Unveiling the Microfiber Release Footprint: Guiding Control Strategies in the Textile Production Industry.

Microplastic fibers from textiles have been known to significantly contribute to marine microplastic pollution. However, little is known about the microfiber formation and discharge during textile production. In this study, we have quantified microfiber emissions from one large and representative textile factory during different stages, spanning seven different materials, including cotton, polyester, and blended fabrics, to further guide control strategies. Wet-processing steps released up to 25 times more microfibers than home laundering, with dyeing contributing to 95.0% of the total emissions. Microfiber release could be reduced by using white coloring, a lower dyeing temperature, and a shorter dyeing duration. Thinner, denser yarns increased microfiber pollution, whereas using tightly twisted fibers mitigated release. Globally, wet textile processing potentially produced 6.4 kt of microfibers in 2020, with China, India, and the US as significant contributors. The study underlined the environmental impact of textile production and the need for mitigation strategies, particularly in dyeing processes and fiber choice. In addition, no significant difference was observed between the virgin polyesters and the used ones. Replacing virgin fibers with recycled fibers in polyester fabrics, due to their increasing consumption, might offer another potential solution. The findings highlighted the substantial impact of textile production on microfiber released into the environment, and optimization of material selection, knitting technologies, production processing, and recycled materials could be effective mitigation strategies.

A review of antibiotic removal from domestic wastewater using the activated sludge process: removal routes, kinetics and operational parameters.

Many advanced technologies have shown encouraging results in removing antibiotics from domestic wastewater. However, as activated sludge treatment is the most common sewage treatment system employed worldwide, improving its effect on antibiotic removal would be more desirable. Understanding the removal mechanisms, kinetics and factors that affect antibiotic removal in the activated sludge process is important as it would allow us to improve the treatment performance. Although these have been discussed in various literature covering different types of antibiotics and wastewater, a specific review on antibiotics and domestic wastewater is clearly missing. This review paper collates, discusses and analyses the removal of antibiotics from sewage in the activated sludge process along with the removal mechanisms and kinetics. The antibiotics are categorised into six classes: ß-lactam, dihydrofolate reductase inhibitor, fluoroquinolone, macrolide, sulfonamides and tetracycline. Furthermore, the factors affecting the system performance with regard to antibiotic removal are examined.

Effects of land use configuration, seasonality and point source on water quality in a tropical watershed: A case study of the Johor River Basin.

Land use plays a significant role in determining the spatial patterns of water quality in the Johor River Basin (JRB), Malaysia. In the recent years, there have been several occurrences of pollution in these rivers, which has generated concerns over the long-term sustainability of the water resources in the JRB. Specifically, this water resource is a shared commodity between two states, namely, Johor state of Malaysia and Singapore, a neighbouring country adjacent to Malaysia. Prior to this study, few research on the influence of land use configuration on water quality have been conducted in Johor. In addition, it is also unclear how water quality varies under different seasonality in the presence of point sources. In this study, we investigated the influence of land use and point sources from wastewater treatment plants (WWTPs) on the water quality in the JRB. Two statistical techniques - Multivariate Linear Regression (MLR) and Redundancy Analysis (RA) were undertaken to analyse the relationships between river water quality and land use configuration, as well as point sources from WWTPs under different seasonality. Water samples were collected from 49 sites within the JRB from March to December in 2019. Results showed that influence from WWTPs on water quality was greater during the dry season and less significant during the wet season. In particular, point source was highly positively correlated with ammoniacal­nitrogen (NH3-N). On the other hand, land use influence was greater than point source influence during the wet season. Residential and urban land use were important predictors for nutrients and organic matter (chemical oxygen demand); and forest land use were important sinks for heavy metals but a significant source of manganese.

A framework for assessing the adequacy of Water Quality Index - Quantifying parameter sensitivity and uncertainties in missing values distribution.

Water quality monitoring is a pillar in water resource management, but it can be resource intensive, especially for developing countries with limited resources. As such, Water Quality Indices (WQI) are developed to summarise general water quality, but efforts to assess the utility, flexibility, and practicality of WQI have been limited. In this study, we introduced an additional step to the traditional WQI development framework by introducing an adjusted form of WQI (WQIADJUSTED) to handle missing values, and capitalise on the remaining available information for the development of a WQI. A Sub-WQI was also developed to address local water quality conditions. WQI results (weighted and non-weighted) developed using different parameter optimisation methods, namely Multivariate Linear Regression and Principal Component Analysis were compared. To build upon the current framework, a new procedure was developed to assess the adequacy of WQI based on the sensitivity analysis of parameters and uncertainties associated with each parameter's missing values distribution. The number of observations needed for the development of a robust WQI was optimised with respect to user-defined acceptable change in WQI, based on Monte Carlo probabilistic simulation. The Johor River Basin (JRB), Malaysia is used as a case-study for the application of this new framework. The JRB serves as an important resource for Johor, one of the most populous state in Malaysia, and Singapore, a country south of Johor. WQIMLR performed better in explaining the general water quality than WQIPCA for weighted water quality parameters. Optimisation of sampling frequency revealed that around 130 samples will be required if a 2% change in WQI can be tolerated. The results (specific to the JRB) also revealed that total coliform is the most sensitivity parameter to missing values, and the distribution of sensitive parameters are similar for both WQINON-ADJUSTED and WQIADJUSTED.

Genome-Centric Metagenomic Insights into the Impact of Alkaline/Acid and Thermal Sludge Pretreatment on the Microbiome in Digestion Sludge.

Pretreatment of waste-activated sludge (WAS) is an effective way to destabilize sludge floc structure and release organic matter for improving sludge digestion efficiency. Nonetheless, information on the impact of WAS pretreatment on digestion sludge microbiomes, as well as mechanistic insights into how sludge pretreatment improves digestion performance, remains elusive. In this study, a genome-centric metagenomic approach was employed to investigate the digestion sludge microbiome in four sludge digesters with different types of feeding sludge: WAS pretreated with 0.25 mol/liter alkaline/acid (APAD), WAS pretreated with 0.8 mol/liter alkaline/acid (HS-APAD), thermally pretreated WAS (thermal-AD), and fresh WAS (control-AD). We retrieved 254 metagenome-assembled genomes (MAGs) to identify the key functional populations involved in the methanogenic digestion process. These MAGs span 28 phyla, including 69 yet-to-be-cultivated lineages, and 30 novel lineages were characterized with metabolic potential associated with hydrolysis and fermentation. Interestingly, functional populations involving carbohydrate digestion were enriched in APAD and HS-APAD, while lineages related to protein and lipid fermentation were enriched in thermal-AD, corroborating the idea that different substrates are released from alkaline/acid and thermal pretreatments. Among the major functional populations (i.e., fermenters, syntrophic acetogens, and methanogens), significant correlations between genome sizes and abundance of the fermenters were observed, particularly in APAD and HS-APAD, which had improved digestion performance.IMPORTANCE Wastewater treatment generates large amounts of waste-activated sludge (WAS), which consists mainly of recalcitrant microbial cells and particulate organic matter. Though WAS pretreatment is an effective way to release sludge organic matter for subsequent digestion, detailed information on the impact of the sludge pretreatment on the digestion sludge microbiome remains scarce. Our study provides unprecedented genome-centric metagenomic insights into how WAS pretreatments change the digestion sludge microbiomes, as well as their metabolic networks. Moreover, digestion sludge microbiomes could be a unique source for exploring microbial dark matter. These results may inform future optimization of methanogenic sludge digestion and resource recovery.

Optimization of aluminium recovery from water treatment sludge using Response Surface Methodology.

For decades, water treatment plants in Malaysia have widely employed aluminium-based coagulant for the removal of colloidal particles in surface water. This generates huge amount of by-product, known as sludge that is either reused for land applications or disposed to landfills. As sludge contains high concentration of aluminium, both can pose severe environmental issues. Therefore, this study explored the potential to recover aluminium from water treatment sludge using acid leaching process. The evaluation of aluminium recovery efficiency was conducted in two phases. The first phase used the one factor at a time (OFAT) approach to study the effects of acid concentration, solid to liquid ratio, temperature and heating time. Meanwhile, second phase emphasized on the optimization of aluminium recovery using Response Surface Methodology (RSM). OFAT results indicated that aluminium recovery increased with the rising temperature and heating time. Acid concentration and solid to liquid ratio, however, showed an initial increment followed by reduction of recovery with increasing concentration and ratio. Due to the solidification of sludge when acid concentration exceeded 4 M, this variable was fixed in the optimization study. RSM predicted that aluminium recovery can achieve 70.3% at optimal values of 4 M, 20.9%, 90 °C and 4.4 h of acid concentration, solid to liquid ratio, temperature and heating time, respectively. Experimental validation demonstrated a recovery of 68.8 ±â€¯0.3%. The small discrepancy of 2.2 ±â€¯0.4% between predicted and validated recovery suggests that RSM was a suitable tool in optimizing aluminium recovery conditions for water treatment sludge.

Assessing the treatment of acetaminophen-contaminated brewery wastewater by an anaerobic packed-bed reactor.

The treatment of high-strength organic brewery wastewater with added acetaminophen (AAP) by an anaerobic digester was investigated. An anaerobic packed-bed reactor (APBR) was operated as a continuous process with an organic loading rate of 1.5-g COD per litre per day and a hydraulic retention time of three days. The results of steady-state analysis showed that the greatest APBR performances for removing COD and TOC were as high as 98 and 93%, respectively, even though the anaerobic digestibility after adding the different AAP concentrations of 5, 10 and 15 mg L(-1) into brewery wastewater can affect the efficiency of organic matter removal. The average CH4 production decreased from 81 to 72% is counterbalanced by the increased CO2 production from 11 to 20% before and after the injection of AAP, respectively. The empirical kinetic models for substrate utilisation and CH4 production were used to predict that, under unfavourable conditions, the performance of the APBR treatment process is able to remove COD with an efficiency of only 6.8%.

Incorporation of initiation, promotion and inhibition in the Rct concept and its application in determining the initiation and inhibition capacities of natural water in ozonation.

Ozonation is widely employed in water treatment to purify water. The R(ct) concept, which is defined as the ratio of OH exposure to ozone exposure, has been commonly used to quantify the OH concentration generating from ozone decomposition and model the removal of organic pollutant. Due to its empirical nature, however, the R(ct) concept is limited in quantitatively elucidating how initiator, promoter and inhibitor involved in the OH chain reactions affect its value. A new R(ct) model was developed by integrating the R(ct) concept and the transient steady-state OH concentration to evaluate the influences of these modes of reactions on the R(ct) value. It was found that the R(ct) value is not only the ratio of OH exposure to ozone exposure but also the ratio of the total initiation capacity to the total inhibition capacity in a system. The presence of promoter, however, does not affect the R(ct) value although it does accelerate ozone decomposition leading to lower ozone and OH exposures and result in hindered removal of target pollutant. The hindered removal of ibuprofen by ozonation in the presence of methanol (promoter) can be quantitatively described by the new R(ct) model. The model can also be used to quantify the initiation and inhibition capacities of an ozonation system via the addition of an external inhibitor. Its application in determining the initiation and inhibition capacities of natural water was demonstrated.