Autors: Marinov, M. B., Hensel, S., Ganev, B. T., Nikolov, G. T.
Title: Performance evaluation of low-cost particulate matter sensors
Keywords: Air quality, Calibration, Correlation, Particulate matter, R

Abstract: Increased particulate matter (PM) concentration in big cities and agglomerations is one of the main risk factors for the health of the residents. Conventional systems for PM monitoring have significant limitations, especially with respect to the costs for installation and maintenance. The number of these monitor stations is limited but PM concentration changes fast, non-linearly, within wide limits and depends on various factors. The large gradients in air quality, especially in urban areas, are a significant challenge for conventional measurement technologies. In recent years there has been a rapid development of compact, mobile low-cost measurement systems with better spatial coverage than that of traditional air quality systems. The present work is dedicated to the performance evaluation of commercial, off-the-shelf PM sensors. The main error sources in these sensors and the possibilities for their reduction are discussed


  1. Olivares, G., Edwards, S. The outdoor dust information node (ODIN)-development and performance assessment of a low cost ambient dust sensor (2015) Atmos. Meas. Tech. Discuss., 8 (7), pp. 7511-7533
  2. Zheng, Y., Liu, F., Hsieh, H.-P. U-Air: When urban air quality inference meets big data (2013) Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Part F128815, art. no. 2488188, pp. 1436-1444.DOI: 10.1145/2487575.2488188
  3. Jovašević-Stojanović, M., Bartonova, A., Topalović, D., Lazović, I., Pokrić, B., Ristovski, Z. On the use of small and cheaper sensors and devices for indicative citizen-based monitoring of respirable particulate matter (2015) Environmental Pollution, 206, art. no. 8112, pp. 696-704. DOI: 10.1016/j.envpol.2015.08.035
  4. Budde, M., El Masri, R., Riedel, T., Beigl, M. Enabling low-cost particulate matter measurement for participatory sensing scenarios (2013) Proceedings of the 12th International Conference on Mobile and Ubiquitous Multimedia, MUM 2013, art. no. a19, DOI: 10.1145/2541831.2541859
  5. EEA (European Environment Agency) (2016) AirBase - The European Air Quality Database.
  6. Fuzzi, S., Baltensperger, U., Carslaw, K., Decesari, S., Denier Van Der Gon, H., Facchini, M.C., Fowler, D., Koren, I., Langford, B., Lohmann, U., Nemitz, E., Pandis, S., Riipinen, I., Rudich, Y., Schaap, M., Slowik, J.G., Spracklen, D.V., Vignati, E., Wild, M., Williams, M., Gilardoni, S. Particulate matter, air quality and climate: Lessons learned and future needs (2015) Atmospheric Chemistry and Physics, 15 (14), pp. 8217-8299. DOI: 10.5194/acp-15-8217-2015
  7. Hojaiji, H., Kalantarian, H., Bui, A.A.T., King, C.E., Sarrafzadeh, M. Temperature and humidity calibration of a low-cost wireless dust sensor for real-time monitoring (2017) SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings, art. no. 7894056, . Cited 34 times. DOI: 10.1109/SAS.2017.7894056


2017 26th International Scientific Conference Electronics, ET 2017 - Proceedings, 2017, Bulgaria, DOI 10.1109/ET.2017.8124367

Copyright IEEE

Цитирания (Citation/s):
1. Alfano B, Barretta L, Giudice AD, De Vito S, Francia GD, Esposito E, Formisano F, Massera E, Miglietta ML, Polichetti T. A review of low-cost particulate matter sensors from the developers’ perspectives. Sensors. - 2020 - в издания, индексирани в Scopus или Web of Science
2. Wang M, Zou J, Zhang H, Wei Y, Liu S. Numerical modeling of particles separation method based on compound electric field. Appl Sci. DOI: 10.3390/app10175999 - 2020 - в издания, индексирани в Scopus или Web of Science
3. Gaur D, Mehrotra D, Singh K. Image correlation method to simulate physical characteristic of particulate matter. Intl J Syst Assur Eng Manage. DOI: 10.1007/s13198-019-00868-9 - 2020 - в издания, индексирани в Scopus или Web of Science
4. Galabov V. How to Measure the Impact of Factors Affecting Life Expectancy. In: 29th International Scientific Symposium;Metrology and Metrology Assurance, MMA 2019 - Proceedings; 2019. DOI: 10.1109/MMA.2019.8936019 - 2019 - в издания, индексирани в Scopus или Web of Science
5. Kulkarni VS, Chorage SS. Review: Soot (Particulate Matter) Sensor with an application to control pollution in diesel exhaust. Proceedings - 2019 5th International Conference on Computing, Communication Control and Automation, ICCUBEA 2019; DOI: 10.1109/ICCUBEA47591.2019.9129133 - 2019 - в издания, индексирани в Scopus или Web of Science
6. Lombardo L, Parvis M, Angelini E, Grassini S. An optical sampling system for distributed atmospheric particulate matter. IEEE Trans Instrum Meas. 2019; DOI: 10.1109/TIM.2019.2890885 - 2019 - в издания, индексирани в Scopus или Web of Science
7. Lombardo L, Parvis M, Vitiello F, Angelini E, Grassini S. A Sensor Network for Particulate Distribution Estimation. In: MeMeA 2018 - 2018 IEEE International Symposium on Medical Measurements and Applications, Proceedings; DOI: 10.1109/MeMeA.2018.8438701 - 2018 - в издания, индексирани в Scopus или Web of Science
8. Zou J, Wang M, Wei Y, Zhang H, Liu S. Separation method of particles based on electromagnetic coupling. Proc Inst Mech Eng Part C J Mech Eng Sci, 2022, DOI 10.1177/09544062211072461 - 2022 - в издания, индексирани в Scopus или Web of Science
9. Amoah, N. A., Xu, G., Wang, Y., Li, J., Zou, Y., & Nie, B. (2022). Application of low-cost particulate matter sensors for air quality monitoring and exposure assessment in underground mines: A review. International Journal of Minerals, Metallurgy and Materials, 29(8), 1475-1490. doi:10.1007/s12613-021-2378-z - 2022 - в издания, индексирани в Scopus или Web of Science

Вид: пленарен доклад в международен форум, публикация в реферирано издание, индексирана в Scopus