Methanogenic toxicity and continuous anaerobic treatment of wood processing effluents

Wood processing effluents contain different types of phenolic compounds, from simple monomers to high molecular weight (MW) polyphenolic polymers, that can inhibit wastewater treatment. This work presents a comparative study of the methanogenic toxicity produced by three wood processing effluents (hardboard, fiberboard and BKME (kraft mill effluent)) using Pinus radiata, Eucalyptus and Tepa as feedstock (the last one being a native Chilean tree species). This study evaluates the influence of non-adapted granular and adapted flocculent sludge on forest industrial wastewater treatment as well as continuous anaerobic biodegradation of hardboard processing effluent using the upflow anaerobic sludge blanket (UASB). The adapted biomass (flocculent sludge) did not show any lag-phase signs. The 50% IC (the concentration causing 50% inhibition of methanogenic activity) was 4.3 g COD-effluent (chemical oxygen demand (COD)-of the effluent)/l and 2.8 g COD-effluent/l for the flocculent sludge and the granular sludge, respectively. The UASB system worked at low organic load rates (0.1-0.4 g COD/l d) with the COD removal ranging between 10 and 30%, and color removal did not occur under anaerobic conditions due to high MW. Indeed, the MW analysis indicates the presence of phenolic compounds over 25,000 Da in the anaerobic effluent.     

Evaluating Spatial Design Techniques for Solving Land-use Allocation Problems

This study examines the use of spatial optimization techniques for multi-site land-use allocation problems (MLUA). 'Multi-site' refers to the problem of allocating more than one land-use type in an area, which are difficult problems as they involve multiple stakeholders with conflicting goals and objectives. Spatial optimization methods consist of (1) an optimization model and (2) an algorithm to solve the model. This study demonstrates a goal-programming model to solve the MLUA problem. The model is solved using both simulated annealing and genetic algorithms. Special attention has been given to introduce a spatial compactness objective in the model. It is shown that the compactness objectives in the optimization model generate compact patches of the same land use for using both the simulated annealing procedure and the genetic algorithm. In addition, it appears that using the proper settings of the compactness objectives, connectivity between patches of land use is promoted. The method is tested for a fictive study and then demonstrated for a real case study, both measuring 20 × 20 cells. The genetic algorithm generally performs better than simulated annealing in terms of solution time and achieving compactness.     

Pollutant source identification and allocation: Advances in hydrocarbon fingerprinting

Often liability for environmental damage and cleanup of contaminated sites is made difficult, especially with chemically complex environments containing different pollutants, by the inability to differentiate potential sources (or “owners”) of pollutants from each other. As a result, unnecessary costs may be associated with having to assume financial responsibility for alleged contamination of a site. This article reviews the advances in chemical fingerprinting as a tool in identifying and differentiating sources of hydrocarbon pollutants in chemically complex environments. Appropriate hydrocarbon target analytes and required analytical methods for hydrocarbon fingerprinting are discussed, and new interpretative tools are presented that may be applied to contaminated soil, sediment, and groundwater environmental situations. With these analytical and interpretative techniques, an appropriate allocation of chemical contamination and costs at a site can be made.