喻家湖水质时空分布特征和影响因子分析

通过设计合理的水质监测网,采用多元统计分析,并结合地理信息技术对武汉市喻家湖在2011年-2012年期间12个监测点、13个水质参数监测值进行水质时空分布特征研究.结果表明,喻家湖13个水质指标概括为4个主成分:第一主成分代表喻家湖的重金属污染,第二主成分代表其富营养化水平,第三主成分代表有机污染程度,第四主成分间接指示富营养化程度;在时间和空间变化上都可分为二组,显著性指标的时空差异较明显,水质污染程度从南至北逐渐减弱,湖溪河是喻家湖的最主要污染源.并对水质参数,监测点位和频次进行了优化.     

环境监测技术培训需求分析——应用OTP模型

简述了环境监测技术培训需求分析的重要性及OTP模型的概念.针对环境监测技术培训的现状和特点,设计了符合环境监测技术培训特点的OTP模型,提出了系统分析环境监测技术培训需求的方法,以及根据实际情况科学设置输入项的不同权重,充分考虑影响模型输出的各种因素,加强研究模型输入项的量化表征,动态调整模型的输入项的建议.     

扬州地区酸雨现状及成因分析

根据2006年1月—2010年12月的酸雨监测数据,对扬州地区酸雨的变化规律和趋势进行了统计分析。结果表明:扬州地区酸雨主要集中在扬州市区与仪征城区,"十一五"期间,扬州市区酸雨呈逐年减少趋势,仪征城区大气污染严重,降水pH年均值均小于5.6,经评价扬州市区属于非酸雨区-较重酸雨区,仪征城区属于轻酸雨区-重酸雨区。高邮、江都、宝应城区从2007年起无酸雨出现。仪征城区酸雨主要是由燃煤型和燃油型混合空气污染造成的,近年来随着机动车拥有量的迅速增加,各种机动车排放的尾气已成为形成酸雨的重要原因,应引起重视。     

兰州市气象要素对大气质量影响力的模拟分析

为了弄清气象要素对大气质量的影响以及大气污染反弹的原因,通过对兰州市冬春之际气象要素对大气质量影响力的模拟分析,建立了气象要素与大气质量间的模拟模型,并应用该模型对兰州市大气污染指数进行预测分析。结果表明,该模型计算精度高,预测结果真实可信,方法可行性好,可用来模拟分析兰州市冬春之际空气污染的成因和动态变化。     

室内空气中的气态多环芳烃的被动采样监测

利用自制被动采样装置,在2011年秋冬季对南京市部分地区室内空气中5种气态多环芳烃(PAHs)(萘、苊烯、苊、芴、菲)进行了为期100d的连续采样检测,被动采样器的采样速率为0.012m3/d,5种PAHs的回收率在63%～105%之间,方法检出限在1.1～2.4ng范围内。结果表明,南京市5处不同室内环境空气中萘的浓度最高,占总量的90%以上。室内环境空气中5种PAHs的总浓度为230～1564ng/m3。住宅内人体对5种PAHs的暴露速率为479～560ng/h。     

Estimating the extent and structure of trade in horticultural orchids via social media

The wildlife trade is a lucrative industry involving thousands of animal and plant species. The increasing use of the internet for both legal and illegal wildlife trade is well documented, but there is evidence that trade may be emerging on new online technologies such as social media. Using the orchid trade as a case study, we conducted the first systematic survey of wildlife trade on an international social‐media website. We focused on themed forums (groups), where people with similar interests can interact by uploading images or text (posts) that are visible to other group members. We used social‐network analysis to examine the ties between 150 of these orchid‐themed groups to determine the structure of the network. We found 4 communities of closely linked groups based around shared language. Most trade occurred in a community that consisted of English‐speaking and Southeast Asian groups. In addition to the network analysis, we randomly sampled 30 groups from the whole network to assess the prevalence of trade in cultivated and wild plants. Of 55,805 posts recorded over 12 weeks, 8.9% contained plants for sale, and 22–46% of these posts pertained to wild‐collected orchids. Although total numbers of posts about trade were relatively small, the large proportion of posts advertising wild orchids for sale supports calls for better monitoring of social media for trade in wild‐collected plants.     

Nutritionally relevant elements in staple foods: influence of arable site versus choice of variety

Eighteen representative sites for the Austrian grain-growing and eight for the potato-growing zones (soils and crops) were investigated. On each site, total element contents (B, Ba, Ca, Cd, Co, Cu, Fe, K, Li, Mg, Mn, Mo, Na, P, Sr and Zn) were determined in 4–12 varieties of winter wheat (n = 136), 6 varieties of spring durum wheat (n = 30), 5 varieties of winter durum wheat (n = 15), 7 varieties of rye (n = 49), 5 varieties of spring barley (n = 30) and 5 varieties of potatoes (n = 40). Element accumulations in grain species and potato tubers varied significantly with site conditions, with the main exceptions for B in potatoes and wheat as well as for Zn, Cu and Co in durum wheat. On average, across all investigated sites, differences in varieties occurred concerning the elements Ca, Cd, Ba, Sr and Zn (except Zn in potatoes and winter durum). A rough estimation revealed that an average Austrian consumer of wheat, rye and potatoes meets more than 50% of the needs of daily element intake for K, P and Mg, between 36 and 72% for Fe, Zn and Cu, and more than 100% for Co, Mo and Mn. In particular, the elements Ca and Na have to be added from other sources.     

Diversity of bacterial isolates during full scale rotary drum composting

Bacterial diversity of full scale rotary drum composter from biodegradable organic waste samples were analyzed through two different approaches, i.e., Culture dependent and independent techniques. Culture-dependent enumerations for indigenous population of bacterial isolates mainly total heterotrophic bacteria (Bacillus species, Pseudomonas species and Enterobacter species), Fecal Coliforms, Fecal Streptococci, Escherichia coli, Salmonella species and Shigella species showed reduction during the composting period. On the other hand, Culture-independent method using PCR amplification of specific 16S rRNA sequences identified the presence of Acinetobacter species, Actinobacteria species, Bacillus species, Clostridium species, Hydrogenophaga species, Butyrivibrio species, Pedobacter species, Empedobactor species and Flavobacterium species by sequences clustering in the phylogenetic tree. Furthermore, correlating physico-chemical analysis of samples with bacterial diversity revealed the bacterial communities have undergone changes, possibly linked to the variations in temperature and availability of new metabolic substrates while decomposing organics at different stages of composting.     

基于物元模型的煤自燃危险性分析

为探索判断煤自燃的危险性新方法,在煤低温氧化试验的基础上,基于可拓理论构建了煤自燃危险性熵权和经验权的物元综合分析模型。采用该方法对4个不同煤样低温氧化试验数据进行自燃危险性分析,得出各煤样自燃危险性的等级及差异程度,并提出相应的防范对策。结果表明:4号煤样比其他煤样更具自燃危险性,需要重点防范。该方法的预测结果与实际情况相吻合。