EVALUATION OF LOW-COST PM2.5 SENSOR ACCURACY IN COMPARISON WITH GOVERNMENT REFERENCE INSTRUMENT

putri ayu risti; Rizki Andre Handika; Fernando Mersa Putra

doi:10.22373/ljee.v7i1.10530

Authors

putri ayu risti universitas jambi
Rizki Andre Handika Environmental Engineering Study Program, Jambi University, Jambi, Indonesia
Fernando Mersa Putra Environmental Engineering Study Program, Jambi University, Jambi, Indonesia

DOI:

https://doi.org/10.22373/ljee.v7i1.10530

Keywords:

Air Quality, PM2.5, IoT, PMS5003, PMS7003, BMKG Sultan Thaha

Abstract

Air pollution in Jambi City, due to the increasing PM_2.5, often exceeds the national quality standards. This situation requires a uniform monitoring solution, since the number of government reference stations is limited. An IoT-based monitoring system using low-cost sensors can be an alternative, which are flexible and real-time monitoring. We developed an IoT-based monitoring system using two low-cost sensors (PMS5003 and PMS7003), which were collocated with and validated against the BAM-1020 reference instrument operated by the Meteorology, Climatology, and Geophysics Agency (BMKG) at the Sultan Thaha Jambi Climatology Station. This quantitative study aims to evaluate the accuracy of the two sensors against the reference instrument for the period December 2025 to January 2026. The analysis was carried out using the statistical parameters MBE, MAE, RMSE, the correlation coefficient (r), and the coefficient of determination (R²), followed by a linear regression-based correction of the sensor readings. The results showed that both sensors were able to follow the pattern of changes in PM_2.5 concentration quite well (R² = 0.60 for PMS5003 and 0.59 for PMS7003), although they tended to produce higher values (overestimate). The PMS7003 sensor showed slightly better accuracy with a lower error rate (MBE=10.46; MAE=12.53; RMSE=18.02 µg/m3) compared to the PMS5003 (MBE=11.84; MAE=13.60; RMSE=19.60 µg/m3). This overestimation is consistent with the influence of high relative humidity and the technical limitation of light-scattering sensors, which cannot distinguish solid particles from water droplets, as reported in previous studies. Overall, both sensors are reliable for real-time monitoring, but still require further calibration.

References

Alamsyah, M, Made Putra Darsana, Direstu Amalia, Yeti Komalasari, and M Rafli Fazal. 2024. “Faktor-Faktor Yang Mempengaruhi Monitoring Real-Time PM2,5 Dan Co2 Di Area Terminal Bandar Udara: Low-Cost Sensor, Internet of Things (IOT) Dan Pengukuran Polutan Udara.” Penelitian Politeknik Penerbangan Surabaya 9 (4): 320–42. https://doi.org/https://doi.org/10.46491/jp.v9i4.1853.

Badura, Marek, Piotr Batog, Anetta Drzeniecka-Osiadacz, and Piotr Modzel. 2018. “Evaluation of Low-Cost Sensors for Ambient PM2.5 Monitoring.” Journal of Sensors 2018:1–16. https://doi.org/https://doi.org/10.1155/2018/5096540.

Barkjohn, Karoline K., Brett Gantt, and Andrea L. Clements. 2021. “Development and Application of a United States-Wide Correction for PM 2.5 Data Collected with the PurpleAir Sensor.” Atmospheric Measurement Techniques 14 (6): 4617–37. https://doi.org/10.5194/amt-14-4617-2021.

Bulot, Florentin M. J., Steven J. Johnston, Philip J. Basford, Natasha H. C. Easton, Mihaela Apetroaie-Cristea, Gavin L. Foster, Andrew K. R. Morris, Simon J. Cox, and Matthew Loxham. 2019. “Long-Term Field Comparison of Multiple Low-Cost Particulate Matter Sensors in an Outdoor Urban Environment.” Scientific Reports 9 (1): 7497. https://doi.org/10.1038/s41598-019-43716-3.

Cowell, Nicole, Clarissa Baldo, Lee Chapman, William Bloss, and Jian Zhong. 2024. “What Can We Learn from Nested IoT Low-Cost Sensor Networks for Air Quality? A Case Study of PM2.5 in Birmingham, UK.” Meteorological Applications 31 (4): 1–21. https://doi.org/10.1002/met.2220.

Fajar, Benedy, Muhammad Damris, Kemas Rahmat Saleh Wiharja, Elma Mutmainnah, Noorlin Mohamad, and Rizki Andre Handika. 2026. “PM2.5 Temporal Pattern in Jambi City: Meteorological Drivers and Air Mass Trajectory Analysis.” Jurnal Presipitasi Media Komunikasi Dan Pengembangan Teknik Lingkungan 23 (2).

Fatkhurrahman, Januar Arif, Ikha Rasti Julia Sari, and Ningsih Ika Pratiwi. 2019. “Verifikasi Sensor Partikulat Sebagai Instrumentasi Pemantauan PM2.5 Dan PM10 Berbasis Low Cost Sensor.” Prosiding Sains dan Teknologi 25–30. https://doi.org/10.36499/psnst.v1i1.2815.

Handika, R. A., R. A. Lestari, and R. Saputra. 2019. “Comparing Contributors and PM10 Dispersion around Tugu Juang and in Governor Office Area of Jambi City, Indonesia.” IOP Conference Series: Earth and Environmental Science 391 (1). https://doi.org/10.1088/1755-1315/391/1/012050.

Kelly, K E, J Whitaker, A Petty, C Widmer, A Dybwad, D Sleeth, R Martin, and A Butterfield. 2017. “Ambient and Laboratory Evaluation of a Low-Cost Particulate Matter Sensor.” Environmental Pollution 221:491–500. https://doi.org/10.1016/j.envpol.2016.12.039.

Lekamge, Savinda Arambawatta, and Henry P. Oswin. 2025. “Exploration of a Practical Approach to Providing RH Corrections to Low Cost Sensor Networks.” Npj Climate and Atmospheric Science 8 (1): 227. https://doi.org/10.1038/s41612-025-01115-8.

Magi, Brian I., Calvin Cupini, Jeff Francis, Megan Green, and Cindy Hauser. 2020. “Evaluation of PM2.5 Measured in an Urban Setting Using a Low-Cost Optical Particle Counter and a Federal Equivalent Method Beta Attenuation Monitor.” Aerosol Science and Technology 54 (2): 147–59. https://doi.org/10.1080/02786826.2019.1619915.

Mathieu-Campbell, Martine E., Chuqi Guo, Andrew P. Grieshop, and Jennifer Richmond-Bryant. 2024. “Calibration of PurpleAir Low-Cost Particulate Matter Sensors: Model Development for Air Quality under High Relative Humidity Conditions.” Atmospheric Measurement Techniques 17 (22): 6735–49. https://doi.org/10.5194/amt-17-6735-2024.

Mutawaqil, M Iqbal. 2025. “Rancang Bangun Alat Monitoring Kualitas Udara PM2,5 Berbasis IOT Dan LORA Dengan Sistem Tapologi STAR.” Universitas Jambi.

Okaem, Tanti Tritama, Yohandri, Nofi Yendri Sudiar, and Hamdi. 2022. “Pengembangan Instrumen Pengukuran Kualitas Udara Menggunakan Sensor Pms7003.” Megasains 13 (01): 31–38. https://doi.org/10.46824/megasains.v13i01.103.

Rachmawati, Arum Vonie, Dzulkiflih, and Meta Yantidewi. 2024. “Analisis Kalibrasi Sensor BME280 Dengan Pendekatan Regresi Linear Pada Pengukuran Temperatur, Kelembaban Relatif, Dan Titik Embun.” Jurnal Kolaboratif Sains 7 (5): 1589–97. https://doi.org/10.56338/jks.v7i5.5272.

Sholahudin, Muchtar Ali Setyo Yudono, and Anang Suryana. 2024. “Perancangan Alat Pemantauan Berkelanjutan Kualitas Udara Dalam Ruangan Design of a Continuous Monitoring Tool for Indoor Air Quality.” Komputika : Jurnal Sistem Komputer 13 (2): 265–75. https://doi.org/10.34010/komputika.v13i2.13413.

Suhartawan, Bambang, and Fatma Sarie. 2024. Pengantar Teknik Lingkungan. Edited by Mohmahad Gita Indrawan. 1st ed. Sumatra Barat: Gita Lentera. https://books.google.co.id/books?hl=id&lr=&id=PMoSEQAAQBAJ&oi=fnd&pg=PA15&dq=Suhartawan,+B.,+%26+MT,+M.+2024.+KUALITAS+UDARA.+Pengantar+Teknik+Lingkungan&ots=OKe9At5HAt&sig=DBwWPF5gQyIVVuR4w47hKPRbt-8&redir_esc=y#v=onepage&q=Suhartawan%2C B.%2C %26 MT%2C.

Wanabil, Naufal, Aswin Rosadi, and Muhammad Amirul Haq. 2024. “Implementasi Monitoring Kualitas Udara Menggunakan Nodemcu Esp8266 Pada Indoor Berbasis Iot.” Prosiding Nasional Sinars 2024 Skema Penelitian 3 (1): 156–61.

https://www.unars.ac.id/ojs/index.php/prosidingSDGs/article/view/4807.

Zulhelman, and Dwi Arif Wisesa. 2021. “Prototype Sistem Pemantau Kualitas Udara Berbasis Raspberry Pi.” Spektral 2 (2): 58–63. https://doi.org/https://doi.org/10.32722/spektral.v2i2.4127.