Autonomous Multi-Sensor Air Quality Monitoring System for Abattoirs and Waste Environments: Development and Performance Evaluation

Abstract

This study reports the development and validation of a low-cost, autonomous multi-sensor device for monitoring gaseous and particulate emissions in waste management and livestock processing environments. The platform integrates electrochemical, metal-oxide semiconductor (MOS), and optical sensors to measure CO, CO₂, CH₄, NH₃, H₂S, NO₂, SO₂, H₂, acetone, TVOCs, and particulate matter (PM₁, PM₂.₅, PM₁₀), together with temperature, relative humidity, and wind speed. To support reliable long-term outdoor deployment, the system was built with dual IP65-rated enclosures, SD card data logging, GSM-based data transmission, and watchdog-protected firmware. Calibration using certified gases, aerosol chambers, and reference instruments produced strong sensor responses, with coefficients of determination (R²) ranging from 0.92 to 0.99 across the monitored parameters. The power subsystem, comprising an 18 Ah, 12 V sealed lead-acid battery and a 30 W photovoltaic panel, sustained off-grid operation for more than 51 hours, while sensitivity analysis indicated that optimized duty-cycling of high-consumption components could extend autonomy to about 72 hours. Field deployments further demonstrated stable operation across wet and dry seasons, minimal zero-drift, and a positive daily energy balance under an average device load of about 4.2 W. These results confirm the system’s suitability for continuous, real-time emission profiling and microclimate monitoring in abattoirs, landfills, and other emission-prone environments. The developed platform, therefore, provides a scalable and cost-effective tool for exposure assessment, environmental risk management, regulatory surveillance, and compliance monitoring in relation to WHO air quality guidelines and national environmental standards. Broader adoption will benefit from routine calibration, adaptive power optimization, and dashboard-based visualization to strengthen evidence-based environmental policy and occupational health interventions.