南黄海中部表层沉积物中多环芳烃含量分布及来源分析

采用气相色谱与质谱联用(GC/MS)技术,在一个航次内对南黄海表层沉积物中16种优先监控的PAHs的污染状况进行了调查,采用菲/蒽、荧蒽/芘、荧蒽/(荧蒽+芘)、吲哚芘/(吲哚芘+苯并(g,h,i)菲)等特定比值对PAHs来源进行了分析.结果表明,南黄海表层沉积物中检出PAHs的总含量为90.4～732.65ng·g-1,各站点均以4～6环为主;与其它站位相比,倾废区的HOI站位受到PAHs污染较为明显,无论是16种PAHs总量还是高分子量组分最高值都出现在该站点,虽然该海区沉积物中PAHs的含量没有超出生物影响低值,但苯并(b)荧蒽、吲哚芘和苯并(g,h,i)芘等一些没有最低安全标准的PAHs也有不同程度的检出,对海洋生物具有潜在的毒副作用.PAHs可能来源于原油、生物和煤燃烧造成的污染.     

粤港澳地区大气中有机污染物初步研究

用Ｔｅｋｍａｒ多填层吸附管连接ＴＭＰ－１５００空气采样采集ＶＯＣｓ样,然后在Ｔｅｋｍａｒ６０３２／３０００吹扫捕集系统与ＧＣ／ＭＳＤ联用仪上分析,用ＴＨ－１０００Ｌ型大量采样器收集ＴＳＰ气溶胶样,ＴＳＰ滤膜经抽提分离后,烷径和芳烃进行ＧＣ／ＭＳＤ分析,了广州,香港和澳门地区大气 有机物和气溶胶可溶有机物的与成因。     

Removal of arsenate and arsenite from aqueous solution by waste cast iron

The removal of As(III) and As(V) from aqueous solution was investigated using waste cast iron, which is a byproduct of the iron casting process in foundries. Two types of waste cast iron were used in the experiment: grind precipitate dust (GPD) and cast iron shot (CIS). The X-ray diffraction analysis indicated the presence of Fe0 on GPD and CIS. Batch experiments were performed under different concentrations of As(III) and As(V) and at various initial pH levels. Results showed that waste cast iron was effective in the removal of arsenic. The adsorption isotherm study indicated that the Langmuir isotherm was better than the Freundlich isotherm at describing the experimental result. In the adsorption of both As(III) and As(V), the adsorption capacity of GPD was greater than CIS, mainly due to the fact that GPD had higher surface area and weight percent of Fe than CIS. Results also indicated the removal of As(III) and As(V) by GPD and CIS was influenced by the initial solution pH, generally decreasing with increasing pH from 3.0 to 10.5. In addition, both GPD and CIS were more effective at the removal of As(III) than As(V) under given experimental conditions. This study demonstrates that waste cast iron has potential as a reactive material to treat wastewater and groundwater containing arsenic.     

An agenda for assessing and improving conservation impacts of sustainability standards in tropical agriculture

Sustainability standards and certification serve to differentiate and provide market recognition to goods produced in accordance with social and environmental good practices, typically including practices to protect biodiversity. Such standards have seen rapid growth, including in tropical agricultural commodities such as cocoa, coffee, palm oil, soybeans, and tea. Given the role of sustainability standards in influencing land use in hotspots of biodiversity, deforestation, and agricultural intensification, much could be gained from efforts to evaluate and increase the conservation payoff of these schemes. To this end, we devised a systematic approach for monitoring and evaluating the conservation impacts of agricultural sustainability standards and for using the resulting evidence to improve the effectiveness of such standards over time. The approach is oriented around a set of hypotheses and corresponding research questions about how sustainability standards are predicted to deliver conservation benefits. These questions are addressed through data from multiple sources, including basic common information from certification audits; field monitoring of environmental outcomes at a sample of certified sites; and rigorous impact assessment research based on experimental or quasi‐experimental methods. Integration of these sources can generate time‐series data that are comparable across sites and regions and provide detailed portraits of the effects of sustainability standards. To implement this approach, we propose new collaborations between the conservation research community and the sustainability standards community to develop common indicators and monitoring protocols, foster data sharing and synthesis, and link research and practice more effectively. As the role of sustainability standards in tropical land‐use governance continues to evolve, robust evidence on the factors contributing to effectiveness can help to ensure that such standards are designed and implemented to maximize benefits for biodiversity conservation.     

Linking irreplaceable landforms in a self‐organizing landscape to sensitivity of population vital rates for an ecological specialist

Irreplaceable, self‐organizing landforms and the endemic and ecologically specialized biodiversity they support are threatened globally by anthropogenic disturbances. Although the outcome of disrupting landforms is somewhat understood, little information exists that documents population consequences of landform disturbance on endemic biodiversity. Conservation strategies for species dependent upon landforms have been difficult to devise because they require understanding complex feedbacks that create and maintain landforms and the consequences of landform configuration on demography of species. We characterized and quantified links between landform configuration and demography of an ecological specialist, the dunes sagebrush lizard (Sceloporus arenicolus), which occurs only in blowouts (i.e., wind‐blown sandy depressions) of Shinnery oak (Quercus havardii) sand‐dune landforms. We used matrix models to estimate vital rates from a multisite mark‐recapture study of 6 populations occupying landforms with different spatial configurations. Sensitivity and elasticity analyses demonstrated demographic rates among populations varied in sensitivity to different landform configurations. Specifically, significant relationships between blowout shape complexity and vital rate elasticities suggested direct links between S. arenicolus demography and amount of edge in Shinnery oak sand‐dune landforms. These landforms are irreplaceable, based on permanent transition of disturbed areas to alternative grassland ecosystem states. Additionally, complex feedbacks between wind, sand, and Shinnery oak maintain this landform, indicating restoration through land management practices is unlikely. Our findings that S. arenicolus population dynamics depended on landform configuration suggest that failure to consider processes of landform organization and their effects on species’ population dynamics may lead to incorrect inferences about threats to endemic species and ineffective habitat management for threatened or endangered species. As such, successful conservation of these systems and the biodiversity they support must be informed by research linking process‐oriented studies of self‐organized landforms with studies of movement, behavior, and demography of species that dwell in them.     

Challenges of diverse knowledge systems in landscape analysis of the Murray–Darling Basin,Australia

Regional Environmental Change - Geographic information systems are a means to develop a common framework for the integration of a range of perspectives into natural resources management decisions....     

Scenario‐Based Evaluation of Commercially Available Cleaning Robots for Collection of Bacillus Spores from Environmental Surfaces

The cleaning robots, a vacuum‐based robot (R2) and a wetted‐wipe‐based robot (R4), were evaluated in this study to determine their effectiveness for sampling Bacillus atrophaeus spores. The tests were designed to evaluate the benefit of robot sampling on large areas with two different contamination scenarios: a high‐concentration, low spatial extent contamination (hot spot) and a low concentration, high spatial extent contamination (widely dispersed). The hot spot tests were conducted with the high spore contamination (approximately 10⁷ colony forming units [CFUs]) on a limited area (30.5 cm × 30.5 cm), 2 percent of the entire test. The widely dispersed tests were conducted with approximately 0.1 CFUs/cm² for floor laminate and approximately 10 CFUs/cm² for carpet surfaces. The widely dispersed tests distributed spores across the test surface and covered approximately 40 percent of the entire test area. The test results showed that both robots successfully sampled a large quantity of spores from carpet and floor laminate surfaces for both test scenarios. Robot performance is discussed in the context of currently used surface sampling methods. © 2014 Wiley Periodicals, Inc.*