Encyclopedia of Sustainability Science and Technology

Living Edition
| Editors: Robert A. Meyers

Low-Cost Sensors for Indoor and Outdoor Pollution

  • Louise Bøge Frederickson
  • Emma Amalie Petersen-Sonn
  • Yuwei Shen
  • Ole Hertel
  • Youwei Hong
  • Johan Schmidt
  • Matthew S. JohnsonEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4939-2493-6_1084-1
  • 23 Downloads

Glossary

Band gap

A solid will have a density of electronic states as a function of energy. For example, a certain solid may have a band of fully occupied states, a gap or energy range in which there are no states, and at higher energies, an unoccupied band. This gap is called the bandgap. Electrons may be thermally excited from the fully occupied band into the unoccupied band, resulting in limited conductivity; the solid is then a semiconductor. A solid with a large bandgap is an insulator and with no bandgap, a conductor. The top of the occupied states is called the Fermi level [1].

Dynamic range

The range of performance of a sensor: the analyte concentration range between the highest observable concentration and the detection limit [2].

Explosion range and limits

The explosion range specifies the concentration range of a species in air, over which a given compound can burn or explode. This range extends from the lower to the upper explosive limit and is often given in % v/v. The...

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Bibliography

  1. 1.
    Atkins P, de Paula J, Friedman R (2009) Quanta, matter, and change: a molecular approach to physical chemistry. OUP, OxfordGoogle Scholar
  2. 2.
    Bochenkov VE, Sergeev GB (2010) Sensitivity, selectivity, and stability of gas-sensitive metal-oxide nanostructures. Metal oxide nanostructures and their applications, vol 3. pp 31–52Google Scholar
  3. 3.
    Guidelines for exposure assessment (1992). Federal Register 57(104):22888–22938Google Scholar
  4. 4.
    Kemibrug. [Online]. Available: https://kemibrug.dk/. Accessed 25 Feb 2019
  5. 5.
    Avgelis A, Papadopoulos AM (2004) Indoor air quality guidelines and standards – a state of the art review. Int J Vent 3(3):267–278CrossRefGoogle Scholar
  6. 6.
    Assen AH, Yassine O, Shekhah O, Eddaoudi M, Salama KN (2017) MOFs for the sensitive detection of ammonia: deployment of fcu-MOF thin films as effective chemical capacitive sensors. ACS Sens 2(9):1294–1301CrossRefGoogle Scholar
  7. 7.
    Choi Y-J, Hwang I-S, Park J-G, Choi KJ, Park J-H, Lee J-H (2008) Novel fabrication of an SnO2 nanowire gas sensor with high sensitivity. Nanotechnology 19(9):095508CrossRefGoogle Scholar
  8. 8.
    Peng K-Q, Wang X, Lee S-T (2009) Gas sensing properties of single crystalline porous silicon nanowires. Appl Phys Lett 95(24):243112CrossRefGoogle Scholar
  9. 9.
    Zhang J, Qin Z, Zeng D, Xie C (2017) Metal-oxide-semiconductor based gas sensors: screening, preparation, and integration. Phys Chem Chem Phys 19(9):6313–6329CrossRefGoogle Scholar
  10. 10.
    Harris DC (2007) Quantitative chemical analysis, 9th edn. W.H. Freeman, New YorkGoogle Scholar
  11. 11.
    Böer KW (2010) Introduction to space charge effects in semiconductors, vol 37. Springer, BerlinCrossRefGoogle Scholar
  12. 12.
    Chas Early, December 30, 1986: Coal mine canaries redundencies’ announced, British Telecommunications 21 Dec 2018Google Scholar
  13. 13.
    Apte JS et al (2017) High-resolution air pollution mapping with google street view cars: exploiting big data. Environ Sci Technol 51(12):6999–7008CrossRefGoogle Scholar
  14. 14.
    Kumar P, Morawska L, Martani C, Biskos G, Neophytou M, Di Sabatino S, Bell M, Norford L, Britter R (2015) The rise of low-costsensing for managing air pollution in cities. Environ Int 75:199–205CrossRefGoogle Scholar
  15. 15.
    Liu JH, Chen YF, Lin TS, Chen CP, Chen PT, Wen TH, …, Jiang JA (2012). An air quality monitoring system for urban areas based on the technology of wireless sensor networks. Int J Smart Sens Intell Syst 5(1)CrossRefGoogle Scholar
  16. 16.
    Steinle S, Reis S, Sabel CE (2013) Quantifying human exposure to air pollution–moving from static monitoring to spatio-temporally resolved personal exposure assessment. Sci Total Environ 443:184–193CrossRefGoogle Scholar
  17. 17.
    Piedrahita R et al (2014) The next generation of low-cost personal air quality sensors for quantitative exposure monitoring. Atmos Meas Tech 7(10):3325–3336CrossRefGoogle Scholar
  18. 18.
    Good N et al (2016) The Fort Collins Commuter Study: impact of route type and transport mode on personal exposure to multiple air pollutants. J Expo Sci Environ Epidemiol 26(4):397–404CrossRefGoogle Scholar
  19. 19.
    Alvear O, Zema NR, Natalizio E, Calafate CT (2017) Using UAV-based systems to moniter air pollution in areas with poor accessibility. J Adv Transport, Volume 2017, Article ID 8204353, p 14Google Scholar
  20. 20.
    Sustainable Development Goals. https://sustainabledevelopment.un.org. Accessed 7 Sep 2019
  21. 21.
    CDC – The National Institute for Occupational Safety and Health (NIOSH). [Online]. Available: https://www.cdc.gov/niosh/index.htm. Accessed 25 Feb 2019
  22. 22.
    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, https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32008L0050, Accessed 7 Sep 2019
  23. 23.
    Air Quality Standards, https://ec.europa.eu/environment/air/quality/standards.htm, Accessed 7 Sep 2019
  24. 24.
    WHO air quality guidelines for Europe, 2nd edition, 2000 (CD ROM version), 18-Mar-2017. [Online]. Available: http://www.euro.who.int/en/health-topics/environment-and-health/air-quality/publications/pre2009/who-air-quality-guidelines-for-europe,-2nd-edition,-2000-cd-rom-version. Accessed 20 Mar 2019
  25. 25.
    Danish Building Code, Ventilation (§420–§452), https://bygningsreglementet.dk/Tekniske-bestemmelser/22/vejledninger/General_vejledning/Kap-1_4, Accessed 7 Sep 2019
  26. 26.
    Stocker TF (ed) (2013) IPCC in climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University PressGoogle Scholar
  27. 27.
    Godwin C, Batterman S (2007) Indoor air quality in Michigan schools. Indoor Air 17:109–121CrossRefGoogle Scholar
  28. 28.
    Miranda AI, Martins V, Cascão P, Amorim JH, Valente J, Tavares R, Borrego C, Tchepel O, Ferreira AJ, Cordeiro CR, Viegas DX (2010) Monitoring of firefighters exposure to smoke during fire experiments in Portugal. Environ Int 36(7):736–745CrossRefGoogle Scholar
  29. 29.
    Lewné M, Nise G, Lind M-L, Gustavsson P (2006) Exposure to particles and nitrogen dioxide among taxi, bus and lorry drivers. Int Arch Occup Environ Health 79(3):220–226CrossRefGoogle Scholar
  30. 30.
    Popoola OAM et al (2018) Use of networks of low cost air quality sensors to quantify air quality in urban settings. Atmos Environ 194:58–70CrossRefGoogle Scholar
  31. 31.
    Apte JS, Messier KP, Gani S, Brauer M, Kirchstetter TW, Lunden MM, Marshall JD, Portier CJ, Vermeulen RC, Hamburg SP (2017) High-resolution air pollution mapping with google street views cars: exploiting big data. Environ Sci Technol 51(12):6999–7008CrossRefGoogle Scholar
  32. 32.
    Lin C et al (2018) High performance colorimetric carbon monoxide sensor for continuous personal exposure monitoring. ACS Sens 3(2):327–333CrossRefGoogle Scholar
  33. 33.
    Holøs SB, Yang A, Lind M, Thunshelle K, Schild P, Mysen M (2018) VOC emission rates in newly built and renovated buildings, and the influence of ventilation – a review and meta-analysis. Int J Vent:1–14Google Scholar
  34. 34.
    Jo W-K, Song K-B (2001) Exposure to volatile organic compounds for individuals with occupations associated with potential exposure to motor vehicle exhaust and/or gasoline vapor emissions, Sci Total Environ 269(1–3):25–37CrossRefGoogle Scholar
  35. 35.
    Hagan DH et al (2017) Calibration and assessment of electrochemical air quality sensors by co-location with regulatory-grade instruments. Atmos Meas Tech 11(1):315–328CrossRefGoogle Scholar
  36. 36.
    Hensen A, Skiba U, Famulari D (2013) Low cost and state of the art methods to measure nitrous oxide emissions. Environ Res Lett 8(2):025022CrossRefGoogle Scholar
  37. 37.
    Tokura A, Asobe M, Enbutsu K, Yoshihara T, Hashida S, Takenouchi H (2013) Real-time N2O gas detection system for agricultural production using a 4.6-μm-band laser source based on a periodically poled LiNbO3 ridge waveguide. Sensors 13(8):9999–10013CrossRefGoogle Scholar
  38. 38.
    Bochenkov VE, Seergev GB (eds) (2010) Metal oxide nanostructures and their applications. American Scientific Publisher. Valeucia, California, USAGoogle Scholar
  39. 39.
    Tung RT (2001) Recent advances in Schottky barrier concepts. Mater Sci Eng R Rep 35(1):1–138CrossRefGoogle Scholar
  40. 40.
    Moore JH, Coplan MA, Davis C (1983) Building scientific apparatus. Addison-Wesley. Boston, Massachussetts, USAGoogle Scholar
  41. 41.
    Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423CrossRefGoogle Scholar
  42. 42.
    Price E, Woodruff DP (2012) Applications of the Shannon-Hartley theorem to data streams and sparse recovery. In: 2012 IEEE international symposium on information theory proceedings, Cambridge, MA, USA, 2012, pp 2446–2450Google Scholar
  43. 43.
    IEEE std 952-1997, IEEE standard specification format guide and test procedure for single –axis interferometric fiber optic gyros. IEEE Std (1998):952–1997Google Scholar
  44. 44.
    Ng LC, Pines DJ (1997) Characterization of ring laser gyro performance using the Allan variance method. J Guid Control Dynam 20(1):211–214CrossRefGoogle Scholar
  45. 45.
    Martin CR et al (2017) Evaluation and environmental correction of ambient CO2 measurements from a low-cost NDIR sensor. Atmos Meas Tech 10(7):2383–2395CrossRefGoogle Scholar
  46. 46.
    Lewis A, Edwards P (2016) Validate personal air-pollution sensors. Nat News 535(7610):29CrossRefGoogle Scholar
  47. 47.
    Picco GP, Heinzelmann W, EWSN (eds) (2012) Wireless sensor networks: 9th European conference, EWSN 2012, Trento, Italy, February 15–17, 2012; proceedings, pp 228–244Google Scholar
  48. 48.
    Mead MI et al (2013) The use of electrochemical sensors for monitoring urban air quality in low-cost, high-density networks. Atmos Environ 70:186–203CrossRefGoogle Scholar
  49. 49.
    Schütze A, Leidinger M, Schmitt B, Sauerwald T, Rieger M, Alépée C (2015) A novel low-cost pre-concentrator concept to boost sensitivity and selectivity of gas sensor systems. In: 2015 IEEE SENSORS, 2015, pp 1–4Google Scholar
  50. 50.
    Wei P et al (2018) Impact analysis of temperature and humidity conditions on electrochemical sensor response in ambient air quality monitoring. Sensors 18(2)CrossRefGoogle Scholar
  51. 51.
    Peterson PJD et al (2017) Practical use of metal oxide semiconductor gas sensors for measuring nitrogen dioxide and ozone in urban environments. Sensors 17(7):1653CrossRefGoogle Scholar
  52. 52.
    Hossain M, Saffell J, Baron R (2016) Differentiating NO2 and O3 at low cost air quality amperometric gas sensors. ACS Sens 1(11):1291–1294CrossRefGoogle Scholar
  53. 53.
    Eranna G, Joshi BC, Runthala DP, Gupta RP (2004) Oxide materials for development of integrated gas sensors – a comprehensive review. Crit Rev Solid State Mater Sci 29(3–4):111–188CrossRefGoogle Scholar
  54. 54.
    Korotcenkov G (2007) Metal oxides for solid-state gas sensors: what determines our choice? Mater Sci Eng B 139(1):1–23CrossRefGoogle Scholar
  55. 55.
    Lee AP, Reedy BJ (1999) Temperature modulation in semiconductor gas sensing. Sensors Actuators B Chem 60(1):35–42CrossRefGoogle Scholar
  56. 56.
    Gurlo A (2006) Interplay between O2 and SnO2: oxygen ionosorption and spectroscopic evidence for adsorbed oxygen. ChemPhysChem 7(10):2041–2052CrossRefGoogle Scholar
  57. 57.
    Scales C, Berini P (2010) Thin-film Schottky barrier photodetector models. IEEE J Quantum Electron 46(5):633–643CrossRefGoogle Scholar
  58. 58.
    Ganose AM, Scanlon DO (2016) Band gap and work function tailoring of SnO2 for improved transparent conducting ability in photovoltaics. J Mater Chem C 4(7):1467–1475CrossRefGoogle Scholar
  59. 59.
    Srikant V, Clarke DR (1998) On the optical band gap of zinc oxide. J Appl Phys 83(10):5447–5451CrossRefGoogle Scholar
  60. 60.
    Serpone N (2006) Is the band gap of pristine TiO2 narrowed by anion- and cation-doping of titanium dioxide in second-generation photocatalysts? J Phys Chem B 110(48):24287–24293CrossRefGoogle Scholar
  61. 61.
    Rao MC Structure and properties of WO3 thin films for electrochromic device application, J Non-Oxide glasses 5:1–8Google Scholar
  62. 62.
    Walsh A, Da Silva JLF, Wei S-H (2008) Origins of band-gap renormalization in degenerately doped semiconductors. Phys Rev B 78(7):075211CrossRefGoogle Scholar
  63. 63.
    Prado AGS, Bolzon LB, Pedroso CP, Moura AO, Costa LL (2008) Nb2O5 as efficient and recyclable photocatalyst for indigo carmine degradation. Appl Catal B Environ 82(3):219–224CrossRefGoogle Scholar
  64. 64.
    McGregor KG, Calvin M, Otvos JW (1979) Photoeffects in Fe2O3 sintered semiconductors. J Appl Phys 50(1):369–373CrossRefGoogle Scholar
  65. 65.
    Higashiwaki M, Sasaki K, Kuramata A, Masui T, Yamakoshi S (2012) Gallium oxide (Ga2O3) metal-semiconductor field-effect transistors on single-crystal β-Ga2O3 (010) substrates. Appl Phys Lett 100(1):013504CrossRefGoogle Scholar
  66. 66.
    Brito PCA, Santos DAA, Duque JGS, Macêdo MA (2010) Structural and magnetic study of Fe-doped CeO2. Phys B Condens Matter 405(7):1821–1825CrossRefGoogle Scholar
  67. 67.
    Filatova EO, Konashuk AS (2015) Interpretation of the changing the band gap of Al2 O3 depending on its crystalline form: connection with different local symmetries. J Phys Chem C 119(35):20755–20761CrossRefGoogle Scholar
  68. 68.
    Zandiehnadem F, Murray RA, Ching WY (1988) Electronic structures of three phases of zirconium oxide. Phys BC 150(1):19–24Google Scholar
  69. 69.
    Lösch M, Baumbach M, Schütze A (2008) Ozone detection in the ppb-range with improved stability and reduced cross sensitivity. Sensors Actuators B Chem 130(1):367–373CrossRefGoogle Scholar
  70. 70.
    Castell N et al (2017) Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates? Environ Int 99:293–302CrossRefGoogle Scholar
  71. 71.
    Mikołajczyk J et al (2016) Detection of gaseous compounds with different techniques. Metrol Meas Syst 23(2):205–224CrossRefGoogle Scholar
  72. 72.
    Mendes LB, Ogink NWM, Edouard N, van Dooren HJC, Tinôco IFF, Mosquera J (2015) NDIR gas sensor for spatial monitoring of carbon dioxide concentrations in naturally ventilated livestock buildings. Sensors 15(5):11239–11257CrossRefGoogle Scholar
  73. 73.
    Ahuja D, Parande D (2012). Optical sensors and their applications. J Sci Res Rev 1(5):060–068Google Scholar
  74. 74.
    Marinov MB, Djermanova N, Ganev B, Nikolov G, Janchevska E (2018) Performance evaluation of low-cost carbon dioxide sensors. In: 2018 IEEE XXVII international scientific conference electronics – ET, Sofia, Bulgaria, pp 1–4Google Scholar
  75. 75.
    Fietzek P, Fiedler B, Steinhoff T, Körtzinger A (2014) In situ quality assessment of a novel underwater p CO 2 sensor based on membrane equilibration and NDIR spectrometry. J Atmos Ocean Technol 31(1):181–196CrossRefGoogle Scholar
  76. 76.
    Manikonda A, Zíková N, Hopke PK, Ferro AR (2016) Laboratory assessment of low-cost PM monitors. J Aerosol Sci 102:29–40CrossRefGoogle Scholar
  77. 77.
    Wang Y, Li J, Jing H, Zhang Q, Jiang J, Biswas P (2015) Laboratory evaluation and calibration of three low-cost particle sensors for particulate matter measurement. Aerosol Sci Technol 49(11):1063–1077CrossRefGoogle Scholar
  78. 78.
    Li J, Biswas P (2017) Optical characterization studies of a low-cost particle sensor. Aerosol Air Qual Res 17(7):1691–1704CrossRefGoogle Scholar
  79. 79.
    Baron R, Saffell J (2017) Amperometric gas sensors as a low cost emerging technology platform for air quality monitoring applications: a review. ACS Sens 2(11):1553–1566CrossRefGoogle Scholar
  80. 80.
    Roberts TJ, Saffell JR, Oppenheimer C, Lurton T (2014) Electrochemical sensors applied to pollution monitoring: measurement error and gas ratio bias – a volcano plume case study. J Volcanol Geotherm Res 281:85–96CrossRefGoogle Scholar
  81. 81.
    Yunusa Z, Hamidon MN, Kaiser A, Awang Z (2014) Gas sensors: a review. [Online]. Available: https://www.ingentaconnect.com/content/doaj/23068515/2014/00000168/00000004/art00009. Accessed 08 Mar 2019
  82. 82.
    Lee C, Akbar SA, Park CO (Dec. 2001) Potentiometric CO2 gas sensor with lithium phosphorous oxynitride electrolyte. Sensors Actuators B Chem 80(3):234–242CrossRefGoogle Scholar
  83. 83.
    Pang X, Shaw MD, Lewis AC, Carpenter LJ, Batchellier T (Mar. 2017) Electrochemical ozone sensors: a miniaturised alternative for ozone measurements in laboratory experiments and air-quality monitoring. Sensors Actuators B Chem 240:829–837CrossRefGoogle Scholar
  84. 84.
    Pang X, Shaw MD, Gillot S, Lewis AC (2018) The impacts of water vapour and co-pollutants on the performance of electrochemical gas sensors used for air quality monitoring. Sensors Actuators B Chem 266:674–684CrossRefGoogle Scholar
  85. 85.
    Popoola OAM, Stewart GB, Mead MI, Jones RL (2016) Development of a baseline-temperature correction methodology for electrochemical sensors and its implications for long-term stability. Atmos Environ 147:330–343CrossRefGoogle Scholar
  86. 86.
    Kim J, Chu C, Shin S (2014) ISSAQ: an integrated sensing systems for real-time indoor air quality monitoring. IEEE Sensors J 14(12):4230–4244CrossRefGoogle Scholar
  87. 87.
    Cross ES et al (2017) Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements. Atmos Meas Tech 10(9):3575–3588CrossRefGoogle Scholar
  88. 88.
    Spinelle L, Gerboles M, Villani MG, Aleixandre M, Bonavitacola F (2015) Field calibration of a cluster of low-cost available sensors for air quality monitoring. Part a: ozone and nitrogen dioxide. Sensors Actuators B Chem 215:249–257CrossRefGoogle Scholar
  89. 89.
    Lewis AC et al (2016) Evaluating the performance of low cost chemical sensors for air pollution research. Faraday Discuss 189(0):85–103CrossRefGoogle Scholar
  90. 90.
    Jiao W et al (2016) Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States. Atmos Meas Tech 9(11):5281–5292CrossRefGoogle Scholar
  91. 91.
    Borrego C et al (2016) Assessment of air quality microsensors versus reference methods: the EuNetAir joint exercise. Atmos Environ 147:246–263CrossRefGoogle Scholar
  92. 92.
    Stetter JR, Li J (2008) Amperometric gas sensors a review. Chem Rev 108(2):352–366CrossRefGoogle Scholar
  93. 93.
    Lim S et al (2012) A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the global burden of disease study 2010. Lancet 380(9859):2224–2260CrossRefGoogle Scholar
  94. 94.
    Carslaw DC, Rhys-Tyler G (2013) New insights from comprehensive on-road measurements of NOx, NO2 and NH3 from vehicle emission remote sensing in London, UK. Atmos Environ 81:339–347CrossRefGoogle Scholar
  95. 95.
    Carslaw D, Beevers S, Tate J, Westmoreland E, Williams M (2011) Recent evidence concerning higher NOx emissions from passenger cars and light duty vehicles. Atmos Environ 45:7053–7063CrossRefGoogle Scholar
  96. 96.
    Tsujita W, Yoshino A, Ishida H, Moriizumi T (2005) Gas sensor network for air-pollution monitoring. Sensors Actuators B Chem 110(2):304–311CrossRefGoogle Scholar
  97. 97.
    Kularatna N, Sudantha BH (2008) An environmental air pollution monitoring system based on the IEEE 1451 standard for low cost requirements. IEEE Sensors J 8(4):415–422CrossRefGoogle Scholar
  98. 98.
    Abraham S, Li X (2014) A cost-effective wireless sensor network system for indoor air quality monitoring applications. Procedia Comput Sci 34:165–171CrossRefGoogle Scholar
  99. 99.
    Albino V, Berardi U, Dangelico RM (2015) Smart cities: definitions, dimensions, performance, and initiatives. J Urban Technol 22(1):3–21CrossRefGoogle Scholar
  100. 100.
    Penza M, Suriano D, Villani MG, Spinelle L, Gerboles M (2014) Towards air quality indices in smart cities by calibrated low-cost sensors applied to networks. In: 2014 IEEE sensors, 2014, pp 2012–2017Google Scholar
  101. 101.
    Ali H, Soe JK, Weller SR (2015) A real-time ambient air quality monitoring wireless sensor network for schools in smart cities. In: 2015 IEEE first international smart cities conference (ISC2), 2015, Guadalajava, Mexico pp 1–6Google Scholar
  102. 102.
    Zanella A, Bui N, Castellani A, Vangelista L, Zorzi M (2014) Internet of things for smart cities. IEEE Internet Things J 1(1):22–32CrossRefGoogle Scholar
  103. 103.
    Talari S, Shafie-khah M, Siano P, Loia V, Tommasetti A, Catalão JPS (2017) A review of smart cities based on the internet of things concept. Energies 10(4):421CrossRefGoogle Scholar
  104. 104.
    Rout CS, Ganesh K, Govindaraj A, Rao CNR (2006) Sensors for the nitrogen oxides, NO2, NO and N2O, based on In2O3 and WO3 nanowires. Appl Phys A 85(3):241–246CrossRefGoogle Scholar
  105. 105.
    Burnett BJ, Choe W (2012) Sequential self-assembly in metal–organic frameworks. Dalton Trans 41(14):3889CrossRefGoogle Scholar
  106. 106.
    Homayoonnia S, Zeinali S (2016) Design and fabrication of capacitive nanosensor based on MOF nanoparticles as sensing layer for VOCs detection. Sensors Actuators B Chem 237:776–786CrossRefGoogle Scholar
  107. 107.
    Hao J-N, Yan B (2016) A dual-emitting 4d–4f nanocrystalline metal–organic framework as a self-calibrating luminescent sensor for indoor formaldehyde pollution. Nanoscale 8(23):12047–12053CrossRefGoogle Scholar
  108. 108.
    Ambient (outdoor) air quality and health. [Online]. Available: https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health. Accessed 18 Mar 2019
  109. 109.
    Kochakian CR (1980) Time-domain uncertainty charts (green charts): a tool for validating the design of IMU/instrument interfaces. Proceedings of the AIAA guidance and control conference, Danveus, Massachussetts, USA 1980Google Scholar
  110. 110.
    Edwards R, Smith KR, Kirby B, Allen T, Litton CD, Hering S (2006) An inexpensive dual-chamber particle monitor: laboratory characterization. J Air Waste Manage Assoc 56(6):789–799CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Louise Bøge Frederickson
    • 1
    • 2
  • Emma Amalie Petersen-Sonn
    • 1
  • Yuwei Shen
    • 1
  • Ole Hertel
    • 3
  • Youwei Hong
    • 4
  • Johan Schmidt
    • 2
  • Matthew S. Johnson
    • 1
    • 2
    Email author
  1. 1.Department of ChemistryUniversity of CopenhagenCopenhagen ØDenmark
  2. 2.AirlabsCopenhagenDenmark
  3. 3.Department of Environmental ScienceAarhus UniversityRoskildeDenmark
  4. 4.Institute of Urban Environment, Chinese Academy of ScienceXiamenChina

Section editors and affiliations

  • Michael Evan Goodsite
    • 1
  • Matthew Stanley Johnson
    • 2
  • Ole Hertel
    • 3
  • Nanna Rahbek Jørgensen
    • 4
  1. 1.Faculty of ECMSThe University of AdelaideAdelaideAustralia
  2. 2.Department of ChemistryUniversity of CopenhagenCopenhagenDenmark
  3. 3.Department of Environmental ScienceAarhus UniversityRoskildeDenmark
  4. 4.Department of Chemical Engineering, Biotechnology and Environmental Technology, Faculty of EngineeringUniversity of Southern DenmarkOdense MDenmark