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Efficient solutions for storing and converting energy sources with sustainable and environment-friendly materials play an increasingly important role in ensuring energy security and promoting the development of sustainable energy sectors. Biochar-based materials have been known as promising materials for energy storage and conversion applications owing to their superior structural properties (e.g., the porosity and large surface area) and diversity of functional groups, which can be exploited for safe, modern, and environment-friendly materials. In addition, owing to the abundance of raw materials (in particular, waste biomass sources), biochar-based materials for energy storage and conversion applications can be produced at a reasonable cost. This chapter presents a critical overview of the importance of biochar for energy storage and conversion applications and the presented biochar production and modification techniques. The potential applications and challenges of these biochar materials in the energy storage and conversion field are also discussed to make relevant judgments for the future.

The COVID-19 pandemic has caused significant disruptions to the world since 2020, with over 647 million confirmed cases and 6.7 million reported deaths as of January 2023. Despite its far-reaching impact, the effects of COVID-19 on the progress of global climate change negotiations have yet to be thoroughly evaluated. This discussion paper conducts an examination of COVID-19's impact on climate change actions at global, national, and local levels through a comprehensive review of existing literature. This analysis reveals that the pandemic has resulted in delays in implementing climate policies and altered priorities from climate action to the pandemic response. Despite these setbacks, the pandemic has also presented opportunities for accelerating the transition to a low-carbon economy. The interplay between these outcomes and the different levels of governance will play a crucial role in determining the success or failure of future climate change negotiations.

This study examined >140 relevant publications from the last few years (2018-2021). In this study, classification was reviewed depending on the operation's progress. Electrocoagulation (EC), electrooxidation (EO), electroflotation (EF), electrodialysis (ED), and electro-Fenton (EFN) processes have received considerable attention. The type of action (individual or hybrid) for each electrochemical procedure was evaluated, and statistical analysis was performed to compare them as a new manner of reviewing cited papers providing a massive amount of information efficiently to the readers. Individual or hybrid operation progress of the electrochemical techniques is critical issues. Their design, operation, and maintenance costs vary depending on the in-situ conditions, as evidenced by surveyed articles and statistical analyses. This work also examines the variables affecting the elimination efficacy, such as the applied current, reaction time, pH, type of electrolyte, initial pollutant concentration, and energy consumption. In addition, owing to its efficacy in removing toxins, the hybrid activity showed a good percentage among the studies reviewed. The promise of each wastewater treatment technology depends on the type of contamination. In some cases, EO requires additives to oxidise the pollutants. EF and EFN eliminated lightweight organic pollutants. ED has been used to treat saline water. Compared to other methods, EC has been extensively employed to remove a wide variety of contaminants.

During the wastewater treatment process, the disposal of sewage sludge has raised many concerns about the various pollutants that are contained within it. Given the high concentrations of organic substances and nutrients found in sewage sludge, it is now attractive to apply sewage sludge as an agricultural soil amendment for growing crops and an environmentally friendly method of waste management. However, it is important to identify the properties of sewage sludge and possible challenges prior to the application. In this chapter, the physico-chemical properties of sewage sludge are described, as are the types of treatment processes and quantity and quality of sewage. Applying sewage sludge in agricultural soil was evaluated in terms of soil property and plant growth. Since sewage sludge contains pollutants, such as antibiotics, heavy metals and microplastics, the use of this sludge in agriculture may result in serious unintended environmental problems. For this reason, such issues were identified here. Lastly, conclusions are documented and possible future directions for developing agricultural applications of sewage sludge were suggested.

INTRODUCTION: SARS-CoV-2, a highly contagious severe acute respiratory syndrome, has spread to most countries in the world and resulted in a change to practice patterns for the assessment and diagnosis of people with voice disorders. Many services are transitioning to telehealth models to maintain physical distancing measures and conserve personal protective equipment used by healthcare workers during laryngoscopy examinations. The speech-language pathology primary contact (SLPPC) assessment for patients referred to ear, nose and throat (ENT) services in Australia has been shown to reduce waiting times for assessment while streamlining access to ENT assessment and allied health practitioner treatment pathways. METHODS AND ANALYSIS: A prospective observational cohort study will see patients in a newly developed telehealth model which uses the principles from a usual care SLPPC assessment protocol. Participants will be offered an initial telehealth assessment (speech-language pathology primary contact telehealth (SLPPC-T)) prior to being prioritised for a face-to-face laryngoscopy assessment to complete the diagnostic process. The telehealth assessment will collect sociodemographic information, personal and family medical history, key symptoms, onset and variability of symptoms, red-flag signs or symptoms for laryngeal malignancy, and clinical voice assessment data for auditory-perceptual and acoustic analysis. The study outcomes include (1) association of signs, symptoms and specific voice measures collected during SLPPC-T with voice disorder classification provided after laryngoscopy; (2) degree of concordance between voice disorder classification after SLPPC-T and after laryngoscopy; (3) health service and patient-related costs and health outcomes of the SLPPC-T; (4) patient and stakeholder views and beliefs about the SLPPC-T process. ETHICS AND DISSEMINATION: Ethical approval has been granted prior to commencement of the study enrolment by the Gold Coast Hospital

Knowing the effluent quality of treatment systems in advance to enable the design of treatment systems that comply with environmental standards is a realistic strategy. This study aims to develop machine learning - based predictive models for designing the subsurface constructed wetlands (SCW). Data from the SCW literature during the period of 2009-2020 included 618 sets and 10 features. Five algorithms namely, Random forest, Classification and Regression trees, Support vector machines, K-nearest neighbors, and Cubist were compared to determine an optimal algorithm. All nine input features including the influent concentrations, C:N ratio, hydraulic loading rate, height, aeration, flow type, feeding, and filter type were confirmed as relevant features for the predictive algorithms. The comparative result revealed that Cubist is the best algorithm with the lowest RMSE (7.77 and 21.77 mg.L-1 for NH4-N and COD, respectively) corresponding to 84% of the variance in the effluents explained. The coefficient of determination of the Cubist algorithm obtained for NH4-N and COD prediction from the test data were 0.92 and 0.93, respectively. Five case studies of the application of SCW design were also exercised and verified by the prediction model. Finally, a fully developed Cubist algorithm-based design tool for SCW was proposed.

Volatile fatty acids (VFAs) produced from organic-rich wastewater by anaerobic digestion attract attention due to the increasing volatile fatty acids market, sustainability and environmentally friendly characteristics. This review aims to give an overview of the roles and applications of enzymes, a biocatalyst which plays a significant role in anaerobic digestion, to enhance volatile fatty acids production. This paper systematically overviewed: (i) the enzymatic pathways of VFAs formation, competition, and consumption; (ii) the applications of enzymes in VFAs production; and (iii) feasible measures to boost the enzymatic processes. Furthermore, this review presents a critical evaluation on the major obstacles and feasible future research directions for the better applications of enzymatic processes to promote VFAs production from wastewater.

As a clean energy carrier, hydrogen is a promising alternative to fossil fuel so as the global growing energy demand can be met. Currently, producing hydrogen from biowastes through fermentation has attracted much attention due to its multiple advantages of biowastes management and valuable energy generation. Nevertheless, conventional dark fermentation (DF) processes are still hindered by the low biohydrogen yields and challenges of biohydrogen purification, which limit their commercialization. In recent years, researchers have focused on various advanced strategies for enhancing biohydrogen yields, such as screening of super hydrogen-producing bacteria, genetic engineering, cell immobilization, nanomaterials utilization, bioreactors modification, and combination of different processes. This paper critically reviews by discussing the above stated technologies employed in DF, respectively, to improve biohydrogen generation and stating challenges and future perspectives on biowaste-based biohydrogen production.

Wastewater treatment is a complex system for which a vast amount of data has been generated through online sensors, providing the opportunity for applying artificial intelligence (AI) to improve the performance of the system. Applied AI was found to demonstrate a better potential for data analysis than conventional statistical assessment. This chapter outlines state-of-the-art development in the use of applied AI for wastewater treatment plants (WWTPs) with a focus on output, algorithms, data, and performance. Real applications of AI in WWTPs include prediction, soft sensors, intelligence control and optimization, and detection. This paper could therefore help environmental scientists, wastewater engineers, and practitioners in the better control and operation of WWTPs.

Overpopulation, industrialization, and unregulated discharge result in the occurrence of the contaminants in water bodies, which calls for treatment technologies. Biological wastewater treatment is a technology where the main objective is to transform dissolved and particulate biodegradable constituents into acceptable end products. Biological treatment technologies are cost-effective, efficient, and many of them offer water reclamation qualities. Many pieces of research have been made to improve the removal of contaminants, trace compounds, operating conditions, and large-scale application. This chapter delivers an overview of biological wastewater treatment systems and highlights the future potential.

Three types of biomass of invasive plants and agrowastes, namely, the wattle bark of Acacia auriculiformis (BA), mimosa (BM), and coffee husks (BC), were converted into biochars through slow pyrolysis and investigated for their ability to remove dyes in water. The properties of the materials were characterized using Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and Brunauer–Emmett–Teller (BET) analysis. The BET surface area (total pore volume) of BC was 2.62 m2/g (0.007 cm3/g), far below those of BA and BM with 393.15 cm2/g (0.195 m3/g) and 285.53 cm2/g (0.153 m3/g), respectively. The optimal adsorption doses for the removal of methylene blue (MB) were found to be 2, 5, and 5 g/L for BC, BA, and BM, respectively. The suitable pH ranges for MB removal were 6–12 for BA, 7–12 for BC, and 2–10 for BM. The majority of MB (over 83%) was removed in the initial 30 min, followed by a more quasisteady state condition after the removal rate exceeded 90%. The experimental data were fitted with the kinetic models (PFO, PSO, Bangham, IDP), indicating that physicochemical adsorption, pore diffusion process, and multiple stages are the dominant mechanisms for the MB adsorption onto biochars. Finally, BA and BM showed similar adsorption efficiencies, while BC may not be favorable for use as an adsorbent due to its low surface area and low pore volume.

Wastewater contains a significant amount of recoverable nitrogen. Hence, the recovery of nitrogen from wastewater can provide an option for generating some revenue by applying the captured nitrogen to producing bio-products, in order to minimize dangerous or environmental pollution consequences. The circular bio-economy can achieve greater environmental and economic sustainability through game-changing technological developments that will improve municipal wastewater management, where simultaneous nitrogen and energy recovery are required. Over the last decade, substantial efforts were undertaken concerning the recovery of nitrogen from wastewater. For example, bio-membrane integrated system (BMIS) which integrates biological process and membrane technology, has attracted considerable attention for recovering nitrogen from wastewater. In this review, current research on nitrogen recovery using the BMIS are compiled whilst the technologies are compared regarding their energy requirement, efficiencies, advantages and disadvantages. Moreover, the bio-products achieved in the nitrogen recovery system processes are summarized in this paper, and the directions for future research are suggested. Future research should consider the quality of recovered nitrogenous products, long-term performance of BMIS and economic feasibility of large-scale reactors. Nitrogen recovery should be addressed under the framework of a circular bio-economy.

The circular bioeconomy is emerging as a new concept within the scientific community, which is attempting to help create sustainable economic development. The general aim of circular bioeconomy is to obtain sustainability through reduction, reuse, recycling, and recovery practices using bio-based resources. Recovery of nutrients from secondary sources is a key way to address the increased demands on resources by an exponentially rising world population growth. Wastewater is a source of nitrogen, phosphorous, and other nutrients necessary for various industries. Microalgae when harnessed with technology are considered to enable to recover nutrients from wastewaters through processes of growth and biomass production. This chapter describes the overview of bio-circular economy using microalgae, the potential of using algae-based technologies for resource recovery from wastewaters and making a circular bioeconomy viable. Challenges and future perspectives of these technologies are also explained.

Microbial electrolysis cell (MEC) system is an environmentally friendly method for clean biohydrogen production from a wide range of biowastes owing to low greenhouse gas emissions. This approach has relatively higher yields and lower energy costs for biohydrogen production compared to conventional biological technologies and direct water electrolysis, respectively. However, biohydrogen production efficiency and operating costs of MEC still need further optimization to realize its large-scale application.This paper provides a unique review of impact factors influencing biohydrogen production in MECs, such as microorganisms and electrodes. Novel strategies, including inhibition of methanogens, development of novel cathode catalyst, advanced reactor design and integrated systems, to enhance low-cost biohydrogen production, are discussed based on recent publications in terms of their opportunities, bottlenecks and future directions. In addition, the current challenges, and effective future perspectives towards the practical application of MECs are described in this review.

IMPORTANCE: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. OBJECTIVE: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. MAIN OUTCOMES AND MEASURES: Interregional profiles of group difference in cortical thickness between cases and controls. RESULTS: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene

This study investigated the effect of CaO2 pretreatment on sulfonamide antibiotics (SMs) remediation by Chlorella sp. Results showed that a CaO2 dose ranging from 0.05 to 0.1 g/g biomass was the best and led to higher SMs removal efficacy 5-10% higher than the control. The contributions made by cometabolism and CaO2 in SMs remediation were very similar. Bioassimilation could remove 24% of sulfadiazine (SDZ) and sulfamethazine (SMZ), and accounted for 38% of sulfamethoxazole (SMX) remediation. Pretreatment by CaO2 wielded a positive effect on microalgae. The extracellular polymeric substances (EPS) level of the CaO2 pretreatment microalgae was three times higher when subjected to non-pretreatment. For the long-term, pretreatment microalgae removed SMs 10-20% more than the non-pretreatment microalgae. Protein fractions of EPS in continuous operation produced up to 90 mg/L for cometabolism. For bioassimilation, SMX intensity of the pretreatment samples was 160-fold less than the non-treatment one. It indicated the CaO2 pretreatment has enhanced the biochemical function of the intracellular environment of microalgae. Peroxidase enzyme involved positively in the cometabolism and degradation of SMs to several metabolites including ring cleavage, hydroxylation and pterin-related conjugation.

Nitrogen removal is crucial in wastewater treatment process as excessive nitrogen content could result in eutrophication and degradation of aquatic ecosystems. Moreover, to satisfy the fast-growing need of fertilizers due to an increase in human population, recovering nitrogen from wastewater is of the most sustainable approach. Currently, the membrane technique integrated with biological processes namely bio-membrane based integrated system (BMIS) is a promising technology for recovering nitrogen from wastewater, including osmotic membrane bioreactors, bioelectrochemical systems and membrane photobioreactors. In this review study, the nitrogen recovery in different BMHSs, the role of operational parameters and the nitrogen recovery mechanism were discussed. Apart from this, the implementation of nitrogen recovery at pilot- and full-scale was summarized. Perspectives on the major challenges and recommendations of the BMIS for the nitrogen recovery in wastewater treatment were proposed, in which the integrated technologies and more scale-up studies regarding nitrogen recovery by the BMISs were also highlighted and recommended.

This study evaluated and compared the performance of two vertical flow constructed wetlands (VF) using expanded clay (VF1) and biochar (VF2), of which both are low-cost, eco-friendly, and exhibit potentially high adsorption as compared to conventional filter layers. Both VFs achieved relatively high removal for organic matters (i.e. Biological oxygen demand during 5 days, BOD5) and nitrogen, accounting for 9.5 - 10.5 g.BOD5.m-2.d-1 and 3.5 - 3.6 g.NH4-N.m-2.d-1, respectively. The different filter materials did not exert any significant discrepancy to effluent quality in terms of suspended solids, organic matters and NO3-N (P > 0.05), but they did influence NH4-N effluent as evidenced by the removal rate of that by VF1 and VF2 being of 82.4 ± 5.7 and 84.6 ± 6.4%, respectively (P < 0.05). The results obtained from the designed systems were further subject to machine learning to clarify the effecting factors and predict the effluents. The optimal algorithms were random forest, generalized linear model, and support vector machine. The values of the coefficient of determination (R2) and the root mean square error (RMSE) of whole fitting data achieved 74.0% and 5.0 mg.L-1, 80.0% and 0.3 mg.L-1, 90.1% and 2.9 mg.L-1, and 48.5% and 0.5 mg.L-1 for BOD5_VF1, NH4-N_VF1, BOD5_VF2, and NH4-N_VF2, respectively.

The failure of the centralized water supply system forced XY community to become more dependent on uncertain and unstable water sources. The results of surveying 50 households showed that 89.18% of total households depended on water collected from rivers, which contributed 58.3% of the total water volume used for the domestic demands. The average water volume consumed was 19.5 liters/person/day (l/p/d), and 86.5% of households used more than one source; 13.5% of households collected water only from rivers, and 45.94% of families had rainwater harvesting (RWH) for their activities (domestic water demand); however, RWH only provided 9.9% of total water consumption. In this study, basic methods were applied to calculate the storage tanks necessary to balance the water deficit created by drought months. Three levels of water demand (14, 20, and 30 l/p/d) can be the best choices for RWH; for a higher demand (40 and 60 l/p/d), small roof area (30-40 m2), and many people (six to seven) per family, RWH might be impractical because of unsuitable rainfall or excessively large storage tanks.

Microbial fuel cell (MFC) systems are promising technologies for wastewater treatment and renewable energy generation simultaneously. Performance of a double-chamber microbial fuel cell (MFC) to treat synthetic swine wastewater containing sulfonamide antibiotics (SMs) was evaluated in this study. The MFC was operated in continuous modes at different conditions. Results indicated that the current was successfully generated during the operation. The performance of MFC under the sequential anode-cathode operating mode is better than that under the single continuous running mode. Specifically, higher removal efficiency of chemical oxygen demand (>90%) was achieved under the sequential anode-cathode operating mode in comparison with that in the single continuous mode (>80%). Nutrients were also be removed in the MFC's cathode chamber with the maximum removal efficiency of 66.6 ± 1.4% for NH4+-N and 32.1 ± 2.8% for PO43--P. Meanwhile, SMs were partly removed in the sequential anode-cathode operating with the value in a range of 49.4%-59.4% for sulfamethoxazole, 16.8%-19.5% for sulfamethazine and 14.0%-16.3% for sulfadiazine, respectively. SMs' inhibition to remove other pollutants in both electrodes of MFC was observed after SMs exposure, suggesting that SMs exert toxic effects on the microorganisms. A positive correlation was found between the higher NH4+-N concentration used in this study and the removal efficiency of SMs in the cathode chamber. In short, although the continuous flow MFC is feasible for treating swine wastewater containing antibiotics, its removal efficiency of antibiotics requires to be further improved.

Sulfonamide antibiotics (SMs), as a class of antibiotics commonly used in swine industries, pose a serious threat to animal and human health. This study aims to evaluate the performance of an anaerobic membrane bioreactor (AnMBR) with and without supplying a new pomelo peel derived biochar to treat swine wastewater containing SMs. Results show that 0.5 g/L biochar addition could increase more than 30% of sulfadiazine (SDZ) and sulfamethazine (SMZ) removal in AnMBR. Approximately 95% of chemical oxygen demand (COD) was removed in the AnMBR at an influent organic loading rate (OLR) of 3.27 kg COD/(m3·d) while an average methane yield was 0.2 L/g CODremoved with slightly change at a small dose 0.5 g/L biochar addition. SMs inhibited the COD removal and methane production and increased membrane fouling. The addition of biochar could reduce the membrane fouling by reducing the concentration of SMP and EPS.