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The ecological environment has been greatly affected by industrialization concerning various hazardous impacts on living beings. Climate change is one of the foremost issues that have been observed in recent decades as a concern of the upsurge in greenhouse gases (GHGs) in the global atmosphere. Industrialization has been marked as the central cause for triggering GHGs in the atmospheric environment. Moreover, carbon dioxide (CO2) is a major content of greenhouse gases that have increased risk at an alarming rate. The level of CO2 in the atmosphere must be addressed through efficient carbon sequestration technologies. Numerous technologies for carbon dioxide sequestration have been investigated with chemical and biological methods. Microalgae research emerged as an economical and beneficial approach for suppressing and balancing the amount of carbon dioxide in the environment. Microalgae have been used extensively for maintaining environmental CO2 levels and efficient generation of biomass, which can be used to generate a variety of biofuels and other valuable products. Many countries have started imperative steps towards the scaling up of microalgae. These crucial steps have led the rest of the world to consider the technology for a cleaner and safer environment by influencing them to start investing in carbon sequestration through microalgae cultivation. This review illustrates several approaches and products generated by photosynthetic microalgae in carbon dioxide sequestration. The critical analysis of the current algae research trend and advanced technologies has been also conferred for a sustainable environment. [ABSTRACT FROM AUTHOR]

As far as routing protocol design for self-organized wireless sensor networks is concerned, energy efficiency and energy balance are critical research topics (WSNs). The fundamental difficulty in every WSN is node die out, which causes loss of connectivity and shortens the network's lifespan. The development of low-power, scalable WSNs remains a major research challenge. The use of clustering and routing to extend the lifetime of a network, which is a significant issue in sensor networks, has been extensively researched. Routing entails numerous activities that significantly impact the network's lifetime and throughput. The clustering strategy with data aggregation on cluster heads impacts total network performance. The proposed method includes the k-medoid technique for clustering and a stochastic model of the CH selection for energy efficient green WSN. A predictive analysis of the slot scheduling model is also incorporated for further network energy conservation. Also, an improved ant colony optimization algorithm is used to find the optimal route. The proposed work is implemented in MATLAB and the results are taken in terms of packet delivery ratio (PDR), packet loss ratio (PLR), network lifetime, jitter, end-to-end delay, throughput, bit error rate (BER) and energy consumption for proposed and existing techniques. The performance matrix for proposed and existing methods is calculated with 100 nodes. The range of proposed PDR at 100 nodes is 87%, PLR at 100 nodes is 1.3%, network lifetime at 100 nodes is 5400 rounds, jitter at 100 nodes is 0.23 ms, delay at 100 nodes is 3.9, BER at 100 nodes is 2.3%, throughput at 100 nodes is 730 Mbps, and energy consumption at 100 nodes is 40 mJ. The proposed method got better performance when compared to existing techniques. This proposed work aims to achieve a high network lifetime and lesser energy consumption with higher reliability. [ABSTRACT FROM AUTHOR]