{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T22:19:13Z","timestamp":1776896353382,"version":"3.51.2"},"reference-count":39,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2020,6,27]],"date-time":"2020-06-27T00:00:00Z","timestamp":1593216000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"City of Seoul through Seoul Urban Data Science Laboratory","award":["0660-20170004"],"award-info":[{"award-number":["0660-20170004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Low-cost light scattering particulate matter (PM) sensors have been widely researched and deployed in order to overcome the limitations of low spatio-temporal resolution of government-operated beta attenuation monitor (BAM). However, the accuracy of low-cost sensors has been questioned, thus impeding their wide adoption in practice. To evaluate the accuracy of low-cost PM sensors in the field, a multi-sensor platform has been developed and co-located with BAM in Dongjak-gu, Seoul, Korea from 15 January 2019 to 4 September 2019. In this paper, a sample variation of low-cost sensors has been analyzed while using three commercial low-cost PM sensors. Influences on PM sensor by environmental conditions, such as humidity, temperature, and ambient light, have also been described. Based on this information, we developed a novel combined calibration algorithm, which selectively applies multiple calibration models and statistically reduces residuals, while using a prebuilt parameter lookup table where each cell records statistical parameters of each calibration model at current input parameters. As our proposed framework significantly improves the accuracy of the low-cost PM sensors (e.g., RMSE: 23.94 \u2192 4.70    \u03bc   g\/m      3     ) and increases the correlation (e.g., R     2    : 0.41 \u2192 0.89), this calibration model can be transferred to all sensor nodes through the sensor network.<\/jats:p>","DOI":"10.3390\/s20133617","type":"journal-article","created":{"date-parts":[[2020,6,29]],"date-time":"2020-06-29T11:17:17Z","timestamp":1593429437000},"page":"3617","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":49,"title":["Long-Term Evaluation and Calibration of Low-Cost Particulate Matter (PM) Sensor"],"prefix":"10.3390","volume":"20","author":[{"given":"Hoochang","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiseock","family":"Kang","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sungjung","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunseok","family":"Im","sequence":"additional","affiliation":[{"name":"Air Quality Analysis and Control Center, Seoul Metropolitan Research Institute of Public Health and Environment, 30, Janggunmaeul 3-gil, Gwacheon-si, Gyeonggi-do, Seoul 08826, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seungsung","family":"Yoo","sequence":"additional","affiliation":[{"name":"Air Quality Analysis and Control Center, Seoul Metropolitan Research Institute of Public Health and Environment, 30, Janggunmaeul 3-gil, Gwacheon-si, Gyeonggi-do, Seoul 08826, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2108-3960","authenticated-orcid":false,"given":"Dongjun","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.envres.2019.01.036","article-title":"Short-term PM 2.5 exposure and emergency hospital admissions for mental disease","volume":"171","author":"Lee","year":"2019","journal-title":"Environ. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"9592","DOI":"10.1073\/pnas.1803222115","article-title":"Global estimates of mortality associated with longterm exposure to outdoor fine particulate matter","volume":"115","author":"Burnett","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_3","unstructured":"World Health Organization (WHO) (2020, June 26). RHN Workshop on Environment and Health (Air Pollution and Active Mobility), Ljubljana, Slovenia, 30 November 2018; p. 39. Available online: https:\/\/www.euro.who.int\/en\/about-us\/networks\/regions-for-health-network-rhn\/activities\/network-updates\/rhn-workshop-on-environment-and-health-air-pollution-and-active-mobility-at-the-11th-european-public-health-conference."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/MCOM.001.1900515","article-title":"Toward Massive Scale Air Quality Monitoring","volume":"58","author":"Motlagh","year":"2020","journal-title":"IEEE Commun. Mag."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.envint.2018.04.018","article-title":"Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?","volume":"116","author":"Morawska","year":"2018","journal-title":"Environ. Int."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1016\/j.scitotenv.2017.06.266","article-title":"End-user perspective of low-cost sensors for outdoor air pollution monitoring","volume":"607\u2013608","author":"Rai","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Gao, Y., Dong, W., Guo, K., Liu, X., Chen, Y., Liu, X., Bu, J., and Chen, C. (2016, January 10\u201314). Mosaic: A low-cost mobile sensing system for urban air quality monitoring. Proceedings of the IEEE INFOCOM 2016\u2014The 35th Annual IEEE International Conference on Computer Communications, San Francisco, CA, USA.","DOI":"10.1109\/INFOCOM.2016.7524478"},{"key":"ref_8","unstructured":"(2019). BALZ MAAG. Air Quality Sensor Calibration and Its Peculiarities. [Ph.D. Thesis, ETH Zurich]."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3090084","article-title":"SCAN: Multi-Hop Calibration for Mobile Sensor Arrays","volume":"1","author":"Maag","year":"2017","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_10","unstructured":"(2019, December 18). Air Korea from Goverment. Available online: https:\/\/www.airkorea.or.kr\/eng\/currentAirQuality?pMENU_NO=68."},{"key":"ref_11","unstructured":"(2019, December 18). Every Air from SK Telecom. Available online: https:\/\/www.onestore.co.kr\/userpoc\/apps\/view?pid=0000745074."},{"key":"ref_12","unstructured":"(2019, December 18). Air map Korea from KT. Available online: https:\/\/iot.airmapkorea.kt.com\/info\/."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-019-43716-3","article-title":"Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment","volume":"9","author":"Bulot","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Mukherjee, A., Stanton, L.G., Graham, A.R., and Roberts, P.T. (2017). Assessing the utility of low-cost particulate matter sensors over a 12-week period in the Cuyama valley of California. Sensors, 17.","DOI":"10.3390\/s17081805"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Liu, H.Y., Schneider, P., Haugen, R., and Vogt, M. (2019). Performance assessment of a low-cost PM 2.5 sensor for a near four-month period in Oslo, Norway. Atmosphere, 10.","DOI":"10.3390\/atmos10020041"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Kim, S., Park, S., and Lee, J. (2019). Evaluation of performance of inexpensive laser based PM2.5 sensor monitors for typical indoor and outdoor hotspots of South Korea. Appl. Sci., 9.","DOI":"10.3390\/app9091947"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Mukherjee, A., Brown, S.G., Mccarthy, M.C., Pavlovic, N.R., Stanton, L.G., Snyder, J.L., Andrea, S.D., and Hafner, H.R. (2019). Measuring Spatial and Temporal PM2.5 Variations in Sacramento, California, Communities Using a Network of Low-Cost Sensors. Sensors, 19.","DOI":"10.3390\/s19214701"},{"key":"ref_18","unstructured":"(2020, January 03). Plantower Inc. Available online: http:\/\/www.plantower.com\/en\/list\/?118_1.html."},{"key":"ref_19","unstructured":"(2020, January 03). DFRobot Inc. Available online: https:\/\/www.dfrobot.com\/product-1272.html?search=sen0177&description=true."},{"key":"ref_20","unstructured":"(2020, January 03). Honeywell Inc. Available online: https:\/\/sensing.honeywell.com\/hpma115s0-xxx-particulate-matter-sensors."},{"key":"ref_21","unstructured":"Karagulian, F., Gerboles, M., Barbiere, M., Kotsev, A., Lagler, F., and Borowiak, A. (2019). Review of Sensors for air Quality Monitoring, Publications Office of the European Union."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"709","DOI":"10.5194\/amt-11-709-2018","article-title":"Evaluation of a low-cost optical particle counter (Alphasense OPC-N2) for ambient air monitoring","volume":"11","author":"Crilley","year":"2018","journal-title":"Atmos. Meas. Tech."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3191750","article-title":"Calibrating Low-Cost Sensors by a Two-Phase Learning Approach for Urban Air Quality Measurement","volume":"2","author":"Lin","year":"2018","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.snb.2018.04.021","article-title":"Using statistical methods to carry out in field calibrations of low cost air quality sensors","volume":"267","author":"Cordero","year":"2018","journal-title":"Sens. Actuators B"},{"key":"ref_25","first-page":"1","article-title":"Evaluation of PM2.5 measured in an urban setting using a low-cost optical particle counter and a Federal Equivalent Method Beta Attenuation Monitor","volume":"54","author":"Magi","year":"2019","journal-title":"Aerosol Sci. Technol."},{"key":"ref_26","unstructured":"(2020, January 03). Kimoto Inc. Available online: https:\/\/www.kimoto-electric.co.jp\/english\/product\/air\/700.html#lineup."},{"key":"ref_27","unstructured":"(2020, January 03). Matlab R2018b. Available online: https:\/\/www.mathworks.com\/."},{"key":"ref_28","unstructured":"(2020, January 03). Pandas. Available online: https:\/\/pandas.pydata.org\/."},{"key":"ref_29","unstructured":"(2020, January 03). Keras. Available online: https:\/\/keras.io\/."},{"key":"ref_30","unstructured":"(2020, January 03). Scikit-Learn. Available online: https:\/\/scikit-learn.org\/stable\/index.html."},{"key":"ref_31","unstructured":"(2020, January 03). Tensorflow. Available online: https:\/\/www.tensorflow.org\/."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4823","DOI":"10.5194\/amt-11-4823-2018","article-title":"Field evaluation of low-cost particulate matter sensors in high-and low-concentration environments","volume":"11","author":"Zheng","year":"2018","journal-title":"Atmos. Meas. Tech."},{"key":"ref_33","unstructured":"(2020, January 03). Metone Inc. Available online: https:\/\/metone.com\/products\/bam-1020."},{"key":"ref_34","unstructured":"(2020, January 03). US EPA, Available online: https:\/\/www.epa.gov\/."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1316","DOI":"10.1021\/acs.jcim.5b00206","article-title":"Beware of R2: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models","volume":"55","author":"Alexander","year":"2015","journal-title":"J. Chem. Inf. Model."},{"key":"ref_36","unstructured":"(2020, January 03). Purple Air Inc. Available online: https:\/\/www2.purpleair.com\/products\/purpleair-pa-ii."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1080\/00031305.1973.10478966","article-title":"Graphs in Statistical Analysis","volume":"27","author":"Anscombe","year":"1973","journal-title":"Am. Stat."},{"key":"ref_38","unstructured":"(2020, June 26). Anscombe\u2019s Quartet. Available online: https:\/\/en.wikipedia.org\/wiki\/Anscombe%27s_quartet."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Nordhausen, K. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition by Trevor Hastie, Robert Tibshirani, Jerome Friedman, Springer.","DOI":"10.1111\/j.1751-5823.2009.00095_18.x"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/13\/3617\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:43:38Z","timestamp":1760175818000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/13\/3617"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,27]]},"references-count":39,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2020,7]]}},"alternative-id":["s20133617"],"URL":"https:\/\/doi.org\/10.3390\/s20133617","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,27]]}}}