Water Resources and Industry最新文献

Due to the structural similarities, sunflower seed husk (SSH), an agricultural, low-cost, and eco-friendly waste, is employed interchangeably with zeolite to extract Ni (II) ions from model and real industrial wastewater in this work. Batch experiment adsorption was carried out to investigate the possibility of Ni (II) ion removal by adsorbents. Zeolite powder and SSH were used in three different sizes and without any modifications to optimize the effect of adsorbent size. The maximum adsorption rate of 76% for the bulk size of SSH was obtained at pH 6.5, 20 g/L of adsoadsorbent, an initial concentration of ions of 20 mg/L, and 2 h of contact time. Thermodynamic results showed that the process is spontaneous, feasible, and exothermic within the set temperature range (10°C-80 °C). It can be concluded from the results that SSH can be used as a feasible, eco-friendly, and biodegradable organic material for Ni ion adsorption.

Hydrazine has been largely replaced by carbohydrazide (CHZ) as an oxygen scavenger due to safety and health concerns and CHZ is now used in Saline Water Conversion Corporation (SWCC) high pressure boilers. However, the operational problem of phosphate hide-out has become a continuous challenge for the plant operators. Advances in boiler water treatment have shown that effective corrosion control and prevention of scaling can be achieved by using a mixture of film-forming and alkalizing amines and polycarboxylates [Film Forming Amine Product (FFAP)]. With the use of FFAP, carbohydrazide/ammonia treatment of make-up water and phosphate treatment in the drum will not be required. A uniform FFAP formulation was used throughout the test.

The evaluation study was carried out at a boiler of the Yanbu Phase 1 Desalination and Power Plant (Mitsubishi) generating 60 MWh, with make-up water of 15 t h⁻¹ producing 330 t h⁻¹ steam at a pressure of 67 barg and temperature of 480 °C.

The trial provided evidence that FFAP was a good alternative to use of an oxygen scavenger. Changeover from CHZ to FFAP without phosphate addition in the drum was done initially by dosing FFAP from both hydrazine tank and phosphate tank so that pH was maintained to the required values in both feed water and drum water. With the optimal dose rate (0.6 ppm) maintaining FFAP in the range of 0.3–1.0 ppm in feed water, all the key parameters (pH, ammonia and specific conductivity) were within the specified boiler design limits. The average corrosion rates on the water side were low for both CHZ and FFAP treatment (0.009 ± 0.001 mm y⁻¹), however FFAP treated coupons showed much lower corrosion rates compared to CHZ in the steam side (0.0006 ± 0.0003 mm y⁻¹ cf. 0.0075 ± 0.0006 mm y⁻¹).

Semiconductor based photocatalysts have been an efficient technology for water and wastewater remediation, addressing the concepts of green chemistry and sustainable development. Owing to narrow and suitable band structure, BiOBr is a promising candidate for efficient wastewater treatment via photocatalysis. Enhancement of photocatalytic properties can be obtained by various techniques like doping, element rich strategy, facet engineering, and defect control. This review primarily focuses on the band engineering of single BiOBr, its binary, ternary composites and their applications in degradation of hazardous pollutants in wastewater. Moreover, current challenges and future perspectives were discussed along with concluding comments.

Sulfate radical AOPs (SR-AOP) were successfully utilized in degradation of antibiotics in water and wastewater treatment. The review discusses details on SR-AOPs mechanisms and applications for antibiotics degradation. The progress in this field was discussed, highlighting the most promising developments and remaining challenges. The applicability of SR-AOPs was summarized revealing the most susceptible and persistent to oxidation groups of pharmaceuticals. Highest effectiveness was reported for degradation of pharmaceuticals on ppb level. Systems revealed a scavenging effect in case of oxidant dose 0.7 mM of the PS and 2 mM of PMS. Future development demands simple persulfates activation systems for real matrix treatment.

Agriculture, industry and municipal water supply compete over scarce freshwater. This study calculated sectoral blue water footprints (WFs) in water scarce Pakistan between 1971 and 2020. Agriculture dominates blue WFs, industry contributed 0.5–1.4%, municipal WFs 0.5–1.7%. Manufacture (cloth and yarn) and electricity production (hydropower) dominated blue industrial WFs. Agricultural crop and livestock production tripled using the same amount of blue water, but industrial and municipal WFs increased with increasing production/population, the blue industrial WF by a factor of 3.3, municipal WFs by a factor of 3.6. Pakistan's water scarcity depends on environmental flow requirement (EFR) definitions. Volumetric government definitions generate low water scarcity allocating almost all water to society. Higher EFR's generate moderate to severe scarcity. Efficient agriculture leaves more water for industry and municipal supply, increasing crop output and decreasing sectoral competition. Policy might support improved water infrastructure. Pakistan's lessons are relevant for other water scarce countries.

The choice of constructed wetlands substrate is a very important issue, there is still a lack of studies that analyse the effect of different types of substrate on the efficiency of the accumulate and translocate contaminants from landfill leachate. Therefore, the objectives of study were to evaluate the effect of substrate on the potential of Phragmites australis to accumulate and translocate selected contaminants from leachate. The lowest translocation was recorded for Fe and Cu, and the highest for K and Ni. Translocation between root and shoots for most parameters (total Kjeldahl nitrogen, total phosphorus, K and Mn) was high (TF > 1.0). However, for Fe, Cu, Cr and Ni translocation was low in most variants (TF < 1.0). Only for Cr there were statistically significant differences between the substrates. The obtained bioaccumulation factor values for Cu, Cr and Ni show that P.australis does not have a good ability to phytoaccumulate heavy metals from leachate.

An alternative chitosan-based adsorbent modified by impregnation with deep eutectic solvent (DES) choline-chloride:urea at a molar ratio 1:2 proved efficient removal of the anthraquinone dye Acid Blue 80 (AB80) from aqueous solutions, and offered enhanced adsorption capacity compared to the starting materials. The adsorption was mainly affected by initial AB80 concentration, adsorbent dosage, contact time, and slightly influenced by temperature (25–45 °C), and pH (3.5–10). The pseudo-second-order kinetic model fitted the experimental data, and pseudo-first order model fitted as well at the highest AB80 concentration, 250 mg/L. The experimental data agreed with the Langmuir isotherm model, with a maximum adsorption capacity of 61.64 mg/g at 35 °C. The process was exothermic above 100 mg/L of dye and spontaneous up to 200 mg/L (T < 35 °C). The adsorbent could be reused without further treatment at least 5 times providing ≥40% removal, whereas the dye could be efficiently recovered by NaOH desorption. Electrostatic interactions as well as physisorption could explain the adsorption behavior.

Various techniques have been researched and introduced in water treatment plants to optimise treatment and management processes. This paper presents a solution that can help treatment plants to work more effectively and reach their mine water management goals. Using Python 3.7.1 programming language within an Anaconda 4.11.0 platform, neural networks and regression tree algorithms were compared to find the best performing model after the data had undergone robust data pre-processing and exploratory data analysis statistical techniques. The main aim was to use this best performing model to forecast mining influenced water (MIW) parameters. This approach will help the treatment plant operators in knowing the future MIW chemistry, and they can eventually plan ahead of time what chemicals and methods to use to treat and manage polluted MIW. Westrand mine pool water near Randfontein, South Africa is used as a case study, in which historical data (2016–2021) from shaft № 9 is used to train and test the algorithms. These algorithms included the artificial neural network (ANN), deep neural network (DNN), gradient boosting and random forest regression trees, while the multivariate long short-term memory (LSTM) was used to generate new data for the best performing algorithm. Different data pre-processing approaches were explored, including data interpolation and anomaly detection. These processes were carried out to highlight the most important part of completing a machine learning related project, which is data analytics. Finally, the random forest regression tree algorithm showed the overall best performance and was used to forecast Fe and acidity concentrations of MIW for 60 days. It could be shown that artificial intelligence techniques are capable to optimise and forecast mine water treatment plant parameters, and it is imperative to perform robust statistical analysis on the data before attempting to build forecasting models.

In the manufacturing sector, water has been often considered too cheap to conserve. Such thinking relies on water valuations that limit the value of water to the price paid. Using such simple methods, the share of water cost to total manufacturing cost is significantly small, <3%. As a result, conserving water and enabling technology uptake is difficult to justify economically and slow to advance, hindering progress toward sustainable water use.

However, the value of water to a manufacturer is far greater than the price paid. Valuations such as the true cost of water consider the additional in-plant treatment and energy costs and have been gaining greater traction in the manufacturing sector. However, true cost alone still undervalues water by not accounting for economic and social costs related to scarcity and environmental externalities.

This paper makes the case and presents a framework for valuing manufacturing water beyond the price paid and the true cost. The proposed fuller valuation of manufacturing water takes into account the internal and opportunity costs associated with the realization of water risks. The paper follows with a review of a wide range of water valuation metrics, both at the specific industry level and regional/economy-wide level. The use of various valuation metrics incorporating the relationship between the change in value with change in water use, such as marginal value of water, shadow price, and elasticity at the specific industry level, has been limited in the U.S. manufacturing sector. Further, a limited number of studies exist on data-intensive subjective evaluation techniques such as computable general equilibrium modeling and input-output modeling for regional water valuation.

After reviewing water value metrics, several recent case studies from manufacturers from the literature are presented to illustrate both the promise and challenges of a fuller valuation of water as proposed here. Some large multinational corporations have moved toward assessing the value of water via supply chain sustainability initiatives, environmental profit and loss accounting, estimating risk-adjusted values of water, hydro-economic modeling, natural capital asset valuation, and developing value chain indices. This paper provides policymakers and technology developers a framework for monetizing water value beyond its true cost and current metrics. If adopted, such fuller water valuations can help make the business case for the development and deployment of cost-effective water-conserving technologies, thereby improving the sustainability of the manufacturing sector with respect to water.

Simple and green natural deep eutectic solvent (NADES) based ultrasound assisted liquid-liquid micro-extraction (UA-LLME) method was developed for extraction and determination of methyl violet dye in contaminated river water samples using UV/Vis spectrophotometry. Choline chloride - decanoic acid based natural deep eutectic solvent was used for extraction. Important analytical parameters like pH, deep eutectic solvent volume/phase ratio, tetrahydrofuran volume, sonication time, and temperature were optimized. Limit of detection (LOD) and limit of quantification (LOQ) were 2.20 μg/L and 7.34 μg/L respectively. Relative standard deviation was 2.35–3.21%. Linearity of method was investigated in a concentration range 10–400 μg/L. Enrichment factor was calculated as 20. For 20 mL sample, the optimized parameters were as deep eutectic solvent volume 1.5 mL, tetrahydrofuran volume was 0.6 mL, pH = 6, sonication time 2 min. The optimized method was tested for extraction of methyl violet in real water samples confirming its applicability in routine environmental analysis.