Assessment of surface water quality parameters using multivariate analysis-A case study of Kurichi and big lakes in Coimbatore.

Water quality deterioration due to industrialization and urbanization is a growing environmental concern, particularly in developing regions. This study assesses the surface water quality of Kurichi and Big Lakes in the Ukkadam area, Coimbatore, India, using multivariate statistical techniques to identify key pollution sources and evaluate contamination levels. Despite prior research on water quality in urban lakes, limited studies have systematically analyzed multiple contaminants using advanced statistical approaches.

Conversion of seaweed waste to biochar for the removal of heavy metal ions from aqueous solution: A sustainable method to address eutrophication problem in water bodies.

The present study investigated the sustainable approach for wastewater treatment using waste algal blooms. The current study investigated the removal of toxic metals namely chromium (Cr), nickel (Ni), and zinc (Zn) from aqueous solutions in batch and column studies using biochar produced by the marine algae Ulva reticulata. SEM/EDX, FTIR, and XRD were used to examine the adsorbents' properties and stability.

Exploring Modified Rice Straw Biochar as a Sustainable Solution for Simultaneous Cr(VI) and Pb(II) Removal from Wastewater: Characterization, Mechanism Insights, and Application Feasibility.

This study aimed to investigate the efficacy of a rice straw biosorbent in batch adsorption for the removal of chromium (Cr(VI)) and lead (Pb(II)) heavy-metal ions from wastewater. The biosorbent was chemically synthesized and activated by using concentrated sulfuric acid. The produced biosorbent was then characterized by using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), and X-ray diffraction (XRD) analyses, which provided insights into surface morphology and functional groups.

Impact of air pollutants on climate change and prediction of air quality index using machine learning models.

The impact of air pollution in Chennai metropolitan city, a southern Indian coastal city was examined to predict the Air Quality Index (AQI). Regular monitoring and prediction of the Air Quality Index (AQI) are critical for combating air pollution. The current study created machine learning models such as XGBoost, Random Forest, BaggingRegressor, and LGBMRegressor for the prediction of the AQI using the historical data available from 2017 to 2022.

Emerging waste-to-wealth applications of fly ash for environmental remediation: A review.

The considerable increase in world energy consumption owing to rising global population, intercontinental transportation and industrialization has posed numerous environmental concerns. Particularly, in order to meet the required electricity supply, thermal power plants for electricity generation are widely used in many countries. However, an annually excessive quantity of waste fly ash up to 1 billion tones was globally discarded from the combustion of various carbon-containing feedstocks in thermoelectricity plants.

Removing microplastics from wastewater using leading-edge treatment technologies: a solution to microplastic pollution-a review.

Microplastics (MPs) in environmental studies have revealed that public sewage treatment plants are a common pathway for microplastics to reach local surroundings. Microplastics are becoming more of a worry, posing a danger to both marine wildlife and humans. These plastic items not only contribute to the macrocosmic proliferation of plastics but also the scattering of microplastics and the concentration of other micropollutant-containing objects, increasing the number of pollutants identified.