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.

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.

Impact of climate change and anthropogenic activities on aquatic ecosystem - A review.

All living things depend on their natural environment, either directly or indirectly, for their high quality of life, growth, nutrition, and development. Due to the fast emissions of greenhouse gases (GHGs), the Earth's climate system is being negatively impacted by global warming. Stresses caused by climate change, such as rising and hotter seas, increased droughts and floods, and acrid waters, threaten the world's most populated areas and aquatic ecosystems.

Air quality prediction by machine learning models: A predictive study on the indian coastal city of Visakhapatnam.

Clean air is critical component for health and survival of human and wildlife, as atmospheric pollution is associated with a number of significant diseases including cancer. However, due to rapid industrialization and population growth, activities such as transportation, household, agricultural, and industrial processes contribute to air pollution. As a result, air pollution has become a significant problem in many cities, especially in emerging countries like India.

Soft computing-based models and decolorization of Reactive Yellow 81 using Ulva Prolifera biochar.

The present research explores the application of optimization tools namely Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) in the decolorization of Reactive Yellow 81 (RY81) from an aqueous solution. The characterization of the biochar was carried out using FTIR, elemental analysis, proximate analysis, BET analysis and Thermogravimetric analysis. Five independent variables namely solution pH, biochar dose, contact time, initial dye concentration and temperature were analyzed using RSM, ANN and ANFIS models.

Towards sustainable biodiesel production by solar intensification of waste cooking oil and engine parameter assessment studies.

Renewable energy sources for harnessing biofuels are the viable solution to substitute fossil fuels and reduce production cost. In this study, waste cooking oil was converted into biodiesel via a customized solar reactor. The solar reactor was customized using copper tubes and black surface to trap solar energy for conversion of waste cooking oil into biodiesel.

Artificial neural network modelling for biodecolorization of Basic Violet 03 from aqueous solution by biochar derived from agro-bio waste of groundnut hull: Kinetics and thermodynamics.

In this study, Levenberg Marquardt back propagation algorithm was used to train the Artificial Neural Network (ANN) and to predict the adsorptive removal of cationic dye Basic Violet 03 (BV03) by biochar derived from biowaste of groundnut hull. The experimental conditions such as solution pH, biochar dose, initial dye concentration, contact time and temperature were used as input variables and BV03 percentage removal as target. The hidden and the output layer of the network was trained by tangent sigmoid and liner transfer functions.

Remediation of complex remazol effluent using biochar derived from green seaweed biomass.

The unique property of biochar, synthesized from a green seaweed (), to remediate complex Remazol dye bearing wastewater was investigated. Preliminary trials were targeted to explore the remediation capacity of biochar towards each of Remazol dyes (Remazol brilliant blue R (RBBR), Remazol brilliant orange 3R (RBO3R), Remazol brilliant violet 5R (RBV5R), and Remazol Black B (RBB)) in single-solute system. The results show that equilibrium pH played a vital part with maximum sorption observed at pH 2.