PREDICTION OF BOD AND COD OF A REFINERY WASTEWATER USING MULTILAYER ARTIFICIAL NEURAL NETWORKS

In the recent past, artificial neural networks (ANNs) have shown the ability to learn and capture non-linear static or dynamic behaviour among variables based on the given set of data. Since the knowledge of internal procedure is not necessary, the modelling can take place with minimum previous knowledge about the process through proper training of the network. In the present study, 12 ANN based models were proposed to predict the Biochemical Oxygen Demand (BOD5) and Chemical Oxygen Demand (COD) concentrations of wastewater generated from the effluent treatment plant of a petrochemical industry. By employing the standard back error propagation (BEP) algorithm, the network was trained with 103 data points for water quality indices such as Total Suspended Solids (TSS), Total Dissolved Solids (TDS), Phenol concentration, Ammoniacal Nitrogen (AMN), Total Organic Carbon (TOC) and Kjeldahl’s Nitrogen (KJN) to predict BOD and COD. After appropriate training, the network was tested with a separate test data and the best model was chosen based on the sum square error (training) and percentage average relative error (% ARE for testing). The results from this study reveal that ANNs can be accurate and efficacious in predicting unknown concentrations of water quality parameters through its versatile training process

Biogas bioconversion into poly(3-hydroxybutyrate) by a mixed microbial culture in a novel Taylor flow bioreactor

Producción CientíficaBiogas-based biopolymer production represents an alternative biogas valorization route with potential to cut down plastic pollution and greenhouse gas emissions. This study investigated for the first time the continuous bioconversion of methane, contained in biogas, into poly(3-hydroxybutyrate) (PHB) by a mixed methanotrophic culture using an innovative high mass-transfer Taylor flow bioreactor. Following a hydrodynamic flow regime mapping, the influence of the gas residence time and the internal gas recirculation on CH4 abatement was assessed under non nutrient limiting conditions. Under optimal operational conditions (gas residence time of 60 min and internal gas recycling ratio of 17), the bioreactor was able to support a CH4 removal efficiency of 63.3%, a robust CH4 elimination capacity (17.2 g-CH4 m-3h-1) and a stable biomass concentration (1.0 g L-1). The simultaneous CH4 abatement and PHB synthesis was investigated under 24-h:24-h nitrogen feast/famine continuous operation. The cyclic nitrogen starvation and the Taylor flow imposed in the bioreactor resulted in a relatively constant biomass concentration of 0.6 g L-1 with PHB contents ranging from 11 to 32% w w-1 (on a dry weight basis), entailing an average PHB productivity of 5.9 g-PHB m-3 d-1 with an associated PHB yield of 19.8 mg-PHB g-CH4-1. Finally, the molecular analysis of the microbial population structure indicated that type II methanotrophs outcompeted non-PHB accumulating type I methanotrophs, with a heterotrophic-methanotrophic consortium enriched in Methylocystis, Hyphomicrobium, Rubinisphaeraceae SH PL14 and Pseudonocardia.Ministerio de Ciencia, Innovación y Universidades (project RTI2018-0-096441-B-I00)Erasmus+ International Master of Science in Environmental Technology and Engineering (project 2017-1957/001-001-EMJMD)Junta de Castilla y Leon - Fondo Europeo de Desarrollo Regional (grants CLU 2017-09 and UIC 315

Pollution prevention and sustainable future

This special issue contains 7 articles that are disseminating the physical, chemical and biological process techniques and tools for pollution prevention and sustainability. They are selected from the presentations made at the 13th annual international conference on the “Challenges in Environmental Science and Engineering”, CESE-2020 that was held online on the 7th and the 8th of November 2020. There were 177 delegates from 18 countries and regions participated in CESE-2020. This special issue covers the removal of chemical species such as phosphorus from water and related effects, recovery of chemical species such as copper and nickel, carbon capture using activated carbon, utilization of hydrogels, detection technology and inverter technology

Acetaminophen micropollutant: Historical and current occurrences, toxicity, removal strategies and transformation pathways in different environments

Acetaminophen (ACT) is commonly used as a counter painkiller and nowadays, it is increasingly present in the natural water environment. Although its concentrations are usually at the ppt to ppm levels, ACT can transform into various intermediates depending on the environmental conditions. Due to the complexity of the ACT degradation products and the intermediates, it poses a major challenge for monitoring, detection and to propose adequate treatment technologies. The main objectives of this review study were to assess (i) the occurrences and toxicities, (2) the removal technologies and (3) the transformation pathways and intermediates of ACT in four environmental compartments namely wastewater, surface water, ground water, and soil/sediments. Based on the review, it was observed that the ACT concentrations in wastewater can reach up to several hundreds of ppb. Amongst the different countries, China and the USA showed the highest ACT concentration in wastewater (≤300 μg/L), with a very high detection frequency (81–100%). Concerning surface water, the ACT concentrations were found to be at the ppt level. Some regions in France, Spain, Germany, Korea, USA, and UK comply with the recommended ACT concentration for drinking water (71 ng/L). Notably, ACT can transform and degrade into various metabolites such as aromatic derivatives or organic acids. Some of them (e.g., hydroquinone and benzoquinone) are toxic to human and other life forms. Thus, in water and wastewater treatment plants, tertiary treatment systems such as advanced oxidation, membrane separation, and hybrid processes should be used to remove the toxic metabolites of ACT