微生物絮凝剂改善城市污水厂浓缩污泥脱水性能的研究

采用酱油曲霉(Aspergillus sojae)产生的微生物絮凝剂(MBF)作为污泥絮凝脱水剂,对城市污水处理厂浓缩污泥进行调理,确定该絮凝剂对浓缩污泥脱水的处理工艺参数为：微生物絮凝液最佳投加体积为6%～8%（体积比）,发挥絮凝作用的最适污泥温度为28～32℃,最适pH为6～7。经微生物絮凝剂调理的污泥在3 000 r/min离心9 min,污泥脱水率高达82.7%,滤饼含水率降低至77.3%,污泥脱水后体积减至原来的1/5左右。     

Cleaner tanning practices for tannery pollution abatement: Role of enzymes in eco-friendly vegetable tanning

Concern about pollution related problems in the global scenario are persuading all the processing industries to adopt cleaner manufacturing practices. Thus, the leather industry is also under pressure to look for effective alternative tanning materials for chromium. Natural products like vegetable tannins are regaining importance. However, there are limitations in the use of vegetable tanning materials because of its high organic load in the effluent, which are difficult to degrade leading to high chemical oxygen demand (COD). Moreover, conventional vegetable tanning process requires partial pickling that involves the use of sodium chloride, to suppress osmotic swelling. This results in very high amount of total dissolved solid (TDS) content in wastewaters. In this investigation, an attempt has been made to design an eco-friendly vegetable tanning process combining pickle-free tanning and application of proteolytic enzymes to improve the exhaustion of vegetable tannins. Such an approach has resulted in more than 95% tannin exhaustion in the case of the experimental process, an increase of 10% compared with the conventional vegetable tanning process. The tanned leathers showed slight improvement in hydrothermal stability. Physical and tactile evaluation of experimental leathers has been better than conventionally tanned leathers. Surface colour values illustrated negligible variation in colour and shade between control and experimental leathers. The resultant leather showed opened up, split compact fibre structure that has been well coated, indicating that the enzyme assisted tanning process did not bring about any major change or destruction on the fibre structure of the leathers. The optimized system has been field tested in a commercial tannery. The results showed that the enzyme assisted tanning process is efficient in terms of improved quality of leather and also led to reduction in total solids (TS), chlorides and COD loads. The enzyme assisted tanning system presented appears to be a viable option for combating pollution arising from the conventional vegetable tanning system.     

A database for integrated assessment of European agricultural systems

A major bottleneck for data-based policy making is that data sources are collected, managed, and distributed by different institutions, residing in different locations, resulting in conceptual and practical problems. The use of dispersed data for agricultural systems research requires the integration of data sources, which means to ensure consistency in data interpretations, units, spatial and temporal scales, to respect legal regulations of privacy, ownership and copyright, and to enable easy dissemination of data. This paper describes the SEAMLESS integrated database on European agricultural systems. It contains data on cropping patterns, production, farm structural data, soil and climate conditions, current agricultural management and policy information. To arrive at one integrated database, a shared ontology was developed according to a collaborative process, which facilitates interdisciplinary research. The paper details this process, which can be re-used in other research projects for integrating data sources.     

Future risk of flooding: an analysis of changes in potential loss of life in South Holland (The Netherlands)

Potential loss of life is considered an important indicator of flood risk. We examine the future development of potential loss of life due to flooding for a major flood prone area in The Netherlands. The analysis is based on projections and spatial distribution of population under a high economic growth scenario and a loss of life model. Results show that the projected population growth in flood prone areas is higher than average in the Netherlands between 2000 and 2040. Due to this effect the potential number of fatalities is projected to increase by 68% on average for 10 different flood scenarios, not including impacts from climate change and sea level rise. Just sea level rise of 0.30 m leads to an average 20% increase in the number of fatalities. The combined impact of sea level rise and population growth leads to an estimated doubling in the potential number of fatalities. Taking into account increasing probability of flooding due to sea level rise and extreme river discharges, the expected number of fatalities could quadruple by 2040. The presented results give a conservative and upper bound estimate of the increase of the risk level when no preventive measures are undertaken. It is found that the consideration of the exact spatial distribution of population growth is essential for arriving at reliable estimates of future risk of flooding.     

北京山前典型细粒子污染过程的气象条件分析

可吸入颗粒物(PM₁₀)是近年来北京地区冬季首要污染物,其中细粒子(PM_2.5)污染受到广泛关注,由于该地区具有山前地区的地形和气象条件,使其细粒子污染更具区域代表性.对2007年12月北京出现的4次细粒子污染过程及气象条件进行了分析,结果表明:细粒子山前累积/清除时间,ρ(PM_2.5)峰值均与气象条件相关;12月23─26日的3 d连续累积,使26日的ρ(PM_2.5)日均值达到313.4 μg/m3,是国家ρ(PM₁₀₎二级标准〔环境空气质量标准(GB3095─1996)〕(150 μg/m3)的2.1倍,超过世界卫生组织ρ(PM_2.5)日均指导值(25 μg/m3)的11倍;持续的偏南风和边界层底层局地性环流,使得京津冀南部区域细粒子以日均96.7 μg/m3的高值累积在北京山前地区,造成了12月23—31日具有代表性的北京冬季严重细粒子污染.      

四川省卧龙地区土壤中二噁英类化合物和多氯萘的海拔梯度分布及对牦牛的毒性风险评价

初步研究了四川省卧龙地区5个不同海拔高度的表层土壤和2个牦牛样品中二噁英/呋喃(PCDD/Fs)、共平面多氯联苯(co-PCBs)和多氯萘(PCNs)的分布特征、来源、毒性当量以及生态风险状况.土壤样品中总2,3,7,8-PCDD/Fs的含量范围为2.48-4.30 pg·g-1dw,平均3.50 pg·g-1dw,最高含量在海拔3927 m的塘房.co-PCBs的总含量平均为9.14 pg·g-1dw,最高值在海拔4487 m的垭口.总2,3,7,8-PC-DD/Fs和总co-PCBs含量随海拔高度的变化表现出正相关关系.不同海拔高度土壤中的PCDD/Fs和co-PCBs异构体的分布相似,表明具有相同的来源.总PCNs与海拔梯度呈负相关关系,最高含量出现在海拔3345 m的贝母坪,平均21.4 pg·g-1dw,主要以3.氯为主.土壤中PcDD/Fs毒性当量浓度范围为0.29-0.43pg TEQ·g-1dw.牦牛肉和牦牛组织中PcDD,/Fs总浓度分别为27.5和23.6 pg·g-1脂肪,毒性当量浓度为4.04和4.07 pg TEQ·g-1脂肪.结果表明,牦牛中的PCDD/Fg,co-PcBs和PCNs不大可能对卧龙地区人群导致严重的负面效应.     

Modelling plant species richness using functional groups

Conservation biologists increasingly rely on spatial predictive models of biodiversity to support decision-making. Therefore, highly accurate and ecologically meaningful models are required at relatively broad spatial scales. While statistical techniques have been optimized to improve model accuracy, less focus has been given to the question: How does the autecology of a single species affect model quality? We compare a direct modelling approach versus a cumulative modelling approach for predicting plant species richness, where the latter gives more weight to the ecology of functional species groups. In the direct modelling approach, species richness is predicted by a single model calibrated for all species. In the cumulative modelling approach, the species were partitioned into functional groups, with each group calibrated separately and species richness of each group was cumulated to predict total species richness. We hypothesized that model accuracy depends on the ecology of individual species and that the cumulative modelling approach would predict species richness more accurately. The predictors explained plant species richness by ca. 25%. However, depending on the functional group the deviance explained varied from 3 to 67%. While both modelling approaches performed equally well, the models of the different functional groups highly varied in their quality and their spatial richness pattern. This variability helps to improve our understanding on how plant functional groups respond to ecological gradients.     

Modelling with uncertainty: Introducing a probabilistic framework to predict animal population dynamics

Predictive population models designed to assist managers and policy makers require an explicit treatment of inherent uncertainty and variability. These are particular concerns when modelling non-native and reintroduced species, when data have been collected within one geographical or ecological context but predictions are required for another, or when extending models to predict the consequences of environmental change (e.g., climate or land-use). We present an aspatial, probabilistic framework of hierarchical process models for predicting population growth even when data are sparse or of poor quality. Insight into the factors affecting population dynamics in real landscapes can be provided and Kullback–Leibler distances are used to compare the relative output of models. This flexible yet robust framework gives easily interpretable results, allowing managers as well as modellers to invalidate anomalous models and apply others to real-life scenarios.We illustrate the framework’s power with a meta-analysis of European wild boar (Sus scrofa) data. We test hypotheses about the effect of geographic region, hunting and mast years on wild boar population growth, to build models of wild boar dynamics for the UK. The framework quantifies the importance of hunting pressure as a driver of population growth, and confirms that reproductive success is greatly decreased in poor mast years, suggesting that the key to predicting wild boar dynamics is to ascertain local hunting pressure and to better understand changing food availability. Geography had no significant effect, indicating that it is not a good proxy for modelling the impact of change in climate or land-use on wild boar populations at the European scale. We use the framework to predict population abundance 9 years after an isolated population of wild boar established in the UK; in a comparison with the only field data and two independent modelling exercises, our framework provides the most robust and informative results.