{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T06:59:06Z","timestamp":1775026746290,"version":"3.50.1"},"reference-count":53,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2018,8,28]],"date-time":"2018-08-28T00:00:00Z","timestamp":1535414400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A low-cost air quality station has been developed for real-time monitoring of main atmospheric pollutants. Sensors for CO, CO2, NO2, O3, VOC, PM2.5 and PM10 were integrated on an Arduino Shield compatible board. As concerns PM2.5 and PM10 sensors, the station underwent a laboratory calibration and later a field validation. Laboratory calibration has been carried out at the headquarters of CNR-IBIMET in Florence (Italy) against a TSI DustTrak reference instrument. A MATLAB procedure, implementing advanced mathematical techniques to detect possible complex non-linear relationships between sensor signals and reference data, has been developed and implemented to accomplish the laboratory calibration. Field validation has been performed across a full \u201cheating season\u201d (1 November 2016 to 15 April 2017) by co-locating the station at a road site in Florence where an official fixed air quality station was in operation. Both calibration and validation processes returned fine scores, in most cases better than those achieved for similar systems in the literature. During field validation, in particular, for PM2.5 and PM10 mean biases of 0.036 and 0.598 \u00b5g\/m3, RMSE of 4.056 and 6.084 \u00b5g\/m3, and R2 of 0.909 and 0.957 were achieved, respectively. Robustness of the developed station, seamless deployed through a five and a half month outdoor campaign without registering sensor failures or drifts, is a further key point.<\/jats:p>","DOI":"10.3390\/s18092843","type":"journal-article","created":{"date-parts":[[2018,8,28]],"date-time":"2018-08-28T12:19:06Z","timestamp":1535458746000},"page":"2843","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":108,"title":["Development of Low-Cost Air Quality Stations for Next Generation Monitoring Networks: Calibration and Validation of PM2.5 and PM10 Sensors"],"prefix":"10.3390","volume":"18","author":[{"given":"Alice","family":"Cavaliere","sequence":"first","affiliation":[{"name":"Department of Information Engineering (DINFO), University of Firenze, Via di Santa Marta 3, 50139 Firenze, Italy"}]},{"given":"Federico","family":"Carotenuto","sequence":"additional","affiliation":[{"name":"National Research Council-Institute of Biometeorology (CNR-IBIMET), Via Caproni 8, 50145 Firenze, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0065-1113","authenticated-orcid":false,"given":"Filippo","family":"Di Gennaro","sequence":"additional","affiliation":[{"name":"National Research Council-Institute of Biometeorology (CNR-IBIMET), Via Caproni 8, 50145 Firenze, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7631-2623","authenticated-orcid":false,"given":"Beniamino","family":"Gioli","sequence":"additional","affiliation":[{"name":"National Research Council-Institute of Biometeorology (CNR-IBIMET), Via Caproni 8, 50145 Firenze, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5293-2315","authenticated-orcid":false,"given":"Giovanni","family":"Gualtieri","sequence":"additional","affiliation":[{"name":"National Research Council-Institute of Biometeorology (CNR-IBIMET), Via Caproni 8, 50145 Firenze, Italy"}]},{"given":"Francesca","family":"Martelli","sequence":"additional","affiliation":[{"name":"National Research Council-Institute of Biometeorology (CNR-IBIMET), Via Caproni 8, 50145 Firenze, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8244-2985","authenticated-orcid":false,"given":"Alessandro","family":"Matese","sequence":"additional","affiliation":[{"name":"National Research Council-Institute of Biometeorology (CNR-IBIMET), Via Caproni 8, 50145 Firenze, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9184-0707","authenticated-orcid":false,"given":"Piero","family":"Toscano","sequence":"additional","affiliation":[{"name":"National Research Council-Institute of Biometeorology (CNR-IBIMET), Via Caproni 8, 50145 Firenze, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7318-067X","authenticated-orcid":false,"given":"Carolina","family":"Vagnoli","sequence":"additional","affiliation":[{"name":"National Research Council-Institute of Biometeorology (CNR-IBIMET), Via Caproni 8, 50145 Firenze, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1700-5647","authenticated-orcid":false,"given":"Alessandro","family":"Zaldei","sequence":"additional","affiliation":[{"name":"National Research Council-Institute of Biometeorology (CNR-IBIMET), Via Caproni 8, 50145 Firenze, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Velasco, A., Ferrero, R., Gandino, F., Montrucchio, B., and Rebaudengo, M. (2016). A mobile and low-cost system for environmental monitoring: A case study. Sensors, 16.","DOI":"10.3390\/s16050710"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1056\/NEJMsa0805646","article-title":"Fine particulate air pollution and life expectancy in the United States","volume":"360","author":"Pope","year":"2009","journal-title":"N. Engl. J. Med."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1007\/s11869-012-0185-4","article-title":"PM2.5 and ozone health impacts and disparities in New York City: Sensitivity to spatial and temporal resolution","volume":"6","author":"Kheirbek","year":"2013","journal-title":"Air Qual. Atmos. Health"},{"key":"ref_4","unstructured":"(2018, July 10). Ambient (Outdoor) Air Quality and Health. Available online: http:\/\/www.who.int\/news-room\/fact-sheets\/detail\/ambient-(outdoor)-air-quality-and-health."},{"key":"ref_5","unstructured":"(2018, July 10). Directive 2008\/50\/EC of the European Parliament and of the Council of 21 May 2008 on Ambient Air Quality and Cleaner Air for Europe. Available online: https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=CELEX:32008L0050."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.envint.2014.11.019","article-title":"The rise of low-cost sensing for managing air pollution in cities","volume":"75","author":"Kumar","year":"2015","journal-title":"Environ. Int."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.1109\/JPROC.2003.814918","article-title":"Sensor networks: Evolution, opportunities, and challenges","volume":"91","author":"Chong","year":"2003","journal-title":"Proc. IEEE"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.atmosenv.2012.11.060","article-title":"The use of electrochemical sensors for monitoring urban air quality in low-cost, high-density networks","volume":"70","author":"Mead","year":"2013","journal-title":"Atmos. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/j.snb.2005.02.008","article-title":"Gas sensor network for air-pollution monitoring","volume":"110","author":"Tsujita","year":"2005","journal-title":"Sens. Actuators B Chem."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.snb.2006.04.058","article-title":"Calibration of a multivariate gas sensing device for atmospheric pollution measurement","volume":"118","author":"Kamionka","year":"2006","journal-title":"Sens. Actuators B Chem."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Clements, A.L., Griswold, W.G., Johnston, J.E., Herting, M.M., Thorson, J., Collier-Oxandale, A., and Hannigan, M. (2017). Low-cost air quality monitoring tools: From research to practice (A Workshop Summary). Sensors, 17.","DOI":"10.3390\/s17112478"},{"key":"ref_12","unstructured":"(2018, August 07). Measuring Air Pollution with Low-Cost Sensors. Available online: https:\/\/ec.europa.eu\/jrc\/en\/publication\/brochures-leaflets\/measuring-air-pollution-low-cost-sensors."},{"key":"ref_13","unstructured":"(2018, August 07). Evaluation of Low-Cost Sensors for Air Pollution Monitoring: Effect of Gaseous Interfering Compounds and Meteorological Conditions. Available online: https:\/\/ec.europa.eu\/jrc\/en\/publication\/evaluation-low-cost-sensors-air-pollution-monitoring-effect-gaseous-interfering-compounds-and."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"706","DOI":"10.1016\/j.snb.2016.07.036","article-title":"Field calibration of a cluster of low-cost commercially available sensors for air quality monitoring. Part B: NO, CO and CO2","volume":"238","author":"Spinelle","year":"2017","journal-title":"Sens. Actuators B Chem."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3325","DOI":"10.5194\/amt-7-3325-2014","article-title":"The next generation of low-cost personal air quality sensors for quantitative exposure monitoring","volume":"7","author":"Piedrahita","year":"2014","journal-title":"Atmos. Meas. Tech."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Sun, L., Wong, K.C., Wei, P., Ye, S., Huang, H., Yang, F., Westerdahl, D., Louie, P.K.K., Luk, C.W.Y., and Ning, Z. (2016). Development and application of a next generation air sensor network for the Hong Kong marathon 2015 air quality monitoring. Sensors, 16.","DOI":"10.3390\/s16020211"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.snb.2015.03.031","article-title":"Field calibration of a cluster of low-cost available sensors for air quality monitoring. Part A: Ozone and nitrogen dioxide","volume":"215","author":"Spinelle","year":"2015","journal-title":"Sens. Actuators B Chem."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Gualtieri, G., Camilli, F., Cavaliere, A., De Filippis, T., Di Gennaro, F., Di Lonardo, S., Dini, F., Gioli, B., Matese, A., and Nunziati, W. (2017, January 4\u20136). An integrated low-cost road traffic and air pollution monitoring platform to assess vehicles\u2019 air quality impact in urban areas. Proceedings of the 20th EURO Working Group on Transportation Meeting, Budapest, Hungary.","DOI":"10.1016\/j.trpro.2017.12.043"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Cheadle, L., Deanes, L., Sadighi, K., Gordon Casey, J., Collier-Oxandale, A., and Hannigan, M. (2017). Quantifying neighborhood-scale spatial variations of ozone at open space and urban sites in Boulder, Colorado using low-cost sensor technology. Sensors, 17.","DOI":"10.3390\/s17092072"},{"key":"ref_20","unstructured":"Williams, R., Kilaru, V.J., Snyder, E.G., Kaufman, A., Dye, T., Rutter, A., Russell, A., and Hafner, H. (2014). Air Sensor Guidebook."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Spinelle, L., Gerboles, M., Kok, G., Persijn, S., and Sauerwald, T. (2017). Review of portable and low-cost sensors for the ambient air monitoring of benzene and other volatile organic compounds. Sensors, 17.","DOI":"10.3390\/s17071520"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Ng, C.L., Kai, F.M., Tee, M.H., Tan, N., and Hemond, H.F. (2018). A prototype sensor for in situ sensing of fine particulate matter and volatile organic compounds. Sensors, 18.","DOI":"10.3390\/s18010265"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1121","DOI":"10.5194\/amt-7-1121-2014","article-title":"Field calibrations of a low-cost aerosol sensor at a regulatory monitoring site in California","volume":"7","author":"Holstius","year":"2014","journal-title":"Atmos. Meas. Tech."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Shao, W., Zhang, H., and Zhou, H. (2017). Fine particle sensor based on multi-angle light scattering and data fusion. Sensors, 17.","DOI":"10.3390\/s17051033"},{"key":"ref_25","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_26","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.jaerosci.2016.11.010","article-title":"Evaluation of new low-cost particle monitors for PM2.5 concentrations measurements","volume":"105","author":"Zikova","year":"2017","journal-title":"J. Aerosol Sci."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zikova, N., Masiol, M., Chalupa, D.C., Rich, D.Q., Ferro, A.R., and Hopke, P.K. (2017). Estimating hourly concentrations of PM2.5 across a metropolitan area using low-cost particle monitors. Sensors, 17.","DOI":"10.3390\/s17081922"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Caubel, J.J., Cados, T.E., and Kirchstetter, T.W. (2018). A new black carbon sensor for dense air quality monitoring networks. Sensors, 18.","DOI":"10.3390\/s18030738"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"11369","DOI":"10.1021\/es4022602","article-title":"The changing paradigm of air pollution monitoring","volume":"47","author":"Snyder","year":"2013","journal-title":"Environ. Sci. Technol."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Khedo, K.K., Perseedoss, R., and Mungur, A. (2010). A wireless sensor network air pollution monitoring system. Int. J. Wirel. Mob. Netw., 2.","DOI":"10.5121\/ijwmn.2010.2203"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1016\/j.trpro.2017.06.002","article-title":"An integrated low-cost road traffic and air pollution monitoring platform for next citizen observatories","volume":"24","author":"Zaldei","year":"2017","journal-title":"Transp. Res. Procedia"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Rossi, M., and Tosato, P. (2017, January 24\u201325). Energy Neutral Design of an IoT System for Pollution Monitoring. Proceedings of the 2017 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS), Milan, Italy.","DOI":"10.1109\/EESMS.2017.8052691"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.1016\/j.mejo.2014.08.006","article-title":"Enhancing lifetime of WSN for natural gas leakages detection","volume":"45","author":"Brunelli","year":"2014","journal-title":"Microelectron. J."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Rossi, M., and Brunelli, D. (2012, January 28). Ultra low power wireless gas sensor network for environmental monitoring applications. Proceedings of the 2012 IEEE Workshop on Environmental Energy and Structural Monitoring Systems (EESMS), Perugia, Italy.","DOI":"10.1109\/EESMS.2012.6348397"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Rossi, M., Brunelli, D., Adami, A., Lorenzelli, L., Menna, F., and Remondino, F. (2014, January 2\u20135). Gas-drone: Portable gas sensing system on UAVs for gas leakage localization. Proceedings of the 2014 IEEE SENSORS, Valencia, Spain.","DOI":"10.1109\/ICSENS.2014.6985282"},{"key":"ref_36","unstructured":"Chambers, J.M. (1983). Graphical Methods for Data Analysis, Duxbury Press."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1080\/00401706.1977.10489493","article-title":"Detection of influential observation in linear regression","volume":"19","author":"Cook","year":"1977","journal-title":"Technometrics"},{"key":"ref_38","unstructured":"Fox, J., and Weisberg, S. (2018, July 10). Robust Regression. Available online: http:\/\/users.stat.umn.edu\/~sandy\/courses\/8053\/handouts\/robust.pdf."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1198\/000313002753631330","article-title":"The calculus of M-estimation","volume":"56","author":"Stefanski","year":"2002","journal-title":"Am. Statist."},{"key":"ref_40","unstructured":"Kutner, M.H., Nachtsheim, C., and Neter, J. (2004). Applied Linear Regression Models, McGraw-Hill\/Irwin."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1080\/03610929708831988","article-title":"Robust regression: A weighted least squares approach","volume":"26","author":"Chatterjee","year":"1997","journal-title":"Commun. Stat. Theory Methods"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1080\/03610927708827533","article-title":"Robust regression using iteratively reweighted least-squares","volume":"6","author":"Holland","year":"1977","journal-title":"Commun. Stat. Theory Methods"},{"key":"ref_43","first-page":"1","article-title":"A brief description of the Levenberg-Marquardt algorithm implemented by levmar","volume":"4","author":"Lourakis","year":"2005","journal-title":"Found. Res. Technol."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Draper, N.R., and Smith, H. (1998). Applied Regression Analysis, John Wiley. [3rd ed.].","DOI":"10.1002\/9781118625590"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Spiess, A.N., and Neumeyer, N. (2010). An evaluation of R 2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: A Monte Carlo approach. BMC Pharmacol., 10.","DOI":"10.1186\/1471-2210-10-6"},{"key":"ref_46","unstructured":"Fox, J. (2008). Applied Regression Analysis and Generalized Linear Models, Sage Publications, Inc."},{"key":"ref_47","unstructured":"Annual Report on Air Quality in the Tuscany Region\u2014Year 2016 (2018, July 10). Technical Report; Tuscany Region Environmental Protection Agency (ARPAT). (In Italian)."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"5281","DOI":"10.5194\/amt-9-5281-2016","article-title":"Community Air Sensor Network (CAIRSENSE) project: Evaluation of low-cost sensor performance in a suburban environment in the southeastern United States","volume":"9","author":"Jiao","year":"2016","journal-title":"Atmos. Meas. Tech."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3575","DOI":"10.5194\/amt-10-3575-2017","article-title":"Use of electrochemical sensors for measurement of air pollution: Correcting interference response and validating measurements","volume":"10","author":"Cross","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1016\/j.snb.2016.03.038","article-title":"Dynamic neural network architectures for on field stochastic calibration of indicative low cost air quality sensing systems","volume":"231","author":"Esposito","year":"2016","journal-title":"Sens. Actuators B Chem."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.atmosenv.2016.09.050","article-title":"Assessment of air quality microsensors versus reference methods: The EuNetAir joint exercise","volume":"147","author":"Borrego","year":"2016","journal-title":"Atmos. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1214\/14-EJS897","article-title":"Monitoring robust regression","volume":"8","author":"Riani","year":"2014","journal-title":"Electron. J. Stat."},{"key":"ref_53","unstructured":"Rousseeuw, P.J., Perrotta, D., Riani, M., and Hubert, M. (arXiv, 2017). Robust monitoring of many time series with application to fraud detection, arXiv."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/9\/2843\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:21:40Z","timestamp":1760196100000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/9\/2843"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,28]]},"references-count":53,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2018,9]]}},"alternative-id":["s18092843"],"URL":"https:\/\/doi.org\/10.3390\/s18092843","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,8,28]]}}}