Abstract
Environmental sustainability is vital in combating climate change, pollution, and resource depletion. This chapter explores four domains, utilizing intelligent engineering and applied sciences. It first addresses pollution control, utilizing technologies such as electrostatic precipitators and AI-enabled monitoring. Next, it emphasizes waste management, focusing on waste-to-energy and AI in recycling. The third section evaluates sustainable construction, exploring bio-based materials and green practices. Fourth, it highlights climate change mitigation through clean energy, efficiency measures, and CCUS technology. Additionally, the chapter underscores interdisciplinary collaboration and cross-sectoral partnerships for innovative, sustainable solutions. With practical case studies, the chapter offers a comprehensive view of how technology contributes to sustainability, inspiring future research and collaboration.
TopPollution Control
Pollution, particularly air and water pollution, presents significant challenges to environmental sustainability and human health (Anetor et al., 2022). Air pollution, resulting from industrial emissions, vehicular exhaust, and combustion of fossil fuels, contains harmful substances such as sulfur dioxide, nitrogen oxides, and particulate matter. These pollutants can have severe health impacts, leading to respiratory diseases, heart conditions, and even premature death (Ogunkunle, O., & Ahmed, N. A., 2021).
Water pollution, caused by the discharge of industrial waste, agricultural runoff, and domestic sewage, contaminates our water bodies, threatening aquatic ecosystems and posing a risk to human health (Akul, 2018). For instance, the excessive use of fertilizers in agriculture can result in eutrophication, leading to the loss of aquatic biodiversity (Effiong et al., 2022). Additionally, the consumption of polluted water can result in waterborne diseases such as cholera and dysentery (Nenik, S., & Diah, L.W., 2021).
Key Terms in this Chapter
Interdisciplinary Collaboration: An approach integrating different academic disciplines to develop comprehensive solutions, often employed to address environmental issues.
Applied Sciences: Practical application of scientific knowledge to resolve real-world issues, including those related to environmental sustainability.
Pollution Control: The regulation of pollutants in the environment, often involving advanced technologies and systems for monitoring and management.
Predictive Modeling: The use of statistical techniques and AI algorithms to forecast future outcomes based on historical data, such as predicting environmental changes.
Cross-Sectoral Partnerships: Collaborations involving different sectors (government, academia, industry, civil society) aimed at addressing complex problems, including environmental concerns.
Intelligent Engineering Applications: The use of technologies like AI, IoT, and robotics to solve complex problems, including environmental challenges.
Sustainable Construction: The practice of creating structures using processes that are environmentally responsible and resource-efficient throughout a building's life-cycle.
Climate Change Mitigation: Efforts to reduce or prevent emission of greenhouse gases and enhance their absorption.
Waste Management: The process of handling waste materials, encompassing collection, transportation, processing, recycling, or disposal.
Real-Time Monitoring: Live tracking and reporting of information, often used in environmental contexts like pollution levels and energy usage.