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This study reports a literature review of the state of the art, 2000-2020, on the substrates that are used as support media in constructed wetlands with subsurface flow. Its importance compared to the most used substrates worldwide and its economic feasibility as a substrate in CW. 13 different types of substrates have been identified in 155 different studies, but the most used substrates were gravel (32%) and sand (23%) for the development of bacterial associations. However, gravel and sand used in full-scale CW are expensive (10–35 $USD/m3), for wastewater treatment in small communities with economic difficulties. The tendency is to use substrates such as gravel (32%), sand (23%), sediments (13%), limestone or river rock (11%), granite (8%), zeolite (6%) and other alternative materials (7%). Among these we can mention: ceramics, pumice, steel, bricks, shells of different local aquatic fauna and some stone materials easily found in the study area. Therefore, the development of substrates of lower commercial value, reused material and material of easy operation is important, especially in developing countries where economic resources are one of the main constraints in the implementation of wastewater treatment systems. The use of treatment wetlands with economic materials detected in this study indicate that the future in wastewater treatment is this technology, because present multiple objectives, which include water treatment, fertilizer production, enhancement of biodiversity and cooling, vegetation production for handicraft, etc. CW are a technology with future role in circular economy that want to respond to sanitation worldwide. [ABSTRACT FROM AUTHOR]

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 R2=0.981 for the DSS and R2=0.963 for soil analyzes. The P rate shows R2=0.9702 for the DSS and R2=0.9183 for the soil analyzes. The K rate shows R2=0.9691 for the DSS and R2=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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]