The rapid expansion of lithium-ion battery (LIB) markets for electric vehicles and renewable energy storage has exponentially increased lithium demand, driving research into sustainable extraction methods. Traditional lithium recovery from brine using evaporation ponds is resource intensive, consuming vast amounts of water and causing severe environmental issues. In response, Direct Lithium Extraction (DLE) technologies have emerged as more efficient, eco-friendly alternatives. This review explores two promising electrochemical DLE methods: Electrodialysis (ED) and Capacitive Deionization (CDI). ED employs ion-exchange membranes (IEMs), such as cation exchange membranes, to selectively transport lithium ions from sources like brine and seawater and achieves high recovery rates. IEMs utilize chemical and structural properties to enhance the selectivity of Li⁺ over competing ions like Mg²⁺ and Na⁺. However, ED faces challenges such as high energy consumption, membrane fouling, and reduced efficiency in ion-rich solutions. CDI uses electrostatic forces to adsorb lithium ions onto electrodes, offering low energy consumption and adaptability to varying lithium concentrations. Advanced variants, such as Membrane Capacitive Deionization (MCDI) and Flow Capacitive Deionization (FCDI), enhance ion selectivity and enable continuous operation. MCDI incorporates IEMs to reduce co-ion interference effects, while FCDI utilizes liquid electrodes to enhance scalability and operational flexibility. Advancements in electrode materials remain crucial to enhance selectivity and efficiency. Validating these methods at the pilot scale is crucial for assessing performance, scalability, and economic feasibility under real-world conditions. Future research should focus on reducing operational costs, developing more durable and selective electrodes, and creating integrated systems to enhance overall efficiency. By addressing these challenges, DLE technologies can provide sustainable solutions for lithium resource management, minimize environmental impact, and support a low-carbon future.

The purpose of this study is to compare the spectral indices for a two-dimensional river algae map using an unmanned aerial vehicle (UAV) and an unmanned surface vehicle (USV) hybrid system. The UAV and USV hybrid systems can overcome the limitation of not being able to effectively compare images of the same region obtained at different times and under different seasonal conditions, when using a method of comparing and analyzing with absolute values in remote sensing. Radiometric correction was performed to minimize the interference that could distort the analysis results of the UAV imagery, and the images were taken under weather conditions that would minimally affect them. Three spectral indices, namely, normalized difference vegetation index (NDVI), normalized green–red difference index (NGRDI), green normalized difference vegetation index (GNDVI), and normalized difference red edge index (NDRE) were compared for the chlorophyll-a images. In field application and correlational analysis, the NDVI was strongly correlated with chlorophyll-a (R² = 0.88, p < 0.001), and the GNDVI was moderately correlated with chlorophyll-a (R² = 0.74, p < 0.001). As a result of comparing the chlorophyll-a concentration with the in-situ chlorophyll-a imagery by UAV, we obtained the RMSE of NDVI at 2.25, and the RMSE of GNDVI at 3.41.

Membrane distillation is a process combining thermal and membrane technology, which uses the vapor pressure difference as driving force because of the temperature difference. Of the MD configurations, VMD can achieve high flux due to the application of vacuum. This paper analyzes operating parameters (vacuum pressure, feed flow rate, and feed concentration) that affect permeate flux in a modified design VMD system vacuum multi-effect membrane distillation (V-MEMD). The study investigated the most suitable operating parameters that would enhance the performance of V-MEMD system at high salinity (1–4 M of NaCl) with a moderate bulk temperature of 60°C. The result of this study showed that vacuum pressure is the most influential factor of the selected, and the effect of temperature polarization is more dominant to permeate flux than concentration polarization. Above this, the high-salinity solution can be treated by V-MEMD system because it does not affect the permeate total dissolved solid and flux. A dominant reduction ratio of vapor pressure was observed even at a low ratio of temperature polarization.

Taste and odor (T&O) compounds present in natural water bodies could originate from algae. In this study, alga-generated compounds that can cause T&O issues in water, such as geosmin (GE), 2-Methylisoborneol (MIB), 2,4,6-Trichloroanisole (TCA), 2-Methylbenzofuran (MB), 2-Isopropyl-3-methoxypyrazine (IPMP), 2-Isobutyl-3-methoxypyrazine (IBMP), cis-3-Hexenyl acetate (HA), trans,trans-2,4-Heptadienal (HD), trans,cis-2,6-Nonadienal (ND), and trans-2-Decenal (DN), were determined through solid-phase microextraction coupled with gas chromatography/mass spectrometry (HS-SPME GC/MS) and electronic tongue (E-tongue), and the results from the two techniques were compared. Although HS-SPME GC/MS facilitates the detection and quantification of T&O compounds with high precision and accuracy, the sample preparation and handling is difficult and the analysis time (1 h) is longer than those of other analytical methods. E-tongue can be used as an alternative analytical method for water quality analysis and risk management because it enables controlled and rapid analysis (3 min) of T&O compounds in water at a low cost. Notably, principal component analysis indicated that E-tongue can discriminate and quantify eight T&O compounds at as low as 0.02 μg L^-1 concentration. Further, partial least squares analysis confirmed that the sensor exhibits high sensitivity to concentration changes. The sensors with the highest variable importance in projection scores were determined to be SCS (1.39 and 1.38) for GE and MIB, CTS (1.34) for IPMP, CPS (1.33) for IBMP, AHS (1.42) for HA, ANS (1.22) for HD, and NMS (1.14 and 1.19) for ND and DN.