Effects of Ornamental Plant Density and Mineral/Plastic Media on the Removal of Domestic Wastewater Pollutants by Home Wetlands Technology.

Wastewater treatment (WWT) is a priority around the world; conventional treatments are not widely used in rural areas owing to the high operating and maintenance costs. In Mexico, for instance, only 40% of wastewater is treated. One sustainable option for WWT is through the use of constructed wetlands (CWs) technology, which may remove pollutants using cells filled with porous material and vegetation that works as a natural filter. Knowing the optimal material and density of plants used per square meter in CWs would allow improving their WWT effect. In this study, the effect of material media (plastic/mineral) and plant density on the removal of organic/inorganic pollutants was evaluated. Low (three plants), medium (six plants) and high (nine plants) densities were compared in a surface area of 0.3 m2 of ornamental plants (Alpinia purpurata, Canna hybrids and Hedychium coronarium) used in polycultures at the mesocosm level of household wetlands, planted on the two different substrates. Regarding the removal of contaminants, no significant differences were found between substrates (p ≥ 0.05), indicating the use of plastic residues (reusable) is an economical option compared to typical mineral materials. However, differences (p = 0.001) in removal of pollutants were found between different plant densities. For both substrates, the high density planted CWs were able to remove COD in a range of 86-90%, PO4-P 22-33%, NH4-N in 84-90%, NO3-N 25-28% and NO2-N 38-42%. At medium density, removals of 79-81%, 26-32, 80-82%, 24-26%, and 39-41%, were observed, whereas in CWs with low density, the detected removals were 65-68%, 20-26%, 79-80%, 24-26% and 31-40%, respectively. These results revealed that higher COD and ammonia were removed at high plant density than at medium or low densities. Other pollutants were removed similarly in all plant densities (22-42%), indicating the necessity of hybrid CWs to increase the elimination of PO4-P, NO3-N and NO2-N. Moreover, high density favored 10 to 20% more the removal of pollutants than other plant densities. In addition, in cells with high density of plants and smaller planting distance, the development of new plant shoots was limited. Thus, it is suggested that the appropriate distance for this type of polyculture plants should be from 40 to 50 cm in expansion to real-scale systems in order to take advantage of the harvesting of species in these and allow species of greater foliage, favoring its growth and new shoots with the appropriate distance to compensate, in the short time, the removal of nutrients.

Decision support system for NPK fertilization: a solution method for minimizing the impact on human health, climate change, ecosystem quality and resources.

Sugarcane cultivation requires correct fertilizer rates. However, when nutrients are not available, or there is over-fertilization, the yields are significantly reduced and the environmental burden increase. In this study, it is proposed a decision support system (DSS) for the correct NPK (nitrogen, phosphorus and potassium) fertilization. The DSS consists of two fuzzy models; the edaphic condition model (EDC-M) and the NPK fertilization model (NPK-M). The DSS using parameters from soil analysis and is based on the experience of two groups of experts to avoid the bias to the reality of a single group of professionals. The results of the DSS are compared with the results of soil analysis and those of the group of experts. One hundred and sixty tests were developed in the NPK-M. The N rate shows R 2=0.981 for the DSS and R 2=0.963 for soil analyzes. The P rate shows R 2=0.9702 for the DSS and R 2=0.9183 for the soil analyzes. The K rate shows R 2=0.9691 for the DSS and R 2=0.9663 for the soil analyzes. Environmental results indicate that the estimated rates with the DSS do reduce the environmental impact on the tests performed.

Analysis of the behavior for operation parameters in the anaerobic digestion process with thermal pretreatment, using fuzzy logic.

This article presents a study that identifies the variables with greatest impact on the biogas and methane production over a process with thermal pretreatment, to accelerate anaerobic digestion process in sewage sludge in a water treatment plant, for a poultry processing factory, by using fuzzy logic. The designed fuzzy logic model includes 688 inference rules, with a correlation of 99.3% between prediction data against experimental data, for the biogas variable; and 97% for the methane variable. The predictions of the fuzzy logic model were analyzed with response surface models, and it is concluded that the temperature and operating time variables are mutually determining in the biogas and methane production. Likewise, this research provides a methodology for the design of an expert decision support system that allows to evaluate and optimize a mesophilic anaerobic digestion process through a previous thermal treatment in order to improve the yields of biogas and methane in the treatment of effluent sludge from agroindustry. These results propose to diffuse logic as a reliable tool to make comparisons, and predictions for operation variables management on the treatment of residual sludge with thermal pretreatment on anaerobic digestion.

Life cycle assessment of cane sugar production: The environmental contribution to human health, climate change, ecosystem quality and resources in México.

The cane sugar industry in Mexico depends heavily on the supply of energy, fossil fuels and material resources for its proper operation. The overuse of these resources plus the technical and technological deficiency causes severe environmental consequences. This scientific work aims to analyze the environmental damage attributable to cane sugar production following the life cycle assessment (LCA) methodology. System boundaries include sugarcane growing and harvesting, sugarcane transportation, sugar milling and electricity cogeneration from bagasse. The associated emissions were acquired from the SimaPro-Ecoinvent database, the Roundtable on Sustainable Biofuels (RSB) and the Agroscope Reckenholz-Tänikon Research Station (ART). The life cycle impact assessment (LCIA) was carried out by SimaPro 8.3.0 software and the characterization method used was IMPACT 2002+. The results show that sugarcane growing and harvesting stage provides the most harmful environmental impacts (52%) followed by electricity cogeneration (25.7%), sugarcane transportation (12.1%) and finally, sugar milling (10.2%). Regarding the environmental contributions at the endpoint categories, the highest percentage of impacts is found in the Human health category (53%), followed by Climate change (21%), Ecosystem quality (16%) and Resources (10%). The LCA in cane sugar production can support the decision-making process to deal with this environmental problem.