NONLINEAR PROGRAMMING IN RIVER BASIN MODELING1

ABSTRACT: This paper explores the use of nonlinear programming in river basin water quality modelling. Applications recently reported in the literature, along with the author's experience with nonlinear programming, are reviewed. Results obtained using nonlinear programming are compared with the results obtained by other researchers using linear and dynamic programming to solve river basin water quality optimization problems. These water quality models have objective functions with continuous first partial derivatives, several inequality and variable bound constraints, and are of the form: minizie Σ^j=n_j=1Y_j(X_j) subject to Σ^j=n_j=1a_ijX_jb_i, i=1,2, …, m c_jX_jd_j, j= 1,2, …, n The variable X_i is the maximum allowable ratio of the BOD (biochemical oxygen demand) of the effluent outflow to the BOD of the wastewater inflow for treatment plant j, in the range c_j to d_j. The a_ijd and b_i are constants in the DO (dissolved oxygen) and BOD constraints. The resuks show, given certain assumptions about the data, that nonlinear programming is a better solution method for these problems than is either linear programming or dynamic programming.     

GENERATED MONTHLY STREAMFLOWS FOR THE MIDWESTERN AND SOUTHWESTERN UNITED STATES1

ABSTRACT A critical examination of single gage site, monthly streamflow statistical characteristics for two southern Illinois rivers, an Oklahoma river and a Texas river was made using a digital computer at Northwestern University. High flow variability for the rivers was evident in that, for the rivers tested, 8 to 11 months had coefficients of variation in excess of unity. The gamma distribution was not as efficient as the normal distribution for fitting power or logarithmic transforms of the historical monthly flow data (i.e., F^1-0, F^0-5, F^0-25, Fa¹²⁵, F^0.085, and log F). No single transform to a normal distribution was adequate for all twelve monthly flows, since definite seasonal grouping patterns were found for the four rivers examined. The highly variable flow in the low-flow season(s) indicated much more skewness than was typical of the remainder of the year. For the low-flow seasons, the higher-root (smaller exponent) transforms were particularly useful. Flows were generated from a linear regression model of lag one utilizing two or more transforms for the twelve periods. The definite seasonal patterns found historically were reproduced quite well in the generated streamflows. The effect of a change in data transform from one season to the next was insignificant after one month. Thus the use of different transforms within the year did not bias the results from the linear regression model appreciably, but did help in reproducing the seasonal distribution pattern. The technique seems especially well suited for rivers with highly variable flows.     

IMPROVING REGIONAL-MODEL ESTIMATES OF URBAN-RUNOFF QUALITY USING LOCAL DATA1

ABSTRACT: Urban water-quality managers need load estimates of storm-runoff pollutants to design effective remedial programs. Estimates are commonly made using published models calibrated to large regions of the country. This paper presents statistical methods, termed model-adjustment procedures (MAPs), which use a combination of local data and published regional models to improve estimates of urban-runoff quality. Each MAP is a form of regression analysis that uses a local data base as a calibration data set to adjust the regional model, in effect increasing the size of the local data base without additional, expensive data collection. The adjusted regional model can then be used to estimate storm-runoff quality at unmonitored sites and storms in the locality. The four MAPs presented in this study are (1) single-factor regression against the regional model prediction, P_u; (2) least-squares regression against P_u; (3) least-squares regression against P_u and additional local variables; and (4) weighted combination of P_u and a local-regression prediction. Identification of the statistically most valid method among these four depends upon characteristics of the local data base. A MAP-selection scheme based on statistical analysis of the calibration data set is presented and tested.     

The influence of different surface-modification treatments on biomass-based carbons and their effects on adsorption of carbon dioxide

Surface modification of biomass-based carbon with nitrogen-containing functional groups is performed by the different modification method, including the thermal and chemical methods. We also investigate the effect of the different reaction parameters on their pore structure using the Brunauer–Emmett–Teller surface area and adsorption performance based on methylene blue value. Fourier transforms infrared spectroscopy methods are performed to confirm the presence of N-containing groups. Based on above results, the comparison effect of different modification methods on physico-chemical propriety and adsorption properties of biomass-based carbon materials are carried out. In conclusion, all modification methods could enhance CO₂ adsorption capability. However, the carbon materials treated with ammonia using thermal method show the best performance.     

WASTE LOADINGS FROM A FRESHWATER ATLANTIC SALMON FARM IN SCOTLAND1

ABSTRACT: Recent studies suggest that waste generation from the freshwater phase of Atlantic salmon (Salmo salar L.) production varies considerably on an annual basis. A fish farm on the West Coast of Scotland was visited regularly during a two-year period to determine inflow and outflow water quality. Waste output budgets of suspended solids (SS), biochemical oxygen demand (BOD), total nitrogen (TN), total phosphorus (TP), total ammonia nitrogen (TAN = NH₃+NH₄⁺), dissolved reactive phosphorus (DRP) and total phosphorus (TP) were produced. The annual waste loadings obtained were 71 kg TN t fish^?1 yr^?1 (one year of data only), 10.9–11.1 kg TP t fish^?1 yr^?1, 1.2–2.1 kg DRP t fish^?1 yr^?1, 422–485 kg BOD₅ t fish^?1 yr^?1, 327–337 kg SS t fish^?1 yr^?1, and 30–35 kg TAN-N t fish^?1 yr^?1. Simple linear regression models relating waste parameter production to water temperature and feeding regime were developed. When compared to existing data for other salmonid production systems, greater ranges of daily waste loadings were observed. Wide variations in concentrations of these parameters during a daily cycle were also observed, suggesting that mass balance estimates of waste production will provide more robust estimates of waste output than frequent monitoring of outflow water quality.     

LAKEMAP: A 2-D AND 3-D MAPPING SYSTEM FOR VISUALIZING WATER QUALITY DATA IN LAKES1

ABSTRACT: The visualization of water quality data in lakes was achieved by integrating the U.S. Environmental Protection Agency's (EPA) STORET water quality database, lake shoreline polygons from EPA's Reach File (version 3), and the UNIMAP 2-D and 3-D interactive mapping and modeling software. Based on lake name (and state abbreviation), a lake shoreline polygon can be accessed from the Reach File. The coordinates of the polygon are portrayed by the U.S. Geological Survey (USGS) 1:100,000 scale Digital Line Graph (DLG) hydrography layer. This polygon is passed, in turn, to the STORET water quality file. Monitoring stations located within the polygon boundary are extracted along with the complete sampling survey. Specific parameters, such as total phosphorus, pH, ammonia, and optional time and depth restrictions can be selected to build a file of x, y, z₁, z₁…, zn data which is imported to UNIMAP. Up to four parameters, including depth, can be selected at a time. Within UNIMAP, the data is gridded and then displayed as a 2-D color contour map, 3-D perspective contour map, or 2-D projected time or depth slices. This system operates on the EPA ES9000 mainframe computer located in Research Triangle Park (RIP), North Carolina. LAKEMAP is the culmination of an effort to bridge the gap between the vast array of environmental data collected by the EPA and the complex analytical and display software resident on the mainframe.     

ESTIMATING ANNUAL FLOOD PROBABILITIES USING FOURIER SERIES METHOD1

ABSTRACT: The Fourier series method is proposed as a feasible non-parametric approach for the estimation of the density and distribution functions of annual floods. Clearly, the goodness of fit to empirical data improves as higher Fourier terms are incorporated, and the choice of a higher term depends on whether the inclusion of this term will reduce the fitting error to within a specified tolerance level. This method was applied to the flood data from eight rivers, and to data simulated from known distributions. The results are clearly better than other parametric methods, just like other non-parametric techniques currently used to estimate annual flood probabilities.     

基于Matlab曲线拟合的山东省各地市人口密度预测及Cartogram地图表现

通过Matlab软件的曲线拟合功能,以1993-2012年《山东省统计年鉴》中的人口统计数据为基础数据,对山东省17地市分别选择最佳拟合模型进行人口规模预测,依据行政区划面积计算人口密度,对结果以Cartogram的技术方法进行地图表现,得出直观的结果.该研究采用了新颖的专题地图表示方法,丰富了人口预测方法,对了解未来社会的供求关系和人口发展趋势、拟定正确合理的人口规划方案具有重大的理论和实践意义.     

A STATISTICAL APPROACH TO ASSESS FACTORS AFFECTING WATER CHEMISTRY USING MONITORING DATA1

ABSTRACT: A method to partition the variation in concentrations of water chemistry parameters in a river is described. The approach consists of fitting a family of curves for each chemical parameter. Each curve indicates the response of the parameter to river flow for a particular time period or location. An analysis of covariance is then used to identify statistically significant differences between curves. Such differences result largely from two factors: (1) the discharge of effluents and (2) river flow-concentration relationships. The deviations from the fitted curves indicate month-to-month variations unrelated to river flow that are controlled by factors such as temperature-related seasonal patterns. Underlying statistical assumptions are discussed with respect to water chemistry data. The technique is applied to a data set consisting of monthly samples of 22 water chemistry parameters from the Sulphur River of Texas and Arkansas. Several patterns of response to river flow and to two effluent discharges were revealed.     

Experimental investigation of adsorption capacity of anthill in the removal of heavy metals from aqueous solution

In the present work, the adsorption capacity of anthill was investigated as a low‐cost adsorbent to remove the heavy metal ions, lead (II) ion (Pb²⁺), and zinc (II) ion (Zn²⁺) from an aqueous solution. The equilibrium adsorption isotherms of the heavy metal ions were investigated under batch process. For the study we examined the effect of the solution's pH and the initial cations concentrations on the adsorption process under a fixed contact time and temperature. The anthill sample was characterized using a scanning electron microscope (SEM), X‐ray fluorescence (XRF), and Fourier transform infrared (FTIR) techniques. From the SEM analysis, structural change in the adsorbent was a result of heavy metals adsorption. Based on the XRF analysis, the main composition of the anthill sample was silica (SiO₂), alumina (Al₂O₃), and zirconia (ZrO₂). The change in the peaks of the spectra before and after adsorption indicated that there was active participation of surface functional groups during the adsorption process. The experimental data obtained were analyzed using 2‐ and 3‐parameter isotherm models. The isotherm data fitted very well to the 3‐parameter Radke–Prausnitz model. It was noted that Pb²⁺ and Zn²⁺ can be effectively removed from aqueous solution using anthill as an adsorbent.     

ESTIMATING AVERAGE MONTHLY LAKE EVAPORATION IN THE NORTHEAST UNITED STATES1

ABSTRACT: A methodology to estimate the average monthly lake evaporation, E(τ), (month τ=1,12) for fresh water bodies located in the northeast United States is presented. The approach combines analysis of at‐site, lake‐specific vertical water temperature profile data and a previously developed regional air temperature based model approximation of the widely accepted modified Penman energy budget estimate of mean monthly potential evaporation, E_p(τ) (mm/day). The paper presents procedures to develop site‐specific estimates of E_p(τ) and to convert water temperature data to average monthly conductive heat flux, G(τ). With monthly estimates of G(τ), the average monthly potential evaporation, E_p(τ), is then convertible to estimates of the average monthly lake evaporation, E(τ). This new method permits a good estimate of site‐specific lake evaporation rates without the data and computational requirements of the Penman energy budget procedure nor the comparatively expensive, time consuming field eddy correlation approach.     

Evaluation of life cycle inventory data for recycling systems

This paper reviews databases on material recycling (primary as well as secondary production) used in life cycle assessments (LCA) of waste management systems. A total of 366 datasets, from 1980 to 2010 and covering 14 materials, were collected from databases and reports. Totals for CO₂-equivalent emissions were compared to illustrate variations in the data. It was hypothesised that emissions from material production and the recycling industry had decreased over time due to increasing regulation, energy costs and process optimisation, but the reported datasets did not reveal such a general trend. Data representing the same processes varied considerably between databases, and proper background information was hard to obtain, which in turn made it difficult to explain the large differences observed. Those differences between the highest and lowest estimated CO₂ emissions (equivalents) from the primary production of newsprint, HDPE and glass were 238%, 443% and 452%, respectively. For steel and aluminium the differences were 1761% and 235%, respectively. There is a severe lack of data for some recycled materials; for example, only one dataset existed for secondary cardboard. The study shows that the choice of dataset used to represent the environmental load of a material recycling process and credited emissions from the avoided production of virgin materials is crucial for the outcome of an LCA on waste management. Great care and a high degree of transparency are mandatory, but advice on which datasets to use could not be determined from the study. However, from the gathered data, recycling in general showed lower emission of CO₂ per kg material than primary production, so the recycling of materials (considered in this study) is thus beneficial in most cases.     

Catalytic degradation of toxic organic dye using an aluminum-doped Cu0.4Zn0.6-xAlxFe2O4 (x = 0.0, 0.2, 0.4, 0.6) spinel ferrite in a photo-Fenton system

Catalytic activity of spinel ferrite in breaking down toxic dye materials are promising due to their uniqueness. In this study, aluminum-doped copper zinc ferrite, Cu_0.4Zn_0.6-xAl_xFe₂O₄ (x = 0.0, 0.2, 0.4, 0.6), a catalyst for toxic dye degradation is synthesized through chemical co-precipitation route. The formation of the spinel ferrite catalyst is initially confirmed by Fourier transform infrared spectra, which shows the frequency of metal-oxygen bond vibration at 539 and 427 cm⁻¹ attributed to the tetrahedral and octahedral sites respectively. Higher intensity sharp peak of X-ray diffraction for (311) plane is the evidence for the phase purity and the formation of spinel ferrite. The crystallite size is found to decrease with the increase of Al³⁺ ion. The surface structure of the obtained particles is investigated using a scanning electron microscope. Analyses of the material's magnetic characteristics using a vibrating sample magnetometer (VSM) revealed that it is, in fact, a soft magnet, as evidenced by the loop of its hysteresis, which is narrow. The catalytic degradation of methylene blue dye under the mechanism of the photo-Fenton process is studied with the obtained spinel ferrites and the result is found to be as high as 96.5%. The process follows pseudo-second order kinetics and the Langmuir isotherm.     

Zeolite formation from coal fly ash and heavy metal ion removal characteristics of thus-obtained Zeolite X in multi-metal systems

Zeolitic materials have been prepared from coal fly ash as well as from a SiO₂–Al₂O₃ system upon NaOH fusion treatment, followed by subsequent hydrothermal processing at various NaOH concentrations and reaction times. During the preparation process, the starting material initially decomposed to an amorphous form, and the nucleation process of the zeolite began. The carbon content of the starting material influenced the formation of the zeolite by providing an active surface for nucleation. Zeolite A (Na-A) was transformed into zeolite X (Na-X) with increasing NaOH concentration and reaction time. The adsorption isotherms of the obtained Na-X based on the characteristics required to remove heavy ions such as Ni²⁺, Cu²⁺, Cd²⁺ and Pb²⁺ were examined in multi-metal systems. Thus obtained experimental data suggests that the Langmuir and Freundlich models are more accurate compared to the Dubinin–Kaganer–Radushkevich (DKR) model. However, the sorption energy obtained from the DKR model was helpful in elucidating the mechanism of the sorption process. Further, in going from a single- to multi-metal system, the degree of fitting for the Freundlich model compared with the Langmuir model was favored due to its basic assumption of a heterogeneity factor. The Extended-Langmuir model may be used in multi-metal systems, but gives a lower value for equilibrium sorption compared with the Langmuir model.     

The Impact of Scientific Information on Ecosystem Management: Making Sense of the Contextual Gap Between Information Providers and Decision Makers

Scientific information is not always effectively incorporated into decision-making processes. This phenomenon seems to hold even when the information is aligned with an articulated need, is generated according to sound scientific procedures, and is packaged with end-user preferences in mind. We propose that contextual or cultural differences contribute significantly to the misalignment in communication between those who generate information and those who seek information for improved management of natural resources. The solution is to cultivate shared understanding, which in turn relies on acknowledgment and sharing of diverse values and attitudes. This constitutes a difficult challenge in a culturally diverse environment. Whereas cultural diversity represents wealth in experiences, knowledge and perspectives it can constrain the potential to develop the shared understandings necessary for effective integration of new information. This article illustrates how a lack of shared understanding among participants engaged in a resource-management process can produce and perpetuate divergent views of the world, to the extent that information and knowledge flows are ineffective and scientific information, even when requested, cannot be used effectively. Four themes were distilled from interviews with management and scientific staff of a natural resource–management agency in South Africa. The themes are used to illustrate how divergent views embedded in different cultures can discourage alignment of effort toward a common purpose. The article then presents a sense-making framework to illustrate the potential for developing shared understandings in a culturally diverse world.     

GENERALIZED LOW-FLOW FREQUENCY RELATIONSHIPS FOR UNGAGED SITES IN MASSACHUSETTS1

ABSTRACT: Regional hydrologic procedures such as generalized least squares regression and streamflow record augmentation have been advocated for obtaining estimates of both flood-flow and low-flow statistics at ungaged sites. While such procedures are extremely useful in regional flood-flow studies, no evaluation of their merit in regional low-flow estimation has been made using actual streamflow data. This study develops generalized regional regression equations for estimating the d-day, T-year low-flow discharge, Q_{d, t}, at ungaged sites in Massachusetts where d = 3, 7, 14, and 30 days. A two-parameter lognormal distribution is fit to sequences of annual minimum d-day low-flows and the estimated parameters of the lognormal distribution are then related to two drainage basin characteristics: drainage area and relief. The resulting models are general, simple to use, and about as precise as most previous models that only provide estimates of a single statistic such as Q_7,10. Comparisons are provided of the impact of using ordinary least squares regression, generalized least squares regression, and streamflow record augmentation procedures to fit regional low-flow frequency models in Massachusetts.     

Energy and carbon dioxide intensity of Thailand's steel industry and greenhouse gas emission projection toward the year 2050

The purpose of this article is to study the energy and carbon dioxide intensities of Thailand's steel industry and to propose greenhouse gas emission trends from the year 2011 to 2050 under plausible scenarios. The amount of CO₂ emission from iron and steel production was calculated using the 2006 Intergovernmental Panel on Climate Change (IPCC) guidelines in the boundary of production process (gate to gate). The results showed that energy intensity of semi-finished steel product was 2.84 GJ/t semi-finished steel and CO₂ intensity was 0.37 tCO_2eq/t semi-finished steel. Energy intensity of steel finishing process was 1.86 GJ/t finished steel and CO₂ intensity was 0.16 tCO_2eq/t finished steel. Using three plausible scenarios from Thailand's steel industry, S1: without integrated steel plant (baseline scenario), S2: with a traditional integrated BF–BOF route and S3: with an alternative integrated DR-EAF route; the Greenhouse Gas emissions from the year 2011 to 2050 were projected. In 2050, the CO₂ emission from S1 (baseline scenario) was 4.84 million tonnes, S2 was 21.96 million tonnes increasing 4.54 times from baseline scenario. The CO₂ emission from S3 was 7.12 million tonnes increasing 1.47 times from baseline scenario.     

Why be poor when we can be rich? Constructing responsible mining in El Pangui,Ecuador

Mining companies operating in Latin America are giving Corporate Social Responsibility (CSR) more attention than before, in part because of the rise in mining-related conflicts and criticism about the industry's social and environmental impacts. Companies propose that CSR could play an important role in mitigating conflict or lessening its risk. This article argues that the opposite may also be the case. As the mining conflict in El Pangui, Southeast Ecuador transforms social territorial dynamics, CSR also has a function in those transformations by contributing to the polarisation of conflict. The paper provides a brief ethnographic account of the ongoing conflict in El Pangui, and critically examines the moves made by the company, Corriente Resources Inc., to illustrate how CSR discourses and programmes may play an adverse role in social conflict.     

A MODIFIED RATIONAL FORMULA FOR FLOOD DESIGN IN SMALL BASINS1

ABSTRACT: New formulas and procedures under the framework of the Rational Formula are presented that are applicable to flood design problems for a small basin if the geometry of the basin can be approximated as an ellipse or a rhombus. Instead of making the assumption in the traditional rational formula that the rainfall is uniformly distributed in the whole duration (D_w) of a design storm, the new method modifies that assumption as: the rainfall is uniformly distributed only in each time interval CD) of the design storm hyetograph, thus extending the rational formula applicable to the case that the rainfall duration is less than the basin concentration time (T_c). The new method can be applied to estimate the flood design peak discharge, and to generate the flood hydrograph simultaneously. The derivation of the formulas is provided in detail in this paper, and an example is also included to illustrate how to apply the new formulas to the flood design problems in small basins.     

Phosphate rock production and depletion: Regional disaggregated modeling and global implications

Numerous recent studies discuss phosphate rock extraction, and some even propose that a peak in production could be reached in coming decades. This would have great consequences as phosphate rock based fertilizers are irreplaceable in modern agriculture. Studies suggesting an impending peak commonly use curve fitting models where mathematical functions are fitted to historical world production data, while studies using other methods reach completely different results. Also, a sudden increase in global reserve estimates is commonly used to dismiss these warnings, and has somewhat altered the debate. The recent multiplication of estimated reserves is mostly based on an increase of the Moroccan reserve estimate, leading to Morocco currently making up most of the global reserves. This study models global phosphate rock production using a disaggregated curve fitting model based on the production in individual major producing countries, providing a somewhat different view than most studies, and show that the global trade of phosphate rock could be completely dependent on Morocco in the future. There are several different factors that can potentially limit global production and these factors should be considered for the individual producing countries. Society's total dependence on phosphate rock should be further investigated despite claims of large resource occurrences.