Household Carbon Footprint Assessment Using Real-Time Monitoring Devices: A Case Study of Talba Estate, Minna, Nigeria

Abstract

The study focuses on the design, validation, and pilot deployment of a low-cost, real-time household carbon monitoring system in the Talba Estate, Minna, Nigeria, addressing the limited availability of affordable household-level emission monitoring tools in developing urban contexts. Due to ethical access and resource constraints, ten (10) households were randomly selected. This served as an exploratory pilot study to capture diurnal fluctuations of indoor CO₂ concentration and the household electricity consumption over a period of 30 days. Each sensor node, comprised of a Raspberry Pi 3B and an NDIR CO₂ sensor, was calibrated to a reference gas source recording an accuracy of ±2.8% (R² = 0.985). The study incorporated data on energy consumption, transportation, and the socio-economic status of households to determine the CO₂-equivalent emissions on a household basis. Emission levels were found to be significantly lower as the average household emission was 24.57 ± 4.21 kg CO₂ eq day⁻¹, almost 35% lower than the national average and significantly correlated with household income (r = 0.71) and with household size (r = 0.63). The findings emphasis that household emissions may be meaningfully reduced with targeted interventions that enhance energy efficiency. The created prototype served its purpose of consistent monitoring in resource-limited environments and did so at a cost 80% less than competing commercial systems. Overall, the study offers a complete and localised empirical analysis, aiding the formulation of sustainable policies for climate change mitigation in alignment with SDG 13 and the NDC targets of Nigeria. The study also provides a scalable model for localized carbon monitoring and responsive planning in adaptive environmental management for developing urban areas.