Environmental Monitoring for Industrial Sites (ÉMIS): A Distributed LoRa-based Network for Real-Time Particulate Matter Characterization in Complex Environments

In situ atmospheric particulate matter (PM) monitoring networks play a critical role in advancing understanding of air quality dynamics across local to regional scales by providing continuous, site-resolved observations. In contrast to short-term measurement campaigns, sustained monitoring networks enable the characterization of long-term trends, episodic events, and source-specific variability, while providing essential data for model validation and exposure assessment. These capabilities are especially useful in industrial environments, where emissions are spatially heterogeneous, temporally variable, and chemically complex.

We present the design and implementation of the Environmental Monitoring for Industrial Sites (ÉMIS) network, a ground-based, distributed system developed to monitor complex industrial emission environments. The network is designed to operate under challenging conditions, including high-latitude environments with extreme seasonal variability, limited access to grid power, and constrained connectivity. Each station integrates measurements of particulate matter across multiple size fractions (PM_2.5, PM₅, and PM₁₀) and volatile organic compounds using low-cost optical sensors, local meteorology, and visual documentation via a conditionally triggered camera. Stations are additionally equipped with a modified Wilson and Cooke (MWAC) bottle sampler to collect long-term, sector-representative samples for chemical characterization.

Stations transmit data using long-range radio (LoRa) at user-defined intervals (e.g., two-minute resolution) to a hub node, which aggregates and relays data via cellular or satellite communication to an online dashboard. Unlike Bluetooth or Wi-Fi, LoRa enables kilometer-scale data transmission without the cost or infrastructure requirements of cellular modems. This architecture provides near–real-time insight into emission dynamics while supporting long-term data continuity. Emphasis on low-cost, modular instrumentation reduces financial and logistical barriers associated with traditional monitoring systems, enabling high-density deployments accessible to researchers, industries and public stakeholders.

The initial field deployment consisted of fifteen (15) stations distributed across a copper smelter in Quebec, Canada, spanning more than 1 km². This case study demonstrates the network’s ability to resolve spatial gradients and localized emission signals, while dealing with complex topography and climate conditions. Analysis reveals persistent PM hotspots associated with heavy machinery traffic, ore handling operations, and slag cooling. Periodic PM spikes linked to train transport, as well as clear relationships between wind speed, wind direction, and plume occurrence were identified.

The multi-level data output from the ÉMIS network supports a wide range of applications, including PM source attribution, evaluation of emission dynamics, integration with receptor and dispersion modeling, and validation of satellite-derived products. The network also serves as a testbed for sensor development, quality assurance refinement, and cross-network harmonization under real-world industrial conditions. This work highlights how adaptable, cost-effective ground-based monitoring networks can expand observational capacity in industrial environments and support advances in atmospheric science, air-quality management, and community-informed decision-making.