IoT system for CO₂ measurement in urban areas: A systematic approach
Abstract
The concentration of carbon dioxide (CO₂) in urban areas constitutes a key environmental challenge, given the impact of mobile and industrial emissions and the complexity of urban microclimates. In this context, IoT systems utilizing low-cost sensors, connectivity architectures like LoRaWAN and NB-IoT, and cloud analysis platforms emerge as a complementary alternative to traditional regulatory networks. This systematic review, developed following the PRISMA 2020 guidelines, analyzed studies published between 2015 and 2025 in databases such as Scopus, IEEE Xplore, ACM Digital Library, and ScienceDirect, applying strict inclusion and exclusion criteria. Out of 125 initial records, 15 studies were selected for qualitative synthesis and 10 for meta-analysis. Results indicate that low-cost NDIR sensors achieve accuracies of 8–12 ppm after calibration and co-location processes, while eCO₂ sensors derived from VOCs lack reliability for urban decision-making. LoRaWAN proved to be the most energy-efficient option, although NB-IoT demonstrated greater robustness in high-interference scenarios. Heterogeneity in performance metrics and a lack of standardized interoperability protocols were evident. The review concludes that IoT systems offer advantages in cost and scalability but require improvements in calibration, quality assurance, and their integration with predictive models and digital twins to enhance their value for urban public policies.
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Ashkanan, H., Wang, R., Shi, W., Siefert, N., Thompson, R., Smith, K., & Morsi, B. (2021). Effect of power plant capacity on the CAPEX, OPEX, and LCOC of the CO2 capture process in pre-combustion applications. International Journal of Greenhouse Gas Control, 109. https://doi.org/10.1016/j.ijggc.2021.103355
Chicaiza, W., Gómez, J., Sánchez, A., & Escaño, J. (2024). El Gemelo Digital y su aplicación en la Automática. Revista Iberoamericana de Automática e Informática Industrial, 21(2), 91–115.
Cifuentes, S. (2021). Estudio de consumo energético para algoritmos de recolección de datos en redes de sensores inalámbricos bajo el protocolo Lorawan. Fondef. https://www.conicyt.cl/fondef/
Cisneros, X., & Jacome, D. (2025). Ciberseguridad en los dispositivos IOT de uso doméstico: una revisión sistemática de la literatura. Revista Científica Arbitrada Multidisciplinaria PENTACIENCIAS, 7(1), 140–170.
Clavé, N., & Estécahandy, M. (2023). Optimización del equilibrio entre la disponibilidad de producción, el gasto de capital y el gasto operativo de los proyectos, gestionando los aspectos ambientales con una herramienta de simulación. En M. Al Zaabi, (ed.). Proceedings of the Exposición y Conferencia Internacional del Petróleo de Abu Dabi (pp. 1-12). EDICON.
Delaria, E., Kin, J., Fitzmaurice, H., Newman, C., Wooldridge, P., Worthington, K., & Cohen, R. (2021). The Berkeley Environmental Air-quality and CO2 Network: Field calibrations of sensor temperature dependence and assessment of network scale CO2 accuracy. Atmospheric Measurement Techniques, 14(8), 5487–5501. https://doi.org/10.5194/amt-14-5487-2021
Dubey, R., Telles, A., Nikkel, J., Cao, C., Gewirtzman, J., Raymond, P., & Lee, X. (2024). Low-cost CO2 NDIR sensors: Performance evaluation and calibration using machine learning techniques. Sensors, 24(17), 5675. https://doi.org/10.3390/s24175675
Gulati, K., Boddu, R., Kapila, D., Bangare, S., Chandnani, N., & Saravanan, G. (2022). A review paper on wireless sensor network techniques in Internet of Things (IoT). Materials Today: Proceedings, 51, 161–165.
Jabbar, W. A., Subramaniam, T., Ong, A. E., Iqbal, M. N., Wu, W. K., & De Oliveira, M. A. (2022). LoRaWAN-based IoT system implementation for long-range outdoor air quality monitoring. Internet of Things, 20. https://doi.org/10.1016/j.iot.2022.100540
Jaimes, M., Servin, H., Argueta, I., Sánchez, M., & Beiza, I. (2025). Cambio climático y salud respiratoria. Revisión sistemática de la literatura. Revista Científica de Salud y Desarrollo Humano, 6(1), 1452–1469.
Jiang, H., Han, Y., Zalhaf, A. S., Yang, P., & Wang, C. (2023). Low-cost urban carbon monitoring network and implications for China: A comprehensive review. Environmental Science and Pollution Research, 30(48), 105012–105029. https://doi.org/10.1007/s11356-023-29719-8
Kumar, V., Jha, R. K., & Jain, S. (2020). NB-IoT security: A survey. Wireless Personal Communications, 113(4), 2661–2708. https://doi.org/10.1007/s11277-020-07346-7
Lee, J., Mulder, F., Leeflang, M., Wolff, R., Whiting, P., & Bossuyt, P. (2022). QUAPAS: An adaptation of the QUADAS-2 tool to assess prognostic accuracy studies. Annals of Internal Medicine, 175(7), 1010–1018. https://doi.org/10.7326/M21-4295
Lwasa, S., Seto, K. C., Bai, X., Blanco, H., Gurney, K. R., Kılkış, Ş., & Yamagata, Y. (2022). Urban systems and other settlements. Cambridge University Press.
Marinho, F., Neto, A., & Rocha, P. (2022). Previsão de irradiância solar de curto prazo utilizando modelo de envelopes para os preditores. Congresso Brasileiro de Automática.
Müller, M., Graf, P., Meyer, J., Pentina, A., Brunner, D., Perez-Cruz, F., & Emmenegger, L. (2020). Integración y calibración de sensores de CO₂ infrarrojos no dispersivos (NDIR) de bajo coste y su funcionamiento en una red de sensores que cubre Suiza. Atmospheric Measurement Techniques, 13(7), 3815–3834. https://doi.org/10.5194/amt-13-3815-2020
Osorio, A., Calle, M., Soto, J. D., & Candelo-Becerra, J. E. (2020). Routing in LoRaWAN: Overview and challenges. IEEE Communications Magazine, 58(6), 72–76. https://doi.org/10.1109/MCOM.001.1900529
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372(1). https://doi.org/10.1136/bmj.n71
Rethlefsen, M. L., Kirtley, S., Waffenschmidt, S., Ayala, A. P., Moher, D., Page, M. J., & Koffel, J. B. (2021). PRISMA-S: An extension to the PRISMA statement for reporting literature searches in systematic reviews. Journal of the Medical Library Association, 109(2), 174–200. https://doi.org/10.5195/jmla.2021.962
Vafaei, M., & Amini, A. (2021). Chamberless NDIR CO2 sensor robust against environmental fluctuations. ACS Sensors, 6(4), 1536–1542. https://doi.org/10.1021/acssensors.0c02620
Winter, A., Zhu, Y., Asimow, N., Patel, M., & Cohen, R. C. (2025). A scalable calibration method for enhanced accuracy in dense air quality monitoring networks. Acs Publications. https://doi.org/10.1021/acs.est.4c08855
Copyright (c) 2025 José Andrés Nicolalde López, Luis Miguel Acevedo Heredia, Lenin Daniel Ruales Franco
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