改良型AO法组合工艺中有机物的三维荧光分析

采用三维荧光(EEM)光谱技术,对上海竹园第二污水处理厂改良型AO法组合工艺运行过程中的各种溶解性有机物(DOM)进行分析,并对比研究传统好氧活性污泥法曝气池出水和A/O脱氮工艺硝化池出水DOM的EEM光谱的迁移变化特性.结果表明,各种DOM中主要的荧光物质有类蛋白质(荧光峰A和B)及类腐殖质(荧光峰C),经改良型AO法组合工艺处理后,荧光峰的强度降低了14％～60％,同时类蛋白质和腐殖质的结构也发生了变化;腐殖酸溯源表明DOM中的腐殖酸以微生物代谢产生的带有荧光基团的腐殖酸类为主.     

动态污水处理过程的多模型动态矩阵控制

针对活性污泥法污水处理系统的强耦合和动态变化特性,提出一种用于前置反硝化脱氮工艺的多模型动态矩阵(DMC)解耦控制方法;通过K-均值聚类分析法对外界入水中氨氮浓度进行聚类,获得以聚类中心为入水氨氮浓度的静态模型集合,分别设计线性DMC解耦控制器;再以当前时刻外界进水氨氮浓度和聚类中心为基本元素,构造切换函数,实现多模型切换。将该方法应用于活性污泥1号模型(ASM1)中,获得了较好的动态仿真效果。     

A biology-based dynamic approach for the reconciliation of acute and chronic toxicity tests: application to Daphnia magna

There is the need to integrate existing toxicity data in a coherent framework for extending their domain of applicability as well as their extrapolation potential. This integration would also reduce time and cost-consuming aspects of these tests and reduce animal usage. In this work, based on data extracted from literature, we have assessed the advantages that a dynamic biology-toxicant fate coupled model for Daphnia magna could provide when assessing toxicity data, in particular, the possibility to obtain from short-term (acute) toxicity test long-term (chronic) toxicity values taking into account the inherent variability of D. magna populations and the multiple sources of data. The results show that this approach overcomes some of the limitations of existing toxicity tests and that the prediction errors are considerably reduced when compared with the factor from 2 to 5 obtained using acute-to-chronic ratios.     

初始pH值对磷酸盐还原除磷的影响研究

以超高盐（盐度7％,以NaCI计）高磷榨菜废水为研究对象,考察了初始pH值对磷酸盐还原进程的影响。实验结果表明,初始pH值对磷酸盐还原除磷效能影响显著。初始pH为8时,磷酸盐还原除磷率达到最高,平均值为65．45％。同时,初始pH值还会影响污泥中活性磷的形成以及基体对磷化氢的吸附。此外,偏碱性有利于磷形态转化,且BD-P（主要是一些可溶性的、还原性强的、带有Fe-P化合物的集合）含量的高低调控着生物膜内间隙水中溶解态可反应性磷（DRP）和可还原水溶态磷（RSP）含量,最终决定着磷酸盐还原进程。随着初始pH值的升高,污泥对磷化氢的吸附能力降低导致污泥中结合态磷化氢（MBP）含量不断减少。     

Carry-over of dietary organochlorine pesticides, PCDD/Fs, PCBs, and brominated flame retardants to Atlantic salmon (Salmo salar L.) fillets

Information on carry-over of contaminants from feed to animal food products is essential for appropriate human risk assessment of feed contaminants. The carry-over of potentially hazardous persistent organic pollutants (POPs) from feed to fillet was assessed in consumption sized Atlantic salmon (Salmo salar). Relative carry-over (defined as the fraction of a certain dietary POP retained in the fillet) was assessed in a controlled feeding trial, which provided fillet retention of dietary organochlorine pesticides (OCPs), dioxins (PCDD/Fs), polychlorinated biphenyls (PCBs), and brominated flame retardants (BFRs). Highest retention was found for OCPs, BFRs and PCBs (31-58%), and the lowest retentions were observed for PCDD/Fs congeners (10-34%). National monitoring data on commercial fish feed and farmed Atlantic salmon on the Norwegian market were used to provide commercially relevant feed-to-fillet transfer factors (calculated as fillet POP level divided by feed POP level), which ranged from 0.4 to 0.5, which is a factor 5-10 times higher than reported for terrestrial meat products. For the OCP with one of the highest relative carry-over, toxaphene, uptake and elimination kinetics were established. Model simulations that are based on the uptake and elimination kinetics gave predicted levels that were in agreement with the measured values. Application of the model to the current EU upper limit for toxaphene in feed (50 μg kg⁻¹) gave maximum fillet levels of 22 μg kg⁻¹, which exceeds the estimated permissible level (21 μg kg⁻¹) for toxaphene in fish food samples in Norway.     

Water-soluble matter in PM2.5 in a coastal city over China: Chemical components, optical properties, and source analysis

Although marine and terrestrial emissions simultaneously affect the formation of atmospheric fine particles in coastal areas, knowledge on the optical properties and sources of water-soluble matter in these areas is still scarce. In this work, taking Qingdao, China as a typical coastal location, the chemical composition of PM_2.5 during winter 2019 was analyzed.Excitation-emission matrix fluorescence spectroscopy was combined with parallel factor analysis model to explain the component...     

Using the land transformation model to forecast vacant land

Growing or shrinking cities can experience increases in vacant land. As urban populations and boundaries fluctuate, holes can open in once tight urban areas. Many cities chase growth-oriented approaches to dealing with vacancies. It is critical to understand land-use alteration to accurately predict transformations of physical change in order to make better informed decisions about this phenomenon. This research utilizes the land transformation model (LTM), an artificial neural networking mechanism in Geographic Information Systems, to forecast vacant land. Variable influence on vacant land prediction and accuracy of the LTM is assessed by comparing input factors and patterns, using time-series data from 1990 to 2010 in Fort Worth, Texas, USA. Results indicate that the LTM can be useful in simulating vacant land-use changes but more precise mechanisms are necessary to increase accuracy. This will allow for more proactive decisions to better regulate the process of urban decline and regeneration.     

Predicting occurrence of juvenile shark habitat to improve conservation planning

Fishing and habitat degradation have increased the extinction risk of sharks, and conservation strategies recognize that survival of juveniles is critical for the effective management of shark populations. Despite the rapid expansion of marine protected areas (MPAs) globally, the paucity of shark‐monitoring data on large scales (100s–1000s km) means that the effectiveness of MPAs in halting shark declines remains unclear. Using data collected by baited remote underwater video systems (BRUVS) in northwestern Australia, we developed generalized linear models to elucidate the ecological drivers of habitat suitability for juvenile sharks. We assessed occurrence patterns at the order and species levels. We included all juvenile sharks sampled and the 3 most abundant species sampled separately (grey reef [Carcharhinus amblyrhynchos], sandbar [Carcharhinus plumbeus], and whitetip reef sharks [Triaenodon obesus]). We predicted the occurrence of juvenile sharks across 490,515 km² of coastal waters and quantified the representation of highly suitable habitats within MPAs. Our species‐level models had higher accuracy (? ≥ 0.69) and deviance explained (≥48%) than our order‐level model (? = 0.36 and deviance explained of 10%). Maps of predicted occurrence revealed different species‐specific patterns of highly suitable habitat. These differences likely reflect different physiological or resource requirements between individual species and validate concerns over the utility of conservation targets based on aggregate species groups as opposed to a species‐focused approach. Highly suitable habitats were poorly represented in MPAs with the most restrictions on extractive activities. This spatial mismatch possibly indicates a lack of explicit conservation targets and information on species distribution during the planning process. Non‐extractive BRUVS provided a useful platform for building the suitability models across large scales to assist conservation planning across multiple maritime jurisdictions, and our approach provides a simple for method for testing the effectiveness of MPAs.     

Vertical migration of radionuclides in undisturbed grassland soils

Literature data on numerical values obtained for the parameters of the two most popular models for simulating the migration of radionuclides in undisturbed soils have been compiled and evaluated statistically. Due to restrictions on the applicability of compartmental models, the convection–dispersion equation and its parameter values should be preferred. For radiocaesium, recommended values are derived for its effective convection velocity and dispersion coefficient. Data deficiencies still exist for radionuclides other than caesium and for soils of non-temperate environments.     

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.