This comprehensive review examines the evolving landscape of PM2.5 monitoring, emphasizing its critical role in environmental chemistry, public health and electrical/electronic engineering. Traditional methods, including manual sampling, gravimetric analysis, and the Federal Reference Method (FRM), have long been relied upon for PM2.5 measurement but are hindered by limitations in spatial coverage, temporal resolution, and cost. In response, emerging technologies such as wireless sensor networks, low-cost sensor technologies, remote sensing techniques, and machine learning algorithms offer promising solutions to overcome these challenges. Through an analysis of case studies and applications in various environmental settings, including urban areas, industrial zones, and indoor environments, the review highlights the effectiveness of monitoring networks in enhancing spatial and temporal resolution, as well as the need for community engagement and real-time monitoring solutions. Furthermore, technological innovations such as sensor fusion, data analytics, and artificial intelligence hold great promise for improving the accuracy, reliability, and accessibility of PM2.5 monitoring data. Regulatory agencies and policymakers play a crucial role in advancing PM2.5 monitoring by harmonizing monitoring standards, strengthening quality assurance measures, and developing evidence-based regulations to mitigate air pollution and protect public health. In conclusion, international cooperation and collaboration are essential for addressing transboundary air pollution and global environmental challenges. Regional monitoring networks and international agreements provide frameworks for data sharing, standardization of monitoring practices, and collaborative research efforts. To this end, stakeholders can leverage PM2.5 monitoring by adopting new technologies, improving data quality, and supporting evidence-based actions to safeguard public health, the environment, and sustainability
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