Application of an artificial neural network for the improvement of agricultural drainage water quality using a submerged biofilter

Influences of straw alkaline pretreatment on biogas production and digestate characteristics: artificial neural network and multivariate statistical techniques

Anaerobic digestion is one of the best options for producing valuable end products (biogas and biofertilizer). The aim of this study was to investigate the influences of thermoalkaline pretreatment of wheat straw on biogas production and digestate characteristics from codigestion with waste-activated sludge. Different alkaline conditions (NaOH, KOH and Na2CO3) and pretreatment durations (1, 3 and 5 h) were used for straw pretreatment. Batch anaerobic codigestion of sludge and pretreated straw was conducted under different pretreatment conditions. A feedforward neural network (FFNN) model, logistic model and statistical analysis were applied to the experimental data to predict biogas and investigate the significance and relationships among the variables. NaOH pretreatment for 5 h showed the best treatment conditions: biogas yield was 6.59 times higher than that without treatment. Moreover, the proportions of total solids, total volatile solids, chemical oxygen demand and microbial count removed reached 63.52%, 74.60%, 78.15% and 82.22%, respectively. The methane content was 67.50%, indicating that the biogas had a high quality. The thermoalkaline pretreatment significantly affected biogas production and digestate characteristics, allowing it to be used as a biofertilizer. Experimental data were successfully modelled for predicting biogas production using the applied models. The R2 values reached 0.985 and 0.999 for the logistic and FFNN models, respectively.

Relationship between anthropogenic factors and freshwater quality in Hainan Province, south China

Water resource security directly or indirectly affects the development of society, economy, and the environment, and is of massive significance for regional sustainable development. This study addresses whether anthropogenic activities, especially from tourism, significantly affect the freshwater quality in Hainan Province, China. The freshwater quality in Hainan Province was generally good in 2012 to 2015 (at level II, GB3838-2002). Agriculture, fishery, animal husbandry, and chemical oxygen demand discharge mainly affect freshwater quality in the Nandu and Changhua rivers. Water quality in Wanquan River is more susceptible to tourism in comparison with the Nandu and Changhua rivers. DO content in the Wanquan River fluctuated greatly. It remains necessary to closely monitor negative changes in water quality due to increasing tourism, especially in Wanquan River and eastern Hainan Province. The developed radial basis function neural network shows that the changes in water quality are predicted accurately in comparison with experimental values in the present study. Our results suggested that current anthropogenic factors had a modest effect on water quality on Hainan Island, while tourism had a perceptible effect in eastern Hainan. Our findings provide a reference for the interplay of water quality, people's livelihood, and economic development (tourism and port construction) in Hainan Province.

Using chemometric models to predict the biosorption of low levels of dysprosium by Euglena gracilis

The critical rare earth element dysprosium (Dy) is integral for sustainable technologies. What is concerning is that Dy is in imminent short supply and no current replacements yet exist, coupled with increasing environmental Dy levels influenced by anthropogenic activities. This study applies chemometric methods such as response surface methodology and artificial neural networks to predict low Dy removal levels using the biosorbent Euglena gracilis. A three-factor Box-Behnken experimental design was conducted with initial concentration (1 to 100 µg L^-1), contact time (30 to 180 min), and pH (3 to 8) as the three independent variables, and percentage removal and sorption capacity (q) as dependent variables. Using Dy percentage removal as response, for the worst and best conditions ranged from 0 to 92% respectively, with an average removal of 66 ± 4%. Using sorption capacity (q) as a different response variable, q varied from 0 to 93 µg/g with 27 ± 4 µg/g capacity as average. Maximum removal was 92% (q = 93 µg/g) was at pH 3, a contact time of 105 min and at a concentration of 100 µg/L. Using sorption capacity as the response variable for ANOVA, pH and metal concentrations were statistically significant factors, with lower pH and higher metal concentration having improved Dy removal, with a desirability near 1. Statistical tests such as analysis of variance, lack-of-fit, and coefficient of determination (R²) confirmed model validity. A 3-10-1 ANN network array was used to model experimental responses (q). RSM and ANN effectively modeled Dy biosorption. E. gracilis proved to be a cheap and effective biosorbent for Dy biosorption and has the potential to remediate acid mine drainage areas exhibiting low Dy concentrations.

Improving the Hydraulic Effects Resulting from the Use of a Submerged Biofiter to Enhance Water Quality in Polluted Streams

Water scarcity is one of the most serious problems facing many countries. In addition, water pollution could lose more water. A submerged biofilter (SB) is used to enhance the self-purification process in polluted streams. However, most previous studies have focused on the efficiency of SB to remove pollutants and there is a lack of studies investigating the hydraulic changes in streams. The current paper aimed to study the hydraulic effects of SB on the flow behavior in streams and how to improve it. An empirical equation for determining the flow rate through SB was developed. Different cases were studied to improve the hydraulic effects resulting from the use of SB. The effect of increasing SB length was tested using different SB lengths. The results showed that increasing the length increased the upstream water depth (h₁) and relative heading up (h₁/h₂). In the second case, comparison between continuous and fragmented SB was tested. The results showed that a fragmented biofilter increased the upstream water depth and the relative heading up. Case three tested the effect of SB height. Different SB heights were tested with a fixed length and constant flow rate. The results revealed that the upstream water depth and relative heading up decreased when the biofilter height decreased. Case four tested the effect of SB with a fixed volume and constant flow rate. In this case, the length and height of SB were changed where the volume was fixed. The results showed that the relative heading up decreased when the SB height decreased and the length increased, which revealed that the SB height can improve the hydraulic impacts. Finally, the use of SB to improve the water quality in polluted streams led to an increase of the relative heading up, which can be reduced by decreasing the height of SB.