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Organic-rich wastewater is a feasible feedstock for biohydrogen production. Numerous review on the performance of microorganisms and the diversity of their communities during a biohydrogen process were published. However, there is still no in-depth overview of enzymes for biohydrogen production from wastewater and their scale-up applications. This review aims at providing an insightful exploration of critical discussion in terms of: (i) the roles and applications of enzymes in wastewater-based biohydrogen fermentation; (ii) systematical introduction to the enzymatic processes of photo fermentation and dark fermentation; (iii) parameters that affect enzymatic performances and measures for enzyme activity/ability enhancement; (iv) biohydrogen production bioreactors; as well as (v) enzymatic biohydrogen production systems and their larger scales application. Furthermore, to assess the best applications of enzymes in biohydrogen production from wastewater, existing problems and feasible future studies on the development of low-cost enzyme production methods and immobilized enzymes, the construction of multiple enzyme cooperation systems, the study of biohydrogen production mechanisms, more effective bioreactor exploration, larger scales enzymatic biohydrogen production, and the enhancement of enzyme activity or ability are also addressed.

This research explores the possibilities of a dual-chamber microbial fuel cell as a biosensor to measure Bisphenol A (BPA) in wastewater. BPA is an organic compound and is considered to be an endocrine disruptor, affecting exposed organisms, the environment, and human health. The performance of the microbial fuel cells (MFCs) was first controlled with specific operational conditions (pH, temperature, fuel feeding rate, and organic loading rate) to obtain the best accuracy of the sensor signal. After that, BPA concentrations varying from 50 to 1000 μg L

Due to the impact of methane, carbon dioxide and nitrous oxide on global warming, the quantity of these greenhouse gases (GHG) emissions from municipal wastewater treatment plants (WWTPs) has attracted more and more attention. Consequently, GHG emissions from the two popular treatment technologies: anaerobic/anoxic/oxic (AAO) process and sequencing batch reactor (SBR) should be properly identified and discussed toward the current situation in developing countries. Direct and indirect carbon dioxide (with and/or without including in Intergovernmental Panel on Climate Change (IPCC) report) are all discussed in this article. This literature study observed that a quantity of total carbon dioxide emissions from SBR (374 g/m3 of wastewater) was double that of AAO whilst 10% of these was direct carbon dioxide. Methane emitted from an SBR was 0.50 g/m3 wastewater while 0.18 g CH4/m3 wastewater was released from an AAO. The level of nitrous oxide from AAO and SBR accounted for 0.97 g/m3 wastewater and 4.20 g/m3 wastewater, respectively. Although these results were collected from different WWTPs and where influent was in various states, GHGs emitted from both biological units and other treatment units in various processes are significant. The results also revealed that aerated zone is the major contributing factor in a wastewater treatment plant to the large amount of GHG emissions.

The development of the photobioreactors (PBs) is recently noticeable as cutting-edge technology while the correlation of PBs' engineered elements such as modellings, configurations, biomass yields, operating conditions and pollutants removal efficiency still remains complex and unclear. A systematic understanding of PBs is therefore essential. This critical review study is to: (1) describe the modelling approaches and differentiate the outcomes; (2) review and update the novel technical issues of PBs' types; (3) study microalgae growth and control determined by PBs types with comparison made; (4) progress and compare the efficiencies of contaminants removal given by PBs' types and (5) identify the future perspectives of PBs. It is found that Monod model's shortcoming in internal substrate utilization is well fixed by modified Droop model. The corroborated data also remarks an array of PBs' types consisting of flat plate, column, tubular, soft-frame and hybrid configuration in which soft-frame and hybrid are the latest versions with higher flexibility, performance and smaller foot-print. Flat plate PBs is observed with biomass yield being 5 to 20 times higher than other PBs types while soft-frame and membrane PBs can also remove pharmaceutical and personal care products (PPCPs) up to 100%. Looking at an opportunity for PBs in sustainable development, the flat plate PBs are applicable in PB-based architectures and infrastructures indicating an encouraging revenue-raising potential.

A high-resolution soil moisture prediction method has recently gained its importance in various fields such as forestry, agricultural and land management. However, accurate, robust and non- cost prohibitive spatially monitoring of soil moisture is challenging. In this research, a new approach involving the use of advance machine learning (ML) models, and multi-sensor data fusion including Sentinel-1(S1) C-band dual polarimetric synthetic aperture radar (SAR), Sentinel-2 (S2) multispectral data, and ALOS Global Digital Surface Model (ALOS DSM) to predict precisely soil moisture at 10 m spatial resolution across research areas in Australia. The total of 52 predictor variables generated from S1, S2 and ALOS DSM data fusion, including vegetation indices, soil indices, water index, SAR transformation indices, ALOS DSM derived indices like digital model elevation (DEM), slope, and topographic wetness index (TWI). The field soil data from Western Australia was employed. The performance capability of extreme gradient boosting regression (XGBR) together with the genetic algorithm (GA) optimizer for features selection and optimization for soil moisture prediction in bare lands was examined and compared with various scenarios and ML models. The proposed model (the XGBR-GA model) with 21 optimal features obtained from GA was yielded the highest performance (R

This study investigated a dual-chamber microbial fuel cell-based biosensor (DC-MFC-B) for monitoring copper and arsenic in municipal wastewater. Operational conditions, including pH, flow rate, a load of organic substrate and external resistance load, were optimized to improve the biosensor's sensitivity. The DC-MFC-B's toxicity response was established under the electroactive bacteria inhibition rate function to a specific heavy metal level as well as the recovery of the DC-MFC-B. Results show that the DC-MFC-B was optimized at the operating conditions of 1000 Ω external resistance, COD 300 mg L

Wastewater is now considered to be a vital reusable source of water reuse and saving energy. However, current wastewater has multiple limitations such as high energy costs, large quantities of residuals being generated and lacking in potential resources. Recently, great attention has been paid to microbial fuel cells (MFCs) due to their mild operating conditions where a variety of biodegradable substrates can serve as fuel. MFCs can be used in wastewater treatment facilities to break down organic matter, and they have also been analysed for application as a biosensor such as a sensor for biological oxygen which demands monitoring. MFCs represent an innovation technology solution that is simple and rapid. Despite the advantages of this technology, there are still practical barriers to consider including low electricity production, current instability, high internal resistance and costly materials used. Thus, many problems must be overcome and doing this requires a more detailed analysis of energy production, consumption, and application. Currently, real-world applications of MFCs are limited due to their low power density level of only several thousand mW/m2. Efforts are being made to improve the performance and reduce the construction and operating costs of MFCs. This paper explores several aspects of MFCs such as anode, cathode and membrane, and in an effort to overcome the practical challenges of this system.

This study investigated the environmental burdens concerning the recycling/recovery process of a wastewater treatment plant's construction material waste and biogas. Detailed data inventories of case studies were employed in several scenarios to explore the role of end-of-life treatment methods. The ReCiPe 2016 and the Greenhouse gas Protocol life cycle impact methods were conducted to measure the impact categories. The construction and demolition phases were considered for recycling potential assessment, while the operational phase was examined for assessing the advantages of energy recovery. Metal and concrete recycling show environmental benefits. Increasing the reprocessing rate requires more water consumption but results in: firstly, a decrease of 18.8% in total damage; secondly, reduces problematic mineral scarcity by 3.9%; and thirdly, a shortfall in fossil fuels amounting to 11.6%. Recycling concrete helps to reduce the amount of GHG emissions 1.4-fold. Different biogas treatment methods contribute to various outcomes. Biogas utilization for on-site energy purposes has more advantages than flaring and offsite consumption. Electricity and heat generation originating from biogas can provide 70% of the energy requirement and replace 100% natural gas usage. Biomethane production from biogas requires extreme power and more resources. Meanwhile, producing heat and electricity can offset 102.9 g of fossil CO2, and manufacturing biomethane contributes the equivalent of 101.2 g of fossil fuel-derived CO2. Reducing 10% of recovered electricity creation could rise 19.19% global warming indicator of the wastewater treatment plant.

This study aims to investigate the environmental issues regarding the construction phase of the wastewater treatment plant (WWTP) and explore the roles of different materials through their environmental impacts. Detailed inventories of the two WWTPs were conducted by involving materials and transportation for civil works undertaken. EPD 2018 and ReCiPe life cycle impact assessment methods were employed to measure all the impact categories. Five treatment processes - (1) pumping, (2) primary treatment, (3) secondary treatment, (4) sludge line, and (5) building landscape - were considered for the assessment. It was found that concrete and reinforcing steel played similarly vital roles in most of the EPD 2018 impacts. The significant score of reinforcing steel was found on human cancer toxicity, which contributed more than 90% of the impacts. The contribution of diesel on ozone formation was 5% higher than that of reinforcing steel. Glassfiber was responsible for 70% of the burdens on ozone depletion, showing much higher than the total share of concrete and reinforcing steel. Primary treatment units only contributed 9.5% of the construction impacts in the Girona WWTP but up to 43.8% in Mill Creek WWTP mainly because of the proportion of consumed materials. In short, the comprehensive data inventories were necessary when evaluating the total environmental impacts of the WWTP.

Removal of tetracycline antibiotics (TCs) by biochar adsorption is emerging as a cost-effective and environmentally friendly strategy. This study developed a novel pomelo peel derived biochar, which was prepared at 400 °C (BC-400) and 600 °C (BC-600) under nitrogen conditions. To enhance the adsorption capacity, BC-400 was further activated by KOH at 600 °C with a KOH: BC-400 ratio of 4:1. The activated biochar (BC-KOH) displayed a much larger surface area (2457.37 m2/g) and total pore volume (1.14 cm3/g) than BC-400 and BC-600. High adsorption capacity of BC-KOH was achieved for removing tetracycline (476.19 mg/g), oxytetracycline (407.5 mg/g) and chlortetracycline (555.56 mg/g) simultaneously at 313.15 K, which was comparable with other biochars derived from agricultural wastes reported previously. The adsorption data could be fitted by the pseudo-second-order kinetic model and Langmuir isotherm model successfully. The initial solution pH indicated the potential influence of TCs adsorption capacity on BC-KOH. These results suggest that pore filling, electrostatic interaction and π–π interactions between the adsorbent and adsorb ate may constitute the main adsorption mechanism. BC-KOH can be used as a potential adsorbent for removing TCs from swine wastewater effectively, cheaply and in an environmentally friendly way.