Horizontal mergers in the iron ore industry—An application of PCAIDS

The purpose of this paper is to estimate and analyse the price effects of the iron ore mergers between Rio Tinto and North Ltd in 2000, and CVRD and Caemi in 2001. The analyses are conducted using a merger simulation model that, based on the pre-merger situation, estimates the post-merger outcome. This paper applies the so-called proportionality-calibrated almost ideal demand system (PCAIDS) model, which assumes that the product is differentiated and that the strategic variable is price. The results from the merger simulations show that in the case of the merger between Rio Tinto and North Ltd, the merged firm has a combined market share of almost 20%. However, the estimated market weighted average price effect is only 2.6%. Regarding the merger between CVRD and Caemi, the merged firm's market share is about 29%, and the estimated market weighted average price effect is 4.6%. When removing Caemi's Canadian asset, which was the Commission decision in order to allow the merger, the market price effect decreases to 3.1%. Overall the results in this study support the Commission's decisions regarding both merger cases, and shows that merger simulations of price effects can be valuable tools in merger assessments.     

Exploratory Analysis of the Winter Chemistry of Five Lakes on the North Slope of Alaska1

Abstract: Lakes are important water resources on the North Slope of Alaska. Freshwater is required for oilfield production as well as exploration, which occurs largely on ice roads and pads. Since most North Slope lakes are shallow, the quantity and quality of the water under ice at the end of winter are important environmental management issues. Currently, water‐use permits are a function of the presence of overwintering fish populations, and their sensitivity to low oxygen concentrations. Sampling of five North Slope lakes during the winter of 2004‐2005 shed some light on the winter chemistry of four lakes that were used as water supplies and one undisturbed lake. Field analysis was conducted for oxygen, conductivity, pH, and temperature throughout the lake depth, as well as ice thickness and water depth. Water samples were retrieved from the lakes and analyzed for Na, Ca, K, Mg, Fe, dissolved‐organic carbon, and alkalinity in the laboratory. Lake properties, rather than pumping, were the best predictors of oxygen depletion, with the highest dissolved‐oxygen levels maintained in the lake with the lowest concentration of constituents. Volume weighted mean dissolved‐oxygen concentrations ranged from 4 to 94% of saturation in March. Dissolved oxygen and specific conductance data suggested that the lakes began to refresh in May.     

Integrated Modular Modeling of Water and Nutrients From Point and Nonpoint Sources in the Patuxent River Watershed1

Abstract: We present a simple modular landscape simulation model that is based on a watershed modeling framework in which different sets of processes occurring in a watershed can be simulated separately with different models. The model consists of three loosely coupled submodels: a rainfall‐runoff model (TOPMODEL) for runoff generation in a subwatershed, a nutrient model for estimation of nutrients from nonpoint sources in a subwatershed, and a stream network model for integration of point and nonpoint sources in the routing process. The model performance was evaluated using monitoring data in the watershed of the Patuxent River, a tributary to the Chesapeake Bay in Maryland, from July 1997 through August 1999. Despite its simplicity, the landscape model predictions of streamflow, and sediment and nutrient loads were as good as or better than those of the Hydrological Simulation Program‐Fortran model, one of the most widely used comprehensive watershed models. The landscape model was applied to predict discharges of water, sediment, silicate, organic carbon, nitrate, ammonium, organic nitrogen, total nitrogen, organic phosphorus, phosphate, and total phosphorus from the Patuxent watershed to its estuary. The predicted annual water discharge to the estuary was very close to the measured annual total in terms of percent errors for both years of the study period (≤2%). The model predictions for loads of nutrients were also good (20‐30%) or very good (<20%) with exceptions of sediment (40%), phosphate (36%), and organic carbon (53%) for Year 1.     

Projecting Cumulative Benefits of Multiple River Restoration Projects: An Example from the Sacramento-San Joaquin River System in California

Despite increasingly large investments, the potential ecological effects of river restoration programs are still small compared to the degree of human alterations to physical and ecological function. Thus, it is rarely possible to “restore” pre-disturbance conditions; rather restoration programs (even large, well-funded ones) will nearly always involve multiple small projects, each of which can make some modest change to selected ecosystem processes and habitats. At present, such projects are typically selected based on their attributes as individual projects (e.g., consistency with programmatic goals of the funders, scientific soundness, and acceptance by local communities), and ease of implementation. Projects are rarely prioritized (at least explicitly) based on how they will cumulatively affect ecosystem function over coming decades. Such projections require an understanding of the form of the restoration response curve, or at least that we assume some plausible relations and estimate cumulative effects based thereon. Drawing on our experience with the CALFED Bay-Delta Ecosystem Restoration Program in California, we consider potential cumulative system-wide benefits of a restoration activity extensively implemented in the region: isolating/filling abandoned floodplain gravel pits captured by rivers to reduce predation of outmigrating juvenile salmon by exotic warmwater species inhabiting the pits. We present a simple spreadsheet model to show how different assumptions about gravel pit bathymetry and predator behavior would affect the cumulative benefits of multiple pit-filling and isolation projects, and how these insights could help managers prioritize which pits to fill.     

Amelioration of physical strength in waste foundry green sands for reuse as a soil amendment

To avoid increasing costs of landfill disposal, it has become increasingly important for U.S. foundries to identify beneficial reuses for the 8 to 12 million tons of waste foundry sand (WFS) generated annually. A major drawback to the reuse of some WFSs as a soil amendment is their high soil strength, under dry conditions, where root growth may be limited. Fifteen WFSs were analyzed for strength to rupture using lab-formed clods, exchangeable cations (Na, Mg, Ca), metal oxide concentration (Fe, Mn, Al, Si), cation exchange capacity (CEC), and % clay. Several WFS samples from gray iron foundries demonstrated high strength to rupture values (> 1.5 MPa), and could potentially restrict root growth in amended soils. The percentage of Na-bentonite exhibited a positive correlation (R(2) = 0.84) with strength to rupture values. When WFSs containing more Na-bentonite were saturated with 1 mol L(-1) Ca ions, strength values decreased by approximately 70%. Waste foundry sands containing less Na-bentonite were saturated with 1 mol L(-1) Na ions and exhibited a threefold increase in strength. Additions of gypsum (up to 9.6 g kg(-1) sand) to high strength waste foundry sands also caused decreases in strength. These results indicate that high strength WFSs have properties similar to hardsetting soils which are caused by high Na(+) clay content and can be ameliorated by the addition of Ca(2+).     

Sorption and mobility of ivermectin in different soils

Avermectins are widely used to treat livestock for parasite infections. Ivermectin, which belongs to the group of avermectins, is particularly hazardous to the environment, especially to crustaceans and to soil-dwelling organisms. Sorption is one of the key factors controlling transport and bioavailability. Therefore, batch studies have been conducted to characterize the sorption and desorption behavior of ivermectin in three European soils (Madrid, York, and artificial soil). The solid-water distribution coefficient (K(d)) for ivermectin sorption to the tested soils were between 57 and 396 L kg(-1) (determined at 0.1 microg g(-1)), while the organic carbon-normalized sorption coefficients (K(oc)) ranged from 4.00 x 10(3) to 2.58 x 10(4) L kg(-1). The Freundlich sorption coefficient (K(F)) was 396 (after 48 h) for the artificial soil over a concentration range of 0.1 to 50 microg g(-1), with regression constants indicating a concentration-dependent sorption. The obtained data and data in the literature are inconclusive with regard to whether hydrophobic partitioning or more specific interactions are involved in sorption of avermectins. For abamectin, hydrophobic partitioning seems to be one of the dominant types of binding, while hydrophobicity is less important for ivermectin, which is probably due to the lower lipophilicity of the molecule. Furthermore, the presence of cations such as Ca(2+) leads to decreasing sorption. Thus, it is presumed that ivermectin binds to soil by formation of complexes with immobile, inorganic soil matter. In contrast to abamectin, hysteresis could be excluded for ivermectin in the studied soils for the evaluation of sorption and desorption. The sorption mechanism is highly dependent on physicochemical properties of the avermectin.     

Seasonal variation of leaf dust accumulation and pigment content in plant species exposed to urban particulates pollution

To assess the dust interception efficiency of some selected tree species and impact of dust deposition on chlorophyll and ascorbic acid content of leaves the present study was undertaken. The plant species selected for the study were Ficus religiosa, Ficus benghalensis, Mangifera indica, Dalbergia sissoo, Psidium guajava, and Dendrocalamus strictus. It was found that all species have maximum dust deposition in the winter season followed by summer and rainy seasons. Chlorophyll content decreased and ascorbic acid content increased with the increase of dust deposition. There was significant negative and positive correlation between dust deposition and chlorophyll and ascorbic acid content, respectively. Maximum dust interception was done by Dalbergia sisso and least by Dendrocalamus strictus. Thus plants can be used to intercept dust particles which are of potential health hazards to humans.     

Empirical models based on the universal soil loss equation fail to predict sediment discharges from Chesapeake Bay catchments

The Universal Soil Loss Equation (USLE) and its derivatives are widely used for identifying watersheds with a high potential for degrading stream water quality. We compared sediment yields estimated from regional application of the USLE, the automated revised RUSLE2, and five sediment delivery ratio algorithms to measured annual average sediment delivery in 78 catchments of the Chesapeake Bay watershed. We did the same comparisons for another 23 catchments monitored by the USGS. Predictions exceeded observed sediment yields by more than 100% and were highly correlated with USLE erosion predictions (Pearson r range, 0.73-0.92; p < 0.001). RUSLE2-erosion estimates were highly correlated with USLE estimates (r = 0.87; p < 001), so the method of implementing the USLE model did not change the results. In ranked comparisons between observed and predicted sediment yields, the models failed to identify catchments with higher yields (r range, -0.28-0.00; p > 0.14). In a multiple regression analysis, soil erodibility, log (stream flow), basin shape (topographic relief ratio), the square-root transformed proportion of forest, and occurrence in the Appalachian Plateau province explained 55% of the observed variance in measured suspended sediment loads, but the model performed poorly (r(2) = 0.06) at predicting loads in the 23 USGS watersheds not used in fitting the model. The use of USLE or multiple regression models to predict sediment yields is not advisable despite their present widespread application. Integrated watershed models based on the USLE may also be unsuitable for making management decisions.     

Characterizing Storm Hydrograph Rise and Fall Dynamics With Stream Stage Data1

Abstract: Storm‐flow transients (i.e., hydrograph rise and fall dynamics) may represent an important aspect of understanding streamflow dynamics. However, little is known about how temporal resolution of transient data and climate variability may color these potential indicators of hydrologic pattern or condition. Warm‐season stream stage and rainfall were monitored continuously (5 min) during the 2002 water year in eight tributaries of the Little Miami River (Ohio), which drain 17‐58 km² catchments. Rise rates generated using 5‐min data were different than those generated with mean daily data [calculated with the Indicators of Hydrologic Alteration (IHA) software], though fall rates were similar for fine and coarse temporal data. This result suggests that data with low temporal resolution may not be adequate to fully represent the dynamics of storm rise rates. Conversely, fall rates based on daily stage data (via IHA) were similar to those based on the 5‐min data, and so daily mean data may be appropriate for characterizing fall rates. We next analyzed the possible correlations between rainfall variability and storm‐flow stage dynamics. We derived rise and recession rates from storm stage hydrographs by assuming exponential rise and decay of a runoff peak. We found that raw rise rates (R_raw) were correlated with both the maximum rainfall rate and the time to the centroid of a rain event. We subsequently removed the trend based on these rainfall characteristics, which yielded new representations of rise rates abbreviated as R_rate and R_tcent, respectively, and that had lower variability than the uncorrected (raw) data. Fall rates were found to be independent of rainfall characteristics. Due to the predominant influence of stream hydrology upon aquatic biota and nutrient fluxes, our work suggests that these stage data analysis protocols can refine or otherwise reduce variability in these indices by accounting for relevant factors such as rainfall forcing. These protocols for derivation of transient indices should be tested for their potential to improve correlations between stream hydrology and temporally aligned biotic data and dissolved nutrient fluxes in streams.