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Abstract
This study Analyzed Atmospheric Parameters, PM₂.₅ concentration, temperature, and relative humidity within the University of Benin (UNIBEN) using a PurpleAir
sensor between January and March 2025. The research aimed to assess the air quality and evaluate the microclimatic conditions affecting the campus environment. The PurpleAir sensor was installed at the Space-Earth Environment Research Laboratory to record real-time data at two-minute intervals. Data were processed and analyzed using Microsoft Excel for descriptive statistics, correlation, and graphical presentation. The results revealed that PM₂.₅ concentrations ranged
between 58 µg/m³ and 202 µg/m³, exceeding the World Health Organization (WHO) recommended limit of 25 µg/m³, indicating consistently unhealthy air quality. Temperature values ranged from 20°C to 33°C, typical of the tropical dry and early wet seasons, while relative humidity varied between 32% and 100%. Analysis showed an inverse relationship between PM₂.₅ and relative humidity, implying that drier air conditions intensified particulate pollution. The findings highlight the need for continuous air monitoring and pollution control measures within the university. This study demonstrates the effectiveness of low-cost IoT- based sensors in generating reliable, real-time atmospheric data for environmental management and campus sustainability
sensor between January and March 2025. The research aimed to assess the air quality and evaluate the microclimatic conditions affecting the campus environment. The PurpleAir sensor was installed at the Space-Earth Environment Research Laboratory to record real-time data at two-minute intervals. Data were processed and analyzed using Microsoft Excel for descriptive statistics, correlation, and graphical presentation. The results revealed that PM₂.₅ concentrations ranged
between 58 µg/m³ and 202 µg/m³, exceeding the World Health Organization (WHO) recommended limit of 25 µg/m³, indicating consistently unhealthy air quality. Temperature values ranged from 20°C to 33°C, typical of the tropical dry and early wet seasons, while relative humidity varied between 32% and 100%. Analysis showed an inverse relationship between PM₂.₅ and relative humidity, implying that drier air conditions intensified particulate pollution. The findings highlight the need for continuous air monitoring and pollution control measures within the university. This study demonstrates the effectiveness of low-cost IoT- based sensors in generating reliable, real-time atmospheric data for environmental management and campus sustainability
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