Embedded System Application for Establishing Variability and the Relationship Between Meteorological Parameters and Particulate Matter Pollution in a Lagos Site
Keywords:
PM Pollution, Meteorological Parameters, Embedded System, Correlation Analysis, Environmental HealthAbstract
Air pollution from particulate matter (PM) remains a major environmental and public health concern, particularly in rapidly urbanizing cities. This study investigated the variability of PM (PM1, PM2.5, and PM10) and their relationship with meteorological parameters in Lagos, Nigeria, using a low-cost embedded monitoring system. Data were collected continuously over a two-year period (May 2021–April 2023) at two-minute intervals, providing one of the longest continuous PM datasets reported for Lagos. Results revealed distinct diurnal and seasonal patterns, with concentrations consistently higher at night and during the dry season. Temperature, relative humidity, atmospheric pressure, and wind speed showed significant inverse relationships with PM across all size fractions, with humidity and wind speed emerging as the strongest predictors. However, regression analysis indicated modest explanatory power (R² = 0.280 for PM2.5 and R² = 0.201 for PM10), suggesting that local emission sources have a dominant influence. Comparison with air quality benchmarks showed substantial exceedances. The daily mean concentration of PM2.5 (37.39 µg/m³) exceeded the WHO 24-hour guideline (15 µg/m³) and marginally exceeded the U.S. NAAQS limit (35 µg/m³). In contrast, PM10 (43.88 µg/m³) remained below the WHO guideline (45 µg/m³) and well within the Nigerian NESREA 24-hour limit (150 µg/m³). The study is limited by its single-site design, which may constrain spatial generalization. Nonetheless, the findings highlight elevated health risks from fine particulates in Lagos and demonstrate the effectiveness of low-cost embedded systems for long-term urban air quality assessment, supporting their integration into regulatory and public health strategies.
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