Air pollution is the existence of atmospheric chemicals damaging the health of human beings and other living organisms or damaging the environment or resources. Rarely any common contaminants are smog, nicotine, mold, yeast, biogas, or carbon dioxide. The paper will primarily observe, visualize and anticipate pollution levels. In particular, three algorithms of Artificial Intelligence were used to create good forecasting models and a predictive AQI model for 4 distinct gases: carbon dioxide, sulphur dioxide, nitrogen dioxide, and atmospheric particulate matter. Thus, in this paper, the Air Qualification Index is developed utilizing Linear Regression, Support Vector Regression, and the Gradient Boosted Decision Tree GBDT Ensembles model over the next 5 h and analyzes air qualities using various sensors. The hypothesized artificial intelligence models are evaluated to the Root Mean Squares Error, Mean Squared Error and Mean absolute error, depending upon the performance measurements and a lower error value model is chosen. Based on the algorithm of the Artificial Intelligent System, the level of 5 air pollutants like CO2, SO2, NO2, PM 2.5 and PM10 can be predicted immediately by integrating the observations with errors. It may be used to detect air quality from distance in large cities and can assist lower the degree of environmental pollution.
The usage of waste for the development of sustainable building materials has received an increasing attention in socio-eco-environment spheres. The rice husk ash (RHA) produced during burning of rice husk and the ever-increasing plastic wastes are useless causing detrimental effects on the environment. This research supports the idea of sustainability and circular economy via utilization of waste to produce value-added products. This research explores the potential of waste plastics, RHA, and silica sand as thermoplastic composite materials. The different composite samples were prepared through waste plastics which includes low- and high-density polyethylene and polypropylene with incorporation of RHA and silica sand in proportions. The study investigates the effect of filler/polymer in 30/70, 20/80, and 10/90 (wt. %) on the workability of the developed composite materials. The workability of the composites was found to improve with filler reinforcement. The experimental results showed the maximum density of 1.676 g/cm3 and mechanical strength of 26.39, 4.89, and 3.25 MPa as compressive, flexural, and tensile strengths, respectively. The minimum percentage of water absorption was 0.052%. The wear tests resulted in a minimum abrasive and sliding wear rate of 0.03759 (cm3) and 0.00692 × 10-6 kg/m. The correlations between wear mechanisms and responses were morphologically analyzed. The developed composites verify the feasibility of RHA and plastics waste as a cost effective and environmentally competent product. The results and discussions provided a direction for the future research on sustainable polymeric composite materials.
An emerging contaminant of concern in aqueous streams is naproxen. Due to its poor solubility, non-biodegradability, and pharmaceutically active nature, the separation is challenging. Conventional solvents employed for naproxen are toxic and harmful. Ionic liquids (ILs) have attracted great attention as greener solubilizing and separating agent for various pharmaceuticals. ILs have found extensive usage as solvents in nanotechnological processes involving enzymatic reactions and whole cells. The employment of ILs can enhance the effectiveness and productivity of such bioprocesses. To avoid cumbersome experimental screening, in this study, conductor like screening model for real solvents (COSMO-RS) was used to screen ILs. Thirty anions and eight cations from various families were chosen. Activity coefficient at infinite dilution, capacity, selectivity, performance index, molecular interactions using σ-profiles and interaction energies were used to make predictions about solubility. According to the findings, quaternary ammonium cations, highly electronegative, and food-grade anions will form excellent ionic liquid combinations for solubilizing naproxen and hence will be better separating agents. This research will contribute easy designing of ionic liquid-based separation technologies for naproxen. In different separation technologies, ionic liquids can be employed as extractants, carriers, adsorbents, and absorbents.