生物法-人工湿地组合工艺处理小城镇混合污水研究

为适应小城镇污水处理高效、低耗、管理简单的要求,开展了生物法(水解酸化/生物接触氧化)-人工湿地组合工艺(A/BCO-CW)处理小城镇片区混合污水的研究。结果表明,A/BCO系统在停留时间为3～6 h条件下,对悬浮物和有机物有高的去除效率,COD、BOD5和TSS去除率分别达到63.1%、67.7%和66.2%,避免了人工湿地堵塞和提高处理效率,减少了所需湿地面积44%。全年运行结果表明,在0.30～0.59 m/d水力负荷率下,垂直流-表面流-水平潜流人工湿地组合系统对COD、BOD5和TSS平均去除负荷达9.4、5.1和7.2 g/(m2.d)(42%、71.2%和85.2%);COD、BOD5去除速率常数为74.6±12.1 m/y、166±30.5 m/y,这些数值均处于文献中k值范围的高量程内。A/BCO-人工湿地系统对COD、BOD5和TSS具有好的处理效果,出水水质能够稳定达到《地表水环境质量标准》(GB 3838-2002)的IV类水标准,2种处理方法有效组合起来,所开发的低成本、高效率、可持续运行的城镇废水处理组合系统,将会在实际应用尤其是高有机负荷污水处理中发挥良好效用。     

国内外可持续发展评价方法对比分析

国际、国内很多组织都对可持续性评价方法进行过研究分析,但大多是特定的案例研究.目前国内外对可持续发展评价方法没有一个全面系统的分析比较,使得不同地区比较起来很困难.本文对各种评价方法如环境可持续性指数法、生态足迹法、能值分析法和指标综合评价法的来源、理论和应用作了介绍.得出各方法适用范围:可持续性指数法适合于国家间的综合评价;生态足迹和能值分析法适合于各种范围,包括国家、区域、地区和小系统;指标体系综合评价法对于小范围更合适.同时对各种方法的优势和缺陷进行了分析讨论,得出:可持续性指数法信息量大,但是计算复杂;生态足迹法计算过程简单,但是缺失一些可持续性信息;能值分析法考虑问题全面,但是其原理涉及热力学知识,很难被一些学者认同;指标体系评价法变通性较大,可随着评价系统的变化而进行调整,但是主观性较强.通过分析指出不同方法适用范围并指出每种分析方法的优势和不足,为以后选择合适的分析方法评价对象的可持续性提供依据.     

Tissue distribution of Dechlorane Plus and its dechlorinated analogs in contaminated fish: high affinity to the brain for anti-DP

Information on tissue distribution of Dechlorane Plus (DP) and its dechlorinated analogs in wildlife is scarce. DP isomers and two dechlorinated compounds, anti-Cl₁₁-DP and anti-Cl₁₀-DP, were examined in the muscle, liver, and brain tissues of two bottom fish species collected from an electronic waste recycling site, South China. The median levels of syn-, anti-, and anti-Cl₁₁-DP isomers in the tissues ranged 0.18-39.1, 0.22-52.9, and 0.01-5.63 ng/g wet wt, respectively. Anti-Cl₁₀-DP was only detected in one muscle sample of mud carp (0.01 ng/g wet wt), although it was consistently detected in the sediments (0.42-0.83 ng/g dry wt). Preferential distribution in liver relative to muscle was observed for syn-DP and anti-Cl₁₁-DP. However, a high persistent retention in the brain compared to the liver was observed for anti-DP, suggesting that this isomer can across the blood-brain barrier of fish, and may cause adverse effects to the nervous system in the exposed biota.     

Levels and distribution of Dechlorane Plus in coastal sediments of the Yellow Sea, North China

Dechlorane Plus (DP) has been determined in surface sediments from three Chinese coastal bays, e.g. Jiaozhou, Sishili and Taozi Bay in North China. DP concentrations ranged from <1.2 to 187 pg g⁻¹ dry weight (dw) (mean: 24.7 pg g⁻¹ dw) in Jiaozhou Bay, <1.2 to 135 pg g⁻¹ dw (mean 69.9 pg g⁻¹ dw) in Sishili Bay and <1.2 to 66.7 pg g⁻¹ dw (mean: 40.4 pg g⁻¹ dw) in Taozi Bay, respectively. Additionally, two dechlorinated species were quantified, which accounted for 0.6-5.1% of the ∑DP concentration.The f_syn values (syn-isomer/(syn- + anti-isomer)) in sediments from Jiaozhou Bay (mean 0.29) were close to the technical DP mixture (0.2-0.4), probably indicating local inputs of DP. In contrast, sediments in Sishili and Taozi Bay showed much lower f_syn values (mean 0.16). During transportation the DP isomers are subject to stereo selective degradation which partly resulted in the relative enrichment of anti-DP in coastal sediments.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

The multifunctionality of urban farming: perceived benefits for neighbourhood improvement

Urban farming – a type of urban agriculture focused on entrepreneurial food production – serves multiple functions in neighbourhoods; yet these are not well delineated. Expectations for urban farming often centre on traditional measures of economic development, potentially overlooking other benefits. Through a qualitative case study conducted in Baltimore, Maryland, we sought to understand community perceptions regarding the ways in which urban farms can benefit cities. Interviews with residents, neighbourhood leaders, and urban farmers in three residential neighbourhoods with urban farms revealed the pathways by which community members view farms as improving neighbourhoods. Benefits stemmed from four primary changes urban farms made to study neighbourhoods: creation of public projects welcoming involvement, physical improvement of degraded space, production of local food, and creation of new businesses. These changes led to multiple perceived benefits including increased social connectedness, a transformed physical landscape, improved neighbourhood reputation, increased access to fresh produce, and educational, youth development, and employment opportunities. Our findings demonstrate the importance of a multifunctional paradigm that accounts for social and educational functions in assessing the value of urban farming and bring empirical evidence to the concept of multifunctional agriculture. Urban farms with strong social aims may appear to contribute little to economic development if measured using traditional indicators of success such as job creation or fiscal impacts, but provide numerous other benefits for community development.     

Monitoring Environmental Impact in the Upper Sonoran Lifestyle: A New Tool for Rapid Ecological Assessment

Characterized by expensive housing, high socioeconomic status, and topographic relief, Upper Sonoran Lifestyle communities are found primarily along the Wildland-Urban Interface (WUI) in the Phoenix, Arizona metro area. Communities like these sprawl into the wildlands in the United States Southwest, creating a distinct urban fringe. This article, through locational comparison, introduces and evaluates a new field assessment tool for monitoring anthropogenic impact on soil–vegetation interactions along the well-maintained multi-use recreational trails in Upper Sonoran Lifestyle region. Comparing data from randomly selected transects along other multi-use trails with data from a control site revealed three key indicators of anthropogenic disturbances on soil–vegetation interactions: soil disturbance, vegetation disturbance, and vegetation density. Soil and vegetation disturbance displayed an average distance decay exponent factor of −0.60, while vegetation density displayed a reverse decay average of 0.60. Other important indicators of disturbance included vegetation type, biological soil crusts, and soil bulk density. The predictive ability of this new field tool enhances its applicability, offering a powerful rapid ecological assessment method for monitoring long-term anthropogenic impact in the Upper Sonoran Lifestyle, and other sprawling cities along the WUI.     

可靠性技术的发展与应用

本文介绍了可靠性标准体系与参数体系,可靠性的分析与设计方法,可靠性试验的发展趋势,指出可靠性管理是产品可靠性工作的核心,以及提高电子设备可靠性的发展策略。     

Incorporating Uncertainty Into the Ranking of SPARROW Model Nutrient Yields From Mississippi/Atchafalaya River Basin Watersheds1

Abstract: Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient‐reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight‐digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.     

Best Practices in Environmental Communication: A Case Study of Louisiana's Coastal Crisis

This mixed-method case study of environmental communication best practices in Louisiana, USA, identifies trends and approaches as informed by environmental psychology. The results provide key insights for environmental communicators, especially communicators in coastal regions. In-depth interviews with both environmental psychologists and environmental communicators showed that both groups emphasized knowing the audience, telling local stories, building relationships with target audiences and targeted messaging. Both psychologists and communicators also frequently mentioned general messaging concerns of source credibility, avoiding controversial terms and talking about issues, impacts and solutions to which the target audience can relate. A representative survey revealed that Louisiana residents are most interested in hearing about how environmental issues such as climate change, coastal land loss and flooding are affecting their own communities. This finding supports the idea that environmental communicators could do a better job tapping into strong place attachment and sense of community among coastal residents to promote action.