A~2/O工艺厌氧池有机物降解动力学模型对比研究

试验考察了东阿县污水处理厂一期A2/O工艺厌氧池去除有机污染物效能,当进水ρ(COD)为548.3 mg/L时,厌氧池平均去除率达78.7%。同时探讨了几种常见数学模型模拟厌氧池去除有机物规律情况,根据实际工程监测数据确定有机底物降解动力学常数,得出Grau模型、Stover-kincannon模型和改进的Monod模型较适合模拟厌氧池去除有机物的规律,并对模型进行了检验。     

膜污染层微生物与聚丙烯微滤膜间的界面作用及其吸附特征

采用热力学方法及界面吸附理论,对2株膜污染层微生物(Aeromonas veronii M4、Aeromonas caviae N25)与聚丙烯(PP)微滤膜间的界面作用及吸附特征进行研究.结果表明,Aeromonas veronii M4与PP膜表面均表现出明显的疏水性特征,而Aeromonas caviae N25则呈现亲水性特征,并且A.veronii M4的运动性能也要高于A.caviae N25;另外,2株细菌及PP膜的表面均带有负电荷,表现出明显的电子供体特征,而Lewis酸碱分量U_(mlb)~(AB)则在2株细菌与PP膜的界面作用能中占据着主导地位;依据XDLVO理论,A.caviae N25及A.veronii M4与PP膜之间的总界面作用能均为负值,表明二者在膜上的吸附是一个主动吸附过程,而A.veronii M4-PP膜之间的界面作用能负值最大,说明A.veronii M4具有较高的吸附能力;静态吸附结果则表明,A.veronii M4在PP膜上的吸附量要明显高于A.caviae N25,而2株菌在膜上的吸附行为可由准二级动力学模型进行描述.     

大气作用下膨胀土地基的水分迁移与胀缩变形分析

运用土体渗流和蒸发理论,建立了大气-非饱和土相互作用模型;以现场观测的气象数据作为边界条件,进行了地基土中水分迁移的数值模拟,得到了大气作用下地基土体含水量的动态分布规律.计算结果表明,地基土中含水量变化幅度随深度增加而递减,3.5m深度以下土体的体积含水量基本不变,从而确定了南宁地区膨胀土地基的大气影响层深度为3.5...     

New Development in Study of the Faustmann Optimal Forest Harvesting

Chinese forest resources have become very scarce in the face of rapid economic growth demand, while the reform of collective forest right system is in full swing across the country. It will directly affect the regeneration level of forest resources and the diverse ecological value functions. In this article, the mainstream model paradigm of forest economics, that is, the basic framework of the Faustmann model and its evolution process are made in a more detailed explanation, especially the extended model in...     

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.     

Robustness of Meteorological Droughts in Dynamically Downscaled Climate Simulations

We examine the robustness of a suite of regional climate models (RCMs) in simulating meteorological droughts and associated metrics in present‐day climate (1971‐2003) over the conterminous United States (U.S.). The RCMs that are part of North American Regional Climate Change Assessment Program (NARCCAP) simulations are compared with multiple observations over the climatologically homogeneous regions of the U.S. The seasonal precipitation, climatology, drought attributes, and trends have been assessed. The reanalysis‐based multi‐model median RCM reasonably simulates observed statistical attributes of drought and the regional detail due to topographic forcing. However, models fail to simulate significant drying trend over the Southwest and West. Further, reanalysis‐based NARCCAP runs underestimate the observed drought frequency overall, with the exception of the Southwest; whereas they underestimate persistence in the drought‐affected areas over the Southwest and West‐North Central regions. However, global climate model‐driven NARCCAP ensembles tend to overestimate regional drought frequencies. Models exhibit considerable uncertainties while reproducing meteorological drought statistics, as evidenced by a general lack of agreement in the Hurst exponent, which in turn controls drought persistence. Water resources managers need to be aware of the limitations of current climate models, while regional climate modelers may want to fine‐tune their parameters to address impact‐relevant metrics.     

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.     

A Multilevel Model of the Impact of Farm‐Level Best Management Practices on Phosphorus Runoff1

Abstract: Multilevel or hierarchical models have been applied for a number of years in the social sciences but only relatively recently in the environmental sciences. These models can be developed in either a frequentist or Bayesian context and have similarities to other methods such as empirical Bayes analysis and random coefficients regression. In essence, multilevel models take advantage of the hierarchical structure that exists in many multivariate datasets; for example, water quality measurements may be taken from individual lakes, lakes are located in various climatic zones, lakes may be natural or man‐made, and so on. The groups, or levels, may effectively yield different responses or behaviors (e.g., nutrient load response in lakes) that often make retaining group membership more effective when developing a predictive model than when working with either all of the data together or working separately with the individuals. Here, we develop a multilevel model of the impact of farm level best management practices (BMPs) on phosphorus runoff. The result of this research is a model with parameters which vary with key practice categories and thus may be used to evaluate the effectiveness of these practices on phosphorus runoff. For example, it was found that the effect of fertilizer application rate on farm‐scale phosphorus loss is a function of the application method, the hydrologic soil group, and the land use (crop type). Further, results indicate that the most effective method for controlling fertilizer loss is through soil injection. In summary, the resultant multilevel model can be used to estimate phosphorus loss from farms and hence serve as a useful tool for BMP selection.     

Effects of acute γ-irradiation on the aquatic microbial microcosm in comparison with chemicals

Effects of acute γ-irradiation were investigated in the aquatic microcosm consisting of green algae (Chlorella sp. and Scenedesmus sp.) and a blue–green alga (Tolypothrix sp.) as producers; an oligochaete (Aeolosoma hemprichi), rotifers (Lecane sp. and Philodina sp.) and a ciliate protozoan (Cyclidium glaucoma) as consumers; and more than four species of bacteria as decomposers. At 100 Gy, populations were not affected in any taxa. At 500–5000 Gy, one or three taxa died out and populations of two or three taxa decreased over time, while that of Tolypothrix sp. increased. This Tolypothrix sp. increase was likely an indirect effect due to interspecies interactions. The principal response curve analysis revealed that the main trend of the effects was a dose-dependent population decrease. For a better understanding of radiation risks in aquatic microbial communities, effect doses of γ-rays compared with copper, herbicides and detergents were evaluated using the radiochemoecological conceptual model and the effect index for microcosm.     

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.