scholarly journals Environmental applications of Effective Microorganisms: a review of current knowledge and recommendations for future directions

2021 ◽  
Vol 68 (1) ◽  
Author(s):  
Safwat M. Safwat ◽  
Minerva E. Matta

AbstractNowadays, beneficial microorganisms are getting wider applicability. One example is referred to as Effective Microorganisms (EM) having its composition kept a secret. EM is a product in liquid form, which consists of a variety of not only effective and beneficial microorganisms but also nonpathogenic ones, with admirable coexistence between aerobic and anaerobic types of microorganisms. The aim of this narrative review is to provide a summary of the different uses and applications of EM, their applications, their benefits, and the expected results when using them in different applications. This is the first review to focus on the uses of EM in environmental engineering systems and processes such as wastewater treatment processes. Originally, EM was manufactured to be utilized in organic farming, but at the moment, this substance is getting wider applications such as in medicine, environment, livestock sector, forestry, and agriculture. When it comes to the protection of the environment, EM helps in waste deodorization, eutrophication control, and wastewater. Investigation on EM use in water quality restoration, wastewater treatment, the treatment of sludge, and composting has been undertaken by researchers. This review provides an overview of the current situation of environmental application of EM in various fields including water quality, wastewater treatment, sludge treatment, and composting.

2016 ◽  
Vol 7 (1) ◽  
pp. 97-102 ◽  
Author(s):  
Am Jang ◽  
Jong-Tae Jung ◽  
Hayoung Kang ◽  
Hyung-Soo Kim ◽  
Jong-Oh Kim

We evaluate the applicability of a reverse osmosis (RO) system that combines powdered activated carbon (PAC) and ultrafiltration (UF) to treat the effluent discharged from tannery wastewater treatment plants. Conventional treatment processes such as neutralization, clariflocculation, and biological processes are used to clean the effluent before feeding to the PAC and UF combined RO system. The efficiency of the combined system was evaluated using the chemical oxygen demand Mn (CODMn), color, pH, turbidity, total nitrogen, total phosphate, and conductivity. The PAC was effective in greatly reducing the CODMn and color. The turbidity and silt density index of the UF permeate satisfied the water quality indices required for the RO feed. The RO system was constantly maintained at approximately 75% RO recovery, and the RO permeate satisfied the water quality requirements for reusing the processed water. Therefore, the PAC-UF combined RO system can be used to process effluent discharged from tannery wastewater treatment plants for reuse.


2012 ◽  
Vol 246-247 ◽  
pp. 635-639
Author(s):  
Jie Yang

The state and progress in the treatment technology of dyeing wastewater are summarized in this paper, especially the new treatment technologies coming about in the latest years. The developing trend of treatment for organic matters is discussed as well. In the meantime, regional and water-quality water shortages have also been proven to be the bottlenecks for imposing restrictions on the development of the society and economy after land and energy.


2006 ◽  
Vol 5 (4) ◽  
pp. 685-692
Author(s):  
Elisabeta Chirila ◽  
Ionela Carazeanu Popovici ◽  
Techin Ibadula ◽  
Alice Iordache

2019 ◽  
Author(s):  
Chem Int

Recently, process control in wastewater treatment plants (WWTPs) is, mostly accomplished through examining the quality of the water effluent and adjusting the processes through the operator’s experience. This practice is inefficient, costly and slow in control response. A better control of WTPs can be achieved by developing a robust mathematical tool for performance prediction. Due to their high accuracy and quite promising application in the field of engineering, Artificial Neural Networks (ANNs) are attracting attention in the domain of WWTP predictive performance modeling. This work focuses on applying ANN with a feed-forward, back propagation learning paradigm to predict the effluent water quality of the Habesha brewery WTP. Data of influent and effluent water quality covering approximately an 11-month period (May 2016 to March 2017) were used to develop, calibrate and validate the models. The study proves that ANN can predict the effluent water quality parameters with a correlation coefficient (R) between the observed and predicted output values reaching up to 0.969. Model architecture of 3-21-3 for pH and TN, and 1-76-1 for COD were selected as optimum topologies for predicting the Habesha Brewery WTP performance. The linear correlation between predicted and target outputs for the optimal model architectures described above were 0.9201 and 0.9692, respectively.


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