Government fiscal strategy for mining to 2000

World Bank studies predict little or no change in mineral demand in the 1990s, and also an extended period, in real terms, of low mineral prices. In such a climate the fiscal strategy of government needs to be one which emphasizes revenue sources which are independent of mineral prices. In the 1970s, rising prices made fiscal regimes which capture economic rents attractive. In the 1990s, royalties and other duties which are dependent on the level of production and would also take advantage of any short boom in mineral prices would seem to be the best fiscal regime for a government to follow.     

Breakthrough Curves Characterization and Identification of an Unknown Pollution Source in Groundwater System Using an Artificial Neural Network (ANN)

Contamination of groundwater constrains its uses and poses a serious threat to the environment. Once groundwater is contaminated, the cleanup may be difficult and expensive. Identification of unknown pollution sources is the first step toward adopting any remediation strategy. The proposed methodology exploits the capability of a universal function approximation by a feed-forward multilayer artificial neural network (ANN) to identify the sources in terms of its location, magnitudes, and duration of activity. The back-propagation algorithm is utilized for training the ANN to identify the source characteristics based on simulated concentration data at specified observation locations in the aquifer. Uniform random generation and the Latin hypercube sampling method of random generation are used to generate temporal varying source fluxes. These source fluxes are used in groundwater flow and the transport simulation model to generate necessary data for the ANN model-building processes. Breakthrough curves obtained for the specified pollution scenario are characterized by different methods. The characterized breakthrough curves parameters serve as inputs to ANN model. Unknown pollution source characteristics are outputs for ANN model. Experimentation is also performed with different number of training and testing patterns. In addition, the effects of measurement errors in concentration measurements values are used to show the robustness of ANN based methodology for source identification in case of erroneous data.     

Hg Vapor Emission from Broken Compact Fluorescent Lamps (CFLs) in an Acrylic Chamber

The United States Environmental Protection Agency/Environmental Response Team (US EPA/ERT), in collaboration with St. John's College, Dr. B. R. Ambedkar University, Agra, India, is conducting a study to determine Hg vapor emission rates resulting from broken compact fluorescent lamps (CFLs) in a residential setting. The overall objectives of the study are to determine Hg vapor emission data and provide homeowners with cleanup procedures and disposal options for broken CFLs. Most of the currently available CFLs in the US market are manufactured in China for US companies. Several different types of CFLs were purchased from local stores and their Hg content was determined. Based on previous studies, such as the 2011 study by Singhvi and colleagues, five popular spiral CFLs were selected for emission studies in an acrylic chamber. This study found that Hg vapor emissions from CFLs may be significantly greater than those from beads of liquid Hg with weights comparable to the Hg content of the CFLs. The average 24-hour Hg loss into the atmosphere from CFLs broken on a plastic surface ranged from 0.6% to 22% of the bulb content, while that for CFLs broken on carpet ranged from 2.6% to 28%. Projections for a 12 foot × 9.33 foot × 8 foot (25.4 m³) room based on the chamber measurements in this study indicate that CFL breakage in some household settings may produce 24-hour Hg concentrations above the 2000 Agency for Toxic Substances and Disease Registry (ATSDR) minimum risk level (MRL) of 0.2 μg/m³, for typical air exchange rates. This study also indicates that Hg emission may not be proportional to exposed surface area based on experiments using liquid Hg with different surface areas.     

Urban soil quality of Raipur,Chhattisgarh, India

Soil quality in urban areas in India is degraded due to multiple anthropogenic activities. The objectives of this work are to determine the concentration variations, toxicity, and sources of carbons, metals, and ions in the surface soil of Raipur, the industrialized capital city of Chhattisgarh state, India. High concentrations of Al, K, Ca, Ti, Fe, and elemental carbon (EC) were registered. Relatively lower concentrations of V, Cr, Mn, Ni, Cu, Zn, Sr, Ba, Pb, organic carbon (OC), and carbonate carbon (CC), as well as ions (viz. F^–, Cl^–, NO₃^–, SO₄^2–, Na⁺, K⁺, Mg²⁺, and Ca²⁺), were also recorded. EC was found to be one of the major pollutants, although enrichment factors pointed to high contamination with SO₄^2–, K⁺, Mg²⁺_, Cr, Mn, and Pb; and extreme contamination with NO₃^– and Ca²⁺. The spatial and temporal variations, enrichment factors, toxicity, and sources of the chemical species detected in the soil are discussed.     

Supply responses in tropical forestry: A Malaysian case study

The rapid exhaustion of Malaysia's commercial primaeval forest base has raised questions regarding the management and economic responses in the sector. The article assesses the institutional and management structure of Malaysian forestry which, together with the social and political barriers at work, prevent an orderly programme of harvesting and reforestation. The supply is then set out in terms of an econometric model, formulated both in static and dynamic terms to measure, among other things, the responses of output to price changes. The model, which is the first of its kind to be tested for the Malaysian forestry sector, is applied on three wood-based commodities — sawlogs, sawnwood and plywood. To learn of possible regional variations, the model is also applied to data of the country's three principal components — Peninsular Malaysia, Sarawak and Sabah. The results indicate that short-run price elasticities of supply are low, and in some cases, even contrary to expectations based on economic theory. Allowing for data inconsistencies, the slow responses of output to changes in price may be attributed to the method of wood disposal, its timing as well as the social and political barriers to entry at work in the sector.     

GENETIC PROGRAMMING: A NEW PARADIGM IN RAINFALL RUNOFF MODELING1

ABSTRACT: Genetic Programming (GP) is a domain‐independent evolutionary programming technique that evolves computer programs to solve, or approximately solve, problems. To verify GP's capability, a simple example with known relation in the area of symbolic regression, is considered first. GP is then utilized as a flow forecasting tool. A catchment in Singapore with a drainage area of about 6 km² is considered in this study. Six storms of different intensities and durations are used to train GP and then verify the trained GP. Analysis of the GP induced rainfall and runoff relationship shows that the cause and effect relationship between rainfall and runoff is consistent with the hydrologic process. The result shows that the runoff prediction accuracy of symbolic regression based models, measured in terms of root mean square error and correlation coefficient, is reasonably high. Thus, GP induced rainfall runoff relationships can be a viable alternative to traditional rainfall runoff models.