Harmonization and Visualization of Data from a Transnational Multi-Sensor Personal Exposure Campaign
Jazyk angličtina Země Švýcarsko Médium electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
34770131
PubMed Central
PMC8583633
DOI
10.3390/ijerph182111614
PII: ijerph182111614
Knihovny.cz E-zdroje
- Klíčová slova
- air quality, data fusion, data treatment, data visualization, exposure assessment, multi-sensor, participant reports,
- MeSH
- lidé MeSH
- ukládání a vyhledávání informací MeSH
- velkoměsta MeSH
- znečištění ovzduší * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- velkoměsta MeSH
Use of a multi-sensor approach can provide citizens with holistic insights into the air quality of their immediate surroundings and their personal exposure to urban stressors. Our work, as part of the ICARUS H2020 project, which included over 600 participants from seven European cities, discusses the data fusion and harmonization of a diverse set of multi-sensor data streams to provide a comprehensive and understandable report for participants. Harmonizing the data streams identified issues with the sensor devices and protocols, such as non-uniform timestamps, data gaps, difficult data retrieval from commercial devices, and coarse activity data logging. Our process of data fusion and harmonization allowed us to automate visualizations and reports, and consequently provide each participant with a detailed individualized report. Results showed that a key solution was to streamline the code and speed up the process, which necessitated certain compromises in visualizing the data. A thought-out process of data fusion and harmonization of a diverse set of multi-sensor data streams considerably improved the quality and quantity of distilled data that a research participant received. Though automation considerably accelerated the production of the reports, manual and structured double checks are strongly recommended.
Department of Environmental Sciences Jožef Stefan Institute 1000 Ljubljana Slovenia
Eucentre Foundation Via A Ferrata 1 27100 Pavia Italy
Jožef Stefan International Postgraduate School 1000 Ljubljana Slovenia
LCE CNRS Aix Marseille University 13003 Marseille France
RECETOX Faculty of Science Masaryk University 62500 Brno Czech Republic
Zobrazit více v PubMed
Wellenius G.A., Schwartz J., Mittleman M.A. Health and the environment: Addressing the health impact of air pollution: Draft resolution proposed by the delegations of Albania, Chile, Colombia, France, Germany, Monaco, Norway, Panama, Sweden, Switzerland, Ukraine, United States of America, Uruguay and Zambia. Sixty-Eighth World Health Assembly. 2015;14:68.
Payne-Sturges D.C., Marty M.A., Perera F., Miller M.D., Swanson M., Ellickson K., Cory-Slechta D.A., Ritz B., Balmes J., Anderko L., et al. Healthy Air, Healthy Brains: Advancing Air Pollution Policy to Protect Children’s Health. Am. J. Public Health. 2019;109:550–554. doi: 10.2105/AJPH.2018.304902. PubMed DOI PMC
Sicard P., Agathokleous E., De Marco A., Paoletti E., Calatayud V. Urban population exposure to air pollution in Europe over the last decades. Environ. Sci. Eur. 2021;33:28. doi: 10.1186/s12302-020-00450-2. PubMed DOI PMC
Jerrett M., Donaire-Gonzalez D., Popoola O., Jones R., Cohen R.C., Almanza E., de Nazelle A., Mead I., Carrasco-Turigas G., Cole-Hunter T., et al. Validating novel air pollution sensors to improve exposure estimates for epidemiological analyses and citizen science. Environ. Res. 2017;158:286–294. doi: 10.1016/j.envres.2017.04.023. PubMed DOI
Hubbell B.J., Kaufman A., Rivers L., Schulte K., Hagler G., Clougherty J., Cascio W., Costa D. Understanding Social and Behavioral Drivers and Impacts of Air Quality Sensor Use. Sci. Total Environ. 2018;621:886–894. doi: 10.1016/j.scitotenv.2017.11.275. PubMed DOI PMC
Miskell G., Salmond J., Williams D.E. Low-cost sensors and crowd-sourced data: Observations of siting impacts on a network of air-quality instruments. Sci. Total Environ. 2017;575:1119–1129. doi: 10.1016/j.scitotenv.2016.09.177. PubMed DOI
Morawska L., Thai P.K., Liu X., Asumadu-Sakyi A., Ayoko G., Bartonova A., Bedini A., Chai F., Christensen B., Dunbabin M., et al. Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone? Environ. Int. 2018;116:286–299. doi: 10.1016/j.envint.2018.04.018. PubMed DOI PMC
Rai A.C., Kumar P., Pilla F., Skouloudis A.N., Di Sabatino S., Ratti C., Yasar A., Rickerby D. End-user perspective of low-cost sensors for outdoor air pollution monitoring. Sci. Total Environ. 2017;607–608:691–705. doi: 10.1016/j.scitotenv.2017.06.266. PubMed DOI
Robinson J.A., Kocman D., Horvat M., Bartonova A. End-User Feedback on a Low-Cost Portable Air Quality Sensor System—Are We There Yet? Sensors. 2018;18:3768. doi: 10.3390/s18113768. PubMed DOI PMC
Goal 11. Make Cities and Human Settlements Inclusive, Safe, Resilient and Sustainable–Indicators and a Monitoring Framework. [(accessed on 2 March 2021)]. Available online: https://indicators.report/goals/goal-11/
Mean Urban Air Pollution of Particulate Matter (PM10 and PM2.5)–Indicators and a Monitoring Framework. [(accessed on 2 March 2021)]. Available online: https://indicators.report/indicators/i-69/
Jarvis D.J., Adamkiewicz G., Heroux M.-E., Rapp R., Kelly F.J. Nitrogen Dioxide. World Health Organization; Geneva, Switzerland: 2010.
Nuvolone D., Petri D., Voller F. The effects of ozone on human health. Environ. Sci. Pollut. Res. 2018;25:8074–8088. doi: 10.1007/s11356-017-9239-3. PubMed DOI
Shuai J., Kim S., Ryu H., Park J., Lee C.K., Kim G.-B., Ultra V.U., Yang W. Health risk assessment of volatile organic compounds exposure near Daegu dyeing industrial complex in South Korea. BMC Public Health. 2018;18:528. doi: 10.1186/s12889-018-5454-1. PubMed DOI PMC
Casset A., de Blay F. Health effects of domestic volatile organic compounds. Rev. Mal. Respir. 2008;25:475–485. doi: 10.1016/S0761-8425(08)71587-0. PubMed DOI
Jacobson T.A., Kler J.S., Hernke M.T., Braun R.K., Meyer K.C., Funk W.E. Direct human health risks of increased atmospheric carbon dioxide. Nat. Sustain. 2019;2:691–701. doi: 10.1038/s41893-019-0323-1. DOI
Castanedo F. A Review of Data Fusion Techniques. Sci. World J. 2013;2013:e704504. doi: 10.1155/2013/704504. PubMed DOI PMC
Okafor N.U., Alghorani Y., Delaney D.T. Improving Data Quality of Low-cost IoT Sensors in Environmental Monitoring Networks Using Data Fusion and Machine Learning Approach. ICT Express. 2020;6:220–228. doi: 10.1016/j.icte.2020.06.004. DOI
Schneider P., Castell N., Vogt M., Dauge F.R., Lahoz W.A., Bartonova A. Mapping urban air quality in near real-time using observations from low-cost sensors and model information. Environ. Int. 2017;106:234–247. doi: 10.1016/j.envint.2017.05.005. PubMed DOI
Gressent A., Malherbe L., Colette A., Rollin H., Scimia R. Data fusion for air quality mapping using low-cost sensor observations: Feasibility and added-value. Environ. Int. 2020;143:105965. doi: 10.1016/j.envint.2020.105965. PubMed DOI
Senthilkumar N., Gilfether M., Metcalf F., Russell A.G., Mulholland J.A., Chang H.H. Application of a Fusion Method for Gas and Particle Air Pollutants between Observational Data and Chemical Transport Model Simulations Over the Contiguous United States for 2005–2014. Int. J. Environ. Res. Public Health. 2019;16:3314. doi: 10.3390/ijerph16183314. PubMed DOI PMC
Clements A.L., Griswold W.G., Rs A., Johnston J.E., Herting M.M., Thorson J., Collier-Oxandale A., Hannigan M. Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary) Sensors. 2017;17:2478. doi: 10.3390/s17112478. PubMed DOI PMC
Lewis A.C., von Schneidermesser E., Peltier R.E. Low-Cost Sensors for the Measurement of Atmospheric Composition: Overview of Topic and Future Applications. World Meteorological Organization (WMO); Geneva, Switzerland: 2018.
Paul J.D., Buytaert W. Chapter One–Citizen Science and Low-Cost Sensors for Integrated Water Resources Management. In: Friesen J., Rodríguez-Sinobas L., editors. Advances in Chemical Pollution, Environmental Management and Protection. Volume 3. Elsevier; Amsterdam, The Netherlands: 2018. pp. 1–33. Advanced Tools for Integrated Water Resources Management.
Wang Y., Han F., Zhu L., Deussen O., Chen B. Line Graph or Scatter Plot? Automatic Selection of Methods for Visualizing Trends in Time Series. IEEE Trans. Vis. Comput. Gr. 2018;24:1141–1154. doi: 10.1109/TVCG.2017.2653106. PubMed DOI
Saket B., Endert A., Demiralp Ç. Task-Based Effectiveness of Basic Visualizations. IEEE Trans. Vis. Comput. Gr. 2019;25:2505–2512. doi: 10.1109/TVCG.2018.2829750. PubMed DOI
Garcia-Retamero R., Galesic M. Who proficts from visual aids: Overcoming challenges in people’s understanding of risks. Soc. Sci. Med. 2010;70:1019–1025. doi: 10.1016/j.socscimed.2009.11.031. PubMed DOI
Saket B., Srinivasan A., Ragan E.D., Endert A. Evaluating Interactive Graphical Encodings for Data Visualization. IEEE Trans. Vis. Comput. Gr. 2018;24:1316–1330. doi: 10.1109/TVCG.2017.2680452. PubMed DOI
ICARUS2020.eu. [(accessed on 12 October 2018)]. Available online: https://icarus2020.eu/
Kocman D., Kanduč T., Novak R., Robinson J.A., Mikeš O., Degrendele C., Sáňka O., Vinkler J., Prokeš R., Vienneau D., et al. Multi-Sensor Data Collection for Personal Exposure Monitoring: ICARUS Experience. Fresenius Environ. Bull. 2021;6 (accepted for publication)
Sarigiannis D., Chapizanis D., Arvanitis A. D4.1 Report on the Methodology for Estimating Individual Exposure. ICARUS2020 Consortium Publication. [(accessed on 10 September 2021)]. Available online: https://icarus2020.eu/wp-content/uploads/2018/03/ICARUS-Deliverable-D4.1_FINAL.pdf.
Sarigiannis D., Karakitsios S., Chapizanis D., Hiscock R. D4.2_ICARUS_Methodology for Properly Accounting for SES in Exposure Assessment.pdf. ICARUS2020 consortium publication. [(accessed on 10 September 2021)]. Available online: https://icarus2020.eu/wp-content/uploads/2019/02/ICARUS_D4.2.pdf.
Robinson J.A., Novak R., Kanduč T., Sarigiannis D., Kocman D. Articulating User Experience of a Multi-Sensor Personal Air Quality Exposure Study. Department of Environmental Sciences, Jožef Stefan Institute; Ljubljana, Slovenia: 2021. manuscript in preparation.
R: The R Project for Statistical Computing. [(accessed on 5 December 2019)]. Available online: https://www.r-project.org/
Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer; New York, NY, USA: 2016.
Wickham H., François R., Henry L., Müller K. Dplyr: A Grammar of Data Manipulation. CRAN. 2018. [(accessed on 10 September 2021)]. Available online: https://dplyr.tidyverse.org.
Xie Y. Knitr: A General-Purpose Package for Dynamic Report Generation in R. CRAN. 2021. [(accessed on 10 September 2021)]. Available online: https://yihui.org/knitr/
Allaire J.J., Xie Y., McPherson J., Luraschi J., Ushey K., Atkins A., Wickham H., Cheng J., Chang W., Iannone R. Rmarkdown: Dynamic Documents for R. CRAN. 2021. [(accessed on 10 September 2021)]. Available online: https://pkgs.rstudio.com/rmarkdown/
Novak R., Kocman D., Robinson J.A., Kanduč T., Sarigiannis D., Horvat M. Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data. Sensors. 2020;20:1406. doi: 10.3390/s20051406. PubMed DOI PMC
Industries A. Adafruit PCF8523 Real Time Clock Assembled Breakout Board. [(accessed on 30 September 2020)]. Available online: https://www.adafruit.com/product/3295.
Garmin; subsidiaries, G.L. or its Garmin vívosmart® 3 | Fitness Activity Tracker. [(accessed on 3 September 2019)]. Available online: https://buy.garmin.com/en-US/US/p/567813.
uHoo | Product. [(accessed on 16 November 2018)]. Available online: https://uhooair.com/product/
Mahajan S., Kumar P., Pinto J.A., Riccetti A., Schaaf K., Camprodon G., Smári V., Passani A., Forino G. A citizen science approach for enhancing public understanding of air pollution. Sustain. Cities Soc. 2020;52:101800. doi: 10.1016/j.scs.2019.101800. DOI
Nikolakopoulos T., Gotti A., Tsiros E., Siora E. D7.2: Report on the Design of Technical Framework and System Architecture of the ICARUS DSS. ICARUS2020 Consortium Publication. [(accessed on 10 September 2021)]. Available online: https://icarus2020.eu/wp-content/uploads/2017/08/D.7.2_ICARUS_Design_of_%20technical_framework_and_system_architecture_of_the_ICARUS_DSS_FINAL.pdf.
Novak R., Kocman D., Robinson J.A., Kanduč T., Sarigiannis D., Džeroski S., Horvat M. Low-Cost Environmental and Motion Sensor Data for Complex Activity Recognition: Proof of Concept. Eng. Proc. 2020;2:54. doi: 10.3390/ecsa-7-08194. DOI
Robinson J.A., Novak R., Kanduč T., Maggos T., Pardali D., Stamatelopoulou A., Saraga D., Vienneau D., Flückiger B., Mikeš O., et al. User-Centred Design of a Final Results Report for Participants in Multi-Sensor Personal Air Pollution Exposure Monitoring Campaigns. Preprints. 2021 doi: 10.20944/preprints202110.0031.v1. PubMed DOI PMC
Air Quality Now–Indices Definition. [(accessed on 20 January 2021)]. Available online: http://airqualitynow.eu/about_indices_definition.php.
Zhang X., Zhao Z., Nordquist T., Norback D. The prevalence and incidence of sick building syndrome in Chinese pupils in relation to the school environment: A two-year follow-up study. Indoor Air. 2011;21:462–471. doi: 10.1111/j.1600-0668.2011.00726.x. PubMed DOI
AQ-SPEC . Field Evaluation–uHoo PM2.5, Ozone, and CO Sensor. AQ-SPEC; Diamond Bar, CA, USA: 2019. [(accessed on 10 September 2021)]. Available online: http://www.aqmd.gov/docs/default-source/aq-spec/field-evaluations/uhoo---field-evaluation.pdf?sfvrsn=12.
Baldelli A. Evaluation of a low-cost multi-channel monitor for indoor air quality through a novel, low-cost, and reproducible platform. Meas. Sens. 2021;17:100059. doi: 10.1016/j.measen.2021.100059. DOI
Tran V.V., Park D., Lee Y.-C. Indoor Air Pollution, Related Human Diseases, and Recent Trends in the Control and Improvement of Indoor Air Quality. Int. J. Environ. Res. Public Health. 2020;17:2927. doi: 10.3390/ijerph17082927. PubMed DOI PMC
Wei Y., Wang Y., Di Q., Choirat C., Wang Y., Koutrakis P., Zanobetti A., Dominici F., Schwartz J.D. Short term exposure to fine particulate matter and hospital admission risks and costs in the Medicare population: Time stratified, case crossover study. BMJ. 2019;367:l6258. doi: 10.1136/bmj.l6258. PubMed DOI PMC
Orellano P., Reynoso J., Quaranta N., Bardach A., Ciapponi A. Short-term exposure to particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), and ozone (O3) and all-cause and cause-specific mortality: Systematic review and meta-analysis. Environ. Int. 2020;142:105876. doi: 10.1016/j.envint.2020.105876. PubMed DOI
WHO Guidelines: Ambient (Outdoor) Air Pollution (Prior to 2021) [(accessed on 3 March 2021)]. Available online: https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health.
New WHO Global Air Quality Guidelines Aim to Save Millions of Lives from Air Pollution. [(accessed on 27 September 2021)]. Available online: https://www.euro.who.int/en/media-centre/sections/press-releases/2021/new-who-global-air-quality-guidelines-aim-to-save-millions-of-lives-from-air-pollution.
Park J., Kim S. Machine Learning-Based Activity Pattern Classification Using Personal PM2.5 Exposure Information. Int. J. Environ. Res. Public Health. 2020;17:6573. doi: 10.3390/ijerph17186573. PubMed DOI PMC