保持75 cm + NP输入4项处理(后3项处理中营养输入总量相同),研究了极端洪水对沉水植物苦草(Vallisneria natans)生长、繁殖对策及生物量分配的影响,实验过程中还同步监测了浮游植物、附着藻类和水体营养状况(TN和TP)。在苦草的17个测定指标中,只有根生物量分配和有性繁殖分配在4个处理下无明显变化。从水位的单独作用看,相对于营养增加且水位恒定的处理,两种洪水条件(水位急剧上升和逐步上升)均降低了苦草的分株数、叶片数、间隔子数、间隔子总长、最大根长、花果数以及各器官生物量和总生物量,促进了人工基质表面附着藻类的生长。水位急剧上升时,植株对间隔子的生物量投资倾向于最小,而株高和植株对叶的生物量投资倾向于最大。从营养负荷的单独作用来看,相对于对照组,营养增加且水位恒定的处理中水体N浓度显著增加,促进浮游植物和苦草表面附着藻类的生长,但是从二者的Chl.a浓度来看,浮游植物遮光作用相对较大,抑制了苦草叶、根和间隔子的生长,但有性繁殖生物量无明显变化。从水位和营养负荷联合作用的模式来看,水位上升和营养负荷两个环境因素的联合作用会使入湖营养负荷加强水位上升对沉水植物生长的影响效应,二者的联合作用使叶、根、间隔子和有性繁殖生物量均大大降低。因此,极端洪水对沉水植物的不利影响较大,一方面水位抬升会直接影响沉水植物,另一方面会通过浮游植物间接影响沉水植物生长发育。     

葛洲坝至胭脂坝长江干流段江豚活动规律

长江江豚是我国一级保护野生动物,也是长江生态系统的指示性物种,其种群数量恢复情况及活动规律一直备受关注。本文选择长江宜昌段江豚活动频繁的葛洲坝下游至胭脂坝江段为研究区域,于2021年6月-2022年5月采用定点目测、水上流动监测与无人机监测相结合的方法分区监测长江江豚的游泳行为,分析长江江豚的活动规律,构建了长江江豚出水头次的零膨胀泊松回归模型,识别影响长江江豚出水头次的关键因素,建立长江江豚出水头次与各因素间的相关关系。结果表明:(1)葛洲坝至胭脂坝长江干流段监测到最大江豚出水头次为19头次,长江江豚集群规模以2~3头最为常见,占比达58.1%;长江江豚主要表现出4种行为特征,各行为占比从大到小依次为:玩耍＞休息＞摄食＞抚幼。(2)长江江豚在葛洲坝下游近坝区(A区,葛洲坝至至喜长江大桥)出水头次最多,且在秋冬季节累计出水头次多于春夏季节,冬季累计出水头次最高,达252头次。(3)长江江豚出水头次与电站下泄流量呈显著负相关;浊度增大,长江江豚出水的概率减小。本文研究结果对长江江豚生态保护策略及长江十年禁渔效果评估具有重要参考价值。     

基于周仲瑛外感热病学术思想构建中医急诊诊治思路探析

目的：阐述周仲瑛教授外感热病学术思想对江苏中医急诊诊治思路的指导作用。方法：通过文献整理,归纳总结周教授外感热病学术思想;通过病案分析与数据挖掘的方法,分析周教授学术思想在中医急诊外感热病中的运用。结果：周教授创建的中医病机辨证理论是外感热病中医急诊辨治新体系的重要特征,主张审证求机,重视病机演变,提出截断逆转、祛邪外出两大治则。数据分析结果显示,江苏中医急诊学临床运用的外感热病诊治思路、方法与周教授的学术观点、学术理论相一致,学术思想一脉相承。结论：以周教授中医病机辨证理论为特征的外感热病中医急诊辨治新体系为临床诊治提供了纲领性指导,对中医急诊临床的学术影响举足轻重。     

近30年夏季亚欧大陆中高纬度阻塞高压的统计特征

文中利用1970～2001年NCEP再分析500 hPa逐日高度场资料,根据阻塞高压的天气学定义,采用客观统计方法检索出近32 a亚欧中高纬度392个阻塞高压个例,对其进行了气候学分析.结果表明,亚欧中高纬地区夏季阻塞高压活动频繁,10 d以下的过程占绝对多数,地理分布主要集中在45～70°N之间,纬向上可划分5个高发区,其中乌拉尔山和贝加尔湖东部阻高活动频次最高,同时,每个区域中又存在着相应的阻高活跃区.亚欧中高纬地区夏季阻高活动具有明显的季节内变化特征.6月份,阻塞活动多发生在乌拉尔山地区和鄂霍次克海地区,以双阻为主要形势;7月份,欧洲区和贝加尔湖地区的阻塞活动有所增多,尤其贝加尔湖东部地区增多明显,而乌拉尔山地区的阻塞形势明显减少,鄂霍次克海地区的阻塞活动位置向北移动,多发生在60°N以北,双阻形势逐渐减弱,贝加尔湖地区的中阻形势有所增强.8月份,阻塞形势主要存在于贝加尔湖东西两区,中阻形势占据主导地位.亚欧中高纬地区夏季阻塞高压活动年际变化特征也很突出,且这种年际振荡有明显的地理差异.另外,研究表明亚洲北部的阻高活动多以稳定型为主,移动型阻高个例仅占6.6%.移动型阻高以起源于乌拉尔山地区最多,移距最长,生命期最长.偶极子类阻高多集中在贝加尔湖东部与乌拉尔山地区,约占该地区总阻高频次的62.0%和49.7%,平均生命期分别达到7 d/次和9 d/次以上.     

基于三角形网格的气象场等值线自动分析

针对矩形网格法的不足，提出了用三角形网格法实现气象场等值线自动分析方法。通过对站点资料的边界插值、三角形剖分等处理后，再在剖分出来的三角形网格中按照一定方式连接等值线即可实现等值线的自动分析。给出了等值线自动生成算法，并将实例的分析结果同Grads绘制图进行对比分析。结果表明，该方法不仅有效可行，而且分析的结果更为精确合理。     

重庆城区浓雾的基本特征

统计分析沙坪坝1951～2002年间发生的浓雾事件，结合2001年12月重庆市雾的外场试验资料，探索重庆市主城区浓雾的基本特征。重庆主城区浓雾随年代演变有减缓趋势；主城区浓雾是自然雾与烟尘等的混合物，河谷及城市效应使雾更浓；城市中出现浓雾的大气边界层特征是在近地面层有逆温及增湿降温现象；高浓度气溶胶的净辐射效应阻碍白天混合层发展，使大气边界层趋于稳定，它是重庆连续几天有雾的原因之一；浓雾具有一定的湿沉降作用，能有限地清洁空气；有浓雾的天气条件下，建议降低污染物的排放总量，以避免严重大气污染事件发生。     

云南省Internet网络天气预报会商系统

云南省基于Internet网络的天气预报会商系统覆盖云南省、地 (州 )、县三级。系统采用了Internet网络技术、数据库技术 ,实现了省、地 (州 )、县天气预报发布及浏览查询、预报讨论BBS、天气预报会商室、系统管理 ,在线短消息互发等功能。     

Vertical structures of PM10 and PM 2.5 and their dynamical character in low atmosphere in Beijing urban areas

The vertical structures and their dynamical character of PM2.5 and PM10 over Beijing urban areas are revealed using the 1 min mean continuous mass concentration data of PM2.5 and PM10 at 8, 100, and 320 m heights of the meteorological observation tower of 325 m at Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP CAS tower hereafter) on 10―26 August, 2003, as well as the daily mean mass concentration data of PM2.5 and PM10 and the continuous data of CO and NO2 at 8, 100 (low layer), 200 (middle layer), and 320 m (high layer) heights, in combination with the same period meteorological field observation data of the meteorological tower. The vertical distributions of aerosols observed on IAP CAS tower in Beijing can be roughly divided into two patterns: gradually and rapidly decreasing patterns, I.e. The vertical distribution of aerosols in calm weather or on pollution day belongs to the gradually decreasing pattern, while one on clean day or weak cold air day belongs to the rapidly decreasing pattern. The vertical distributive characters of aerosols were closely related with the dynamical/thermal structure and turbulence character of the atmosphere boundary layer. On the clean day, the low layer PM2.5 and PM10 concentrations were close to those at 8 m height, while the concentrations rapidly decreased at the high layer, and their values were only one half of those at 8 m, especially, the concentration of PM2.5 dropped even more. On the clean day, there existed stronger turbulence below 150 m, aerosols were well mixed, but blocked by the more stronger inversion layer aloft, and meanwhile, at various heights, especially in the high layer, the horizontal wind speed was larger, resulting in the rapid decrease of aerosol concentration, I.e. Resulting in the obvious vertical difference of aerosol concentrations between the low and high layers. On the pollution day, the concentrations of PM2.5 and PM10 at the low, middle, and high layers dropped successively by, on average, about 10% for each layer in comparison with those at 8 m height. On pollution days, in company with the low wind speed, there existed two shallow inversion layers in the boundary layer, but aerosols might be, to some extent, mixed below the inversion layer, therefore, on the pollution day the concentrations of PM2.5 and PM10 dropped with height slowly; and the observational results also show that the concentrations at 320 m height were obviously high under SW and SE winds, but at other heights, the concentrations were not correlated with wind directions. The computational results of footprint analysis suggest that this was due to the fact that the 320 m height was impacted by the pollutants transfer of southerly flow from the southern peripheral heavier polluted areas, such as Baoding, and Shijiazhuang of Hebei Province, Tianjin, and Shandong Province, etc., while the low layer was only affected by Beijing's local pollution source. The computational results of power spectra and periods preliminarily reveal that under the condition of calm weather, the periods of PM10 concentration at various heights of the tower were on the order of minutes, while in cases of larger wind speed, the concentrations of PM2.5 and PM10 at 320 m height not only had the short periods of minute-order, but also the longer periods of hour order. Consistent with the conclusion previously drawn by Ding et al., that air pollutants at different heights and at different sites in Beijing had the character of "in-phase" variation, was also observed for the diurnal variation and mean diurnal variation of PM2.5 and PM10 at various heights of the tower in this experiment, again confirming the "in-phase" temporal/spatial distributive character of air pollutants in the urban canopy of Beijing. The gentle double-peak character of the mean diurnal variation of PM2.5 and PM10 was closely related with the evident/similar diurnal variation of turbulent momentum fluxes, sensible heat fluxes, and turbulent kinetic energy at various heights in the urban canopy. Besides, under the condition of calm weather, the concentration of PM2.5 and PM10 declined with height slowly, it was 90% of 8 m concentration at the low layer, a little lesser than 90% at the middle layer, and 80% at the high layer, respectively. Under the condition of weak cold air weather, the concentration remarkably dropped with height, it was 70% of 8 m concentration at the low layer, and 20%―30% at the middle and high layers, especially the concentration of PM2.5 was even lower.     

Uncertainty analysis of CO_2 flux components in subtropical evergreen coniferous plantation

We present an uncertainty analysis of ecological process parameters and CO2 flux components (Reco, NEE and gross ecosystem exchange (GEE)) derived from 3 years’ continuous eddy covariance meas-urements of CO2 fluxes at subtropical evergreen coniferous plantation, Qianyanzhou of ChinaFlux. Daily-differencing approach was used to analyze the random error of CO2 fluxes measurements and bootstrapping method was used to quantify the uncertainties of three CO2 flux components. In addition, we evaluated different ...