IoT-based environmental monitoring network for PM2.5 in the Veracruz-Boca del Río metropolitan area

Abstract

The Veracruz–Boca del Río metropolitan area is exposed to multiple air pollution sources associated with port activity, vehicular traffic, industrial operations, and limited official monitoring coverage. This study presents the design, calibration, and preliminary field deployment of an expandable IoT-based environmental monitoring network intended to characterize the short-term spatial and temporal variability of PM2.5 in this coastal urban–port region. The network consisted of four monitoring stations installed along a north–south urban–port transect. Each node integrated an ESP32 microcontroller, a PMS5003 optical particle sensor for PM2.5 and PM10, local microSD data storage, and a BME680 sensor processed with the Bosch Software Environmental Cluster algorithm to obtain auxiliary gas-related indicators, including BSEC-derived CO 2 -equivalent concentration. The PMS5003 readings were corrected using a nonlinear polynomial calibration based on paired measurements with an SPS30 sensor used as a secondary transfer reference. During the initial complete-network operation period in May 2025, average PM2.5 concentrations exceeded the revised 24-h reference value of 30 μg m -3 at the four stations. Inter-station Spearman analysis indicated coherent temporal PM2.5 patterns across the network. The results demonstrate the feasibility of a calibrated low-cost IoT network for preliminary spatial–temporal screening of PM2.5 in Veracruz–Boca del Río. However, the dataset represents a short-term baseline and should not be interpreted as a regulatory-grade assessment or as evidence of long-term seasonal trends or definitive source attribution.