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Assessing and monitoring air quality in cities and urban areas with a portable, modular and low-cost sensor station: calibration challenges
dc.contributor.author | Tarazona Alvarado, Miguel | |
dc.contributor.author | Salamanca-Coy, J. L. | |
dc.contributor.author | Forero-Gutièrrez, K. | |
dc.contributor.author | Núñez, L. A. | |
dc.contributor.author | Pisco-Guabave, J. | |
dc.contributor.author | Escobar-Diaz, Fr. | |
dc.contributor.author | Sierra Porta, David | |
dc.date.accessioned | 2024-08-05T16:41:14Z | |
dc.date.available | 2024-08-05T16:41:14Z | |
dc.date.issued | 2024-06-09 | |
dc.date.submitted | 2024-08-05 | |
dc.identifier.citation | Tarazona Alvarado, M., Salamanca-Coy, J. L., Forero-Gutièrrez, K., Núñez, L. A., Pisco-Guabave, J., Escobar-Diaz, Fr., & Sierra-Porta, D. (2024). Assessing and monitoring air quality in cities and urban areas with a portable, modular and low-cost sensor station: calibration challenges. International Journal of Remote Sensing, 45(17), 5713–5736. https://doi.org/10.1080/01431161.2024.2373338 | spa |
dc.identifier.uri | https://hdl.handle.net/20.500.12585/12703 | |
dc.description.abstract | Air pollution affects not only the air in cities but also extends to all indoor environments (homes, offices, schools, public places, transportation, etc.), where we spend between 80% and 90% of our time. Both indoor and outdoor air quality have emerged as significant health concerns and are integral to national strategies implemented by health and environmental institutes in each country. Recently, complaints regarding outdoor air quality have risen in cities, primarily due to automobile traffic and industrial activities in urban areas, and also indoors within homes, offices, and schools. The following paper presents a methodology for the calibration of low-cost monitoring stations based on measurements in a couple of cities in Colombia as part of the development of a project to reduce the environmental awareness gap in urban areas for the estimation of the air quality through low-cost, flexible, modular, and mobile air quality monitoring station design that could be used to assess air pollution in different indoor and outdoor environments. With the implementation of the low-cost stations, we have calibrated and evaluated the performance of the stations using usual linear regression methods, but we have also explored the use of unsupervised estimation with the help of machine learning algorithms, specifically with Random Forest estimators. We have found a significant improvement with using Random Forest for station calibration compared with those found using simple linear regressions for calibration effects. We have found that all the models offer a significant improvement in terms of RMSE. The regression model improves RMSE by up to 70%, while the multiple regression model does so by up to 73%. However, it is the Random Forest that shows the most remarkable improvement, with a reduction in RMSE of up to 86%. | spa |
dc.format.extent | 25 páginas | |
dc.format.mimetype | application/pdf | spa |
dc.language.iso | eng | spa |
dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
dc.source | International Journal of Remote Sensing Vol. 45, N° 17 (2024) | spa |
dc.title | Assessing and monitoring air quality in cities and urban areas with a portable, modular and low-cost sensor station: calibration challenges | spa |
dcterms.bibliographicCitation | Abdi, H., and L. J. Williams. 2010. “Principal Component Analysis.” Wiley Interdisciplinary Reviews: Computational Statistics 2 (4): 433–459. https://doi.org/10.1002/wics.101 . | spa |
dcterms.bibliographicCitation | Abu El-Magd, S., G. Soliman, M. Morsy, and S. Kharbish. 2023. “Environmental Hazard Assessment and Monitoring for Air Pollution Using Machine Learning and Remote Sensing.” International Journal of Environmental Science and Technology 20 (6): 6103–6116. https://doi.org/10.1007/ s13762-022-04367-6 . | spa |
dcterms.bibliographicCitation | Adong, P., E. Bainomugisha, D. Okure, R. Sserunjogi, and P. Nachev. 2022. “Generative Model-Enhanced Human Motion Prediction.” Applied AI Letters 3 (2): e76. https://doi.org/10. 1002/ail2.63 . | spa |
dcterms.bibliographicCitation | Afshar-Mohajer, N., and C.-Y. Wu. 2023. “Use of a Drone-Based Sensor As a Field-Ready Technique for Short-Term Concentration Mapping of Air Pollutants: A Modeling Study.” Atmospheric Environment 294:119476. https://doi.org/10.1016/j.atmosenv.2022.119476 . | spa |
dcterms.bibliographicCitation | Aleixandre, M., and M. Gerboles. 2012. “Review of Small Commercial Sensors for Indicative Monitoring of Ambient Gas.” Chemical Engineering Transactions 30 | spa |
dcterms.bibliographicCitation | Amir, F., H. Muhammad, N. A. Abdullah, S. Rizal, R. Thaib, and H. Umar. 2023. “Performance Analysis of Heat Recovery in Heat Pipe Heat Exchanger on Room Air Conditioning Systems.” AIMS Energy 11 (4): 612–627. https://doi.org/10.3934/energy.2023031 . | spa |
dcterms.bibliographicCitation | Anjomshoaa, A., F. Duarte, D. Rennings, T. J. Matarazzo, P. deSouza, and C. Ratti. 2018. “City Scanner: Building and Scheduling a Mobile Sensing Platform for Smart City Services.” IEEE Internet of Things Journal 5 (6): 4567–4579. https://doi.org/10.1109/JIOT.2018.2839058 | spa |
dcterms.bibliographicCitation | Annesi-Maesano, I., N. Baiz, S. Banerjee, P. Rudnai, S. G. Solenne Rive. 2013. “Indoor Air Quality and Sources in Schools and Related Health Effects.” Journal of Toxicology and Environmental Health Part B 16 (8): 491–550. https://doi.org/10.1080/10937404.2013.853609 . | spa |
dcterms.bibliographicCitation | Apte, J. S., K. P. Messier, S. Gani, M. Brauer, T. W. Kirchstetter, M. M. Lunden, J. D. Marshall, C. J. Portier, R. C. Vermeulen, and S. P. Hamburg. 2017. “High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data.” Environmental Science & Technology 51 (12): 6999–7008. https://doi.org/10.1021/acs.est.7b00891 | spa |
dcterms.bibliographicCitation | Badura, M., P. Batog, A. Drzeniecka-Osiadacz, P. Modzel. 2018. “Evaluation of Low-Cost Sensors for Ambient PM 2.5 Monitoring.” Journal of Sensors 2018:1–16. https://doi.org/10.1155/2018/ 5096540 . | spa |
dcterms.bibliographicCitation | Bagkis, E., T. Kassandros, M. Karteris, A. Karteris, and K. Karatzas. 2021. “Analyzing and Improving the Performance of a Particulate Matter Low Cost Air Quality Monitoring Device.” Atmosphere 12 (2): 251. https://doi.org/10.3390/atmos12020251 . | spa |
dcterms.bibliographicCitation | Bai, X., H. Tian, C. Zhu, L. Luo, Y. Hao, S. Liu, Z. Guo, et al. 2023. “Present Knowledge and Future Perspectives of Atmospheric Emission Inventories of Toxic Trace Elements: A Critical Review.” Environmental Science & Technology 57 (4): 1551–1567. https://doi.org/10.1021/acs.est.2c07147 | spa |
dcterms.bibliographicCitation | Baklanov, A., and Y. Zhang. 2020. “Advances in Air Quality Modeling and Forecasting.” Global Transitions 2:261–270. https://doi.org/10.1016/j.glt.2020.11.001 . | spa |
dcterms.bibliographicCitation | Baqer, N. S., H. Mohammed, A. S. Albahri. 2023. “Development of a Real-Time Monitoring and Detection Indoor Air Quality System for Intensive Care Unit and Emergency Department.” Signa Vitae 19 (1). 77–92 | spa |
dcterms.bibliographicCitation | Barros, N., P. Sobral, R. S. Moreira, J. Vargas, A. Fonseca, I. Abreu, and M. Simas Guerreiro. 2023. “SchoolAIR: A Citizen Science IoT Framework Using Low-Cost Sensing for Indoor Air Quality Management.” Sensors 24 (1): 148. https://doi.org/10.3390/s24010148 . | spa |
dcterms.bibliographicCitation | Baudet, A., E. Baurès, O. Blanchard, P. Le Cann, J.-P. Gangneux, and A. Florentin. 2022. “Indoor Carbon Dioxide, Fine Particulate Matter and Total Volatile Organic Compounds in Private Healthcare and Elderly Care Facilities.” Toxics 10 (3): 136. https://doi.org/10.3390/ toxics10030136 | spa |
dcterms.bibliographicCitation | Baurès, E., O. Blanchard, F. Mercier, E. Surget, P. Le Cann, A. Rivier, J.-P. Gangneux, and A. Florentin. 2018. “Indoor Air Quality in Two French Hospitals: Measurement of Chemical and Microbiological Contaminants.” Science of the Total Environment 642:168–179. https://doi.org/10.1016/j.scitotenv. 2018.06.047 . | spa |
dcterms.bibliographicCitation | Becerra, J. A., J. Lizana, M. Gil, A. Barrios-Padura, P. Blondeau, and R. Chacartegui. 2020. “Identification of Potential Indoor Air Pollutants in Schools.” Journal of Cleaner Production 242:118420. https://doi.org/10.1016/j.jclepro.2019.118420 | spa |
dcterms.bibliographicCitation | Blanco, M. N., A. Gassett, T. Gould, A. Doubleday, D. L. Slager, E. Austin, E. Seto, T. V. Larson, J. D. Marshall, and L. Sheppard. 2022. “Characterization of Annual Average Traffic-Related Air Pollution Concentrations in the Greater Seattle Area from a Year-Long Mobile Monitoring Campaign.” Environmental Science & Technology 56 (16): 11460–11472. https://doi.org/10.1021/ acs.est.2c01077 | spa |
dcterms.bibliographicCitation | Breiman, L. 2001. “Random Forests.” Machine Learning 45 (1): 5–32. https://doi.org/10.1023/ A:1010933404324 . | spa |
dcterms.bibliographicCitation | Bro, R., and A. K. Smilde. 2014. “Principal Component Analysis.” Analytical Methods 6 (9): 2812–2831. https://doi.org/10.1039/C3AY41907J . | spa |
dcterms.bibliographicCitation | Burgués, J., and S. Marco. 2023. “Drone-Based Monitoring of Environmental Gases.” In Air Quality Networks. Environmental Informatics and Modeling, edited by S. De Vito, K. Karatzas, A. Bartonova, G. Fattoruso, 115–137. Cham: Springer. https://doi.org/10.1007/978-3-031-08476-8_6 | spa |
dcterms.bibliographicCitation | Castell, N., F. R. Dauge, P. Schneider, M. Vogt, U. Lerner, B. Fishbain, D. Broday, and A. Bartonova. 2017. “Can Commercial Low-Cost Sensor Platforms Contribute to Air Quality Monitoring and Exposure Estimates?” Environment International 99:293–302. https://doi.org/10.1016/j.envint. 2016.12.007 | spa |
dcterms.bibliographicCitation | Concas, F., J. Mineraud, E. Lagerspetz, S. Varjonen, X. Liu, K. Puolamäki, P. Nurmi, and S. Tarkoma. 2021. “Low-Cost Outdoor Air Quality Monitoring and Sensor Calibration: A Survey and Critical Analysis.” ACM Transactions on Sensor Networks 17 (2): 1–44. https://doi.org/10.1145/3446005 . | spa |
dcterms.bibliographicCitation | Considine, E. M., D. Braun, L. Kamareddine, R. C. Nethery, and P. deSouza. 2023. “Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information.” Environmental Science & Technology 57 (3): 1391–1402. https://doi.org/10.1021/acs.est.2c06626 . | spa |
dcterms.bibliographicCitation | Cordero, J. M., R. Borge, and A. Narros. 2018. “Using Statistical Methods to Carry Out in Field Calibrations of Low Cost Air Quality Sensors.” Sensors and Actuators: B, Chemical 267:245–254. https://doi.org/10.1016/j.snb.2018.04.021 | spa |
dcterms.bibliographicCitation | Dai, X., W. Shang, J. Liu, M. Xue, and C. Wang. 2023. “Achieving Better Indoor Air Quality with IoT Systems for Future Buildings: Opportunities and Challenges.” Science of the Total Environment 895:164858. https://doi.org/10.1016/j.scitotenv.2023.164858 | spa |
dcterms.bibliographicCitation | de Gennaro, G., P. R. Dambruoso, A. Demarinis Loiotile, A. Di Gilio, P. Giungato, M. Tutino, A. Marzocca, A. Mazzone, J. Palmisani, and F. Porcelli. 2014. “Indoor Air Quality in Schools.” Environmental Chemistry Letters 12 (4): 467–482. https://doi.org/10.1007/s10311-014-0470-6 | spa |
dcterms.bibliographicCitation | De Vito, S., G. D. Francia, E. Esposito, S. Ferlito, F. Formisano, and E. Massera. 2020. “Adaptive Machine Learning Strategies for Network Calibration of IoT Smart Air Quality Monitoring Devices.” Pattern Recognition Letters 136:264–271. https://doi.org/10.1016/j.patrec.2020.04.032 | spa |
dcterms.bibliographicCitation | Donnelly, A., B. Misstear, and B. Broderick. 2015. “Real Time Air Quality Forecasting Using Integrated Parametric and Non-Parametric Regression Techniques.” Atmospheric Environment 103:53–65. https://doi.org/10.1016/j.atmosenv.2014.12.011 | spa |
dcterms.bibliographicCitation | Drajic, D. D., and N. R. Gligoric. 2020. “Reliable Low-Cost Air Quality Monitoring Using Off-The-Shelf Sensors and Statistical Calibration.” Elektronika Ir Elektrotechnika 26 (2): 32–41. https://doi.org/10. 5755/j01.eie.26.2.25734 | spa |
dcterms.bibliographicCitation | EPA, U.S. Environmental Protection Agency | US. 2023. Title 40 of the CFR (Code of Federal Regulations). U.S. Government Publishing Office. https://www.ecfr.gov/current/title-40 . | spa |
dcterms.bibliographicCitation | Esposito, E., S. De Vito, V. B. Maria Salvato, R. Lewis Jones, O. Popoola, and O. Popoola. 2016. “Dynamic Neural Network Architectures for on Field Stochastic Calibration of Indicative Low Cost Air Quality Sensing Systems.” Sensors and Actuators: B, Chemical 231:701–713. https://doi. org/10.1016/j.snb.2016.03.038 | spa |
dcterms.bibliographicCitation | Feenstra, B., V. Papapostolou, S. Hasheminassab, H. Zhang, B. Der Boghossian, D. Cocker, and A. Polidori. 2019. “Performance Evaluation of Twelve Low-Cost PM2. 5 Sensors at an Ambient Air Monitoring Site.” Atmospheric Environment 216:116946. https://doi.org/10.1016/j.atmosenv. 2019.116946 . | spa |
dcterms.bibliographicCitation | Flores-Cortez, O. O., R. Adalberto Cortez, and V. Idalia Rosa. 2019. “A Low-Cost IoT System for Environmental Pollution Monitoring in Developing Countries.” In 2019 MIXDES-26th International Conference“Mixed Design of Integrated Circuits and Systems”, Rzeszow, Poland, 386–389. IEEE. | spa |
dcterms.bibliographicCitation | Francesco, B., E. Brattich, C. Cintolesi, A. Ghafoor Nizamani, S. Di Sabatino, M. Milelli, E. E. Peerlings, S. Polder, G.-J. Steeneveld, and A. Parodi. 2024. “Performance Evaluation of MeteoTracker Mobile Sensor for Outdoor Applications.” Atmospheric Measurement Techniques 17 (10): 3255–3278. | spa |
dcterms.bibliographicCitation | Ganji, A., O. Youssefi, J. Xu, K. Mallinen, M. Lloyd, A. Wang, A. Bakhtari, S. Weichenthal, and M. Hatzopoulou. 2023. “Design, Calibration, and Testing of a Mobile Sensor System for Air Pollution and Built Environment Data Collection: The Urban Scanner Platform.” Environmental Pollution 317:120720. https://doi.org/10.1016/j.envpol.2022.120720 | spa |
dcterms.bibliographicCitation | Harleman, M., L. Harris, M. D. Willis, B. Ritz, P. Hystad, and E. L. Hill. 2023. “Changes in Traffic Congestion and Air Pollution Due to Major Roadway Infrastructure Improvements in Texas.” Science of the Total Environment 898:165463. https://doi.org/10.1016/j.scitotenv.2023.165463 . | spa |
dcterms.bibliographicCitation | Hernández-Gordillo, A., S. Ruiz-Correa, V. Robledo-Valero, C. Hernández-Rosales, and S. Arriaga. 2021. “Recent Advancements in Low-Cost Portable Sensors for Urban and Indoor Air Quality Monitoring.” Air Quality, Atmosphere & Health 14 (12): 1931–1951. https://doi.org/10.1007/ s11869-021-01067-x . | spa |
dcterms.bibliographicCitation | Hudda, N., L. W. Durant, S. A. Fruin, and J. L. Durant. 2020. “Impacts of Aviation Emissions on Near-Airport Residential Air Quality.” Environmental Science & Technology 54 (14): 8580–8588. https://doi.org/10.1021/acs.est.0c01859 . | spa |
dcterms.bibliographicCitation | Ilie, A. M. C., N. McCarthy, L. Velasquez, M. Moitra, and H. Michael Eisl. 2022. “Air Pollution Exposure Assessment at Schools and Playgrounds in Williamsburg Brooklyn NYC, with a View to Developing a Set of Policy Solutions.” Journal of Environmental Studies and Sciences 12 (4): 838–852. https://doi.org/10.1007/s13412-022-00777-7 . | spa |
dcterms.bibliographicCitation | Jovašević-Stojanović, M., A. Bartonova, D. Topalović, I. Lazović, B. Pokrić, and Z. Ristovski. 2015. “On the Use of Small and Cheaper Sensors and Devices for Indicative Citizen-Based Monitoring of Respirable Particulate Matter.” Environmental Pollution 206:696–704. https://doi.org/10.1016/j. envpol.2015.08.035 . Jung, C.-C., P.-C. Wu, C.- | spa |
dcterms.bibliographicCitation | Jung, C.-C., P.-C. Wu, C.-H. Tseng, and H.-J. Su. 2015. “Indoor Air Quality Varies with Ventilation Types and Working Areas in Hospitals.” Building & Environment 85:190–195. https://doi.org/10.1016/j. buildenv.2014.11.026 . | spa |
dcterms.bibliographicCitation | Karagulian, F., M. Barbiere, A. Kotsev, L. Spinelle, M. Gerboles, F. Lagler, N. Redon, S. Crunaire, and A. Borowiak. 2019. “Review of the Performance of Low-Cost Sensors for Air Quality Monitoring.” Atmosphere 10 (9): 506. https://doi.org/10.3390/atmos10090506 . | spa |
dcterms.bibliographicCitation | Kerckhoffs, J., J. Khan, G. Hoek, Z. Yuan, T. Ellermann, O. Hertel, M. Ketzel, S. Solvang Jensen, K. Meliefste, and R. Vermeulen. 2022. “Mixed-Effects Modeling Framework for Amsterdam and Copenhagen for Outdoor NO2 Concentrations Using Measurements Sampled with Google Street View Cars.” Environmental Science & Technology 56 (11): 7174–7184. https://doi.org/10.1021/acs. est.1c05806 | spa |
dcterms.bibliographicCitation | Kerckhoffs, J., J. Khan, G. Hoek, Z. Yuan, O. Hertel, M. Ketzel, S. Solvang Jensen, F. Al Hasan, K. Meliefste, and R. Vermeulen. 2022. “Hyperlocal Variation of Nitrogen Dioxide, Black Carbon, and Ultrafine Particles Measured with Google Street View Cars in Amsterdam and Copenhagen.” Environment international 170:107575. https://doi.org/10.1016/j.envint.2022.107575 | spa |
dcterms.bibliographicCitation | Kow, P.-Y., I.-W. Hsia, L.-C. Chang, and F.-J. Chang. 2022. “Real-Time Image-Based Air Quality Estimation by Deep Learning Neural Networks.” Journal of Environmental Management 307:114560. https://doi.org/10.1016/j.jenvman.2022.114560 | spa |
dcterms.bibliographicCitation | Lee, S. C., and M. Chang. 2000. “Indoor and Outdoor Air Quality Investigation at Schools in Hong Kong.” Chemosphere 41 (1–2): 109–113. https://doi.org/10.1016/S0045-6535(99)00396-3 . | spa |
dcterms.bibliographicCitation | Liu, H., G. Yan, Z. Duan, and C. Chen. 2021. “Intelligent Modeling Strategies for Forecasting Air Quality Time Series: A Review.” Applied Soft Computing 102:106957. https://doi.org/10.1016/j. asoc.2020.106957 . | spa |
dcterms.bibliographicCitation | Liu, X., R. Jayaratne, P. Thai, T. Kuhn, I. Zing, B. Christensen, R. Lamont, et al. 2020. “Low-Cost Sensors As an Alternative for Long-Term Air Quality Monitoring.” Environmental Research 185:109438. https://doi.org/10.1016/j.envres.2020.109438 . | spa |
dcterms.bibliographicCitation | Mamun, A., M. Abdulla, and M. Rasit Yuce. 2019. “Sensors and Systems for Wearable Environmental Monitoring Toward IoT-Enabled Applications: A Review.” IEEE Sensors Journal 19 (18): 7771–7788. https://doi.org/10.1109/JSEN.2019.2919352 | spa |
dcterms.bibliographicCitation | Manshur, T., C. Luiu, W. R. Avis, V. Bukachi, M. Gatari, J. Mulligan, J. Radcliffe, et al. 2023. “A Citizen Science Approach for Air Quality Monitoring in a Kenyan Informal Development.” City and Environment Interactions 19:100105. https://doi.org/10.1016/j.cacint.2023.100105 | spa |
dcterms.bibliographicCitation | Margaritis, D., C. Keramydas, I. Papachristos, D. Lambropoulou. 2021. “Calibration of Low-Cost Gas Sensors for Air Quality Monitoring.” Aerosol & Air Quality Research 21 (11): 210073. https://doi.org/ 10.4209/aaqr.210073 . | spa |
dcterms.bibliographicCitation | Marinov, M. B., I. Topalov, E. Gieva, and G. Nikolov. 2016. “Air Quality Monitoring in Urban Environments.” In 2016 39th International Spring Seminar on Electronics Technology (ISSE), Pilsen, Czech Republic, 443–448. IEEE. | spa |
dcterms.bibliographicCitation | Marjovi, A., A. Arfire, and A. Martinoli. 2017. “Extending Urban Air Quality Maps Beyond the Coverage of a Mobile Sensor Network: Data Sources, Methods, and Performance Evaluation.” In Proceedings of the International Conference on Embedded Wireless Systems and Networks, Uppsala, Sweden, February 20-22, 2017, 12–23. | spa |
dcterms.bibliographicCitation | Mata, T. M., A. A. Martins, C. S. Calheiros, F. Villanueva, N. P. Alonso-Cuevilla, M. Fonseca Gabriel, and G. Ventura Silva. 2022. “Indoor Air Quality: A Review of Cleaning Technologies.” Environments 9 (9): 118. https://doi.org/10.3390/environments9090118 | spa |
dcterms.bibliographicCitation | Mead, M. I., O. A. M. Popoola, G. B. Stewart, M. C. Peter Landshoff, M. Hayes, J. J. Baldovi, J. J. Baldovi, et al. 2013. “The Use of Electrochemical Sensors for Monitoring Urban Air Quality in Low-Cost, High-Density Networks.” Atmospheric Environment 70:186–203. https://doi.org/10.1016/j.atmo senv.2012.11.060 . | spa |
dcterms.bibliographicCitation | Ministry of Environment and Sustainable Development. 2017. “Resolution 2254 of 2017 from the Ministry of Environment and Sustainable Development.” https://www.ccacoalition.org/partners/ colombia | spa |
dcterms.bibliographicCitation | Morawska, L., P. K. Thai, X. Liu, A. Asumadu-Sakyi, G. Ayoko, A. Bartonova, A. Bedini, et al. 2018. “Applications of Low-Cost Sensing Technologies for Air Quality Monitoring and Exposure Assessment: How Far Have They Gone?” Environment international 116:286–299. https://doi. org/10.1016/j.envint.2018.04.018 . | spa |
dcterms.bibliographicCitation | Motlagh, N. H., E. Lagerspetz, P. Nurmi, X. Li, S. Varjonen, J. Mineraud, M. Siekkinen, et al. 2020. “Toward Massive Scale Air Quality Monitoring.” IEEE Communications Magazine 58 (2): 54–59. https://doi.org/10.1109/MCOM.001.1900515 | spa |
dcterms.bibliographicCitation | Nishitateno, S., P. J. Burke, and T. H. Arimura. 2024. “Road Traffic Flow and Air Pollution Concentrations: Evidence from Japan.” International Journal of Economic Policy Studies 1–29. https://doi.org/10.1007/s42495-024-00132-4 . | spa |
dcterms.bibliographicCitation | Piersanti, A., L. Vitali, G. Righini, G. Cremona, and L. Ciancarella. 2015. “Spatial Representativeness of Air Quality Monitoring Stations: A Grid Model Based Approach.” Atmospheric Pollution Research 6 (6): 953–960. https://doi.org/10.1016/j.apr.2015.04.005 . | spa |
dcterms.bibliographicCitation | Ranganathan, R. H., S. Balusamy, P. Partheeban, C. Mani, M. Sridhar, and V. Rajasekaran. 2023. “Air Quality Monitoring and Analysis for Sustainable Development of Solid Waste Dump Yards Using Smart Drones and Geospatial Technology.” Sustainability 15 (18): 13347. https://doi.org/10.3390/ su151813347. | spa |
dcterms.bibliographicCitation | Reis, J., D. Lopes, D. Graça, A. Patrcia Fernandes, A. Isabel Miranda, and M. Lopes. 2023. “Using Low-Cost Sensors to Assess Real-Time Comfort and Air Quality Patterns in Indoor Households.” Environmental Science and Pollution Research 30 (3): 7736–7751. https://doi.org/10.1007/s11356- 022-22771-w . | spa |
dcterms.bibliographicCitation | Renwick, J. D., L. J. Klein, and H. F. Hamann. 2016. “Drone-Based Reconstruction for 3D Geospatial Data Processing.” In 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), Reston, VA, USA, 729–734. IEEE. | spa |
dcterms.bibliographicCitation | Sahu, R., A. Nagal, K. Kumar Dixit, H. Unnibhavi, S. Mantravadi, S. Nair, Y. Simmhan, et al. 2021. “Robust Statistical Calibration and Characterization of Portable Low-Cost Air Quality Monitoring Sensors to Quantify Real-Time O3 and NO2 Concentrations in Diverse Environments.” Atmospheric Measurement Techniques 14 (1): 37–52. https://doi.org/10.5194/amt-14-37-2021 | spa |
dcterms.bibliographicCitation | Schneider, P., N. Castell, M. Vogt, F. R. Dauge, W. A. Lahoz, and A. Bartonova. 2017. “Mapping Urban Air Quality in Near Real-Time Using Observations from Low-Cost Sensors and Model Information.” Environment International 106:234–247. https://doi.org/10.1016/j.envint.2017.05.005 . | spa |
dcterms.bibliographicCitation | Shaibal, M., S. Luther, B. Halley, S. Casson, N. Lucas, K. Sue, and W. Ronald. 2015. “Comparison of Modeled Traffic Exposure Zones Using On–Road Air Pollution Measurements.” Atmospheric Pollution Research 6 (1): 82–87. https://doi.org/10.5094/APR.2015.010 . | spa |
dcterms.bibliographicCitation | Sher, F., D. Raore, J. Jaromr Klemeš, P. Muhammad Rafi-Ul Shan, M. Khzouz, K. Marintseva, and O. Razmkhah. 2021. “Unprecedented Impacts of Aviation Emissions on Global Environmental and Climate Change Scenario.” Current Pollution Reports 7 (4): 549–564. https://doi.org/10.1007/ s40726-021-00206-3 . | spa |
dcterms.bibliographicCitation | Singh, D., M. Dahiya, R. Kumar, and C. Nanda. 2021. “Sensors and Systems for Air Quality Assessment Monitoring and Management: A Review.” Journal of Environmental Management 289:112510. https://doi.org/10.1016/j.jenvman.2021.112510 | spa |
dcterms.bibliographicCitation | Smart, N. R., C. J. Horwell, T. S. Smart, and K. S. Galea. 2020. “Assessment of the Wearability of Facemasks Against Air Pollution in Primary School-Aged Children in London.” International Journal of Environmental Research and Public Health 17 (11): 3935. https://doi.org/10.3390/ ijerph17113935 | spa |
dcterms.bibliographicCitation | Sokhi, R. S., N. Moussiopoulos, A. Baklanov, J. Bartzis, I. Coll, S. Finardi, R. Friedrich, et al. 2021. “Advances in Air Quality Research–Current and Emerging Challenges.” Atmospheric Chemistry and Physics Discussions 22 (7): 1–133. | spa |
dcterms.bibliographicCitation | Sonawani, S., and K. Patil. 2024. “Air Quality Measurement, Prediction and Warning Using Transfer Learning Based IOT System for Ambient Assisted Living.” International Journal of Pervasive Computing and Communications 20 (1): 38–55. https://doi.org/10.1108/IJPCC-07-2022-0271 . | spa |
dcterms.bibliographicCitation | Spengler, J. D., and D. G. Wilson. 2003. “Air Quality in Aircraft.” Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 217 (4): 323–335. https:// doi.org/10.1243/095440803322611688 | spa |
dcterms.bibliographicCitation | Spinelle, L., M. Gerboles, M. Gabriella Villani, M. Aleixandre, and F. Bonavitacola. 2014. “Calibration of a Cluster of Low-Cost Sensors for the Measurement of Air Pollution in Ambient Air.” SENSORS, 2014 IEEE, Valencia, Spain, 21–24. IEEE. | spa |
dcterms.bibliographicCitation | Spinelle, L., M. Gerboles, M. Gabriella Villani, M. Aleixandre, and F. Bonavitacola. 2015. “Field Calibration of a Cluster of Low-Cost Available Sensors for Air Quality Monitoring. Part A: Ozone and Nitrogen Dioxide.” Sensors and Actuators: B, Chemical 215:249–257. https://doi.org/10.1016/j. snb.2015.03.031 . | spa |
dcterms.bibliographicCitation | Spinelle, L., M. Gerboles, M. Gabriella Villani, M. Aleixandre, and F. Bonavitacola. 2017. “Field Calibration of a Cluster of Low-Cost Commercially Available Sensors for Air Quality Monitoring. Part B: NO, CO and CO2.” Sensors and Actuators: B, Chemical 238:706–715. https://doi.org/10.1016/ j.snb.2016.07.036 | spa |
dcterms.bibliographicCitation | Tsymbal, A., M. Pechenizkiy, and P. Cunningham. 2006. “Dynamic Integration with Random Forests.” In Machine Learning: ECML 2006. ECML 2006. Lecture Notes in Computer Science, edited by J. Fürnkranz, T. Scheffer, and M. Spiliopoulou, Vol. 4212, 801–808. Berlin, Heidelberg: Springer. https://doi.org/10.1007/11871842_82 . | spa |
dcterms.bibliographicCitation | Van den Bossche, J., J. Peters, J. Verwaeren, D. Botteldooren, J. Theunis, and B. De Baets. 2015. “Mobile Monitoring for Mapping Spatial Variation in Urban Air Quality: Development and Validation of a Methodology Based on an Extensive Dataset.” Atmospheric Environment 105:148–161. https://doi.org/10.1016/j.atmosenv.2015.01.017 | spa |
dcterms.bibliographicCitation | Vitali, G., M. Arru, and E. Magnanini. 2023. “A Scalable Device for Undisturbed Measurement of Water and CO 2 Fluxes Through Natural Surfaces.” Sensors 23 (5): 2647. https://doi.org/10.3390/ s23052647 | spa |
dcterms.bibliographicCitation | Wargocki, P., J. Ali Porras-Salazar, S. Contreras-Espinoza, and W. Bahnfleth. 2020. “The Relationships Between Classroom Air Quality and children’s Performance in School.” Building & Environment 173:106749. https://doi.org/10.1016/j.buildenv.2020.106749 . | spa |
dcterms.bibliographicCitation | Waters, M. A., T. F. Bloom, B. Grajewski, and J. Deddens. 2002. “Measurements of Indoor Air Quality on Commercial Transport Aircraft.” In Proceedings of indoor air, OH, USA, 782–787 | spa |
dcterms.bibliographicCitation | Wivou, J., L. Udawatta, A. Alshehhi, E. Alzaabi, A. Albeloshi, and S. Alfalasi. 2016. “Air Quality Monitoring for Sustainable Systems via Drone Based Technology.” In 2016 IEEE International Conference on Information and Automation for Sustainability (ICIAfS), Galle, Sri Lanka, 1–5. IEEE. | spa |
dcterms.bibliographicCitation | Zhang, Y., M. Bocquet, V. Mallet, C. Seigneur, and A. Baklanov. 2012. “Real-Time Air Quality Forecasting, Part I: History, Techniques, and Current Status.” Atmospheric Environment 60:632–655. https://doi.org/10.1016/j.atmosenv.2012.06.031. | spa |
datacite.rights | http://purl.org/coar/access_right/c_abf2 | spa |
oaire.version | http://purl.org/coar/version/c_b1a7d7d4d402bcce | spa |
dc.type.driver | info:eu-repo/semantics/article | spa |
dc.type.hasversion | info:eu-repo/semantics/draft | spa |
dc.identifier.doi | 10.1080/01431161.2024.2373338 | |
dc.subject.keywords | Air quality | spa |
dc.subject.keywords | Low-cost sensor | spa |
dc.subject.keywords | Citizen science | spa |
dc.subject.keywords | Calibration models | spa |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
dc.rights.cc | CC0 1.0 Universal | * |
dc.identifier.instname | Universidad Tecnológica de Bolívar | spa |
dc.identifier.reponame | Repositorio Universidad Tecnológica de Bolívar | spa |
dc.publisher.place | Cartagena de Indias | spa |
dc.subject.armarc | LEMB | |
dc.type.spa | http://purl.org/coar/resource_type/c_6501 | spa |
dc.audience | Público general | spa |
oaire.resourcetype | http://purl.org/coar/resource_type/c_2df8fbb1 | spa |
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Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.