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Air pollution imposes a substantial economic burden globally, with estimated annual losses exceeding 8. 1 trillion due to healthcare costs, lost productivity, infrastructure degradation, and agricultural damage. This review assesses the economic effectiveness of advanced air pollution control technologies within the broader context of sustainable energy transitions. Through comparative life-cycle cost-benefit analyses, we evaluate the financial viability, energy efficiency, and policy relevance of innovations such as carbon capture and storage (CCS), AI-driven emissions monitoring, and nanotechnology-enhanced filtration. Among the technologies assessed, CCS presents the most significant capital expenditure (up to 500 million per facility) but offers long-term returns through carbon credits and enhanced oil recovery, yielding up to 30–40 in economic benefits for every 1 invested. AI-based monitoring systems demonstrate strong economic efficiency by reducing energy consumption in industrial operations by up to 15% and improving regulatory compliance at a larger scale. Nanotechnology-enabled filters provide high pollutant capture efficiency and reduce operational resistance, yet face scalability and end-of-life challenges. Additionally, emerging technologies such as bioengineered filters offer promise for low-resource settings but require further economic validation. The integration of these technologies with renewable energy systems, such as hydrogen-powered pollution control units and solar-driven filtration, further amplifies their environmental and economic benefits. By aligning air pollution mitigation with climate and energy goals, this review highlights a pathway for policymakers and industries to achieve both economic resilience and environmental sustainability. The findings underscore that, while upfront costs may be high, strategic investments in advanced pollution control deliver substantial long-term returns across sectors.
Melhim et al. (Tue,) studied this question.