A mathematical model for metal ions uptake by aquatic plants for waste water treatment

A mathematical model is developed for metal ions uptake by aquatic plants. The model is based on a mechanism which assumes that the complex biological substances present in the plant react with the metal ions to form complexes of these ions at the solution–plant interface, and then the metal complexes diffuse through a membrane towards the bulk phase of the plant because of the concentration gradients present in the membrane. The model predicts the decreasing capacity of the plants for metal ions uptake as the contact time between the solution and the plant is increased. Experiments are conducted in the laboratory for the removal of chromium, copper, iron, nickel, lead and zinc by measuring metal ions uptake by two aquatic plants, Salvinia and Spirodela, in the solution of these metal ions of concentration ranging from 1 to 8 ppm. After estimating the parameters of the model, it is used for predicting the metal ions concentration in the solution as a function of time and the metal ions concentration inside the plants after 14 days of contact time. The comparison of the model predictions with the experimental results shows excellent agreement. The above model may be used for design and analysis of an aquatic‐plant‐based waste water treatment system. This revised version was published online in August 2006 with corrections to the Cover Date.     

A mathematical model to estimate errors associated with closed flux chambers

Errors associated with the closed flux chamber technique, used to measure surface emissions from landfills, were investigated by using a combination of numerical modeling and laboratory studies. A transient-state, advective–dispersive–reactive model was developed and used in conjunction with its steady-state version to quantify the errors associated with closed flux chambers. In developing the model, all four major gases, CH₄, O₂, CO₂, and N₂, and the oxidation of CH₄ to CO₂ were considered. Laboratory experiments were conducted on a monolayered as well as a two-layered landfill cover system to calibrate and verify the model. The model was used to develop a plot of the percentage errors associated with closed flux chambers of different dimensions and surface flux rates.     

以酵母菌作为敏感材料的BOD生物传感器研究

以一株耐高渗透压的酵母菌种作为敏感材料 ,研制的的生物传感器可采用稳态呼吸速率法进行 BOD快速测定。该方法与广为采用的五天生化需氧量标准稀释测定法有良好的相关性 ,线性范围为 0～ 2 0 0 mg/ L,可在 1 5 min内完成一个样品 BOD的测定。测定结果具有良好的重现性和准确度 ,标准曲线的线性相关系数达到 0 .9987     

Effects of organic ligands and pH on the leaching of copper from brake wear debris in model environmental solutions

Copper leaching from a disc brake wear debris sample was examined in a variety of aqueous solutions to simulate potential leaching processes during rain events and in surface waters. Synthetic rainwater leached 40% of the total copper present in the brake wear debris into solution after 18 h in batch reactors, which was approximately three times more copper than that extracted by the US Environmental Protection Agency's Synthetic Precipitation Leaching Procedure. Formate and acetate were responsible for the enhanced copper leaching, as demonstrated by higher average amounts of leached copper in synthetic rainwater with- versus without the organic acids (40 versus 31% recovery). This observation suggests leaching tests that do not incorporate the appropriate types and concentrations of organic ligands present in rainwater will likely underestimate copper mobilization from brake wear debris during rain events. Leaching of copper from the brake wear debris ranged from 23 to 40% in solutions containing 3 to 15 mg C L(-1) dissolved humic substances, and was higher still in solutions containing relatively high concentrations of the synthetic metal chelating agent ethylenediaminetetraacetic acid. Static pH tests demonstrated that copper leaching from brake wear debris is highly pH dependent, with more leaching occurring at lower solution pH values. Leaching rate studies revealed that equilibrium generally was not attained within 48 h in the model solutions, indicating that additional copper can be expected to be released in environments where brake wear debris is exposed to long-term leaching processes.     

A model for the sustainable selection of building envelope assemblies

The aim of this article is to define an evaluation model for the environmental impacts of building envelopes to support planners in the early phases of materials selection. The model is intended to estimate environmental impacts for different combinations of building envelope assemblies based on scientifically recognised sustainability indicators. These indicators will increase the amount of information that existing catalogues show to support planners in the selection of building assemblies.To define the model, first the environmental indicators were selected based on the specific aims of the intended sustainability assessment. Then, a simplified LCA methodology was developed to estimate the impacts applicable to three types of dwellings considering different envelope assemblies, building orientations and climate zones. This methodology takes into account the manufacturing, installation, maintenance and use phases of the building. Finally, the model was validated and a matrix in Excel was created as implementation of the model.     

WF-8型在线富集进样器应用于水中痕量CuPbCd测定的研究

用 WF 8型在线富集进样器与火焰原子吸收光度计联用 ,应用于水中痕量 Cu、Pb、Cd的测定 ,其富集倍数分别是 1 2 2、1 3 6和 94倍 ,测定的精密度分别是 3 7%、2 8%和 3 9% ,检出限分别是 0 4 7、1 3和 0 2 2μg L,在地表水样中的加标回收率分别为 94 2 %～ 1 0 0 %、98 8%～ 1 0 7%和 1 0 8%～ 1 2 0 % ,并对 WF 8型进样器与火焰原子吸收光度计的成功联用 ,提出了一种新操作程序。     

Continuous flow methods for evaluating the response of a copper ion selective electrode to total and free copper in seawater

This work describes the development of an instrument for measuring free and total copper in seawater by continuous flow analysis (CFA) with an Orion copper (II) ion selective electrode (CuISE). Sample analysis times are reduced considerably by using an extrapolation technique based on the fitting of an empirical mathematical expression to the electrode time-response curve enabling a prediction of the final equilibrium potential. CuISE measurements in seawater samples containing nanomolar levels of total copper can be very time consuming, and this predictive approach significantly reduces sample analysis time, and improves sample throughput. The time taken to measure pCu in seawater to a precision of +/- 0.1, using conventional potentiometry, varies considerably depending on the condition of the electrode membrane but can be reduced by a factor of 3-6 (typically from 60 to 10 min) by using the extrapolation technique in conjunction with CFA. Details are given of the protocols used for preconditioning the CuISE. The system can be used as a portable instrument for field measurements or for shipboard measurements of free copper in seawater. Extrapolated equilibrium potentials are within +/- 0.5 mV of true steady state values.     

A model of objective weighting for EIA

In spite of progress achieved in the research of environmental impact assessment (EIA), the problem of weight distribution for a set of parameters has not as yet, been properly solved. This paper presents an approach of objective weighting by using a procedure of P _ij principal component-factor analysis (P _ij PCFA), which suits specifically those parameters measured directly by physical scales. The P _ij PCFA weighting procedure reforms the conventional weighting practice in two aspects: first, the expert subjective judgment is replaced by the standardized measure P _ij as the original input of weight processing and, secondly, the principal component-factor analysis is introduced to approach the environmental parameters for their respective contributions to the totality of the regional ecosystem. Not only is the P _ij PCFA weighting logical in theoretical reasoning, it also suits practically all levels of professional routines in natural environmental assessment and impact analysis. Having been assured of objectivity and accuracy in the EIA case study of the Chuansha County in Shanghai, China, the P _ij PCFA weighting procedure has the potential to be applied in other geographical fields that need assigning weights to parameters that are measured by physical scales.     

A new model for climate system analysis: Outline of the model and application to palaeoclimate simulations

We present a new reduced-form model for climate system analysis. This model, called CLIMBER-2 (for CLIMate and BiosphERe, level 2), fills the current gap between simple, highly parameterized climate models and computationally expensive coupled models of global atmospheric and oceanic circulation. We outline the basic assumptions implicit in CLIMBER-2 and we present examples of climate system analysis including a study of atmosphere–ocean interaction during the last glacial maximum, an analysis of synergism between various components of the climate system during the mid-Holocene around 6000 years ago, and a transient simulation of climate change during the last 8000 years. These studies demonstrate the feasibility of a computationally efficient analysis of climate system dynamics which is a prerequisite for future climate impact research and, more generally, Earth system analysis, i.e., the analysis of feedbacks between our environment and human activities.     

A cost-precision model for marine environmental monitoring,based on time-integrated averages

Ongoing marine monitoring programs are seldom designed to detect changes in the environment between different years, mainly due to the high number of samples required for a sufficient statistical precision. We here show that pooling over time (time integration) of seasonal measurements provides an efficient method of reducing variability, thereby improving the precision and power in detecting inter-annual differences. Such data from weekly environmental sensor profiles at 21 stations in the northern Bothnian Sea was used in a cost-precision spatio-temporal allocation model. Time-integrated averages for six different variables over 6 months from a rather heterogeneous area showed low variability between stations (coefficient of variation, CV, range of 0.6–12.4%) compared to variability between stations in a single day (CV range 2.4–88.6%), or variability over time for a single station (CV range 0.4–110.7%). Reduced sampling frequency from weekly to approximately monthly sampling did not change the results markedly, whereas lower frequency differed more from results with weekly sampling. With monthly sampling, high precision and power of estimates could therefore be achieved with a low number of stations. With input of cost factors like ship time, labor, and analyses, the model can predict the cost for a given required precision in the time-integrated average of each variable by optimizing sampling allocation. A following power analysis can provide information on minimum sample size to detect differences between years with a required power. Alternatively, the model can predict the precision of annual means for the included variables when the program has a pre-defined budget. Use of time-integrated results from sampling stations with different areal coverage and environmental heterogeneity can thus be an efficient strategy to detect environmental differences between single years, as well as a long-term temporal trend. Use of the presented allocation model will then help to minimize the cost and effort of a monitoring program.     

Structural perturbations of models used in mathematical biology

The paper discusses the importance of understanding structural perturbations of models used in mathematical biology, where we mainly focus on ecology and dynamical systems. We describe first briefly the classical modeling strategy and the derivation of model structures. Structural perturbations are then discussed, mainly in the framework of ODEs. We give some examples how insights obtained from this type of model could be transfered to other kinds of models. Finally we propose an alternative modeling strategy characterized by a systematic investigation of a models neighbourhood in an appropriately chosen model class.     

Modelling and mapping of copper runoff for Europe

A predictive runoff rate model for copper has been refined and used to generate copper runoff maps for Europe. The new model is based on laboratory and field runoff data and expresses the runoff rate R (g m(-2) yr(-1)) through two contributions, both with a physical meaning: R = (0.37SO(0.5)(2) = 0.96 rain10(-0.62 pH) (cos(theta)/cos(45 degree)). Input parameters are the SO(2) concentration (microg m(-3)), pH, amount of rain (mm yr(-1)), and surface angle of inclination (theta). The first contribution originates from dry periods between rain events (the first-flush effect) and the second from the rain events. The dry term has been refined in comparison to the original model by assuming a mass balance between measured corrosion mass loss, calculated copper retention in the patina and predicted copper runoff. The refined model predicts 76% of all reported runoff rates, worldwide, within 35% from their measured value. This includes sites with low SO(2) concentration, where the original model erroneously predicted higher runoff rates than corrosion rates. Based on environmental data from the EMEP programme for the years 1980-2000, the new model has been used to derive runoff rate maps for Europe with 50 x 50 km grid resolution. The runoff mapping shows a substantial reduction in runoff rate over the investigated time period, and with copper runoff rates now generally less than 2 g m(-2) yr(-1).     

A groundwater flow model for water resources management in the Ismarida plain,North Greece

This paper presents the development of a regional flow simulation model of the stream–aquifer system of Ismarida plain, northeastern Greece. It quantifies the water budget for this aquifer system and describes the components of groundwater and the characteristics of this system on the basis of results of a 3-year field study. The semiconfined aquifer system of Ismarida Lake plain consists of unconsolidated deltaic clastic sediments, is hydraulically connected with Vosvozis River, and covers an area of 46.75 km². The annual precipitation ranges in the study area from 270 to 876 mm. Eighty-seven irrigation wells are densely located and have been widely used for agricultural development. Groundwater flow in this aquifer was simulated with MODFLOW. Model calibration was done with observed water levels, and match was excellent. To evaluate the impacts of the current pumping schedule and propose solutions, four management scenarios were formulated and tested with the model. Based on model results, the simulated groundwater budget indicates that there must be approximately 33% decrease of withdrawals to stop the dramatic decline of groundwater levels. The application of these scenarios shows that aquifer discharge to the nearby river would be very low after a 20-year period.     

A GIS-based spatial multi-index model for flood risk assessment in the Yangtze River Basin,China

This paper developed a GIS-based spatial multi-index model for large basin-scale flood risk assessment. In terms of the risk definition proposed by the IPCC, the flood risk in the Yangtze River Basin (YRB) was classified into indexes of hazard, vulnerability, and exposure. The model systematically accounts for various flood risk indicators related to the economic, social and ecological environment of the YRB. Using the robust data space analysis and processing capabilities of ArcGIS, these flood risk indicators were superimposed and analyzed to generate an integrated flood risk spatial distribution map for the YRB. The modeling results were verified reasonably well using observation data from the YRB floods in 1998, 2008, and 2016. We found that 24.90% of the study area was at very high and high risk in 1998, and the risk in these areas decreased to 15.95% and 17.61% in 2008 and 2016, respectively. We believe that the GIS-based spatial multi-index model can be applied to other areas where basin-scale flood risk assessment is desired and contribute to further scientific research on flood forecasting and mitigation.     

Multi-component assessment of worker exposures in a copper refinery. Part 2. Biological exposure indices for copper, nickel and cobalt

Urinary copper (Cu), nickel (Ni) and cobalt (Co) concentrations were determined for 127 Cu refinery workers (40 females, 87 males), with values of the 95% upper confidence interval of the geometric mean in nmol per mmol creatinine of 89 (Ni), 42 (Cu) and 3.4 (Co) for electrorefinery workers. In the pyrometallurgical departments, the corresponding concentrations were 37 (Ni), 99 (Cu) and 11 (Co). Female workers had higher Co urinary concentrations than males (p< or = 0.05) while no gender difference was observed for Cu and Ni. Inter-elemental correlations were moderate to weak. Based on the inhalable aerosol levels reported previously for the same workers, the observed urinary Cu concentrations were considerably lower than expected, relative to Co and Ni. This is interpreted in terms of the current understanding of Cu homeostasis.     

A stochastic conflict resolution model for trading pollutant discharge permits in river systems

This paper presents an efficient methodology for developing pollutant discharge permit trading in river systems considering the conflict of interests of involving decision-makers and the stakeholders. In this methodology, a trade-off curve between objectives is developed using a powerful and recently developed multi-objective genetic algorithm technique known as the Nondominated Sorting Genetic Algorithm-II (NSGA-II). The best non-dominated solution on the trade-off curve is defined using the Young conflict resolution theory, which considers the utility functions of decision makers and stakeholders of the system. These utility functions are related to the total treatment cost and a fuzzy risk of violating the water quality standards. The fuzzy risk is evaluated using the Monte Carlo analysis. Finally, an optimization model provides the trading discharge permit policies. The practical utility of the proposed methodology in decision-making is illustrated through a realistic example of the Zarjub River in the northern part of Iran.     

A model for the maximum credible hourly impact on any ground receptor from point sources with momentumdominated plume rise

A pollutant dispersion model is developed, allowing rapid evaluation of the maximum credible one-hour-average concentration on any given ground-level receptor, along with the corresponding critical meteorological conditions (wind speed and stability class) for stacks with momentum-dominated plume rise in urban or rural areas under buoyancy or no buoyancy induced dispersion. Site-specific meteorological data are not required, as the computed concentrations are maximized against all credible combinations of wind speed, stability class, and mixing height.The analysis is based on the dispersion relations of Pasquill-Gifford and Briggs for rural and urban settings respectively, the buoyancy induced dispersion correlation of Pasquill, the wind profile exponent values suggested by Irwin, the momentum plume rise relations of Briggs, as well as the Benkley and Schulman's model for the minimum mixing heights.The model is particularly suited for air pollution management studies, as it allows fast screening of the maximum impact on any selected receptor and evaluation of the ways to have this impact reduced. Also, for regulatory purposes, as it allows accurate setting of minimum stack height requirements as function of the exit gas volume and velocity, the pollutant emission rates and their hourly concentration standards, as well as the source location relative to sensitive receptors.     

A hybrid model of external environmental benefits compensation to practitioners for the application of prefabricated construction

As the creators of the external benefits of prefabricated construction implementation, the government, real estate developers, and homebuyers have the right to allocate the external benefits. However, there is no effective quantitative method for achieving this goal. Therefore, this study aims to develop a quantitative analysis model for the reasonable allocation of the external benefits among the creators. The externality theory and bargaining theory were introduced to this study as the research foundation. Through literature review, the environmental benefit quantification index was defined. A bargaining model including Game 1 and Game 2 was designed for determining the external benefits allocation ratios for each player. In Game 1, the government was considered as the agent of homebuyers to conduct the bargaining game with real estate developers. Game 2 reflected the bargaining game process between the government and homebuyers for sharing the ratio of external benefits achieved from Game 1. The powerful position in bargaining game and discount factors of each player were considered as the critical factors influencing the distribution ratio because the value will change with the development of prefabricated construction. A prefabricated construction building was selected as a case to illustrate the applicability of this proposed model. The distribution result is that the government, the real estate developers, and homebuyers should share the external benefits of prefabrication implementation by 38%, 35%, and 27% respectively. This study contributes to aiding the creators to achieve optimal benefits allocation and thus motivates the enthusiasm of practitioners in prefabricated construction implementation.