Determination of toxic elements in waters and sediments from River Subin in the Ashanti Region of Ghana

Waters and sediments of Subin River, which flows through the industrial and commercial areas of Kumasi in the Ashanti region of Ghana, were geochemically investigated to ascertain heavy metal pollution levels due to anthropogenic activities. The study shows preoccupying pollution levels that constitute a threat to public and ecological systems. The waters of Subin River are neutral to slightly basic, inferred from pH values of 6.89–7.65). Electric conductivity (EC) of the waters ranges from 822 to 1,821 μs/cm and the range of total dissolved solids (TDS) is from 409 to 913 mg/l. Toxic elements contents of sediments and waters from 10 sites along the river were analysed by instrumental neutron activation analysis (INAA), and Al, As, Cd, Cr, Cu and Zn were determined. The concentrations of Al, As, Cd, Cr, Cu and Zn in the waters range between 4.02–15.18, 0.007–0.16, 0.002–0.05, 0.001–0.019, 1.32–7.04 and 4.28–10.2 mg/l, respectively. The contamination factors (CF) computed for the elements indicate that with the exception of sampling site S10, the sediments are polluted with Cd. Chromium contamination in the sediments is observed at S6 and S7, where the CF values were 1.39 and 1.52, respectively. The pollution load indices (PLI) were low (<1) and ranged from 0.14 to 0.75, suggesting that the overall sediment column of the river is not polluted.     

Step-up multiple regression model to compute Chlorophyll a in the coastal waters off Cochin, southwest coast of India

The interaction effects of abiotic processes in the production of phytoplankton in a coastal marine region off Cochin are evaluated using multiple regression models. The study shows that chlorophyll production is not limited by nutrients, but their physiological regulations (responses to nutrients, pH, temperature and salinity) are mainly responsible for the increased biological production. The model explaining 77% of variability for chlorophyll a production is indicative of preconditioning of the coastal waters. The phytoplankton production is found to be sensitive to the environment, which varies seasonally. Further, the study suggests that supply of organic matter and grazing of zooplankton (not included) would improve the model efficiency. Despite this, the good agreement in the computed and measured chlorophyll a values shows that step-up multiple regression model is a useful tool to understand the influence of environmental variables on the production of phytoplankton in these coastal waters.     

The Need for Scale Sensitive Approaches in Spatially Explicit Land Use Change Modeling

This paper introduces some of the issues that are relevant to the spatially explicit modeling of land use systems. A short overview is given of the ways and means in which a number of different land use change models describe the land use system. Specific attention is given to the empirical modeling approach used in the CLUE (Conversion of Land Use and its Effects) modeling framework. This approach is demonstrated for three case studies in China, Ecuador and the Atlantic Zone of Costa Rica. These case-studies illustrate the methodology for multi-scale analysis of land use driving factors and their application in spatially explicit modeling exercises. Model functioning, performance and limitations are discussed. The presented case-studies indicate that empirical modeling results can contribute to a better theoretic imbedding of land use change research in scale sensitive and integrated theories.     

Concentration of heavy metals in Karanja reservoir, Bidar district, Karnataka, India

In this study, some heavy metals concentrations (Zn, Pb, Fe, Mn, Cu, Ni) and other physico-chemical parameters were studied during October 2001 to September 2003 in Karanja reservoir, Bidar district. Water quality parameters were collected monthly basis whereas heavy metals were analyzed by Atomic Adsorption Spectrometer (AAS). Heavy metals have shown within the permissible limits, except Fe and Ni were recorded higher values in southwest monsoon, where as Mn has showed higher concentration in northeast monsoon in and summer. All other physico-chemical parameters are with in the permissible limit. Water is moderately hard and reservoir is productive.     

Application of GIS in the study of mass transport of pollutants by Adyar and Cooum Rivers in Chennai, Tamilnadu

Residential, industrial, commercial, institutional and recreational activities discharge degradable and non-degradable wastes that reach the coastal water through rivers and cause coastal pollution. In the present study, mass transport of pollutants by Adyar and Cooum Rivers to the coastal water as a result of land-based discharges was estimated during low tide. The lowest and the highest flow recorded in Adyar varied from 514.59 to 2,585.08×10⁶ litres/day. Similarly, the flow in Cooum River fluctuated between 266.45 and 709.34×10⁶ litres/day. The present study revealed that the Adyar River transported 53.89–454.11 t/d of suspended solids, 0.06–19.64 t/d of ammonia, 15.95–123.24 t/d of nitrate and 0.4–17.86 t/d of phosphate, 0.004–0.09 kg/d of cadmium, 0.15–1.29 kg/d of lead and 3.03–17.58 kg/d of zinc to the coastal water owing to its high discharge. Similarly, the Cooum River transported 11.87–120.06 t/d of suspended solids, 0.08–58.7 t/d of ammonia, 6.11–29.25 t/d of nitrate and 0.66–10.73 t/d of phosphate, 0.003–0.021 kg/d of cadmium, 0.02–0.44 kg/d of lead and 1.36–3.87 kg/d of zinc. A higher concentration of suspended solids was noticed in post monsoon and summer months. An increase in the mass transport of ammonia, nitrate, phosphate in summer months (April and May) and an increase in the mass transport of cadmium, lead and zinc were observed in monsoon months (October–December) in both the rivers. Thus mass transport of pollutants study reveal that Cooum and Adyar Rivers in Chennai contribute to coastal pollution by transporting inorganic and trace metals significantly through land drainage.     

The Role of Abatement Costs in GHG Permit Allocations: A Global Stabilization Scenario Analysis

Our objective is to propose permit allocation schemes that lead to a fair distribution of the net abatement cost among regions in a global greenhouse gas (GHG) stabilization scenario. We use a detailed technology-based energy model, World-MARKAL, to determine efficient abatement decisions, and to calculate the regional gross abatement costs (before permit allocation and trading). The net abatement costs are then calculated and used for different permit allocation schemes.     

Optimal Expansion Strategy for a Sewer System under Uncertainty

Because of fast urban sprawl, land use competition, and the gap in available funds and needed funds, municipal decision makers and planners are looking for more cost-effective and sustainable ways to improve their sewer infrastructure systems. The dominant approaches have turned to planning the sanitary sewer systems within a regional context, while the decentralized and on-site/cluster wastewater systems have not overcome the application barriers. But regionalization policy confers uncertainties and risks upon cities while planning for future events. Following the philosophy of smart growth, this paper presents several optimal expansion schemes for a fast-growing city in the US/Mexico borderlands—the city of Pharr in Texas under uncertainty. The waste stream generated in Pharr is divided into three distinct sewer sheds within the city limit, including south region, central region, and north region. The options available include routing the wastewater to a neighboring municipality (i.e., McAllen) for treatment and reuse, expanding the existing wastewater treatment plant (WWTP) in the south sewer shed, and constructing a new WWTP in the north sewer shed. Traditional deterministic least-cost optimization applied in the first stage can provide a cost-effective and technology-based decision without respect to associated uncertainties system wide. As the model is primarily driven by the fees charged for wastewater transfer, sensitivity analysis was emphasized by the inclusion of varying flat-rate fees for adjustable transfer schemes before contracting process that may support the assessment of fiscal benefits to all parties involved. Yet uncertainties might arise from wastewater generation, wastewater reuse, and cost increase in constructing and operating the new wastewater treatment plant simultaneously. When dealing with multiple sources of uncertainty, the grey mixed integer programming (GIP) model, formulated in the second stage, can further allow all sources of uncertainties to propagate throughout the optimization context, simultaneously leading to determine a wealth of optimal decisions within a reasonable range. Both models ran for three 5-year periods beginning in 2005 and ending in 2020. The dynamic outputs of this analysis reflect the systematic concerns about integrative uncertainties within this decision analysis, which enable decision makers and stakeholders to make all-inclusive decisions for sanitary sewer system expansion in an economically growing region.     

Modelling Tracer Dispersion from Landfills

Several wind tunnel experiments of tracer dispersion from reduced-scale landfill models are presented in this paper. Different experimental set-ups, hot-wire anemometry, particle image velocimetry and tracer concentration measurements were used for the characterisation of flow and dispersion phenomena nearby the models. The main aim of these experiments is to build an extensive experimental data set useful for model validation purposes. To demonstrate the potentiality of the experimental data set, a validation exercise on several mathematical models was performed by means of a statistical technique. The experiments highlighted an increase in pollutant ground level concentrations immediately downwind from the landfill because of induced turbulence and mean flow deflection. This phenomenon turns out to be predominant for the dispersion process. Tests with a different set-up showed an important dependence of the dispersion phenomena from the landfill height and highlighted how complex orographic conditions downwind of the landfill do not affect significantly the dispersion behaviour. Validation exercises were useful for model calibration, improving code reliability, as well as evaluating performances. The Van Ulden model proved to give the most encouraging results.     

A Model for Landscape Planning Under Complex Spatial Conditions

We present a new mathematical programming framework that is adaptable to a variety of spatially explicit landscape problems in environmental investment, conservation, and land-use planning, transport planning, and agriculture. As part of capturing spatial interdependencies, the framework considers decision variables at two levels, finely spaced grid cells and landholdings. We applied the framework to an environmental investment problem using objective functions representing biodiversity and carbon sequestration. We also tested the model to optimize the path of a road through part of the landscape. Using the Nambucca case study in eastern Australia, we applied a hybrid greedy randomised adaptive search procedure (GRASP) to find solutions to the model.