Influence of pore structure on biologically activated carbon performance and biofilm microbial characteristics

• Pore structure affects biologically activated carbon performance. • Pore structure determines organic matter (OM) removal mechanism. • Microbial community structure is related to pore structure and OM removal. Optimizing the characteristics of granular activated carbon (GAC) can improve the performance of biologically activated carbon (BAC) filters, and iodine value has always been the principal index for GAC selection. However, in this study, among three types of GAC treating the same humic acid-contaminated water, one had an iodine value 35% lower than the other two, but the dissolved organic carbon removal efficiency of its BAC was less than 5% away from the others. Iodine value was found to influence the removal of different organic fractions instead of the total removal efficiency. Based on the removal and biological characteristics, two possible mechanisms of organic matter removal during steady-state were suggested. For GAC with poor micropore volume and iodine value, high molecular weight substances (3500–9000 Da) were removed mainly through degradation by microorganisms, and the biodegraded organics (soluble microbial by-products,<3500 Da) were released because of the low adsorption capacity of activated carbon. For GAC with higher micropore volume and iodine value, organics with low molecular weight (<3500 Da) were more easily removed, first being adsorbed by micropores and then biodegraded by the biofilm. The biomass was determined by the pore volume with pore diameters greater than 100 μm, but did not correspond to the removal efficiency. Nevertheless, the microbial community structure was coordinate with both the pore structure and the organic removal characteristics. The findings provide a theoretical basis for selecting GAC for the BAC process based on its pore structure.     

Identifying robust strategies for assisted migration in a competitive stochastic metacommunity

Assisted migration (AM) is the translocation of species beyond their historical range to locations that are expected to be more suitable under future climate change. However, a relocated population may fail to establish in its donor community if there is high uncertainty in decision-making, climate, and interactions with the recipient ecological community. To quantify the benefit to persistence and risk of establishment failure of AM under different management scenarios (e.g., choosing target species, proportion of population to relocate, and optimal location to relocate), we built a stochastic metacommunity model to simulate several species reproducing, dispersing, and competing on a temperature gradient as temperature increases over time. Without AM, the species were vulnerable to climate change when they had low population sizes, short dispersal, and strong poleward competition. When relocating species that exemplified these traits, AM increased the long-term persistence of the species most when relocating a fraction of the donor population, even if the remaining population was very small or rapidly declining. This suggests that leaving behind a fraction of the population could be a robust approach, allowing managers to repeat AM in case they move the species to the wrong place and at the wrong time, especially when it is difficult to identify a species’ optimal climate. We found that AM most benefitted species with low dispersal ability and least benefited species with narrow thermal tolerances, for which AM increased extinction risk on average. Although relocation did not affect the persistence of nontarget species in our simple competitive model, researchers will need to consider a more complete set of community interactions to comprehensively understand invasion potential.     

Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.     

砷尾矿污染土壤的细菌群落结构多样性及其相关环境影响因子分析

以湖南石门雄黄尾矿污染土壤为对象,研究纵向不同深度、横向不同距离土样中的重金属污染程度以及细菌群落结构变化规律,查明砷污染土壤的核心微生物组成并将其与土壤理化指标进行共存网络图分析。结果表明:该尾矿区的土壤各项重金属指标严重超标,尤以铅(626.54 mg·kg^?1,Ei=105.48)、砷(1804.75 mg·kg^?1,Ei=565.75)、镉(31.46 mg·kg^?1,Ei=7491.5)的生态危害性最强;土壤采样深度与重金属综合潜在生态风险指数(RI)呈显著正相关(r=0.79,P=0.000),而横向样品中RI与采样距离显著负相关(r=?0.85,P=0.000)。在污染土壤中,变形杆菌门(Proteobacteria,54.35%±17.16%)和放线杆菌门(Actinobacteria,22.39%±10.64%)占主导地位,属层级中假单孢杆菌属(Pseudomonas,16.47%±11.84%)、不动杆菌属(Acinetobacter,8.07%±7.11%)以及硫酸状杆菌属(Acidithiobacillus,7.53%±14.68%)相对丰度较高;而26个共享类群占据了该尾矿污染土壤中微生物群落总平均相对丰度90%以上,尽管不同属的具体相对丰度在不同样品间的分布趋势差异较大。纵剖采集的污染土样中,铁原体属(Ferroplasma)、硫酸状杆菌属(Acidithiobacillus)、硫化杆菌属(Sulfobacillus)、乳杆菌属(Lactobacillus)和硝化螺旋菌属(Nitrospira)占优势,与理化的共存网络图分析(相关系数|r|≥0.6,P<0.05)显示部分类群与亚铁、游离态砷和镉成显著正相关,而与pH成显著负相关;横向采集的土样中,以嗜酸菌属(Acidiphilium)、假单孢杆菌属(Pseudomonas)、棒状杆菌属(Corynebacterium)、硫杆菌属(Thiobacillus)等为主,部分类群与总砷、铅成显著正相关,而与结合态或包蔽型砷成显著负相关。综上,该研究不仅对目标区域尾矿不同重金属污染程度进行了分析,同时探讨了污染土壤中核心响应类群的组成多样性,为筛选潜在重金属抗性菌群或工程菌群提供理论基础。     

高含盐废水脱盐处理技术研究进展

综述了几种常见的高含盐废水脱盐处理技术的发展历程、工艺原理、优缺点及目前的研究进展，分析了热分离、膜分离、电渗析、离子交换、电吸附、微生物脱盐等方法的优缺点，展望了未来废水脱盐工艺的发展方向。指出：脱盐方法将根据各类水体的水质特点更加精细化；多种脱盐技术联合应用也是今后废水脱盐的发展方向。     

Non-timber forest products and village livelihoods in Rajasthan,India: adaptation in a changing environment

This paper presents the results of research conducted between 2009 and 2014 in the village of Khanda Sharol in the state of Rajasthan, India. Our research objective was to determine how the livelihoods of village residents have been affected by the intensification of forest use, and the resulting loss of domestic access to traditionally used forest resources. Results indicate that changes in forest cover have resulted in a loss of livelihood options for village residents. Yet rather than being victimized by environmental change processes, this paper shows how villagers have responded by partnering with public and private actors to develop a community protected forest area that is now helping villagers to meet their livelihood needs. These findings suggest that sustainable livelihoods in rural regions of India require committed and scaled approaches involving local, public, and private actors.     

Flooding and schools: experiences in Hull in 2007

Hull, a city in the East Riding of Yorkshire, United Kingdom, suffered severe flooding in June 2007, affecting some 8,600 households and most schools. Despite the potential for damage in such disasters, no studies of the effects of floods on teachers and schools in the UK appear to have been published previously. This study analysed the impacts of the floods on teachers in Hull in two stages: first through correspondence with Hull City Council and a mailed questionnaire to 91 head teachers of primary, secondary, and special schools; and second, through in‐depth interviews with head teachers from six flooded schools, representing different degrees of flood experience, and a questionnaire completed by eight teachers from the same schools. The findings reveal the importance and the complexity of the role of the school in the wider community in a time of crisis. The study highlights issues concerning preparedness for floods, support for schools, and flood protection for schools.     

Ambivalence towards discourse of disaster resilience

This paper investigates empirically how the international aid community (IAC)—donors and practitioners—considers and implements disaster resilience in a specific country setting, Nepal, and throughout the rest of the world. A key finding is that there is ambivalence about a concept that has become a discourse. On a global level, the IAC utilises the discourse of resilience in a cautiously positive manner as a bridging concept. On a national level, it is being used to influence the Government of Nepal, as well as serving as an operational tool of donors. The mythical resilient urban community is fashioned in the IAC's imaginary; understanding how people create communities and what type of linkages with government urban residents desire to develop their resilience strategies is missing, though, from the discussion. Disaster resilience can be viewed as another grand plan to enhance the lives of people. Yet, regrettably, an explicit focus on individuals and their communities is lost in the process.     

连续流双室微生物燃料电池处理工业废水

以实际中药废水作为阳极基质、实际含镉废水作为阴极电解液,构建了连续流双室微生物燃料电池(MFC),考察了其产电性能及对两种废水的处理效果。78 d的运行数据表明:系统可实现最大输出电压417mV、最大体积功率密度11.8 W/m3,最大体积功率密度运行条件下的库伦效率为18.5%;在阳极进水有机物浓度变化较大的情况下,实现了阳极对中药废水中有机物的有效去除,平均COD去除率为81.5%;阴极对含镉废水中Cd2+的去除率为79.4%～84.8%。这表明MFC同步处理中药废水及重金属废水具有一定的可行性。     

Multi-stakeholder collaboration in community post-disaster reconstruction: case study from the Longmen Shan Fault area in China

While multi-stakeholder collaboration is critical for effective community post-disaster reconstruction (CPDR), it is often very difficult in practice. The Longmen Shan Fault active seismic zone in China has experienced several recent earthquakes with the 2008 Wenchuan earthquake and 2013 Lushan earthquake, both of which caused extensive and widespread damage to many communities, presenting unprecedented challenges for post-disaster reconstruction. This paper develops a multi-cycle field research method that involves three interconnected cycles: internet research, field visits, and extensive surveys: to examine multi-stakeholder collaboration for the CPDR following the Wenchuan earthquake. It was found that there were 12 types of active stakeholders engaged across four main areas: infrastructure rebuilding, psychological recovery, socio-economic rehabilitation, and ecological restoration. Specifically, local community participation and effective collaboration between the community and the external stakeholders were found to be the most crucial elements for successful reconstruction. Multi-stage field research after the Lushan earthquake verified that CPDR was effective and that multi-stakeholder collaboration had improved from the lessons learnt from the Wenchuan earthquake reconstruction experience. Some advantages and limitations of this research are also given.