Waste materials for activated carbon preparation and its use in aqueous-phase treatment: a review

Commercial activated carbon is a preferred adsorbent for the removal of micropollutants from the aqueous phase; however, its widespread use is restricted due to high associated costs. To decrease treatment costs, attempts have been made to find inexpensive alternative activated carbon (AC) precursors, such as waste materials. Some reviews report the use of waste materials for the preparation of AC; however, these studies are restricted to either type of wastes, preparation procedures, or specific aqueous-phase applications. The present work reviews and evaluates literature dedicated both to the preparation of AC by recycling different types of waste materials and also to its application in various aqueous-phase treatments. It is clear that conventional (from agriculture and wood industry) and non-conventional (from municipal and industrial activities) wastes can be used to prepare AC, that can be applied in various aqueous treatment processes, namely to remove organic pollutants, dyes, volatile organic compounds, and heavy metals. Moreover, high surface areas can be obtained using either physical or chemical activation; however, combined treatments might enhance the surface properties of the adsorbent, therefore increasing its adsorption capacity. It is evident from the revision made that AC prepared from both conventional and non-conventional wastes might effectively compete with the commercial ones. This happens mostly when the activation procedures are optimized considering both the raw material used to produce the carbons and the contaminants to be removed.     

Relationships between soil and runoff phosphorus in small Alberta watersheds

Field-scale relationships between soil test phosphorus (STP) and flow-weighted mean concentrations (FWMCs) of dissolved reactive phosphorus (DRP) and total phosphorus (TP) in runoff are essential for modeling phosphorus losses, but are lacking. The objectives of this study were (i) to determine the relationships between soil phosphorus (STP and degree of phosphorus saturation (DPS)) and runoff phosphorus (TP and DRP) from field-sized catchments under spring snowmelt and summer rainfall conditions, and (ii) to determine whether a variety of depths and spatial representations of STP improved the prediction of phosphorus losses. Runoff was monitored from eight field-scale microwatersheds (2 to 248 ha) for 3 yr. Soil test phosphorus was determined for three layers (0 to 2.5 cm, 0 to 5 cm, and 0 to 15 cm) in spring and fall and the DPS was determined for the surface layer. Average STP (0 to 15 cm) ranged from 3 to 512 mg kg(-1), and DPS (0 to 2.5 cm) ranged from 5 to 91%. Seasonal FWMCs ranged from 0.01 to 7.4 mg L(-1) DRP and from 0.1 to 8.0 mg L(-1) TP. Strong linear relationships (r2=0.87 to 0.89) were found between the site mean STP and the FWMCs of DRP and TP. The relationships had similar extraction coefficients, intercepts, and predictive power among all three soil layers. Extraction coefficients (0.013 to 0.014) were similar to those reported for other Alberta studies, but were greater than those reported for rainfall simulation studies. The curvilinear DPS relationship showed similar predictive ability to STP. The field-scale STP relationships derived from natural conditions in this study should provide the basis for modeling phosphorus in Alberta.     

COMPARISON OF STOCHASTIC AND DETERMINISTIC DYNAMIC PROGRAMMING FOR RESERVOIR OPERATING RULE GENERATION1

ABSTRACT: Two dynamic programming models — one deterministic and one stochastic — that may be used to generate reservoir operating rules are compared. The deterministic model (DPR) consists of an algorithm that cycles through three components: a dynamic program, a regression analysis, and a simulation. In this model, the correlation between the general operating rules, defined by the regression analysis and evaluated in the simulation, and the optimal deterministic operation defined by the dynamic program is increased through an iterative process. The stochastic dynamic program (SDP) describes streamflows with a discrete lag-one Markov process. To test the usefulness of both models in generating reservoir operating rules, real-time reservoir operation simulation models are constructed for three hydrologically different sites. The rules generated by DPR and SDP are then applied in the operation simulation model and their performance is evaluated. For the test cases, the DPR generated rules are more effective in the operation of medium to very large reservoirs and the SDP generated rules are more effective for the operation of small reservoirs.     

REAL-TIME SNOW SIMULATION MODEL FOR THE MONONGAHELA RIVER BASIN1

ABSTRACT: The Pittsburgh District, U.S. Army Corps of Engineers, is responsible for operating two multipurpose reservoirs in the 7384 square mile (19198 square kilometer) Monongahela Basin. A third reservoir, presently under construction, will soon be operating. The real-time forecasting of runoff for operational purposes requires simulation of snow accumulation and snowmelt throughout the Basin during the winter season. This article describes capabilities of SNOSIM, a model being developed for performing such simulation. The application of this model as part of a comprehensive system of water control software, and some initial simulation results are presented.