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ABSTRACT
Monitoring air quality is crucial for evaluating environmental conditions and assessing potential health risks associated with airborne pollutants. This study focuses on analyzing PM2.5 levels, temperature, and relative humidity using data from the Purple Air sensor, a cost-effective, high-resolution air monitoring device. By examining data collected over a specific period, this research explores the relationships between these parameters and how they fluctuate. Statistical techniques and data visualization are applied to assess the impact of temperature and humidity on PM2.5 concentrations. The results offer valuable insights into air pollution patterns and demonstrate the reliability of Purple Air sensors for real-time air quality monitoring. This study underscores the importance of low-cost sensors in enhancing public health awareness and environmental management strategies.
