低温浓缩-气相色谱/质谱法分析固定污染源废气中的丙烯腈

建立了固定污染源废气中丙烯腈的气袋采样-低温浓缩-气相色谱/质谱分析方法。结果表明,该法在丙烯腈质量浓度16.1~4 050μg/m~3范围内具有良好的线性,相关系数R~20.999,检出限为9.54μg/m~3,回收率、日内与日间精密度均符合质控要求,能够满足废气中丙烯腈分析的要求。     

Using ecological memory as an indicator to monitor the ecological restoration of four forest plantations in subtropical China

A large area of plantations has been established worldwide and especially in China. Evaluating the restoration status of these plantations is essential for their long-term management. Based on our previous work, we used an ecological memory (EM) approach to evaluate four 26-year-old plantations that represent four common kinds of plantations in subtropical China, i.e., mixed broad-leaved plantation (MBP), mixed coniferous plantation (MCP), eucalyptus plantation (EP), and mixed legume plantation (MLP). Comparing them with the regional climax community, i.e., monsoon evergreen broad-leaved forest (BF), all four plantations accumulated nearly the same pattern of EM during succession. EM was >50 % for soil minerals, light conditions, soil age, soil animals, and soil microbes. EM was about 25 % for soil pollen and 10 % for birds, soil seed bank, and plant species. The total EM value of the four plantations ranged from 50.96 to 52.54, which indicated that all four plantations were in the regional, natural trajectory of succession and between the early and medium successional stages. The results indicated that natural succession processes are unlikely to be accelerated by planting late-stage tree species without sufficient EM. The results also demonstrated that all four plantations were in positive successional trajectories, and the positive succession dynamics were greater in the MLP and MCP. We suggest that the entire natural succession trajectory be used to evaluate the restoration of a site and that the ultimate restoration target be divided into several milestones along the reference trajectory to monitor progress. Forest restoration may be accelerated by starting with a minimum dynamic unit supporting sufficient EM.     

Water chemistry in 179 randomly selected Swedish headwater streams related to forest production,clear-felling and climate

From a policy perspective, it is important to understand forestry effects on surface waters from a landscape perspective. The EU Water Framework Directive demands remedial actions if not achieving good ecological status. In Sweden, 44 % of the surface water bodies have moderate ecological status or worse. Many of these drain catchments with a mosaic of managed forests. It is important for the forestry sector and water authorities to be able to identify where, in the forested landscape, special precautions are necessary. The aim of this study was to quantify the relations between forestry parameters and headwater stream concentrations of nutrients, organic matter and acid-base chemistry. The results are put into the context of regional climate, sulphur and nitrogen deposition, as well as marine influences. Water chemistry was measured in 179 randomly selected headwater streams from two regions in southwest and central Sweden, corresponding to 10 % of the Swedish land area. Forest status was determined from satellite images and Swedish National Forest Inventory data using the probabilistic classifier method, which was used to model stream water chemistry with Bayesian model averaging. The results indicate that concentrations of e.g. nitrogen, phosphorus and organic matter are related to factors associated with forest production but that it is not forestry per se that causes the excess losses. Instead, factors simultaneously affecting forest production and stream water chemistry, such as climate, extensive soil pools and nitrogen deposition, are the most likely candidates The relationships with clear-felled and wetland areas are likely to be direct effects.     

PSO和SVM混合算法确定太湖入湖河流水质主要影响因子

以影响太湖入湖河流水质的24个因子值为研究对象,将PSO算法与SVM算法相结合。PSO算法用于优化SVM算法的参数c和g,以利于快速、高效地确定c和g的全局最优值;SVM算法基于最优的c和g,分别以24,21,18,15,12,9和6个因子作为特征向量预测水质的污染程度。结果表明,当特征向量为9个影响因子时预测率最高。其参数c=18.56,g=1.35,对应的预测率为：全局预测率92.59%,重度污染水质预测率88.89%,轻度污染水质预测率94.45%。因此,通过PSO和SVM混合算法,可以确定影响太湖入湖河流水质的主要因子,利用这些主要因子对水质进行预测预警,不但可以节省时间,而且可以得到精确的结果。     

环境监测实验室方法确认过程中常见问题探讨

根据实验室资质认定对于方法确认的要求,结合环境监测实验室的特点,提出了新项目方法确认的具体步骤,并分析了其中存在的常见问题。指出在方法确认过程中,应严格按照标准方法和监测技术规范进行全过程试验,尤其不能忽视采样现场实验、空白实验和检出限的测定。建议在精密度与准确度检验过程中,使用高、中、低不同浓度的有证标准样品,实际样品加标回收,比对试验（方法比对、人员比对、实验室间比对）,增加分析次数等多种手段,确保新项目开展的可靠性。     

武汉市一次污染过程的局地流场和边界层结构的数值模拟

利用2013年11月武汉市逐日空气质量资料、地面气象观测资料、NCEP/NCAR再分析资料和L波段雷达探空资料,通过WRF模式模拟空气污染生消过程中的局地气象条件变化,探讨特殊地形条件下边界层结构变化和局地环流在污染物生消过程中的作用和影响。结果表明：（1）武汉地区当背景环流场强的时候,由地形引起的局地流场对污染物扩散的影响就弱,反之当背景环流场弱的时候, 地形对流场影响明显:夜间为山风,白天为谷风。夜间山风与偏西北气流及偏东气流在武汉及周边地区辐合,形成气流汇聚带,在武汉地区形成一个反复污染带,即由地形引起的局地流场对污染物扩散的贡献就大;（2）武汉地区发生空气污染时,地面湿度较高,边界层呈上干下湿状态,其特征为暖而干且有偏东小风,这导致污染物不断堆积和重污染过程的形成。     

蔬菜常用农药在地下水中残留风险评估

为明确蔬菜常用农药在地下水中的环境风险,运用China-Pearl和SCI-GROW模型开展地下水环境暴露评估,并根据我国成人和儿童暴露参数推导25种农药预测无效应浓度(PNEC)。研究发现,25种农药PECgw为0~18.340μg·L-1,成年人PNECgw为0.003~19.654 mg·L-1,儿童PNECgw为0.001~23.253 mg·L-1。成年人和儿童的RQgw值均小于1,表明25种农药按照登记用量使用,我国成人和各年龄阶段儿童直接饮用施用农药区域地下水的环境风险可接受。     

农药环境风险评估中常用的计算毒理学模型软件

农药的大量使用为我国带来了严重的环境和健康问题,仅依靠传统生物测试和环境监测的方法已经不能满足农药风险评估的需要。利用计算毒理学模型,可以实现农药的高通量风险评估。本文主要介绍了农药环境风险评估中常用免费的EPI Suite、QSAR Toolbox和PBT Profiler等定量结构-活性关系(Quantitative Structure-Activity Relationship,QSAR)模型软件和SCIGROW、PRZM-GW、China-PEARL和EQC等环境多介质模型软件,以期能为农药的风险评估和科学管理提供参考。     

A dynamic modelling of nutrient metabolism in a cyclic activated sludge technology (CAST) for treating low carbon source wastewater

Environmental Science and Pollution Research - A new mathematical model incorporating biopolymer kinetics and the process of the simultaneous storage and growth are established for the treatment of...     

Application of phosphate solubilizing bacteria in immobilization of Pb and Cd in soil

Environmental Science and Pollution Research - In the present study, heavy metal (HM)-tolerant phosphate solubilizing bacteria (PSB) were isolated and their performance during the remediation of Pb...