环境中的微塑料:赋存、检测及其危害

近年来，由个人护理品及废旧塑料直接或间接产生的微塑料不断地在各种环境介质中被检出，且微塑料会对生态系统产生各种危害，因此对微塑料的研究受到越来越广泛的关注。阐述了微塑料在水体、沉积物、沙滩和生物体中的赋存情况，介绍了微塑料的采集与分离方法，以及定性与定量分析方法。指出微塑料对环境及生物体产生的危害，提出现阶段研究存在的主要问题，并对今后的研究方向进行了展望。     

土壤中重金属测定方法探讨

采用硝酸+氢氟酸+高氯酸全分解方法消解土壤样品,并结合原子吸收分光光度法和标准加入法测定土壤中、锌、铅、镉、镍、总铬的含量.结果表明,该方法具有操作简便、快速,节省试剂,准确可靠等特点:实际土壤样品的检测结果完全能满足环境土壤样品测定的要求.     

水体中磺酸类有机物的检测分析进展

针对水体中磺酸类有机化合物的分离分析,较为系统地总结了近年来国内外学者在磺酸类化合物检测方面所作的研究工作,主要介绍了高效液相色谱、气质联用和电位等检测方法的应用。     

Molecular Study of the Persistence of Infectious Human Norovirus on Food-Contact Surfaces

The aim of this study was to investigate the effect of relative humidity (RH) and temperature on norovirus (NoV) persistence as infectious particles on food-contact surfaces such as stainless steel and polyvinyl chloride (PVC). For this purpose, a new method combining enzymatic digestion with molecular beacon-based NASBA targeting the ORF1-ORF2 domain was developed to discriminate between infectious and noninfectious NoV. Stainless steel and PVC disks were contaminated with known amounts of human NoV and kept for 56 days at 7 and 20°C at high (86% ± 4%) and low (30% ± 10%) RH. NoV retained its putative infectivity for 56 days on PVC and for 49 days on stainless steel at 7°C and for 7 and 28 days, respectively, at low and high RH at 20°C on both tested surfaces. These results confirm that NoV persists in an infective state on inert surfaces for long periods of time and consequently may cause illness. The new molecular approach to detecting infectious NoV on inert surfaces may provide valuable information for evaluating environmental surface decontamination strategies.     

水环境中致病菌分子生物学检测技术研究进展

总结了水环境中主要致病菌及其导致的疾病；介绍了检测水环境样品中致病菌的聚合酶链式反应（PCR）、实时定量PCR、等温扩增技术、生物传感器和高通量测序等分子生物学技术研究进展；分析了不同检测技术的优缺点和应用特点；提出了水环境中致病菌分子生物学检测技术的未来发展方向，为水环境中致病菌分析检测和风险控制提供研究思路和技术支撑。     

水质分析中仪器法的检出限的计算

本文简单论述了几种常见的检出限计算方法,通过吹扫捕集一气质联用法测定水中六氯丁二烯的实验获得数据,并按照不同的计算方式计算检出限,期望寻找出一种满足仪器法进行水质分析要求的计算检出限的方法。     

水体中微囊藻毒素检测技术研究进展

概述了微囊藻毒素的结构和性质,分析了其对人类健康的危害,综述了近年来国内外水体中微囊藻毒素的检测方法,提出了今后的研究方向。     

Contribution of sociodemographic characteristics, occupation, diet and lifestyle to DDT and DDE concentrations in serum and adipose tissue from a Bolivian cohort

The organochlorine pesticide p,p′-Dichlorodiphenyltrichloroethane (DDT) was widely used in the early 1960s-70s for vector control in tropical and subtropical areas of South America. Due to its persistence, DDT has a high potential to bioaccumulate in the food chain and living organisms and is a major public health concern, especially in South America.The main purpose of the present study was to investigate predictors of serum and adipose tissue concentrations of p,p′-DDT and its main metabolite, p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE), in an adult cohort (n = 112) from Santa Cruz de la Sierra, Bolivia, using multiple linear regression models. These models explained 29.3-47.8% of the variability in adipose tissue concentrations of p,p′-DDT and p,p′-DDE, respectively, and 32.9-47.0% of that in serum. Main exposure predictors included age, occupational class, residence, diet, smoking habit, and accumulated breastfeeding time.This is one of the few studies to explore predictors of human exposure to these chemicals using a multivariate approach in a South American population. Results show that predictors of human exposure to p,p′-DDT and p,p′-DDE in Santa Cruz de la Sierra may diverge from those found in other populations of the world, due to particular sociodemographic and lifestyle characteristics of this region.     

Info-gap theory and robust design of surveillance for invasive species: The case study of Barrow Island

Surveillance for invasive non-indigenous species (NIS) is an integral part of a quarantine system. Estimating the efficiency of a surveillance strategy relies on many uncertain parameters estimated by experts, such as the efficiency of its components in face of the specific NIS, the ability of the NIS to inhabit different environments, and so on. Due to the importance of detecting an invasive NIS within a critical period of time, it is crucial that these uncertainties be accounted for in the design of the surveillance system. We formulate a detection model that takes into account, in addition to structured sampling for incursive NIS, incidental detection by untrained workers. We use info-gap theory for satisficing (not minimizing) the probability of detection, while at the same time maximizing the robustness to uncertainty. We demonstrate the trade-off between robustness to uncertainty, and an increase in the required probability of detection. An empirical example based on the detection of Pheidole megacephala on Barrow Island demonstrates the use of info-gap analysis to select a surveillance strategy.