Real-time Read and Analysis of Air Pollution Produced from Private Electrical Generators in Mosul City using LoRaWAN
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Abstract
This study presents a novel, site-specific deployment of a Long Range Wide Area Network (LoRaWAN)-driven air pollution monitoring network specifically for the Iraqi city of Mosul, which is beset by widespread power outages and extensive utilization of decentralized diesel generators. While these generators mitigate electricity shortages, they are enormous contributors to urban air pollution, emitting high levels of CO2 and particulates. As opposed to previous studies, which concentrate on affluent urban areas, this research addresses a very deprived locale using an extensible low-power, low-cost LoRaWAN network and high-precision CO2 sensors (Sensirion SCD30 and MH-Z19) and The Things Network (TTN) for real-time data aggregation. With geo-referenced generator mapping integrated into the system, systematically distributed sensor nodes, and spatial interpolation via Geographic Information System (GIS), the system acquires seasonally varying emissions and identifies hotspots of pollution. Temperature and humidity data are incorporated to calibrate sensors so that the emission models are improved. Furthermore, the study conducts an operational evaluation of the LoRaWAN network over Mosul's urban densification, investigating link stability, RSSI, latency, and packet loss to verify network performance in actual conditions. The results highlight strong seasonal correlation between generator working and CO2 flux, reinforcing the climate-energy-emission nexus. Practically, LoRaWAN's infrastructure-independent and long-range design would be particularly apt to Mosul's connectivity-deficient terrain, serving as a robust platform for environmental monitoring and planning regulation. This research makes a significant contribution to the field by proposing an open, reproducible IoT-based framework for urban air quality control in energy-constrained regions and outlines future directions encompassing multi-pollutant sensing, mobile sensor nodes, and blockchain-secured data communication for enhanced trust and system reliability.
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