The accelerating environmental impact of the textile industry, especially in water management, requires efficient wastewater treatment strategies. This study examines the effectiveness of various electrode pairs in the Electrocoagulation (EC) process for treating textile wastewater, focusing on removing of Total Suspended Solids (TSS), turbidity, Chemical Oxygen Demand (COD), and Total Organic Carbon (TOC). A comprehensive analysis was conducted using thirty-six electrode pair combinations, consisting of six materials: Aluminium (Al), Zinc (Zn), Carbon (C), Copper (Cu), Mild Steel (MS), and Stainless Steel (SS). The results demonstrated that different electrode pairs yielded varying removal efficiencies for various pollutants, with the highest efficiencies being 92.09% for COD (Al-C pair), 99.66% for TSS (Al-Cu pair), 99.17% for turbidity (Al-MS pair), and 70.99% for TOC (SS-SS pair). However, no single electrode pair excelled in removing all pollutant categories. To address this, three Multi-Criteria Decision Making (MCDM) methods such as TOPSIS, VIKOR, and PROMETHEE II were used to assess the most effective electrode pair. The results indicated that the Al-Zn combination was the most efficient, exhibiting high removal efficiencies for various pollutants (99.32% for TSS, 98.88% for turbidity, 68.62% for COD, and 57.96% for TOC). This study demonstrates that the EC process can effectively treat textile effluent and emphasizes the importance of selecting suitable electrode materials. Furthermore, pollutant removal was optimal with the Al-Zn electrode pair, offering a balanced and efficient approach to textile wastewater treatment. Thus, MCDM methods offer a robust framework for assessing and optimizing electrode selection, providing valuable insights for sustainable environmental management practices.

The textile industry is known for its significant environmental impact, and as such, there is a growing need to assess the industry\'s production practices. Life cycle assessment (LCA) is an effective tool for measuring the environmental impact of textile products from raw material production to end-of-life disposal. Surat city, known as textile hub of India, has multiple industrial clusters that play host to different elements of the textile value chain. This research aims to evaluate the environmental performance of a Surat-based textile company. The study involves the collection of data from textile manufacturing facilities, including gray cloth production and wet processes (gate-to-gate approach). The data collected has been analyzed using the GABI (9.2.1 version) software. The study provides potential environmental impact data on present textile technology and production situation. Significant hotspots have been determined throughout supply chain and the associated drivers identified. However, the industry\'s environmental impact can be reduced by practicing ecoefficiency, immaterialization, and recycling textile waste. This research highlights the importance of LCA in identifying the environmental impact of the textile industry and provides a basis for developing sustainable practices to minimize the industry\'s environmental impact.

We piloted the development and implementation of a multifaceted intervention package for improving respiratory health among textile workers using a pre-post design at six mills in Karachi. The intervention, implemented following a baseline survey (n = 498), included health and safety training of workers and managers, promotion of cotton dust control measures, and the provision of facemasks. Follow-up surveys were conducted at 1, 6, and 12 months post-intervention. Knowledge, attitude, and practice (KAP) scores and respiratory symptoms were assessed through a questionnaire and spirometry was conducted. The intervention was provided to 230 workers and led to an improvement in KAP scores that was more likely among workers with a higher educational status, spinners, smokers, those with a permanent employment status, working in morning shifts, and with ⩾5 years of textile experience. We found the intervention acceptable and feasible in these textile mills henceforth, trials are required to determine its effectiveness.

The contradiction between the rapid textile expansion and intensive energy consumption, highly environmental pollution calls for the adoption of cleaner production (CP). However, current evaluation system mainly targeted on CP at production stage, guidance and support on the life cycle assessment is still in its infancy. Meanwhile few studies brought the combination of water conservation and carbon reduction into considerations. This study compared the existing CP evaluation systems including guidelines for the whole industry, standards for textile industry and indicators for the dyeing and finishing sector by quantifying the differences of indicator score compositions. Comparisons analysis from six aspects suggested that all the evaluation systems had relevant indicators regarding \"pollutant emissions\". \"Management\", \"process equipment and techniques\" and \"resource and energy consumption\" have also been well concerned while \"product characteristic\" seemed to be overlooked at current stage. From the perspective of whole life cycle, the key of textile processing is the \"printing and dyeing\" (44.23 %) followed by \"fabric manufacturing\"(28.85 %) and setting (15.38 %). With regards to the environmental impacts, resources depletion gained the highest attention since their indicator scores reached up to 25.71 %, 18.47 % and 20.62 % for EMAS, ERG 2018 and HJ-1852006. Cleaner production awareness and social impact also played significant roles in ISO 14031:2021 and WMG. Subsequently, a set of new comprehensive CP evaluation indicator system was established, including 3 scopes and 7 goals. The newly-built indicator system incorporated with life cycle perspectives gave a powerful tool to measure the CP level in textile industry and of CP will benefit from water reuse and energy utilization with high efficiency.

The wastewater treatment efficiency of Diplosphaera mucosa VSPA was enhanced by optimising five input parameters and increasing the biomass yield. pH, temperature, light intensity, wastewater percentage (pollutant concentration), and N/P ratio were optimised, and their effects were studied. Two competitive techniques, response surface methodology (RSM) and artificial neural network (ANN), were applied for constructing predictive models using experimental data generated according to central composite design. Both MATLAB and Python were used for constructing ANN models. ANN models predicted the experimental data with high accuracy and less error than RSM models. Generated models were hybridised with a genetic algorithm (GA) to determine the optimised values of input parameters leading to high biomass productivity. ANN-GA hybridisation approach performed in Python presented optimisation results with less error (0.45%), which were 7.8 pH, 28.8 °C temperature, 105.20 μmol m-2 s-1 light intensity, 93.10 wastewater % (COD) and 23.5 N/P ratio.

Silica aerogels are highly porous materials with exceptional thermal insulation performance. They become even more attractive if combined thermal and acoustic insulation is achieved. Silica aerogel composites reinforced with fibres are an ingenious way to surpass the fragility stemmed from the aerogel\'s intrinsic porosity, and textile fibres are good sound absorption materials. Reclaimed fibres are a relatively low-cost feedstock and were obtained in this work exclusively through mechanical processes from textile wastes, thus promoting the concept of circular economy, namely for cotton, polyester and wool fibres. These reclaimed fibres were used as reinforcement matrices for silica aerogel composites obtained from sol-gel transformation of tetraethyl orthosilicate and isobutyltriethoxysilane/or vinyltrimethoxysilane precursors and dried at ambient pressure after silylation. Silica aerogel composites reinforced with reclaimed cotton fibres had the best sound absorption coefficient (a peak value of 0.89), while the polyester-reinforced composite exhibited the lowest thermal conductivity (k = ~24 mW m-1 K-1, Hot Disk). The better combined results on thermal and acoustic insulation were achieved by the wool-reinforced composites. The thermal conductivity values were less than 27 mW m-1 K-1, and the sound absorption coefficient achieved a peak value of 0.85. Therefore, the aerogel composites developed here can be selected for thermal or/and acoustic barriers by choosing a suitable type of fibre. Their design and preparation protocol followed environmental-friendly and cost-effective approaches.

Demodex, a type of mite, lives in human hair follicles. They can multiply very quickly in some conditions and then start to irritate the skin by causing skin disorders. This study aims to investigate if working environment conditions affect the prevalence of Demodex. A cross-sectional, multicenter study was conducted with three different occupational groups: mine, textile and food factory workers (n = 102). Determined industry workers who applied to our outpatient dermatology clinics with the complaint of dermatosis in three different cities were included in the study. Demodex positivity was checked by dermoscopy. Differences between categorical variables examined with Chi-square analysis and T test was used to compare continuous variables between groups. 50% Demodex positivity was found in mine workers, 45.3% in food factory workers and 66.7% in textile manufacturing workers. A high rate of Demodex positivity was observed in all three occupational groups. Although the highest positivity rate was observed in textile manufacturing workers, no significant difference was found between the groups (p = 0.320). The overall prevalence of Demodex in female workers was statistically significantly higher than in male workers (p = 0.029). Exposure of workers to a wide variety of factors in work environments such as textile factories and the fact that women are more sensitive to external factors may have caused the prevalence of Demodex to be higher in these groups. So, a change in the work environment or the use of suitable protective equipment may benefit the treatment of diseases caused by Demodex. But, further studies are needed with larger and various industry groups to make more certain views.

Contamination of industry-derived antimony (Sb) is currently of great concern. This study was conducted to identify the source of Sb together with other potential toxic elements (PTEs) in a typical industrial area in China and emphasize the contribution of Sb to ecological risk in the local aquatic environment. By investigating the distribution of nine PTEs in surface water in Wujiang County in dry and wet seasons, this study revealed that textile wastewater was the main source of Sb. The distribution of Sb (0.48~21.4 μg/L) showed the least seasonal variation among the nine elements. Factor analysis revealed that the factor that controlled Sb distribution is unique. In general, Sb was more concentrated in the southeastern part of the study area where there was a large number of textile industries, and was affected by the specific conductivity and total dissolved solids in water (p < 0.01). Sb concentration in 35.71% of samples collected from the drainage outlet exceeded the standard limit of 10 μg/L. Results from three pollution assessment methods suggested that >5% of the sampling sites were slightly too heavily polluted and Sb contributed the most. Therefore, it is necessary to strengthen the administrative supervision of local textile enterprises and elevate the local standard of textile wastewater emission.

To assess the association of exposure in cotton mills in Karachi with different definitions of byssinosis and lung health.
This cross-sectional survey took place between June 2019 and October 2020 among 2031 workers across 38 spinning and weaving mills in Karachi. Data collection involved questionnaire-based interviews, spirometry and measurements of personal exposure to inhalable dust. Byssinosis was defined using both WHO symptoms-based (work-related chest tightness), and Schilling\'s criteria (symptoms with decreased forced expiratory volume in 1 s (FEV1). Values of FEV1/forced vital capacity ratio below the lower limit of normality on postbronchodilator test were considered as \'chronic airflow obstruction\' (CAO).
56% of participants had at least one respiratory symptom, while 43% had shortness of breath (grade 1). Prevalence of byssinosis according to WHO criteria was 3%, it was 4% according to Schilling\'s criteria, and likewise for CAO. We found low inhalable dust exposures (geometric mean: 610 µg/m3). Cigarette smoking (≥3.5 pack-years), increasing duration of employment in the textile industry and work in the spinning section were important factors found to be associated with several respiratory outcomes.
We found a high prevalence of respiratory symptoms but a low prevalence of byssinosis. Most respiratory outcomes were associated with duration of employment in textile industry. We have discussed the challenges faced in using current, standard guidelines for identifying byssinosis.

This study evaluates the adsorptive capacity of elephant grass (EG) in the removal of Methylene blue (MB) dye from wastewater sourced from two major local dyeing industries in Ogun State, Nigeria. Batch adsorption method was used to determine the optimum conditions, characterization of the adsorbent, equilibrium Isotherm models, kinetics and thermodynamics studies were conducted to evaluate the nature of the adsorption process. The optimum adsorption conditions obtained for the standard solution of MB dye were; pH 7, Temp 40 °C, contact time 180 min and adsorbent dosage 2.0 g. The presence of oxygen containing functional groups and shift or disappearance of bands in the FTIR suggested the suitability of EG for the process. The SEM of EG revealed presence and disappearance of pores before and after the adsorption process. The mechanism of this adsorption is complex, the adsorption data is best fitted to Langmuir isotherm, the mean adsorption energy E (≤6.455 kJ/mol), and activation energy (10.84 kJ/mol) represents physical process but, the thermodynamic studies revealed spontaneity (ΔG° -15.93 to -14.26 kJ mol-1), randomness, and endothermic (ΔH° 40.1 kJ/mol) nature, representing chemisorption. Therefore, local dyers around the study sites can make use of the freely available EG for the remediation of their wastewater.
Elephant grass (EG) abundantly thrives on the study sites where dye wastewater is released by local dyers. This serves as the impetus for this research as no other plants thrive on the dye-polluted environment. A favorable adsorption was obtained with EG as adsorbent for the Methylene blue (MB) dye that is a major constituent of the wastewater from the two major local dyeing industries investigated. Therefore, this study provides scientific support for the local dyers around the study sites to make use of the freely available EG for the remediation of their wastewater.