A contribution to the study of phosphate sorption by three Greek fly ashes

Three fly ashes from Greece, produced from lignite burning, proved efficient in removing phosphate from solution. Maximum amounts of phosphate removed ranged from 0.064 to 0.099 mmol PO³ ₄ ^– per g of material. Fly ashes that contained higher amounts of calcite and anhydrite seemed to be better sinks for phosphate. From the various adsorption isotherm equations tested, the Langmuir equation described phosphate sorption satisfactorily. Although, the exact mechanism of phosphate sorption could not be revealed, it is believed that it involved an adsorption and/or precipitation process.     

An analytical solution of the advection-diffusion equation considering non-local turbulence closure

Atmospheric air pollution turbulent fluxes can be assumed to be proportional to the mean concentration gradient. This assumption, along with the equation of continuity, leads to the advection-diffusion equation. Moreover, large eddies are able to mix scalar quantities in a manner that is counter to the local gradient. We present a general solution of a two-dimension steady state advection-diffusion equation, considering non-local turbulence closure using the General Integral Laplace Transform Technique. We show some examples of applications of the new solution with different vertical diffusion parameterisations.     

Spreading of oil on water in the surface-tension regime

The third stage of oil spreading on water, in which surface-tension force promotes spreading against the resisting viscous effect, is investigated using a similarity solution in combination with an integral boundary-layer technique to solve the unidirectional oil-spreading dynamics problem in the last stage of spreading. The thin layer is assumed to be supplied by oil from a bulk boundary. Using a constitutive equation for oil-film surface tension versus oil-film thickness, analytical solutions near the bulk boundary and near the edge are developed. Using the asymptotic solutions to initiate integration, the differential equations for the oil thickness, oil velocity, and boundary-layer profiles are integrated starting from the leading edge and bulk boundary, which after matching provide a complete solution. The results for the spreading-law prefactors are found to differ by about 10 % from published theoretical results using the same constitutive equation. Using an empirical constitutive equation for oil-film surface tension versus distance from the bulk boundary leads to a spreading-law prefactor that is in excellent agreement with the published experimental result and published theoretical work providing and using the same empirical constitutive equation.     

Self-aeration in the rapidly- and gradually-varying flow regions of steep smooth and stepped spillways

In high-velocity chute flows, free-surface aeration is often observed. The phenomenon is called self-aeration or white waters. When the turbulent shear stresses next to the free-surface are large enough, air bubbles are entrained throughout the entire air–water column. A rapidly-varied flow region is observed immediately downstream of the inception point of free-surface aeration. An analytical solution of the air diffusion equation is proposed and the results compare well with new experimental data. Both experiments and theory indicate that the flow bulking spans over approximately 3–4 step cavities downstream of the inception point of free-surface aeration on a stepped chute. Further downstream the void fraction distributions follow closely earlier solutions of the air diffusion equation. The application of the diffusion equation solution to prototype and laboratory data shows air bubble diffusivities typically larger than the momentum transfer coefficient. The result highlights however a marked decrease in the ratio of air bubble diffusivity to eddy viscosity with increasing Reynolds number. The finding might indicate some limitation of laboratory investigations of air bubble diffusion process in self-aerated flows and of their extrapolation to full-scale prototype applications.     

Testing Accuracy of Finite Element and Random Walk Schemes in Prediction of Pollutant Dispersion in Coastal Waters

Distribution of pollutants in coastal waters is usually represented by depth averaged twodimensional convection-dispersion equation. Under very specific conditions this equation can be solved analytically. Although such a solution is restricted to simplified situations it provides a very useful case for testing the performance of various numerical solution techniques currently available for the simulation of convective-dispersion of pollutants in natural water systems. In this paper the analytical solution of the convective dispersion equation is used as a benchmark against which the accuracy of other techniques are assessed. These assessments are based on quantitative comparisons between the results of the solution of two-dimensional convection-dispersion equation by the deterministic finite element and stochastic random walk methods. Both Eulerian and Lagrangian frameworks are employed to obtain the finite element solution of the convection-dispersion problem. It has been shown that the Lagrange–Galerkin finite element scheme yields the most accurate results for the case under study. However, computational costs of the Lagrange–Galerkin method can be relatively high and under certain conditions it may be reasonable to use a less accurate but cost effective random walk scheme to make water quality management decisions.     

Solute transport in a semi-infinite homogeneous aquifer with a fixed point source concentration

This study derives an analytical solution of the advection–dispersion (AD) equation commonly used to describe the transport of pollutants in a semi-infinite homogeneous aquifer. When an extra constant source term is added to the AD equation, it changes the solution of the equation. The AD equation is solved analytically using Laplace transform. Also, the equation is solved numerically using an explicit finite difference method and its stability condition is presented with the aid of matrix method. For the solution of the AD equation the following considerations are made: (1) The dispersion and velocity are considered as time-dependent; (2) dispersion is expressed as directly proportional to the square of velocity; (3) there is also diffusion; (4) there is some initial concentration and the aquifer domain is, therefore, not pollutant-free; (5) There is a time-dependent exponentially decreasing input source; and (6) the concentration gradient is assumed to be zero at the exit boundary. It is found that the contaminant concentration decreases with time contrary to what happens when the extra term is not included.     

A new model for soil–water drainage problems

Seepage flow is an agent related to the transport and dispersion of contamination in groundwater. Steady two-dimensional seepage flow is governed by Laplace’s equation, for which several solution techniques are available. Because computations are complex from a practical point of view, simplified models encompass the Dupuit-Forchheimer approach assuming a horizontal flow. However this approach is inaccurate in seepage problems involving steep drawdowns. In this research, a new theoretical model for 2D seepage flow is proposed based on Fawer’s theory for curved flows Castro-Orgaz (Environ Fluid Mech 10(3):2971–2310, 2010), from which a second-order equation results describing the seepage surface. From this development, a numerical solution for the rectangular dam problem based on the second-order model is presented, whereas a simple first-order equation is found to describe flow to drains under a uniform rainfall. The results of this new model are compared with the full 2D solution of Laplace’s equation for typical test cases, resulting in an excellent agreement.     

Predicting reproduction rate of varroa

A single equation is derived to predict population-density effects on the reproduction rate of the honey bee parasite Varroa destructor Anderson and Trueman. This equation provides a simpler alternative to the approach currently used in the literature, and additionally corrects an anomaly in that approach. The method is then extended to the case of co-existing haplotypes of Varroa. It thus derives an equation used without proof for modelling biocontrol of Varroa, and examines the error caused by an approximation necessary for a closed form solution. Additionally a varroa population model incorporating the derived equation is described.     

新生MnO2对甲基橙废水的脱色特性研究

以化学法合成的新生MnO2作吸附剂,对水中甲基橙染料进行吸附脱色研究,探讨了影响吸附的因素和吸附机理。结果表明：新生Mn2对甲基橙的吸附符合Langmuir吸附等温式,吸附速率大,吸附前溶液pH值是影响染料脱色效果的最主要因素,吸附后溶液pH和温度影响较小。在实验条件下可使甲基橙脱色率达99％。     

Measuring sustainable governance in the European Union

This paper examines the problem of measuring sustainable governance in the European Union (EU-27) through the use of duality and the Slutsky equation. The proposed methodology is based on the application of a three-dimensional optimisation model, where the arguments of the objective (sustainable social welfare) function are economic goods that contribute to sustainable economic growth; environmental goods that provide for sustainable environmental protection; and social goods through which sustainable social development is achieved. The dual problem, formulated through this three-dimensional theoretical model, is solved to find the optimal solution, indicating a certain sustainability level. We suggest that this solution can be used for calculating the value of what we define here as the sustainable governmental policy indicator, which is considered to provide quantitative measurement of government policies on sustainable development within the context of ‘good governance’. Furthermore, it is suggested that the Slutsky equation can be used as a reliable method for long-term monitoring and planning of national as well as international good governance with regard to sustainable development policies. In its empirical part, the paper applies the theoretical model in an analysis of the sustainable development indicators (as set out in the Sustainable Development Strategy (SDS) of the EU) in Bulgaria for the period 2000–2010 and compares them to those of the EU-27.     

Mass conservation and atmospheric dynamics in the Regional Atmospheric Modeling System (RAMS)

This paper examines the spatio-temporal patterns of atmospheric carbon dioxide transport predicted by the Regional Atmospheric Modeling System (RAMS). Forty-eight hour simulations over northern New England incorporating a simple representation of the diurnal summertime surface carbon dioxide forcing arising from biological activity indicate that, in its native formulation, RAMS exhibits a significant degree of mass non-conservation. Domain-wide rates of non-physical mass gain and mass loss are as large as three percent per day which translates into approximately eleven parts per million per day for carbon dioxide — enough to rapidly dilute the signature of carbon dioxide fluxes arising from biological activity. Analysis shows that this is due to the approximation used by RAMS to compute the Exner function. Substitution of the exact, physically complete equation improves mass conservation by two orders of magnitude. In addition to greatly improving mass conservation, use of the complete Exner function equation has a substantial impact on the spatial pattern of carbon dioxide predicted by the model, yielding predictions differing from a conventional RAMS simulation by as much as forty parts per million. Such differences have important implications both for comparisons of modeled atmospheric carbon dioxide concentrations to observations and for carbon dioxide inversion studies, which use estimates of atmospheric transport of carbon dioxide in conjunction with measurements of atmospheric carbon dioxide concentrations to infer the spatio-temporal distribution of surface carbon dioxide fluxes. Furthermore, use of the complete Exner function equation affects the vertical velocity and water mixing ratio fields, causing significant changes in accumulated precipitation over the region.     

Models predicting the fate of pollutants in rivers

The spill of 2,4,‐D in the Rhine river was used to show the evolution from simple to sophisticated models. The first simulation was done with an analytical solution of the dispersion‐advection equation without elimination. Elimination was introduced in a second simulation. The third simulation was carried out with a numerical model. This included elimination and variable dispersion. The lack of data limited the use of very detailed models.     

Use of fly ash agglomerates for removal of arsenic

The aim of this work is to investigate the application of fly ash adsorbent for removal of arsenite ions from dilute solution (100–1,000 ppm). Experiments were carried out using material from the “Turów” (Poland) brown-coal-burning power plant, which was wetted, then mixed and tumbled in a granulator to form spherical agglomerates. Measurements of arsenic adsorption from aqueous solution were carried out at room temperature and natural pH of fly ash agglomerates, in either a shaken flask or circulating column, to compare two different methods of contacting solution with adsorbent. Adsorption isotherms of arsenic were determined for agglomerated material using the Freundlich equation. Kinetic studies indicated that sorption follows a pseudo-second-order model. Preferable method to carry out the process is continuous circulation of arsenite solution through a column.     

Conservation decision-making in large state spaces

When looking for the best course of management decisions to efficiently conserve metapopulation systems, a classic approach in the ecology literature is to model the optimisation problem as a Markov decision process and find an optimal control policy using exact stochastic dynamic programming techniques. Stochastic dynamic programming is an iterative procedure that seeks to optimise a value function at each timestep by evaluating the benefits of each of the actions in each state of the system defined in the Markov decision process.Although stochastic dynamic programming methods provide an optimal solution to conservation management questions in a stochastic world, their applicability in metapopulation problems has always been limited by the so-called curse of dimensionality. The curse of dimensionality is the problem that adding new state variables inevitably results in much larger (often exponential) increases in the size of the state space, which can make solving superficially small problems impossible. The high computational requirements of stochastic dynamic programming methods mean that only simple metapopulation management problems can be analysed. In this paper we overcome the complexity burden of exact stochastic dynamic programming methods and present the benefits of an on-line sparse sampling algorithm proposed by Kearns, Mansour and Ng (2002). The algorithm is particularly attractive for problems with large state spaces as the running time is independent of the size of the state space of the problem. This appealing improvement is achieved at a cost: the solutions found are no longer guaranteed to be optimal.We apply the algorithm of Kearns et al. (2002) to a hypothetical fish metapopulation problem where the management objective is to maximise the number of occupied patches over the management time horizon. Our model has multiple management options to combat the threats of water abstraction and waterhole sedimentation. We compare the performance of the optimal solution to the results of the on-line sparse sampling algorithm for a simple 3-waterhole case. We find that three look-ahead steps minimises the error between the optimal solution and the approximation algorithm. This paper introduces a new algorithm to conservation management that provides a way to avoid the effects of the curse of dimensionality. The work has the potential to allow us to approximate solutions to much more complex metapopulation management problems in the future.     

酸沉降临界负荷计算模式的修正

酸沉降临界负荷是酸沉降水平的函数,不同酸沉降水平下,矿物风化速率有数量级差别,在因此,酸沉降临界负荷的计算应先使用判别方程计算平衡ＰＨ值,然后确定采用何种方法计算,在欧洲可以直接采用动态模式计算临界负荷,是因为其酸沉水平能满足判别方程成立,但在中国大多数情况下不成立。     

Obtaining species: sample size considerations

Suppose fish are to be sampled from a stream. A fisheries biologist might ask one of the following three questions: ‘How many fish do I need to catch in order to see all of the species?’, ‘How many fish do I need to catch in order to see all species whose relative frequency is more than 5%?’, or ‘How many fish do I need to catch in order to see a member from each of the species A, B, and C?’. This paper offers a practical solution to such questions by setting a target sample size designed to achieve desired results with known probability. We present three sample size methods, one we call ‘exact’ and the others approximate. Each method is derived under assumed multinomial sampling, and requires (at least approximate) independence of draws and (usually) a large population. The minimum information needed to compute one of the approximate methods is the estimated relative frequency of the rarest species of interest. Total number of species is not needed. Choice of a sample size method depends largely on available computer resources. One approximation (called the ‘Monte Carlo approximation’) gets within ±6 units of exact sample size, but usually requires 20–30 minutes of computer time to compute. The second approximation (called the ‘ratio approximation’) can be computed manually and has relative error under 5% when all species are desired, but can be as much as 50% or more too high when exact sample size is small. Statistically, this problem is an application of the ‘sequential occupancy problem’. Three examples are given which illustrate the calculations so that a reader not interested in technical details can apply our results.     

Dynamic reserve site selection under contagion risk of deforestation

Recently, dynamic reserve site selection models based on stochastic dynamic programming (SDP) have been proposed. The models consider a random development pattern in which the probability that a site will be developed is independent of the development status of other sites. However, development often takes the form of a contagion process in which the sites most likely to be developed are near sites that already have been developed. To consider site selections in such cases, we propose improved algorithms that make use of a graph representation of the sites network. The first formulation is an exact, dynamic programming algorithm, with which theoretical and experimental complexities are evaluated. The exact method can be applied only to small problems (less than 10 sites), but real-world problems may have hundreds or thousands of sites, implying that heuristic selection methods must be used. We provide a general framework for describing such heuristic solution methods, and propose a new heuristic method based on a parameterised reinforcement learning algorithm. The method allows us to compute a heuristic function by performing and exploiting many simulations of the deforestation process. We show that the method can be applied to problems with hundreds of sites, and demonstrate experimentally that it outperforms previously proposed heuristic methods in terms of the average number of species conserved.     

Analytical solutions of nonlinear and variable-parameter transport equations for verification of numerical solvers

All numerical codes developed to solve the advection–diffusion-reaction (ADR) equation need to be verified before they are moved to the operational phase. In this paper, we initially provide four new one-dimensional analytical solutions designed to help code verification; these solutions are able to handle the challenges of the scalar transport equation including nonlinearity and spatiotemporal variability of the velocity and dispersion coefficient, and of the source term. Then, we present a solution of Burgers’ equation in a novel setup. Proposed solutions satisfy the continuity of mass for the ambient flow, which is a crucial factor for coupled hydrodynamics-transport solvers. By the end of the paper, we solve hypothetical test problems for each of the solutions numerically, and we use the derived analytical solutions for code verification. Finally, we provide assessments of results accuracy based on well-known model skill metrics.     

Lethal effects of elevated pH and ammonia on juveniles of neotropical fish Colosoma macropomum (Pisces, Caracidae)

Ammonia is the main nitrogenous waste material excreted by gills, then is oxided first to nitrite and then to nitrate. The proportion of ionized-un-ionized ammonia depends on pH and temperature, when this variables increase in a solution containing ammonia the equation goes to left, so the proportion of NH3 increases and the solution becomes more toxic. The purpose of this study was to investigate the acute lethal effects of elevated pH and ammonia on tambaqui juveniles. With a constant ammonia concentration of 5.0 mg/l NH3, there was no mortality a pH of 6.0 (control) and 7.0; but was of 10-20% a pH of 8.0 and 100% at 9.0. The lethal effects of elevated pH and un-ionized ammonia should be recognized as a potential factor contributing to the variable success of tambaqui production ponds, but this species is highly resistant in comparison with other freshwater fish.