Articles | Volume 17, issue 21
https://doi.org/10.5194/amt-17-6425-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-6425-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An overview of outdoor low-cost gas-phase air quality sensor deployments: current efforts, trends, and limitations
Atmospheric Science Branch, NASA Ames Research Center, Moffett Field, CA 94035, USA
NASA Postdoctoral Program, Oak Ridge Associated Universities, Oak Ridge, TN 37830, USA
now at: Bay Area Environmental Research Institute, Moffett Field, CA 94035, USA
Laura T. Iraci
Atmospheric Science Branch, NASA Ames Research Center, Moffett Field, CA 94035, USA
Related authors
No articles found.
Emma L. Yates, Laura T. Iraci, Susan S. Kulawik, Ju-Mee Ryoo, Josette E. Marrero, Caroline L. Parworth, Jason M. St. Clair, Thomas F. Hanisco, Thao Paul V. Bui, Cecilia S. Chang, and Jonathan M. Dean-Day
Earth Syst. Sci. Data, 15, 2375–2389, https://doi.org/10.5194/essd-15-2375-2023, https://doi.org/10.5194/essd-15-2375-2023, 2023
Short summary
Short summary
The Alpha Jet Atmospheric eXperiment (AJAX) flew scientific flights between 2011 and 2018 providing measurements of carbon dioxide, methane, ozone, formaldehyde, water vapor and meteorological parameters over California and Nevada, USA. AJAX was a multi-year, multi-objective, multi-instrument program with a variety of sampling strategies resulting in an extensive dataset of interest to a wide variety of users. AJAX measurements have been published at https://asdc.larc.nasa.gov/project/AJAX.
Harrison A. Parker, Joshua L. Laughner, Geoffrey C. Toon, Debra Wunch, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Kathryn McKain, Bianca C. Baier, and Paul O. Wennberg
Atmos. Meas. Tech., 16, 2601–2625, https://doi.org/10.5194/amt-16-2601-2023, https://doi.org/10.5194/amt-16-2601-2023, 2023
Short summary
Short summary
We describe a retrieval algorithm for determining limited information about the vertical distribution of carbon monoxide (CO) and carbon dioxide (CO2) from total column observations from ground-based observations. Our retrieved partial column values compare well with integrated in situ data. The average error for our retrieval is 1.51 ppb (~ 2 %) for CO and 5.09 ppm (~ 1.25 %) for CO2. We anticipate that this approach will find broad application for use in carbon cycle science.
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
Short summary
Short summary
We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
Short summary
Short summary
We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
Short summary
Short summary
This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
Matthieu Dogniaux, Cyril Crevoisier, Raymond Armante, Virginie Capelle, Thibault Delahaye, Vincent Cassé, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. Garcia, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, David F. Pollard, Coleen M. Roehl, Kei Shiomi, Kimberly Strong, Yao Té, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 14, 4689–4706, https://doi.org/10.5194/amt-14-4689-2021, https://doi.org/10.5194/amt-14-4689-2021, 2021
Short summary
Short summary
We present the Adaptable 4A Inversion (5AI), an implementation of the optimal estimation (OE) algorithm, relying on the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer model, that enables the retrieval of greenhouse gas atmospheric weighted columns from infrared measurements. It is tested on a sample of Orbiting Carbon Observatory-2 observations, and its results satisfactorily compare to several reference products, thus showing the reliability of 5AI OE implementation.
Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Stefan Noël, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Antonio Di Noia, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Lianghai Wu, Otto P. Hasekamp, Ilse Aben, Akihiko Kuze, Hiroshi Suto, Kei Shiomi, Yukio Yoshida, Isamu Morino, David Crisp, Christopher W. O'Dell, Justus Notholt, Christof Petri, Thorsten Warneke, Voltaire A. Velazco, Nicholas M. Deutscher, David W. T. Griffith, Rigel Kivi, David F. Pollard, Frank Hase, Ralf Sussmann, Yao V. Té, Kimberly Strong, Sébastien Roche, Mahesh K. Sha, Martine De Mazière, Dietrich G. Feist, Laura T. Iraci, Coleen M. Roehl, Christian Retscher, and Dinand Schepers
Atmos. Meas. Tech., 13, 789–819, https://doi.org/10.5194/amt-13-789-2020, https://doi.org/10.5194/amt-13-789-2020, 2020
Short summary
Short summary
We present new satellite-derived data sets of atmospheric carbon dioxide (CO2) and methane (CH4). The data products are column-averaged dry-air mole fractions of CO2 and CH4, denoted XCO2 and XCH4. The products cover the years 2003–2018 and are merged Level 2 (satellite footprints) and merged Level 3 (gridded at monthly time and 5° x 5° spatial resolution) products obtained from combining several individual sensor products. We present the merging algorithms and product validation results.
Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, John P. Burrows, Tobias Borsdorff, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Christian Hermans, Laura T. Iraci, Rigel Kivi, Jochen Landgraf, Isamu Morino, Justus Notholt, Christof Petri, David F. Pollard, Sébastien Roche, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Voltaire A. Velazco, Thorsten Warneke, and Debra Wunch
Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, https://doi.org/10.5194/amt-12-6771-2019, 2019
Short summary
Short summary
We introduce an algorithm that is used to simultaneously derive the abundances of the important atmospheric constituents carbon monoxide and methane from the TROPOMI instrument onboard the Sentinel-5 Precursor satellite, which enables the determination of both gases with an unprecedented level of detail on a global scale. The quality of the resulting data sets is assessed and the first results are presented.
Susan S. Kulawik, Sean Crowell, David Baker, Junjie Liu, Kathryn McKain, Colm Sweeney, Sebastien C. Biraud, Steve Wofsy, Christopher W. O'Dell, Paul O. Wennberg, Debra Wunch, Coleen M. Roehl, Nicholas M. Deutscher, Matthäus Kiel, David W. T. Griffith, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Mazière, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, Dave F. Pollard, Isamu Morino, Osamu Uchino, Frank Hase, Dietrich G. Feist, Sébastien Roche, Kimberly Strong, Rigel Kivi, Laura Iraci, Kei Shiomi, Manvendra K. Dubey, Eliezer Sepulveda, Omaira Elena Garcia Rodriguez, Yao Té, Pascal Jeseck, Pauli Heikkinen, Edward J. Dlugokencky, Michael R. Gunson, Annmarie Eldering, David Crisp, Brendan Fisher, and Gregory B. Osterman
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-257, https://doi.org/10.5194/amt-2019-257, 2019
Publication in AMT not foreseen
Short summary
Short summary
This paper provides a benchmark of OCO-2 v8 and ACOS-GOSAT v7.3 XCO2 and lowermost tropospheric (LMT) errors. The paper focuses on the systematic errors and subtracts out validation, co-location, and random errors, looks at the correlation scale-length (spatially and temporally) of systematic errors, finding that the scale lengths are similar to bias correction scale-lengths. The assimilates of the bias correction term is used to place an error on fluxes estimates.
Jacob K. Hedelius, Tai-Long He, Dylan B. A. Jones, Bianca C. Baier, Rebecca R. Buchholz, Martine De Mazière, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Laura T. Iraci, Pascal Jeseck, Matthäus Kiel, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Sébastien Roche, Coleen M. Roehl, Matthias Schneider, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Colm Sweeney, Yao Té, Osamu Uchino, Voltaire A. Velazco, Wei Wang, Thorsten Warneke, Paul O. Wennberg, Helen M. Worden, and Debra Wunch
Atmos. Meas. Tech., 12, 5547–5572, https://doi.org/10.5194/amt-12-5547-2019, https://doi.org/10.5194/amt-12-5547-2019, 2019
Short summary
Short summary
We seek ways to improve the accuracy of column measurements of carbon monoxide (CO) – an important tracer of pollution – made from the MOPITT satellite instrument. We devise a filtering scheme which reduces the scatter and also eliminates bias among the MOPITT detectors. Compared to ground-based observations, MOPITT measurements are about 6 %–8 % higher. When MOPITT data are implemented in a global assimilation model, they tend to reduce the model mismatch with aircraft measurements.
Ju-Mee Ryoo, Laura T. Iraci, Tomoaki Tanaka, Josette E. Marrero, Emma L. Yates, Inez Fung, Anna M. Michalak, Jovan Tadić, Warren Gore, T. Paul Bui, Jonathan M. Dean-Day, and Cecilia S. Chang
Atmos. Meas. Tech., 12, 2949–2966, https://doi.org/10.5194/amt-12-2949-2019, https://doi.org/10.5194/amt-12-2949-2019, 2019
Short summary
Short summary
We designed cylindrical flights and computed the emission fluxes using a kriging method and Gauss's theorem over Sacramento, California. Differences in wind treatment and background affect the emission estimates by a factor of 1.5 to 7. The effects of the vertical layer average and the vertical mass transfer on the emission estimates are found to be small, esp. local scale. The result also suggests a closed-shape flight profile can better contain total emissions than a one-sided curtain flight.
Andrew O. Langford, Raul J. Alvarez II, Guillaume Kirgis, Christoph J. Senff, Dani Caputi, Stephen A. Conley, Ian C. Faloona, Laura T. Iraci, Josette E. Marrero, Mimi E. McNamara, Ju-Mee Ryoo, and Emma L. Yates
Atmos. Meas. Tech., 12, 1889–1904, https://doi.org/10.5194/amt-12-1889-2019, https://doi.org/10.5194/amt-12-1889-2019, 2019
Short summary
Short summary
Lidar, aircraft, and surface measurements of ozone made during the 2016 California Baseline Ozone Transport Study (CABOTS) are compared to assess their validity and verify their suitability for investigations into the contributions of stratosphere-to-troposphere transport, Asian pollution, and wildfires to summertime surface ozone concentrations in the San Joaquin Valley of California. Our analysis shows that the lidar and aircraft measurements agree, on average, to within ±5 ppbv.
Christopher W. O'Dell, Annmarie Eldering, Paul O. Wennberg, David Crisp, Michael R. Gunson, Brendan Fisher, Christian Frankenberg, Matthäus Kiel, Hannakaisa Lindqvist, Lukas Mandrake, Aronne Merrelli, Vijay Natraj, Robert R. Nelson, Gregory B. Osterman, Vivienne H. Payne, Thomas E. Taylor, Debra Wunch, Brian J. Drouin, Fabiano Oyafuso, Albert Chang, James McDuffie, Michael Smyth, David F. Baker, Sourish Basu, Frédéric Chevallier, Sean M. R. Crowell, Liang Feng, Paul I. Palmer, Mavendra Dubey, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, Hirofumi Ohyama, Christof Petri, Coleen M. Roehl, Mahesh K. Sha, Kimberly Strong, Ralf Sussmann, Yao Te, Osamu Uchino, and Voltaire A. Velazco
Atmos. Meas. Tech., 11, 6539–6576, https://doi.org/10.5194/amt-11-6539-2018, https://doi.org/10.5194/amt-11-6539-2018, 2018
Jacob K. Hedelius, Junjie Liu, Tomohiro Oda, Shamil Maksyutov, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Jianming Liang, Kevin R. Gurney, Debra Wunch, and Paul O. Wennberg
Atmos. Chem. Phys., 18, 16271–16291, https://doi.org/10.5194/acp-18-16271-2018, https://doi.org/10.5194/acp-18-16271-2018, 2018
Short summary
Short summary
Human activities can cause concentrated emissions of greenhouse gases and other pollutants from cities. There is ongoing effort to convert new satellite observations of pollutants into fluxes for many cities. Here we present a method for determining the flux of three species (CO2, CH4, and CO) from the greater LA area using satellite (CO2 only) and ground-based (all three species) observations. We run tests to estimate uncertainty and find the direct net CO2 flux is 104 ± 26 Tg CO2 yr−1.
Lianghai Wu, Otto Hasekamp, Haili Hu, Jochen Landgraf, Andre Butz, Joost aan de Brugh, Ilse Aben, Dave F. Pollard, David W. T. Griffith, Dietrich G. Feist, Dmitry Koshelev, Frank Hase, Geoffrey C. Toon, Hirofumi Ohyama, Isamu Morino, Justus Notholt, Kei Shiomi, Laura Iraci, Matthias Schneider, Martine de Mazière, Ralf Sussmann, Rigel Kivi, Thorsten Warneke, Tae-Young Goo, and Yao Té
Atmos. Meas. Tech., 11, 3111–3130, https://doi.org/10.5194/amt-11-3111-2018, https://doi.org/10.5194/amt-11-3111-2018, 2018
Ira Leifer, Christopher Melton, Marc L. Fischer, Matthew Fladeland, Jason Frash, Warren Gore, Laura T. Iraci, Josette E. Marrero, Ju-Mee Ryoo, Tomoaki Tanaka, and Emma L. Yates
Atmos. Meas. Tech., 11, 1689–1705, https://doi.org/10.5194/amt-11-1689-2018, https://doi.org/10.5194/amt-11-1689-2018, 2018
Short summary
Short summary
Airborne/mobile-surface data were collected to derive active oil field trace gas emissions near Bakersfield, CA, characterizing the atmosphere from the surface to above the planetary boundary layer (PBL) by combining downwind concentration anomaly (plume) above background with normal winds. Air–surface comparison for a mountain profile (0.1–2.2 km) confirmed surface winds. Annualized oil field emissions were 31.3±16 Gg CH4 and 2.4±1.2 Tg CO2. The PBL was not well mixed even 10–20 km downwind.
Jason M. St. Clair, Andrew K. Swanson, Steven A. Bailey, Glenn M. Wolfe, Josette E. Marrero, Laura T. Iraci, John G. Hagopian, and Thomas F. Hanisco
Atmos. Meas. Tech., 10, 4833–4844, https://doi.org/10.5194/amt-10-4833-2017, https://doi.org/10.5194/amt-10-4833-2017, 2017
Short summary
Short summary
Formaldehyde is an abundant, photochemically influential trace species in the Earth’s atmosphere. We present a new instrument for measuring atmospheric formaldehyde using a laser-based measurement technique that is more compact and lower cost than previous laser-based formaldehyde instruments. The instrument is part of the Alpha Jet Atmospheric eXperiment (AJAX) payload at the NASA Ames Research Center and has collected data on 27 flights between December 2015 and March 2017.
Sven Krautwurst, Konstantin Gerilowski, Haflidi H. Jonsson, David R. Thompson, Richard W. Kolyer, Laura T. Iraci, Andrew K. Thorpe, Markus Horstjann, Michael Eastwood, Ira Leifer, Samuel A. Vigil, Thomas Krings, Jakob Borchardt, Michael Buchwitz, Matthew M. Fladeland, John P. Burrows, and Heinrich Bovensmann
Atmos. Meas. Tech., 10, 3429–3452, https://doi.org/10.5194/amt-10-3429-2017, https://doi.org/10.5194/amt-10-3429-2017, 2017
Short summary
Short summary
This study investigates a subset of data collected during the CO2 and Methane EXperiment (COMEX) in 2014. It focuses on airborne measurements to quantify the emissions from landfills in the Los Angeles Basin. Airborne remote sensing data have been used to estimate the emission rate of one particular landfill on four different days. The results have been compared to airborne in situ measurements. Airborne imaging spectroscopy has been used to identify emission hotspots across the landfill.
Debra Wunch, Paul O. Wennberg, Gregory Osterman, Brendan Fisher, Bret Naylor, Coleen M. Roehl, Christopher O'Dell, Lukas Mandrake, Camille Viatte, Matthäus Kiel, David W. T. Griffith, Nicholas M. Deutscher, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Maziere, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, David Pollard, John Robinson, Isamu Morino, Osamu Uchino, Frank Hase, Thomas Blumenstock, Dietrich G. Feist, Sabrina G. Arnold, Kimberly Strong, Joseph Mendonca, Rigel Kivi, Pauli Heikkinen, Laura Iraci, James Podolske, Patrick W. Hillyard, Shuji Kawakami, Manvendra K. Dubey, Harrison A. Parker, Eliezer Sepulveda, Omaira E. García, Yao Te, Pascal Jeseck, Michael R. Gunson, David Crisp, and Annmarie Eldering
Atmos. Meas. Tech., 10, 2209–2238, https://doi.org/10.5194/amt-10-2209-2017, https://doi.org/10.5194/amt-10-2209-2017, 2017
Short summary
Short summary
This paper describes the comparisons between NASA's Orbiting Carbon Observatory (OCO-2) column-averaged dry-air mole fractions of CO2 with its primary ground-based validation network, the Total Carbon Column Observing Network (TCCON). The paper shows that while the standard bias correction reduces much of the spurious variability in the satellite measurements, residual biases remain.
Susan S. Kulawik, Chris O'Dell, Vivienne H. Payne, Le Kuai, Helen M. Worden, Sebastien C. Biraud, Colm Sweeney, Britton Stephens, Laura T. Iraci, Emma L. Yates, and Tomoaki Tanaka
Atmos. Chem. Phys., 17, 5407–5438, https://doi.org/10.5194/acp-17-5407-2017, https://doi.org/10.5194/acp-17-5407-2017, 2017
Short summary
Short summary
We introduce new vertically resolved GOSAT products that better separate locally and remotely influenced CO2. Current GOSAT column results for CO2 (XCO2) are sensitive to fluxes on continental scales, whereas flux estimates from surface and tower measurements are affected by sampling bias and model transport uncertainty. These new GOSAT measurements of boundary layer CO2 are validated against aircraft and surface observations of CO2 and are compared to vertically resolved MOPITT CO.
Jacob K. Hedelius, Harrison Parker, Debra Wunch, Coleen M. Roehl, Camille Viatte, Sally Newman, Geoffrey C. Toon, James R. Podolske, Patrick W. Hillyard, Laura T. Iraci, Manvendra K. Dubey, and Paul O. Wennberg
Atmos. Meas. Tech., 10, 1481–1493, https://doi.org/10.5194/amt-10-1481-2017, https://doi.org/10.5194/amt-10-1481-2017, 2017
Short summary
Short summary
Two portable spectrometers, assumed to be internally precise, were taken to four different sites with (stationary) TCCON spectrometers. Biases of column averaged CO2 and CH4 measured among the TCCON sites were estimated experimentally. Results suggest that maximum (95 % confidence interval) bias among sites is less than what was estimated from a previous analytical error analysis.
Related subject area
Subject: Gases | Technique: In Situ Measurement | Topic: Instruments and Platforms
Multiphysical description of atmospheric pressure interface chemical ionisation in MION2 and Eisele type inlets
A portable nitrogen dioxide instrument using cavity-enhanced absorption spectroscopy
Development and deployment of a mid-cost CO2 sensor monitoring network to support atmospheric inverse modeling for quantifying urban CO2 emissions in Paris
UAV-based in situ measurements of CO2 and CH4 fluxes over complex natural ecosystems
A new aerial approach for quantifying and attributing methane emissions: implementation and validation
Drone CO2 measurements during the Tajogaite volcanic eruption
Multi-decadal atmospheric carbon dioxide measurements in Hungary, central Europe
Reliable water vapour isotopic composition measurements at low humidity using frequency-stabilised cavity ring-down spectroscopy
A measurement system for CO2 and CH4 emissions quantification of industrial sites using a new in situ concentration sensor operated on board uncrewed aircraft vehicles
Deployment and evaluation of an NH4+/H3O+ reagent-ion switching chemical ionization mass spectrometer for the detection of reduced and oxygenated gas-phase organic compounds
Using metal oxide gas sensors to estimate the emission rates and locations of methane leaks in an industrial site: assessment with controlled methane releases
The ASK-16 Motorized Glider: An Airborne Eddy Covariance Platform to measure Turbulence, Energy and Matter Fluxes
Toward on-demand measurements of greenhouse gas emissions using an uncrewed aircraft AirCore system
Long-term evaluation of commercial air quality sensors: an overview from the QUANT (Quantification of Utility of Atmospheric Network Technologies) study
In-flight characterization of a compact airborne quantum cascade laser absorption spectrometer
Full characterization and calibration of a transfer standard monitor for atmospheric radon measurements
Observing low-altitude features in ozone concentrations in a shoreline environment via uncrewed aerial systems
Eddy-covariance with slow-response greenhouse gas analyser on tall towers: bridging atmospheric and ecosystem greenhouse gases networks
An integrated uncrewed aerial vehicle platform with sensing and sampling systems for the measurement of air pollutant concentrations
Design and evaluation of a low-cost sensor node for near-background methane measurement
Development of a Multichannel Organics In situ enviRonmental Analyzer (MOIRA) for mobile measurements of volatile organic compounds
An Economical Tunable-Diode Laser Spectrometer for Fast-Response Measurements of Water Vapor in the Atmospheric Boundary Layer
Evaluation of Aeris mid-infrared absorption (MIRA), Picarro CRDS (cavity ring-down spectroscopy) G2307, and dinitrophenylhydrazine (DNPH)-based sampling for long-term formaldehyde monitoring efforts
Performance characterization of a laminar gas inlet
Validation and field application of a low-cost device to measure CO2 and evapotranspiration (ET) fluxes
Identifying and correcting interferences to PTR-ToF-MS measurements of isoprene and other urban volatile organic compounds
Development of a continuous UAV-mounted air sampler and application to the quantification of CO2 and CH4 emissions from a major coking plant
Uptake behavior of polycyclic aromatic compounds during field calibrations of the XAD-based passive air sampler across seasons and locations
Effect of land–sea air mass transport on spatiotemporal distributions of atmospheric CO2 and CH4 mixing ratios over the southern Yellow Sea
HYPHOP: a tool for high-altitude, long-range monitoring of hydrogen peroxide and higher organic peroxides in the atmosphere
Portable, low-cost samplers for distributed sampling of atmospheric gases
SI-traceable validation of a laser spectrometer for balloon-borne measurements of water vapor in the upper atmosphere
Field evaluation of low-cost electrochemical air quality gas sensors under extreme temperature and relative humidity conditions
A novel, cost-effective analytical method for measuring high-resolution vertical profiles of stratospheric trace gases using a gas chromatograph coupled with an electron capture detector
Ethylene oxide monitor with part-per-trillion precision for in situ measurements
Development of an automated pump-efficiency measuring system for ozonesondes utilizing an airbag-type flowmeter
Short-term variability of atmospheric helium revealed through a cryo-enrichment method
Using tunable infrared laser direct absorption spectroscopy for ambient hydrogen chloride detection: HCl-TILDAS
New methods for the calibration of optical resonators: integrated calibration by means of optical modulation (ICOM) and narrow-band cavity ring-down (NB-CRD)
A modular field system for near-surface, vertical profiling of the atmospheric composition in harsh environments using cavity ring-down spectroscopy
Field comparison of two novel open-path instruments that measure dry deposition and emission of ammonia using flux-gradient and eddy covariance methods
Development of multi-channel whole-air sampling equipment onboard an unmanned aerial vehicle for investigating volatile organic compounds' vertical distribution in the planetary boundary layer
Electrochemical sensors on board a Zeppelin NT: in-flight evaluation of low-cost trace gas measurements
Evaluating the performance of a Picarro G2207-i analyser for high-precision atmospheric O2 measurements
Airborne flux measurements of ammonia over the southern Great Plains using chemical ionization mass spectrometry
Optical receiver characterizations and corrections for ground-based and airborne measurements of spectral actinic flux densities
Development and validation of a new in situ technique to measure total gaseous chlorine in air
True eddy accumulation – Part 1: Solutions to the problem of non-vanishing mean vertical wind velocity
True eddy accumulation – Part 2: Theory and experiment of the short-time eddy accumulation method
Chemical ionization mass spectrometry utilizing ammonium ions (NH4+ CIMS) for measurements of organic compounds in the atmosphere
Henning Finkenzeller, Jyri Mikkilä, Cecilia Righi, Paxton Juuti, Mikko Sipilä, Matti Rissanen, Douglas Worsnop, Aleksei Shcherbinin, Nina Sarnela, and Juha Kangasluoma
Atmos. Meas. Tech., 17, 5989–6001, https://doi.org/10.5194/amt-17-5989-2024, https://doi.org/10.5194/amt-17-5989-2024, 2024
Short summary
Short summary
Chemical ionisation mass spectrometry is used in the atmospheric sciences to measure trace gas concentrations. Neutral gases require charging in inlets before the mass-to-charge ratio of the resulting ions can be analysed. This study uses multiphysics modelling to investigate how the MION2 and Eisele type inlets work and shows the effect of tuning parameters and their current limitations. The findings are helpful for inlet users and are expected to aid in developing improved inlets.
Steven A. Bailey, Reem A. Hannun, Andrew K. Swanson, and Thomas F. Hanisco
Atmos. Meas. Tech., 17, 5903–5910, https://doi.org/10.5194/amt-17-5903-2024, https://doi.org/10.5194/amt-17-5903-2024, 2024
Short summary
Short summary
We have developed a portable, optically based instrument that measures NO2. It consumes less than 6 W of power, so it can easily run off a small battery. This instrument has made both balloon and UAV flights. NO2 measurement results compare favorably with other known NO2 instruments. We find this instrument to be stable with repeatable results compared with calibration sources. Material cost to build a single instrument is around USD 4000. This could be lowered with economies of scale.
Jinghui Lian, Olivier Laurent, Mali Chariot, Luc Lienhardt, Michel Ramonet, Hervé Utard, Thomas Lauvaux, François-Marie Bréon, Grégoire Broquet, Karina Cucchi, Laurent Millair, and Philippe Ciais
Atmos. Meas. Tech., 17, 5821–5839, https://doi.org/10.5194/amt-17-5821-2024, https://doi.org/10.5194/amt-17-5821-2024, 2024
Short summary
Short summary
We have designed and deployed a mid-cost medium-precision CO2 sensor monitoring network in Paris since July 2020. The data are automatically calibrated by a newly implemented data processing system. The accuracies of the mid-cost instruments vary from 1.0 to 2.4 ppm for hourly afternoon measurements. Our model–data analyses highlight prospects for integrating mid-cost instrument data with high-precision measurements to improve fine-scale CO2 emission quantification in urban areas.
Abdullah Bolek, Martin Heimann, and Mathias Göckede
Atmos. Meas. Tech., 17, 5619–5636, https://doi.org/10.5194/amt-17-5619-2024, https://doi.org/10.5194/amt-17-5619-2024, 2024
Short summary
Short summary
This study describes the development of a new UAV platform to measure atmospheric greenhouse gas (GHG) mole fractions, 2D wind speed, air temperature, humidity, and pressure. Understanding GHG flux processes and controls across various ecosystems is essential for estimating the current and future state of climate change. It was shown that using the UAV platform for such measurements is beneficial for improving our understanding of GHG processes over complex landscapes.
Jonathan F. Dooley, Kenneth Minschwaner, Manvendra K. Dubey, Sahar H. El Abbadi, Evan D. Sherwin, Aaron G. Meyer, Emily Follansbee, and James E. Lee
Atmos. Meas. Tech., 17, 5091–5111, https://doi.org/10.5194/amt-17-5091-2024, https://doi.org/10.5194/amt-17-5091-2024, 2024
Short summary
Short summary
Methane is a powerful greenhouse gas originating from both natural and human activities. We describe a new uncrewed aerial system (UAS) designed to measure methane emission rates over a wide range of scales. This system has been used for direct quantification of point sources and distributed emitters over scales of up to 1 km. The system uses simultaneous measurements of methane and ethane to distinguish between different kinds of natural and human-related emission sources.
John Ericksen, Tobias P. Fischer, G. Matthew Fricke, Scott Nowicki, Nemesio M. Pérez, Pedro Hernández Pérez, Eleazar Padrón González, and Melanie E. Moses
Atmos. Meas. Tech., 17, 4725–4736, https://doi.org/10.5194/amt-17-4725-2024, https://doi.org/10.5194/amt-17-4725-2024, 2024
Short summary
Short summary
Volcanic eruptions emit significant quantities of carbon dioxide (CO2) to the atmosphere. We present a new method for directly determining the CO2 emission from a volcanic eruption on the island of La Palma, Spain, using an unpiloted aerial vehicle (UAV). We also collected samples of the emitted CO2 and analyzed their isotopic composition. Together with the emission rate the isotopic data provide valuable information on the state of volcanic activity and the potential evolution of the eruption.
László Haszpra
Atmos. Meas. Tech., 17, 4629–4647, https://doi.org/10.5194/amt-17-4629-2024, https://doi.org/10.5194/amt-17-4629-2024, 2024
Short summary
Short summary
The paper evaluates a 30-year-long atmospheric CO2 data series from a mid-continental central European site, Hegyhátsál (HUN). It presents the site-specific features observed in the long-term evolution of the atmospheric CO2 concentration. Since the measurement data are widely used in atmospheric inverse models and budget calculations all around the world, the paper provides potentially valuable information for model tuning and interpretation of the model results.
Mathieu Casado, Amaelle Landais, Tim Stoltmann, Justin Chaillot, Mathieu Daëron, Fréderic Prié, Baptiste Bordet, and Samir Kassi
Atmos. Meas. Tech., 17, 4599–4612, https://doi.org/10.5194/amt-17-4599-2024, https://doi.org/10.5194/amt-17-4599-2024, 2024
Short summary
Short summary
Measuring water isotopic composition in Antarctica is difficult because of the extremely cold temperature in winter. Here, we designed a new infrared spectrometer able to measure the vapour isotopic composition during more than 95 % of the year in the coldest locations of Antarctica, whereas current commercial instruments are only able to measure during the warm summer months in the interior.
Jean-Louis Bonne, Ludovic Donnat, Grégory Albora, Jérémie Burgalat, Nicolas Chauvin, Delphine Combaz, Julien Cousin, Thomas Decarpenterie, Olivier Duclaux, Nicolas Dumelié, Nicolas Galas, Catherine Juery, Florian Parent, Florent Pineau, Abel Maunoury, Olivier Ventre, Marie-France Bénassy, and Lilian Joly
Atmos. Meas. Tech., 17, 4471–4491, https://doi.org/10.5194/amt-17-4471-2024, https://doi.org/10.5194/amt-17-4471-2024, 2024
Short summary
Short summary
We present a top-down approach to quantify CO2 and CH4 emissions at the scale of an industrial site, based on a mass balance model relying on atmospheric concentrations measurements from a new sensor embarked on board uncrewed aircraft vehicles (UAVs). We present a laboratory characterization of our sensor and a field validation of our quantification method, together with field application to the monitoring of two real-world offshore oil and gas platforms.
Cort L. Zang and Megan D. Willis
EGUsphere, https://doi.org/10.5194/egusphere-2024-1738, https://doi.org/10.5194/egusphere-2024-1738, 2024
Short summary
Short summary
Atmospheric chemistry of the diverse pool of reactive organic carbon (ROC; all organic species excluding methane) controls air quality, both indoor and outdoors, and influences Earth's climate. However, many important ROC compounds in the atmosphere are difficult to measure. We demonstrate measurement of diverse ROC compounds in a single instrument at a forested site. This approach can improve our ability to measure a broad range of atmospheric ROC.
Rodrigo Rivera-Martinez, Pramod Kumar, Olivier Laurent, Gregoire Broquet, Christopher Caldow, Ford Cropley, Diego Santaren, Adil Shah, Cécile Mallet, Michel Ramonet, Leonard Rivier, Catherine Juery, Olivier Duclaux, Caroline Bouchet, Elisa Allegrini, Hervé Utard, and Philippe Ciais
Atmos. Meas. Tech., 17, 4257–4290, https://doi.org/10.5194/amt-17-4257-2024, https://doi.org/10.5194/amt-17-4257-2024, 2024
Short summary
Short summary
We explore the use of metal oxide semiconductors (MOSs) as a low-cost alternative for detecting and measuring CH4 emissions from industrial facilities. MOSs were exposed to several controlled releases to test their accuracy in detecting and quantifying emissions. Two reconstruction models were compared, and emission estimates were computed using a Gaussian dispersion model. Findings show that MOSs can provide accurate emission estimates with a 25 % emission rate error and a 9.5 m location error.
Inge Wiekenkamp, Anna Katharina Lehmann, Alexander Bütow, Jörg Hartmann, Stefan Metzger, Thomas Ruhtz, Christian Wille, Mathias Zöllner, and Torsten Sachs
EGUsphere, https://doi.org/10.5194/egusphere-2024-1586, https://doi.org/10.5194/egusphere-2024-1586, 2024
Short summary
Short summary
Airborne eddy covariance platforms are crucial, as they measure the three-dimension wind, and turbulent transport of matter and energy between the surface and the atmosphere at larger scales. In this study we introduce the new ASK-16 eddy covariance platform that is able to accurately measure turbulent fluxes and wind vectors. Data from this platform can help to build bridges between local tower measurements and regional remote sensing fluxes or inversion products.
Zihan Zhu, Javier González-Rocha, Yifan Ding, Isis Frausto-Vicencio, Sajjan Heerah, Akula Venkatram, Manvendra Dubey, Don Collins, and Francesca M. Hopkins
Atmos. Meas. Tech., 17, 3883–3895, https://doi.org/10.5194/amt-17-3883-2024, https://doi.org/10.5194/amt-17-3883-2024, 2024
Short summary
Short summary
Increases in agriculture, oil and gas, and waste management activities have contributed to the increase in atmospheric methane levels and resultant climate warming. In this paper, we explore the use of small uncrewed aircraft systems (sUASs) and AirCore technology to detect and quantify methane emissions. Results from field experiments demonstrate that sUASs and AirCore technology can be effective for detecting and quantifying methane emissions in near real time.
Sebastian Diez, Stuart Lacy, Hugh Coe, Josefina Urquiza, Max Priestman, Michael Flynn, Nicholas Marsden, Nicholas A. Martin, Stefan Gillott, Thomas Bannan, and Pete M. Edwards
Atmos. Meas. Tech., 17, 3809–3827, https://doi.org/10.5194/amt-17-3809-2024, https://doi.org/10.5194/amt-17-3809-2024, 2024
Short summary
Short summary
In this paper we present an overview of the QUANT project, which to our knowledge is one of the largest evaluations of commercial sensors to date. The objective was to evaluate the performance of a range of commercial products and also to nourish the different applications in which these technologies can offer relevant information.
Linda Ort, Lenard Lukas Röder, Uwe Parchatka, Rainer Königstedt, Daniel Crowley, Frank Kunz, Ralf Wittkowski, Jos Lelieveld, and Horst Fischer
Atmos. Meas. Tech., 17, 3553–3565, https://doi.org/10.5194/amt-17-3553-2024, https://doi.org/10.5194/amt-17-3553-2024, 2024
Short summary
Short summary
Airborne in situ measurements are of great importance to collect valuable data to improve our knowledge of the atmosphere but also present challenges which demand specific designs. This study presents an IR spectrometer for airborne trace-gas measurements with high data efficiency and a simple, compact design. Its in-flight performance is characterized with the help of a test flight and a comparison with another spectrometer. Moreover, results from its first campaign highlight its benefits.
Roger Curcoll, Claudia Grossi, Stefan Röttger, and Arturo Vargas
Atmos. Meas. Tech., 17, 3047–3065, https://doi.org/10.5194/amt-17-3047-2024, https://doi.org/10.5194/amt-17-3047-2024, 2024
Short summary
Short summary
This paper presents a new user-friendly version of the Atmospheric Radon MONitor (ARMON). The efficiency of the instrument is of 0.0057 s-1, obtained using different techniques at Spanish and German chambers. The total calculated uncertainty of the ARMON for hourly radon concentrations above 5 Bq m-3 is lower than 10 % (k = 1). Results confirm that the ARMON is suitable to measure low-level radon activity concentrations and to be used as a transfer standard to calibrate in situ radon monitors.
Josie K. Radtke, Benjamin N. Kies, Whitney A. Mottishaw, Sydney M. Zeuli, Aidan T. H. Voon, Kelly L. Koerber, Grant W. Petty, Michael P. Vermeuel, Timothy H. Bertram, Ankur R. Desai, Joseph P. Hupy, R. Bradley Pierce, Timothy J. Wagner, and Patricia A. Cleary
Atmos. Meas. Tech., 17, 2833–2847, https://doi.org/10.5194/amt-17-2833-2024, https://doi.org/10.5194/amt-17-2833-2024, 2024
Short summary
Short summary
The use of uncrewed aircraft systems (UASs) to conduct a vertical profiling of ozone and meteorological variables was evaluated using comparisons between tower or ground observations and UAS-based measurements. Changes to the UAS profiler showed an improvement in performance. The profiler was used to see the impact of Chicago pollution plumes on a shoreline area near Lake Michigan.
Pedro Henrique Herig Coimbra, Benjamin Loubet, Olivier Laurent, Laura Bignotti, Mathis Lozano, and Michel Ramonet
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-71, https://doi.org/10.5194/amt-2024-71, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This study explores using infrastructure built to assess atmospheric gas concentration with high precision to measure local emissions and sequestration. This only requires, relatively inexpensive, 3D wind measurements. The study uses the Saclay tower near Paris, in a mixed urban, forest and agricultural area. Results identified strong heating plant emissions and carbon uptake by the forest. Collaboration between scientific communities is further encouraged, so to better monitor greenhouse gases.
Chen-Wei Liang and Chang-Hung Shen
Atmos. Meas. Tech., 17, 2671–2686, https://doi.org/10.5194/amt-17-2671-2024, https://doi.org/10.5194/amt-17-2671-2024, 2024
Short summary
Short summary
In the present study, a UAV platform with sensing and sampling systems was developed for 3D air pollutant concentration measurements. The sensing system of this platform contains multiple microsensors and IoT technologies for obtaining the real-time 3D distributions of critical air pollutants. The sampling system contains gas sampling sets and a 1 L Tedlar bag instead of a canister for the 3D measurement of VOC concentrations in accordance with the TO-15 method of the US EPA.
Daniel Furuta, Bruce Wilson, Albert A. Presto, and Jiayu Li
Atmos. Meas. Tech., 17, 2103–2121, https://doi.org/10.5194/amt-17-2103-2024, https://doi.org/10.5194/amt-17-2103-2024, 2024
Short summary
Short summary
Methane is an important driver of climate change and is challenging to inexpensively sense in low atmospheric concentrations. We developed a low-cost sensor to monitor methane and tested it in indoor and outdoor settings. Our device shows promise for monitoring low levels of methane. We characterize its limitations and suggest future research directions for further development.
Audrey J. Dang, Nathan M. Kreisberg, Tyler L. Cargill, Jhao-Hong Chen, Sydney Hornitschek, Remy Hutheesing, Jay R. Turner, and Brent J. Williams
Atmos. Meas. Tech., 17, 2067–2087, https://doi.org/10.5194/amt-17-2067-2024, https://doi.org/10.5194/amt-17-2067-2024, 2024
Short summary
Short summary
The Multichannel Organics In situ enviRonmental Analyzer (MOIRA) is a new instrument for measuring speciated volatile organic compounds (VOCs) in the air and has been developed for mapping concentrations from a hybrid car. MOIRA is characterized in the lab and pilot field studies of indoor air in a single-family residence and outdoor air during a mobile deployment. Future applications include indoor, outdoor, and lab measurements to grasp the impact of VOCs on air quality, health, and climate.
Emily Wein, Lars Kalnajs, and Darin Toohey
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-34, https://doi.org/10.5194/amt-2024-34, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
We describe a low cost and small research grade spectrometer for measurements of water vapor in the boundary layer. The instrument uses small Arduino microcontrollers and inexpensive laser diodes to reduce cost while maintaining high performance comparable to more expensive instruments. Performance was assessed with intercomparisons between commercially available instruments outdoors. The design's simplicity, performance and price point allow it to be accessible to a variety of users.
Asher P. Mouat, Zelda A. Siegel, and Jennifer Kaiser
Atmos. Meas. Tech., 17, 1979–1994, https://doi.org/10.5194/amt-17-1979-2024, https://doi.org/10.5194/amt-17-1979-2024, 2024
Short summary
Short summary
Three fast-measurement formaldehyde monitors were deployed at two field sites in Atlanta, GA, over 1 year. Four different zeroing methods were tested to develop an optimal field setup as well as procedures for instrument calibration. Observations agreed well after calibration but were much higher compared to the TO-11A monitoring method, which is the golden standard. Historical HCHO concentrations were compared with measurements in this work, showing a 22 % reduction in midday HCHO since 1999.
Da Yang, Margarita Reza, Roy Mauldin, Rainer Volkamer, and Suresh Dhaniyala
Atmos. Meas. Tech., 17, 1463–1474, https://doi.org/10.5194/amt-17-1463-2024, https://doi.org/10.5194/amt-17-1463-2024, 2024
Short summary
Short summary
This paper evaluates the performance of an aircraft gas inlet. Here, we use computational fluid dynamics (CFD) and experiments to demonstrate the role of turbulence in determining sampling performance of a gas inlet and identify ideal conditions for inlet operation to minimize gas loss. Experiments conducted in a high-speed wind tunnel under near-aircraft speeds validated numerical results. We believe that the results obtained from this work will greatly inform future gas inlet studies.
Reena Macagga, Michael Asante, Geoffroy Sossa, Danica Antonijević, Maren Dubbert, and Mathias Hoffmann
Atmos. Meas. Tech., 17, 1317–1332, https://doi.org/10.5194/amt-17-1317-2024, https://doi.org/10.5194/amt-17-1317-2024, 2024
Short summary
Short summary
Using only low-cost microcontrollers and sensors, we constructed a measurement device to accurately and precisely obtain atmospheric carbon dioxide and water fluxes. The device was tested against known concentration increases and high-cost, commercial sensors during a laboratory and field experiment. We additionally tested the device over a longer period in a field study in Ghana during which the net ecosystem carbon balance and water use efficiency of maize cultivation were studied.
Matthew M. Coggon, Chelsea E. Stockwell, Megan S. Claflin, Eva Y. Pfannerstill, Lu Xu, Jessica B. Gilman, Julia Marcantonio, Cong Cao, Kelvin Bates, Georgios I. Gkatzelis, Aaron Lamplugh, Erin F. Katz, Caleb Arata, Eric C. Apel, Rebecca S. Hornbrook, Felix Piel, Francesca Majluf, Donald R. Blake, Armin Wisthaler, Manjula Canagaratna, Brian M. Lerner, Allen H. Goldstein, John E. Mak, and Carsten Warneke
Atmos. Meas. Tech., 17, 801–825, https://doi.org/10.5194/amt-17-801-2024, https://doi.org/10.5194/amt-17-801-2024, 2024
Short summary
Short summary
Mass spectrometry is a tool commonly used to measure air pollutants. This study evaluates measurement artifacts produced in the proton-transfer-reaction mass spectrometer. We provide methods to correct these biases and better measure compounds that degrade air quality.
Tianran Han, Conghui Xie, Yayong Liu, Yanrong Yang, Yuheng Zhang, Yufei Huang, Xiangyu Gao, Xiaohua Zhang, Fangmin Bao, and Shao-Meng Li
Atmos. Meas. Tech., 17, 677–691, https://doi.org/10.5194/amt-17-677-2024, https://doi.org/10.5194/amt-17-677-2024, 2024
Short summary
Short summary
This study reported an integrated UAV measurement platform for GHG monitoring and its application for emission quantification from a coking plant. The key element of this system is a newly designed air sampler, consisting of a 150 m long tube with remote-controlled time stamping. When comparing the top-down results to those derived from the bottom-up inventory method, the present findings indicate that the use of IPCC emission factors for emission calculations can lead to overestimation.
Yuening Li, Faqiang Zhan, Yushan Su, Ying Duan Lei, Chubashini Shunthirasingham, Zilin Zhou, Jonathan P. D. Abbatt, Hayley Hung, and Frank Wania
Atmos. Meas. Tech., 17, 715–729, https://doi.org/10.5194/amt-17-715-2024, https://doi.org/10.5194/amt-17-715-2024, 2024
Short summary
Short summary
A simple device for sampling gases from the atmosphere without the help of pumps was calibrated for an important group of hazardous air pollutants called polycyclic aromatic compounds (PACs). While the sampler appeared to perform well when used for relatively short periods of up to several months, some PACs were lost from the sampler during longer deployments. Sampling rates that can be used to quantitatively interpret the quantities of PACs taken up in the device have been derived.
Jiaxin Li, Kunpeng Zang, Yi Lin, Yuanyuan Chen, Shuo Liu, Shanshan Qiu, Kai Jiang, Xuemei Qing, Haoyu Xiong, Haixiang Hong, Shuangxi Fang, Honghui Xu, and Yujun Jiang
Atmos. Meas. Tech., 16, 4757–4768, https://doi.org/10.5194/amt-16-4757-2023, https://doi.org/10.5194/amt-16-4757-2023, 2023
Short summary
Short summary
Based on observed data of CO2 and CH4 and meteorological parameters over the Yellow Sea in November 2012 and June 2013, a data process and quality control method was optimized and established to filter the data influenced by multiple factors. Spatial and seasonal variations in CO2 and CH4 mixing ratios were mainly controlled by the East Asian Monsoon, while the influence of air–sea exchange was slight.
Zaneta Hamryszczak, Antonia Hartmann, Dirk Dienhart, Sascha Hafermann, Bettina Brendel, Rainer Königstedt, Uwe Parchatka, Jos Lelieveld, and Horst Fischer
Atmos. Meas. Tech., 16, 4741–4756, https://doi.org/10.5194/amt-16-4741-2023, https://doi.org/10.5194/amt-16-4741-2023, 2023
Short summary
Short summary
Hydroperoxide measurements improve the understanding of atmospheric oxidation processes. We introduce an instrumental setup for airborne measurements. The aim of the work is the characterization of the measurement method with emphasis on interferences impacting instrumental uncertainty. Technical and physical challenges do not critically impact the instrumental performance. The instrument resolves dynamic processes, such as convective transport, as shown based on the CAFE-Brazil campaign.
James F. Hurley, Alejandra Caceres, Deborah F. McGlynn, Mary E. Tovillo, Suzanne Pinar, Roger Schürch, Ksenia Onufrieva, and Gabriel Isaacman-VanWertz
Atmos. Meas. Tech., 16, 4681–4692, https://doi.org/10.5194/amt-16-4681-2023, https://doi.org/10.5194/amt-16-4681-2023, 2023
Short summary
Short summary
Volatile organic compounds (VOCs) have a wide range of sources and impacts on environments and human health that make them spatially, temporally, and chemically varied. Current methods lack the ability to collect samples in ways that provide spatial and chemical resolution without complex, costly instrumentation. We describe and validate a low-cost, portable VOC sampler and demonstrate its utility in collecting distributed coordinated samples.
Simone Brunamonti, Manuel Graf, Tobias Bühlmann, Céline Pascale, Ivan Ilak, Lukas Emmenegger, and Béla Tuzson
Atmos. Meas. Tech., 16, 4391–4407, https://doi.org/10.5194/amt-16-4391-2023, https://doi.org/10.5194/amt-16-4391-2023, 2023
Short summary
Short summary
The abundance of water vapor (H2O) in the upper atmosphere has a significant impact on the rate of global warming. We developed a new lightweight spectrometer (ALBATROSS) for H2O measurements aboard meteorological balloons. Here, we assess the accuracy and precision of ALBATROSS using metrology-grade reference gases. The results demonstrate the exceptional potential of mid-infrared laser absorption spectroscopy as a new reference method for in situ measurements of H2O in the upper atmosphere.
Roubina Papaconstantinou, Marios Demosthenous, Spyros Bezantakos, Neoclis Hadjigeorgiou, Marinos Costi, Melina Stylianou, Elli Symeou, Chrysanthos Savvides, and George Biskos
Atmos. Meas. Tech., 16, 3313–3329, https://doi.org/10.5194/amt-16-3313-2023, https://doi.org/10.5194/amt-16-3313-2023, 2023
Short summary
Short summary
In this paper, we investigate the performance of low-cost electrochemical gas sensors. We carried out yearlong measurements at a traffic air quality monitoring station, where the low-cost sensors were collocated with reference instruments and exposed to highly variable environmental conditions with extremely high temperatures and low relative humidity (RH). Sensors provide measurements that exhibit increasing errors and decreasing correlations as temperature increases and RH decreases.
Jianghanyang Li, Bianca C. Baier, Fred Moore, Tim Newberger, Sonja Wolter, Jack Higgs, Geoff Dutton, Eric Hintsa, Bradley Hall, and Colm Sweeney
Atmos. Meas. Tech., 16, 2851–2863, https://doi.org/10.5194/amt-16-2851-2023, https://doi.org/10.5194/amt-16-2851-2023, 2023
Short summary
Short summary
Monitoring a suite of trace gases in the stratosphere will help us better understand the stratospheric circulation and its impact on the earth's radiation balance. However, such measurements are rare and usually expensive. We developed an instrument that can measure stratospheric trace gases using a low-cost sampling platform (AirCore). The results showed expected agreement with aircraft measurements, demonstrating this technique provides a low-cost and robust way to observe the stratosphere.
Tara I. Yacovitch, Christoph Dyroff, Joseph R. Roscioli, Conner Daube, J. Barry McManus, and Scott C. Herndon
Atmos. Meas. Tech., 16, 1915–1921, https://doi.org/10.5194/amt-16-1915-2023, https://doi.org/10.5194/amt-16-1915-2023, 2023
Short summary
Short summary
Ethylene oxide is a toxic, carcinogenic compound used in the medical and bulk sterilization industry. Here we describe a precise and fast laser-based ethylene oxide monitor. We report months-long concentrations at a Massachusetts site, and we show how they suggest a potential emission source 35 km away. This source, and another, is confirmed by driving the instrument downwind of the sites, where concentrations were tens to tens of thousands of times greater than background levels.
Tatsumi Nakano and Takashi Morofuji
Atmos. Meas. Tech., 16, 1583–1595, https://doi.org/10.5194/amt-16-1583-2023, https://doi.org/10.5194/amt-16-1583-2023, 2023
Short summary
Short summary
We have developed a system that can automatically measure the pump efficiency of the ECC-type ozonesonde. Operational measurement for 13 years by this system revealed that the efficiency fluctuates in each and slightly increases over time. Those can affect the estimation of total ozone amount by up to 4 %. This result indicates that it is necessary to understand the tendency of the pump correction factor of each ozonesonde in order to detect the actual atmospheric change with high accuracy.
Benjamin Birner, Eric Morgan, and Ralph F. Keeling
Atmos. Meas. Tech., 16, 1551–1561, https://doi.org/10.5194/amt-16-1551-2023, https://doi.org/10.5194/amt-16-1551-2023, 2023
Short summary
Short summary
Atmospheric variations of helium (He) and CO2 are strongly linked due to the co-release of both gases from natural-gas burning. This implies that atmospheric He measurements may be a potentially powerful tool for verifying reported anthropogenic natural-gas usage. Here, we present the development and initial results of a novel measurement system of atmospheric He that paves the way for establishing a global monitoring network in the future.
John W. Halfacre, Jordan Stewart, Scott C. Herndon, Joseph R. Roscioli, Christoph Dyroff, Tara I. Yacovitch, Michael Flynn, Stephen J. Andrews, Steven S. Brown, Patrick R. Veres, and Pete M. Edwards
Atmos. Meas. Tech., 16, 1407–1429, https://doi.org/10.5194/amt-16-1407-2023, https://doi.org/10.5194/amt-16-1407-2023, 2023
Short summary
Short summary
This study details a new sampling method for the optical detection of hydrogen chloride (HCl). HCl is an important atmospheric reservoir for chlorine atoms, which can affect nitrogen oxide cycling and the lifetimes of volatile organic compounds and ozone. However, HCl has a high affinity for interacting with surfaces, thereby preventing fast, quantitative measurements. The sampling technique in this study minimizes these surface interactions and provides a high-quality measurement of HCl.
Henning Finkenzeller, Denis Pöhler, Martin Horbanski, Johannes Lampel, and Ulrich Platt
Atmos. Meas. Tech., 16, 1343–1356, https://doi.org/10.5194/amt-16-1343-2023, https://doi.org/10.5194/amt-16-1343-2023, 2023
Short summary
Short summary
Optical resonators enhance the light path in compact instruments, thereby improving their sensitivity. Determining the established path length in the instrument is a prerequisite for the accurate determination of trace gas concentrations but can be a significant complication in the use of such resonators. Here we show two calibration techniques which are relatively simple and free of consumables but still provide accurate calibrations. This facilitates the use of optical resonators.
Andrew W. Seidl, Harald Sodemann, and Hans Christian Steen-Larsen
Atmos. Meas. Tech., 16, 769–790, https://doi.org/10.5194/amt-16-769-2023, https://doi.org/10.5194/amt-16-769-2023, 2023
Short summary
Short summary
It is challenging to make field measurements of stable water isotopes in the Arctic. To this end, we present a modular stable-water-isotope analyzer profiling system. The system operated for a 2-week field campaign on Svalbard during the Arctic winter. We evaluate the system’s performance and analyze any potential impact that the field conditions might have had on the isotopic measurements and the system's ability to resolve isotope gradients in the lowermost layer of the atmosphere.
Daan Swart, Jun Zhang, Shelley van der Graaf, Susanna Rutledge-Jonker, Arjan Hensen, Stijn Berkhout, Pascal Wintjen, René van der Hoff, Marty Haaima, Arnoud Frumau, Pim van den Bulk, Ruben Schulte, Margreet van Zanten, and Thomas van Goethem
Atmos. Meas. Tech., 16, 529–546, https://doi.org/10.5194/amt-16-529-2023, https://doi.org/10.5194/amt-16-529-2023, 2023
Short summary
Short summary
During a 5-week comparison campaign, we tested two set-ups to measure half hourly ammonia fluxes. The eddy covariance and flux gradient systems showed very similar results when the upwind terrain was both homogeneous and free of obstacles. We discuss the technical performance and practical limitations of both systems. Measurements from these instruments can facilitate the study of processes behind ammonia deposition, an important contributor to eutrophication and acidificationin natural areas.
Suding Yang, Xin Li, Limin Zeng, Xuena Yu, Ying Liu, Sihua Lu, Xiaofeng Huang, Dongmei Zhang, Haibin Xu, Shuchen Lin, Hefan Liu, Miao Feng, Danlin Song, Qinwen Tan, Jinhui Cui, Lifan Wang, Ying Chen, Wenjie Wang, Haijiong Sun, Mengdi Song, Liuwei Kong, Yi Liu, Linhui Wei, Xianwu Zhu, and Yuanhang Zhang
Atmos. Meas. Tech., 16, 501–512, https://doi.org/10.5194/amt-16-501-2023, https://doi.org/10.5194/amt-16-501-2023, 2023
Short summary
Short summary
Vertical observation of volatile organic compounds (VOCs) is essential to study the spatial distribution and evolution patterns of VOCs in the planetary boundary layer (PBL). This paper describes multi-channel whole-air sampling equipment onboard an unmanned aerial vehicle (UAV) for near-continuous VOC vertical observation. Vertical profiles of VOCs and trace gases during the evolution of the PBL in south-western China have been successfully obtained by deploying the newly developed UAV system.
Tobias Schuldt, Georgios I. Gkatzelis, Christian Wesolek, Franz Rohrer, Benjamin Winter, Thomas A. J. Kuhlbusch, Astrid Kiendler-Scharr, and Ralf Tillmann
Atmos. Meas. Tech., 16, 373–386, https://doi.org/10.5194/amt-16-373-2023, https://doi.org/10.5194/amt-16-373-2023, 2023
Short summary
Short summary
We report in situ measurements of air pollutant concentrations within the planetary boundary layer on board a Zeppelin NT in Germany. We highlight the in-flight evaluation of electrochemical sensors that were installed inside a hatch box located on the bottom of the Zeppelin. Results from this work emphasize the potential of these sensors for other in situ airborne applications, e.g., on board unmanned aerial vehicles (UAVs).
Leigh S. Fleming, Andrew C. Manning, Penelope A. Pickers, Grant L. Forster, and Alex J. Etchells
Atmos. Meas. Tech., 16, 387–401, https://doi.org/10.5194/amt-16-387-2023, https://doi.org/10.5194/amt-16-387-2023, 2023
Short summary
Short summary
Measurements of atmospheric O2 can help constrain the carbon cycle processes and quantify fossil fuel CO2 emissions; however, measurement of atmospheric O2 is very challenging, and existing analysers are complex systems to build and maintain. We have tested a new O2 analyser (Picarro Inc. G2207-i) in the laboratory and at Weybourne Atmospheric Observatory. We have found that the G2207-i does not perform as well as an existing O2 analyser from Sable Systems Inc.
Siegfried Schobesberger, Emma L. D'Ambro, Lejish Vettikkat, Ben H. Lee, Qiaoyun Peng, David M. Bell, John E. Shilling, Manish Shrivastava, Mikhail Pekour, Jerome Fast, and Joel A. Thornton
Atmos. Meas. Tech., 16, 247–271, https://doi.org/10.5194/amt-16-247-2023, https://doi.org/10.5194/amt-16-247-2023, 2023
Short summary
Short summary
We present a new, highly sensitive technique for measuring atmospheric ammonia, an important trace gas that is emitted mainly by agriculture. We deployed the instrument on an aircraft during research flights over rural Oklahoma. Due to its fast response, we could analyze correlations with turbulent winds and calculate ammonia emissions from nearby areas at 1 to 2 km resolution. We observed high spatial variability and point sources that are not resolved in the US National Emissions Inventory.
Birger Bohn and Insa Lohse
Atmos. Meas. Tech., 16, 209–233, https://doi.org/10.5194/amt-16-209-2023, https://doi.org/10.5194/amt-16-209-2023, 2023
Short summary
Short summary
Optical receivers for solar spectral actinic radiation are designed for angle-independent sensitivities within a hemisphere. Remaining imperfections can be compensated for by receiver-specific corrections based on laboratory characterizations and radiative transfer calculations of spectral radiance distributions. The corrections cover a wide range of realistic atmospheric conditions and were applied to ground-based and airborne measurements in a wavelength range 280–660 nm.
Teles C. Furlani, RenXi Ye, Jordan Stewart, Leigh R. Crilley, Peter M. Edwards, Tara F. Kahan, and Cora J. Young
Atmos. Meas. Tech., 16, 181–193, https://doi.org/10.5194/amt-16-181-2023, https://doi.org/10.5194/amt-16-181-2023, 2023
Short summary
Short summary
This study describes a new technique to measure total gaseous chlorine, which is the sum of gas-phase chlorine-containing chemicals. The method converts any chlorine-containing molecule to hydrogen chloride that can be detected in real time using a cavity ring-down spectrometer. The new method was validated through laboratory experiments, as well as by making measurements of ambient outdoor air and indoor air during cleaning with a chlorine-based cleaner.
Anas Emad and Lukas Siebicke
Atmos. Meas. Tech., 16, 29–40, https://doi.org/10.5194/amt-16-29-2023, https://doi.org/10.5194/amt-16-29-2023, 2023
Short summary
Short summary
The true eddy accumulation (TEA) method enables measuring atmospheric exchange with slow-response gas analyzers. TEA is formulated assuming ideal conditions with a zero mean vertical wind velocity during the averaging interval. This core assumption is rarely valid under field conditions. Here, we extend the TEA equation to accommodate nonideal conditions. The new equation allows constraining the systematic error term in the measured fluxes and the possibility to minimize or remove it.
Anas Emad and Lukas Siebicke
Atmos. Meas. Tech., 16, 41–55, https://doi.org/10.5194/amt-16-41-2023, https://doi.org/10.5194/amt-16-41-2023, 2023
Short summary
Short summary
A new micrometeorological method to measure atmospheric exchange is proposed, and a prototype sampler is evaluated. The new method, called short-time eddy accumulation, is a variant of the eddy accumulation method, which is suited for use with slow gas analyzers. The new method enables adaptive time-varying accumulation intervals, which brings many advantages to flux measurements such as an improved dynamic range and the ability to run eddy accumulation in a continuous flow-through mode.
Lu Xu, Matthew M. Coggon, Chelsea E. Stockwell, Jessica B. Gilman, Michael A. Robinson, Martin Breitenlechner, Aaron Lamplugh, John D. Crounse, Paul O. Wennberg, J. Andrew Neuman, Gordon A. Novak, Patrick R. Veres, Steven S. Brown, and Carsten Warneke
Atmos. Meas. Tech., 15, 7353–7373, https://doi.org/10.5194/amt-15-7353-2022, https://doi.org/10.5194/amt-15-7353-2022, 2022
Short summary
Short summary
We describe the development and operation of a chemical ionization mass spectrometer using an ammonium–water cluster (NH4+·H2O) as a reagent ion. NH4+·H2O is a highly versatile reagent ion for measurements of a wide range of oxygenated organic compounds. The major product ion is the cluster with NH4+ produced via ligand-switching reactions. The instrumental sensitivities of analytes depend on the binding energy of the analyte–NH4+ cluster; sensitivities can be estimated using voltage scanning.
Cited articles
Abera, A., Mattisson, K., Eriksson, A., Ahlberg, E., Sahilu, G., Mengistie, B., Bayih, A. G., Aseffaa, A., Malmqvist, E., and Isaxon, C: Air pollution measurements and land-use regression in urban sub-Saharan Africa using low-cost sensors – Possibilities and pitfalls, Atmosphere, 11, 1357, https://doi.org/10.3390/atmos11121357, 2020.
Adamu, A., Arifalo, K. M., and Abulude, F. O.: Indoor air quality assessment using a low-cost sensor: A case study in ikere-ekiti, nigeria, Engineering Proceedings, 58, 42, https://doi.org/10.3390/ecsa-10-16021, 2023.
Afghah, F., Razi, A., Chakareski, J., and Ashdown, J.: Wildfire Monitoring in Remote Areas using Autonomous Unmanned Aerial Vehicles, in: IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, Paris, France, 29 April–2 May 2019, IEEE, 835–840, https://doi.org/10.1109/INFCOMW.2019.8845309, 2019.
Agrawal, G., Mohan, D., and Rahman, H.: Ambient air pollution in selected small cities in India: Observed trends and future challenges, IATSS Research, 45, 19–30, https://doi.org/10.1016/j.iatssr.2021.03.004, 2021.
AGU: AGU Fall Meeting 2022, Chicago, IL, 12–16 December 2022, https://www.agu.org/fall-meeting-2022 (last access: 17 September 2023), 2022.
Aguiar, E. F. K., Roig, H. L., Mancini, L. H., and and de Carvalho, E. N. C. B.: Low-cost sensors calibration for monitoring air quality in the federal district – Brazil, Journal of Environmental Protection, 6, 173–189, https://doi.org/10.4236/jep.2015.62019, 2015.
Aguilera, F., Layana, S., Rojas, F., Arratia, P., Wilkes, T. C., González, C., Inostroza, M., McGonigle, A. J. S., Pering, T. D., and Ureta, G.: First measurements of gas flux with a low-cost smartphone sensor-based UV camera on the volcanoes of northern Chile, Remote Sens.-Basel, 12, 2122, https://doi.org/10.3390/rs12132122, 2020.
AirCare: Free air quality and pollen tracking app, https://getaircare.com/, last access: 10 March 2024.
AirGradient: https://www.airgradient.com/, last access: 26 August 2024.
Airly: Data platform and monitors, https://airly.org/en/, last access: 10 March 2024a.
Airly: Quality & certificates, https://airly.org/en/features/quality-
and-certificates/, last access: 10 March 2024b.
Air Matters: https://air-matters.com/, last access: 10 March 2024.
AirNow: https://www.airnow.gov/, last access: 10 March 2024a.
AirNow: Fire and Smoke Map, https://fire.airnow.gov/, last access: 10 March 2024b.
AirNow: Fire and Smoke Map – Getting Started, https://document.airnow.gov/airnow-fire-and-smoke-map-getting-started.pdf, last access: 10 March 2024c.
AiREAS: Real time measurements, https://aireas.com/en/real-
time-measurements/, last access: 25 October 2024.
AIRU: https://airu.coe.utah.edu/, last access: 9 March 2024.
AirWatchSTL: https://airwatchstl.mcustlouis.org/, last access: 9 March 2024.
Alexander, D. A., Northcross, A., Karrison, T., Morhasson-Bello, O., Wilson, N., Atalabi, O. M., Dutta, A., Adu, D., Ibigbami, T., Olamijulo, J., Adepoju, D., Ojengbede, O., and Olopade, C. O.: Pregnancy outcomes and ethanol cook stove intervention: A randomized-controlled trial in Ibadan, Nigeria, Environ. Int., 111, 152–163, https://doi.org/10.1016/j.envint.2017.11.021, 2018.
Alford, K. L. and Kumar, N.: Pulmonary health effects of indoor volatile organic compounds – A meta-analysis, Int. J. Env. Res. Pub. He., 18, 1578, https://doi.org/10.3390/ijerph18041578, 2021.
Al-Hajjaji, K., Ezzin, M., Khamdan, H., Hassani, A. E., and Zorba, N.: Design, development and evaluation of a UAV to study air quality in Qatar, arXiv [preprint], https://doi.org/10.48550/arXiv.1709.05628, 17 September 2017.
Alvear-Puertas, V. E., Burbano-Prado, Y. A., Rosero-Montalvo, P. D., Tözün, P., Marcillo, F., and Hernandez, W.: Smart and portable air-quality monitoring IOT low-cost devices in Ibarra city, Ecuador, Sensors, 22, 7015, https://doi.org/10.3390/s22187015, 2022.
Amegah, A. K.: Proliferation of low-cost sensors. What prospects for air pollution epidemiologic research in Sub-Saharan Africa?, Environ. Pollut., 241, 1132–1137, https://doi.org/10.1016/j.envpol.2018.06.044, 2018.
AQMesh: Outdoor air quality monitoring system, https://www.aqmesh.com/, last access: 1 September 2024.
Arnold, C., Harms, M., and Goschnick, J.: Air quality monitoring and fire detection with the Karlsruhe electronic micronose KAMINA, IEEE Sens. J., 2, 179–188, https://doi.org/10.1109/JSEN.2002.800681, 2002.
Awokola, B., Okello, G., Johnson, O., Dobson, R., Ouédraogo, A. R., Dibba, B., Ngahane, M., Ndukwu, C., Agunwa, C., Marangu, D., Lawin, H., Ogugua, I., Eze, J., Nwosu, N., Ofiaeli, O., Ubuane, P., Osman, R., Awokola, E., Erhart, A., Mortimer, K., Jewell, C., and Semple, S.: Longitudinal ambient PM2.5 measurement at fifteen locations in eight sub-Saharan African countries using low-cost sensors, Atmosphere, 13, 1593, https://doi.org/10.3390/atmos13101593, 2022.
Awokola, B. I., Okello, G., Mortimer, K. J., Jewell, C. P., Erhart, A., and Semple, S.: Measuring air quality for advocacy in africa (MA3): Feasibility and practicality of longitudinal ambient PM2.5 measurement using low-cost sensors, Int. J. Env. Res. Pub. He., 17, 7243, https://doi.org/10.3390/ijerph17197243, 2020.
Badura, M., Batog, P., Drzeniecka-Osiadacz, A., and Modzel, P.: Low- and medium-cost sensors for tropospheric ozone monitoring – Results of an evaluation study in Wrocław, Poland, Atmosphere, 13, 542, https://doi.org/10.3390/atmos13040542, 2022.
Bahino, J., Giordano, M., Yoboué, V., Ochou, A., Galy-Lacaux, C., Liousse, C., Amegah, K., Hugues, A., Nimo, J., Beekmann, M., and Subramanian, R.: MOPGA/Improving Air Quality in West Africa: Low-cost sensors as a solution to improve the understanding of spatial and temporal variability in urban air pollution, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8210, https://doi.org/10.5194/egusphere-egu21-8210, 2021.
Bainomugisha, E., Ssematimba, J., and Okure, D.: Design considerations for a distributed low-cost air quality sensing system for urban environments in low-resource settings, Atmosphere, 14, 354, https://doi.org/10.3390/atmos14020354, 2023.
Bales, E., Nikzad, N., Quick, N., Ziftci, C., Patrick, K., and Griswold, W.: CitiSense: Mobile air quality sensing for individuals and communities. Design and deployment of the CitiSense mobile air-quality system, in: Proceedings of the 6th International Conference on Pervasive Computing Technologies for Healthcare, 6th International Conference on Pervasive Computing Technologies for Healthcare, San Diego, United States, 21–24 May 2012, IEEE, https://doi.org/10.4108/icst.pervasivehealth.2012.248724, 2012.
Balogun, I. A., Balogun, A. A., and Adegoke, J.: Carbon monoxide concentration monitoring in Akure – A comparison between urban and rural environment, Journal of Environmental Protection, 5, 266–273, https://doi.org/10.4236/jep.2014.54030, 2014.
Barcelo-Ordinas, J. M., Ferrer-Cid, P., Garcia-Vidal, J., Ripoll, A., and Viana, M.: Distributed multi-scale calibration of low-cost ozone sensors in wireless sensor networks, Sensors, 19, 2503, https://doi.org/10.3390/s19112503, 2019.
Barcelo-Ordinas, J. M., Ferrer-Cid, P., Garcia-Vidal, J., Viana, M., and Ripoll, A.: H2020 project CAPTOR dataset: Raw data collected by low-cost MOX ozone sensors in a real air pollution monitoring network, Data in Brief, 36, 107127, https://doi.org/10.1016/j.dib.2021.107127, 2021.
Barkjohn, K. K., Gantt, B., and Clements, A. L.: Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensor, Atmos. Meas. Tech., 14, 4617–4637, https://doi.org/10.5194/amt-14-4617-2021, 2021.
Barkjohn, K. K., Holder, A. L., Frederick, S. G., and Clements, A. L.: Correction and accuracy of PurpleAir PM2.5 measurements for extreme wildfire smoke, Sensors, 22, 9669, https://doi.org/10.3390/s22249669, 2022.
Barot, V., Kapadia, V., and Pandya, S.: QOS enabled IOT based low cost air quality monitoring system with power consumption optimization, Cybernetics and Information Technologies, 20, 122–140, https://doi.org/10.2478/cait-2020-0021, 2020.
Bart, M., Williams, D. E., Ainslie, B., McKendry, I., Salmond, J., Grange, S. K., Alavi-Shoshtari, M., Steyn, D., and Henshaw, G. S.: High density ozone monitoring using gas sensitive semi-conductor sensors in the lower Fraser Valley, British Columbia, Environm. Sci. Technol., 48, 3970–3977, https://doi.org/10.1021/es404610t, 2014.
Bastviken, D., Nygren, J., Schenk, J., Parellada Massana, R., and Duc, N. T.: Technical note: Facilitating the use of low-cost methane (CH4) sensors in flux chambers – calibration, data processing, and an open-source make-it-yourself logger, Biogeosciences, 17, 3659–3667, https://doi.org/10.5194/bg-17-3659-2020, 2020.
BEACO2N: http://beacon.berkeley.edu/, last access: 10 March 2024.
Becnel, T. and Gaillardon, P.-E.: A deep learning approach to sensor fusion inference at the edge, in: 2021 Design, Automation and Test in Europe Conference and Exhibition (DATE), Grenoble, France, 1–5 February 2021, IEEE, 1420–1425, https://doi.org/10.23919/DATE51398.2021.9474178, 2021.
Becnel, T., Sayahi, T., Kelly, K., and Gaillardon, P.-E.: A recursive approach to partially blind calibration of a pollution sensor network, in: 2019 IEEE International Conference on Embedded Software and Systems (ICESS), Las Vegas, NV, USA, 2–3 June 2019, IEEE, 1–8, https://doi.org/10.1109/ICESS.2019.8782523, 2019a.
Becnel, T., Tingey, K., Whitaker, J., Sayahi, T., Lê, K., Goffin, P., Butterfield, A., Kelly, K., and Gaillardon, P.-E.: A distributed low-cost pollution monitoring platform, IEEE Internet Things, 6, 10738–10748, https://doi.org/10.1109/JIOT.2019.2941374, 2019b.
Bettair cities: https://bettaircities.com/, last access: 10 March 2024.
Bittner, A. S., Cross, E. S., Hagan, D. H., Malings, C., Lipsky, E., and Grieshop, A. P.: Performance characterization of low-cost air quality sensors for off-grid deployment in rural Malawi, Atmos. Meas. Tech., 15, 3353–3376, https://doi.org/10.5194/amt-15-3353-2022, 2022.
Bobbia, M., Poggi, J., and Portier, B.: Spatial correction of low-cost sensors observations for fusion of air quality measurements, Appl. Stoch. Model. Bus., 38, 766–786, https://doi.org/10.1002/asmb.2713, 2022.
Borrego, C., Costa, A. M., Ginja, J., Amorim, M., Coutinho, M., Karatzas, K., Sioumis, Th., Katsifarakis, N., Konstantinidis, K., De Vito, S., Esposito, E., Smith, P., André, N., Gérard, P., Francis, L. A., Castell, N., Schneider, P., Viana, M., Minguillón, M. C., Reimringer, W., Otjes, R. P., von Sicard, O., Pohle, R., Elen, B., Suriano, D., Pfister, V., Prato, M., Dipinto, S., and Penza, M.: Assessment of air quality microsensors versus reference methods: The EuNetAir joint exercise, Atmos. Environ., 147, 246–263, https://doi.org/10.1016/j.atmosenv.2016.09.050, 2016.
Brauer, M., Guttikunda, S. K., K A, Nishad, Dey, S., Tripathi, S. N., Weagle, C., and Martin, R. V.: Examination of monitoring approaches for ambient air pollution: A case study for India, Atmos. Environ., 216, 116940, https://doi.org/10.1016/j.atmosenv.2019.116940, 2019.
Brilli, L., Berton, A., Carotenuto, F., Gioli, B., Gualtieri, G., Martelli, F., Profeti, S., Trombi, G., Dibari, C., Moriondo, M., Vagnoli, C., and Zaldei, A.: Innovative low-cost air quality stations as a supporting means for road traffic regulations in urban areas, IOP Conf. Ser.-Earth Environ. Sci., 489, 012023, https://doi.org/10.1088/1755-1315/489/1/012023, 2020.
Brilli, L., Carotenuto, F., Gioli, B., Berton, A., Profeti, S., Gualtieri, G., Andreini, B. P., Stefanelli, M., Martelli, F., Vagnoli, C., and Zaldei, A.: An integrated low-cost monitoring platform to assess air quality over large areas, in: Proceedings of the Future Technologies Conference (FTC) 2020, edited by: Arai, K., Kapoor, S., and Bhatia, R., Springer International Publishing, 2, 965–975, https://doi.org/10.1007/978-3-030-63089-8_63, 2021.
Brynda, P., Kopřiva, J., and Horák, M.: Trafficsensnet sensor network for measuring emissions from transportation, Procedia Engineer., 120, 902–907, https://doi.org/10.1016/j.proeng.2015.08.781, 2015.
Brynda, P., Kosová, Z., and Kopřiva, J.: Mobile sensor unit for online air quality monitoring, in: 2016 Smart Cities Symposium Prague (SCSP), Prague, Czech Republic, 26–27 May 2016, IEEE, 1–4, https://doi.org/10.1109/SCSP.2016.7501028, 2016.
Brynda, P., Honzík, P., Kosová, Z., and Šimonová, K.: Experience from the pilot project of the air quality sensor network in Litoměřice, in: 2020 Smart City Symposium Prague (SCSP), Prague, Czech Republic, 25–25 June 2020, IEEE, 1–6, https://doi.org/10.1109/SCSP49987.2020.9133785, 2020.
Brzeziński, M., Sałach, K., and Wroński, M.: Wealth inequality in Central and Eastern Europe: Evidence from household survey and rich lists' data combined∗, Economics of Transition and Institutional Change, 28, 637–660, https://doi.org/10.1111/ecot.12257, 2020.
Bushnaq, O. M., Chaaban, A., and Al-Naffouri, T.: The Role of UAV-IoT Networks in Future Wildfire Detection, IEEE Internet Things, 8, 23, https://doi.org/10.1109/JIOT.2021.3077593, 2021.
Byrne, R., Ryan, K., Venables, D. S., Wenger, J. C., and Hellebust, S.: Highly local sources and large spatial variations in PM2.5 across a city: evidence from a city-wide sensor network in Cork, Ireland, Environmental Science: Atmospheres, 3, 919–930, https://doi.org/10.1039/D2EA00177B, 2023.
California Air Resources Board: National Ambient Air Quality Standards, https://ww2.arb.ca.gov/resources/national-ambient-air-quality-standards, last access: 17 September 2023.
Campmier, M. J., Gingrich, J., Singh, S., Baig, N., Gani, S., Upadhya, A., Agrawal, P., Kushwaha, M., Mishra, H. R., Pillarisetti, A., Vakacherla, S., Pathak, R. K., and Apte, J. S.: Seasonally optimized calibrations improve low-cost sensor performance: long-term field evaluation of PurpleAir sensors in urban and rural India, Atmos. Meas. Tech., 16, 4357–4374, https://doi.org/10.5194/amt-16-4357-2023, 2023.
Camprodon, G., González, Ó., Barberán, V., Pérez, M., Smári, V., de Heras, M. Á., and Bizzotto, A.: Smart Citizen Kit and Station: An open environmental monitoring system for citizen participation and scientific experimentation, HardwareX, 6, e00070, https://doi.org/10.1016/j.ohx.2019.e00070, 2019.
CAMS-Net (Clean Air Monitoring and Solutions Network): https://camsnet.org/, last access: 10 March 2024.
Candia, A., Represa, S. N., Giuliani, D., Luengo, M. Á., Porta, A. A., and Marrone, L. A.: Solutions for SmartCities: Proposal of a monitoring system of air quality based on a LoRaWAN network with low-cost sensors, in: 2018 Congreso Argentino de Ciencias de La Informática y Desarrollos de Investigación (CACIDI), Buenos Aires, Argentina, 28–30 November 2018, IEEE, 1–6, https://doi.org/10.1109/CACIDI.2018.8584183, 2018.
Čapek, S. M.: The “environmental justice” frame: A conceptual discussion and an application, Soc. Probl., 40, 5–24, https://doi.org/10.2307/3097023, 1993.
Carotenuto, F., Brilli, L., Gioli, B., Gualtieri, G., Vagnoli, C., Mazzola, M., Viola, A. P., Vitale, V., Severi, M., Traversi, R., and Zaldei, A.: Long-term performance assessment of low-cost atmospheric sensors in the arctic environment, Sensors, 20, 1919, https://doi.org/10.3390/s20071919, 2020.
Carotenuto, F., Bisignano, A., Brilli, L., Gualtieri, G., and Giovannini, L.: Low-cost air quality monitoring networks for long-term field campaigns: A review, Meteorol. Appl., 30, e2161, https://doi.org/10.1002/met.2161, 2023.
Carvalho, H.: The air we breathe: Differentials in global air quality monitoring, Lancet Resp. Med., 4, 603–605, https://doi.org/10.1016/S2213-2600(16)30180-1, 2016.
Casey, J. G., Collier-Oxandale, A., and Hannigan, M.: Performance of artificial neural networks and linear models to quantify 4 trace gas species in an oil and gas production region with low-cost sensors, Sensor. Actuat. B-Chem., 283, 504–514, https://doi.org/10.1016/j.snb.2018.12.049, 2019.
Castell, N., Dauge, F. R., Schneider, P., Vogt, M., Lerner, U., Fishbain, B., Broday, D., and Bartonova, A.: Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates?, Environ. Int., 99, 293–302, https://doi.org/10.1016/j.envint.2016.12.007, 2017.
Castell, N., Schneider, P., Grossberndt, S., Fredriksen, Mirjam. F., Sousa-Santos, G., Vogt, M., and Bartonova, A.: Localized real-time information on outdoor air quality at kindergartens in Oslo, Norway using low-cost sensor nodes, Environ. Res., 165, 410–419, https://doi.org/10.1016/j.envres.2017.10.019, 2018.
Chai, T., Kim, H., Pan, L., Lee, P., and Tong, D.: Impact of moderate resolution imaging spectroradiometer aerosol optical depth and AirNow PM2.5 assimilation on community multi-scale air quality aerosol predictions over the contiguous united states, J. Geophys. Res.-Atmos., 122, 5399–5415, https://doi.org/10.1002/2016JD026295, 2017.
Chang, J. B., Liu, V., Subramanian, V., Sivula, K., Luscombe, C., Murphy, A., Liu, J., and Fréchet, J. M. J.: Printable polythiophene gas sensor array for low-cost electronic noses, J. Appl. Phys., 100, 014506, https://doi.org/10.1063/1.2208743, 2006.
Chatzidiakou, L., Archer, R., Beale, V., Bland, S., Carter, H., Castro-Faccetti, C., Edwards, H., Finneran, J., Hama, S., Jones, R. L., Kumar, P., Linden, P. F., Rawat, N., Roberts, K., Symons, C., Vouriot, C., Wang, D., Way, L., West, S., Weston, D., Williams, N., Wood, S., and Burridge, H. C.: Schools' air quality monitoring for health and education: Methods and protocols of the SAMHE initiative and project, Developments in the Built Environment, 16, 100266, https://doi.org/10.1016/j.dibe.2023.100266, 2023.
Cheadle, L., Deanes, L., Sadighi, K., Gordon Casey, J., Collier-Oxandale, A., and Hannigan, M.: Quantifying neighborhood-scale spatial variations of ozone at open space and urban sites in Boulder, Colorado using low-cost sensor technology, Sensors, 17, 2072, https://doi.org/10.3390/s17092072, 2017.
Chen, L. C. and Lippmann, M.: Effects of metals within ambient air particulate matter (PM) on human health, Inhal. Toxicol., 21, 1–31, https://doi.org/10.1080/08958370802105405, 2009.
Chen, W., Yang, Y., Mei, H., Sun, H., Louie, P. K. K., Jiang, S. Y., and Ning, Z.: Analysis of an ozone episode in the Greater Bay Area based on low-cost sensor network, Atmos. Environ., 322, 120367, https://doi.org/10.1016/j.atmosenv.2024.120367, 2024.
Cheng, C., Messerschmidt, L., Bravo, I., Waldbauer, M., Bhavikatti, R., Schenk, C., Grujic, V., Model, T., Kubinec, R., and Barceló, J.: A general primer for data harmonization, Scientific Data, 11, 152, https://doi.org/10.1038/s41597-024-02956-3, 2024.
Cheng, S., Chang-Chien, G.-P., Huang, Q., Zhang, Y.-B., Yan, P., Zhang, J., Wang, Y., Zhang, D., and Teng, G.: Global research trends in health effects of volatile organic compounds during the last 16 years: A bibliometric analysis, Aerosol Air Qual. Res., 19, 1834–1843, https://doi.org/10.4209/aaqr.2019.06.0327, 2019.
Children's Health Alliance of Wisconsin: Love my air Wisconsin, https://www.chawisconsin.org/initiatives/environmental-health/air-quality/, last access: 10 March 2024.
Clarity Movement Co.: https://www.clarity.io/, last access: 10 March 2024a.
Clarity Movement Co.: Open map, https://openmap.clarity.io/, last access: 9 March 2024b.
Coalition for Clean Air: https://www.ccair.org/, last access: 17 September 2023.
Coker, E. S., Buralli, R., Manrique, A. F., Kanai, C. M., Amegah, A. K., and Gouveia, N.: Association between PM2.5 and respiratory hospitalization in Rio Branco, Brazil: Demonstrating the potential of low-cost air quality sensor for epidemiologic research, Environ. Res., 214, 113738, https://doi.org/10.1016/j.envres.2022.113738, 2022.
Collier-Oxandale, A., Casey, J. G., Piedrahita, R., Ortega, J., Halliday, H., Johnston, J., and Hannigan, M. P.: Assessing a low-cost methane sensor quantification system for use in complex rural and urban environments, Atmos. Meas. Tech., 11, 3569–3594, https://doi.org/10.5194/amt-11-3569-2018, 2018a.
Collier-Oxandale, A., Coffey, E., Thorson, J., Johnston, J., and Hannigan, M.: Comparing building and neighborhood-scale variability of CO2 and O3 to inform deployment considerations for low-cost sensor system use, Sensors, 18, 1349, https://doi.org/10.3390/s18051349, 2018b.
Collier-Oxandale, A., Feenstra, B., Papapostolou, V., Zhang, H., Kuang, M., Der Boghossian, B., and Polidori, A.: Field and laboratory performance evaluations of 28 gas-phase air quality sensors by the AQ-SPEC program, Atmos. Environ., 220, 117092, https://doi.org/10.1016/j.atmosenv.2019.117092, 2020a.
Collier-Oxandale, A., Wong, N., Navarro, S., Johnston, J., and Hannigan, M.: Using gas-phase air quality sensors to disentangle potential sources in a Los Angeles neighborhood, Atmos. Environ., 233, 117519, https://doi.org/10.1016/j.atmosenv.2020.117519, 2020b.
Connerton, P., Nogueira, T., Kumar, P., and Ribeiro, H.: Use of low-cost sensors for environmental health surveillance: Wildfire-related particulate matter detection in Brasília, Brazil, Atmosphere, 14, 1796, https://doi.org/10.3390/atmos14121796, 2023.
Cross, E. S., Williams, L. R., Lewis, D. K., Magoon, G. R., Onasch, T. B., Kaminsky, M. L., Worsnop, D. R., and Jayne, J. T.: Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements, Atmos. Meas. Tech., 10, 3575–3588, https://doi.org/10.5194/amt-10-3575-2017, 2017.
David, C. M., River, Q. T., Jorge, R. M., Andres, J. K., and Guillermo, G. L.: A low-cost, rapid-deployment and energy-autonomous wireless sensor network for air quality monitoring, in: 2015 9th International Conference on Sensing Technology (ICST), Auckland, New Zealand, 8–10 December 2015, 122–127, https://doi.org/10.1109/ICSensT.2015.7438376, 2015.
deSouza, P., Nthusi, V., Klopp, J., Shaw, B., Ho, W., Saffell, J., Jones, R., and Ratti, C.: A Nairobi experiment in using low cost air quality monitors, Clean Air Journal, 27, https://doi.org/10.17159/2410-972X/2017/v27n2a6, 2017.
Dewage, P. M. H., Wijeratne, L. O. H., Yu, X., Iqbal, M., Balagopal, G., Waczak, J., Fernando, A., Lary, M. D., Ruwali, S., and Lary, D. J.: Providing Fine Temporal and Spatial Resolution Analyses of Airborne Particulate Matter Utilizing Complimentary In Situ IoT Sensor Network and Remote Sensing Approaches, Remote Sens.-Basel, 16, 2454, https://doi.org/10.3390/rs16132454, 2024.
Dirienzo, N., Mitchell, K., Forde, M., Rainham, D., and Villeneuve, P. J.: Temporal trends in ambient fine particulate matter and the impacts of COVID-19 on this pollutant in Grenada, West Indies, J. Air Waste Manage., 73, 97–108, https://doi.org/10.1080/10962247.2022.2126555, 2023.
Donaldson, K., Mills, N., MacNee, W., Robinson, S., and Newby, D.: Role of inflammation in cardiopulmonary health effects of PM, Toxicol. Appl. Pharm., 207, 483–488, https://doi.org/10.1016/j.taap.2005.02.020, 2005.
Drajic, D. D. and Gligoric, N. R.: Reliable low-cost air quality monitoring using off-the-shelf sensors and statistical calibration, Elektron. Elektrotech., 26, 32–41, https://doi.org/10.5755/j01.eie.26.2.25734, 2020.
EGU: Monitoring Networks, Session GI1.3, EGU General Assembly, Vienna, Austria, 23–28 April 2023, https://meetingorganizer.copernicus.org/EGU23/session/45206, last access: 18 September 2023.
ekoNET: https://ekonet.solutions/air-monitoring, last access: 9 March 2024.
Ellona: https://www.ellona.io/, last access: 10 March 2024a.
Ellona: Ellona customer cases: https://www.ellona.io/customer- case/, last access: 10 March 2024b.
Engel-Cox, J., Kim Oanh, N. T., van Donkelaar, A., Martin, R. V., and Zell, E.: Toward the next generation of air quality monitoring: Particulate Matter, Atmos. Environ., 80, 584–590, https://doi.org/10.1016/j.atmosenv.2013.08.016, 2013.
Envirowatch Ltd.: E-MOTE, http://www.envirowatch.ltd.uk/e-mote/, last access: 10 March 2024.
Fahim, M., El Mhouti, A., Boudaa, T., and Jakimi, A.: Modeling and implementation of a low-cost IoT-smart weather monitoring station and air quality assessment based on fuzzy inference model and MQTT protocol, Modeling Earth Systems and Environment, 9, 4085–4102, https://doi.org/10.1007/s40808-023-01701-w, 2023.
Fiedler, N., Laumbach, R., Kelly-McNeil, K., Lioy, P., Fan, Z.-H., Zhang, J., Ottenweller, J., Ohman-Strickland, P., and Kipen, H.: Health effects of a mixture of indoor air volatile organics, their ozone oxidation products, and stress, Environ. Health Persp., 113, 1542–1548, https://doi.org/10.1289/ehp.8132, 2005.
Fuertes, W., Carrera, D., Villacís, C., Toulkeridis, T., Galárraga, F., Torres, E., and Aules, H.: Distributed system as internet of things for a new low-cost, air pollution wireless monitoring on real time, in: 2015 IEEE/ACM 19th International Symposium on Distributed Simulation and Real Time Applications (DS-RT), Chengdu, China, 14–16 October 2015, IEEE, 58–67, https://doi.org/10.1109/DS-RT.2015.28, 2015.
Gagic, R., Skuric, M., Djukanovic, G., and Nikolic, D.: Establishing Correlation between Cruise Ship Activities and Ambient PM Concentrations in the Kotor Bay Area Using a Low-Cost Sensor Network, Atmosphere, 13, 1819, https://doi.org/10.3390/atmos13111819, 2022.
Giordano, M. R., Malings, C., Pandis, S. N., Presto, A. A., McNeill, V. F., Westervelt, D. M., Beekmann, M., and Subramanian, R.: From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors, J. Aerosol Sci., 158, 105833, https://doi.org/10.1016/j.jaerosci.2021.105833, 2021.
Gnamien, S., Yoboué, V., Liousse, C., Ossohou, M., Keita, S., Bahino, J., Siélé, S., and Diaby, L.: Particulate pollution in korhogo and abidjan (Cote d'Ivoire) during the dry season, Aerosol Air Qual. Res., 21, 200201, https://doi.org/10.4209/aaqr.2020.05.0201, 2021.
González Rivero, R. A., Schalm, O., Alvarez Cruz, A., Hernández Rodríguez, E., Morales Pérez, M. C., Alejo Sánchez, D., Martinez Laguardia, A., Jacobs, W., and Hernández Santana, L.: Relevance and reliability of outdoor SO2 monitoring in low-income countries using low-cost sensors, Atmosphere, 14, 912, https://doi.org/10.3390/atmos14060912, 2023.
Gramsch, E., Morales, L., Baeza, M., Ayala, C., Soto, C., Neira, J., Pérez, P., and Moreno, F.: Citizens' surveillance micro-network for the mapping of PM2.5 in the city of Concón, Chile, Aerosol Air Qual. Res., 20, 358–368, https://doi.org/10.4209/aaqr.2019.04.0179, 2020.
Gramsch, E., Oyola, P., Reyes, F., Vásquez, Y., Rubio, M. A., Soto, C., Pérez, P., Moreno, F., and Gutiérrez, N.: Influence of particle composition and size on the accuracy of low cost PM sensors: Findings from field campaigns, Frontiers in Environmental Science, 9, 751267, https://doi.org/10.3389/fenvs.2021.751267, 2021.
Granados-Bolaños, S., Quesada-Román, A., and Alvarado, G. E.: Low-cost applications in dynamic tropical volcanic landforms, J. Volcanol. Geoth. Res., 410, 107143, https://doi.org/10.1016/j.jvolgeores.2020.107143, 2021.
Gressent, A., Malherbe, L., Colette, A., Rollin, H., and Scimia, R.: Data fusion for air quality mapping using low-cost sensor observations: Feasibility and added-value, Environ. Int., 143, 105965, https://doi.org/10.1016/j.envint.2020.105965, 2020.
Gryech, I., Ben-Aboud, Y., Guermah, B., Sbihi, N., Ghogho, M., and Kobbane, A.: Moreair: A low-cost urban air pollution monitoring system, Sensors-Basel, 20, 998, https://doi.org/10.3390/s20040998, 2020.
Guanochanga, B., Cachipuendo, R., Fuertes, W., Benítez, D. S., Toulkeridis, T., Torres, J., Villacís, C., Tapia, F., and Meneses, F.: Towards a real-time air pollution monitoring systems implemented using wireless sensor networks: Preliminary results, in: 2018 IEEE Colombian Conference on Communications and Computing (COLCOM), Medellin, Colombia, 16–18 May 2017, IEEE, 1–4, https://doi.org/10.1109/ColComCon.2018.8466721, 2018.
Guevara, J., Vargas, E., Barrero, F., and Toral, S.: Ubiquitous architecture for environmental sensor networks in road traffic applications, in: 13th International IEEE Conference on Intelligent Transportation Systems, Funchal, Portugal, 19–22 September 2010, IEEE, 1227–1232, https://doi.org/10.1109/ITSC.2010.5625110, 2010.
Hagan, D. H., Gani, S., Bhandari, S., Patel, K., Habib, G., Apte, J. S., Hildebrandt Ruiz, L., and Kroll, J. H.: Inferring aerosol sources from low-cost air quality sensor measurements: A case study in Delhi, India, Environmental Science and Technology Letters, 6, 467–472, https://doi.org/10.1021/acs.estlett.9b00393, 2019.
Han, P., Mei, H., Liu, D., Zeng, N., Tang, X., Wang, Y., and Pan, Y.: Calibrations of low-cost air pollution monitoring sensors for CO, NO2, O3, and SO2, Sensors, 21, 256, https://doi.org/10.3390/s21010256, 2021.
Hemingway, S. E.: 2022 Air Sensors International Conference Program Topics, https://asic.aqrc.ucdavis.edu/2022-program-topics (last access: 8 March 2024), 2022.
Hodoli, C. G. and the Network for Atmospheric and Air Quality Research (NAAQR): Sensors as a component of urban air quality management planning: a case study with AirGradient OpenAir PM monitors from Accra, Ghana., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20857, https://doi.org/10.5194/egusphere-egu24-20857, 2024.
Hodoli, C. G., Coulon, F., and Mead, M. I.: Source identification with high-temporal resolution data from low-cost sensors using bivariate polar plots in urban areas of Ghana, Environ. Pollut., 317, 120448, https://doi.org/10.1016/j.envpol.2022.120448, 2023.
Hofman, J., Peters, J., Stroobants, C., Elst, E., Baeyens, B., Van Laer, J., Spruyt, M., Van Essche, W., Delbare, E., Roels, B., Cochez, A., Gillijns, E., and Van Poppel, M.: Air quality sensor networks for evidence-based policy making: Best practices for actionable insights, Atmosphere, 13, 944, https://doi.org/10.3390/atmos13060944, 2022.
Hu, J., Wang, F., and Shen, H.: The influence of PM2.5 exposure duration and concentration on outpatient visits of urban hospital in a typical heavy industrial city, Environ. Sci. Pollut. R., 30, 115098–115110, https://doi.org/10.1007/s11356-023-30544-2, 2023.
Ibarrola, E.: Considerations when deploying a sensor-based air quality network, Air Sensors International Conference, https://asic.aqrc.ucdavis.edu/sites/g/files/dgvnsk3466/files/inline-files/Edurne%20Ibarolla%20-%20Considerations%20when%20deploying%20a%20sensor-based%20air%20quality%20network%20.pdf, 2022.
IQAir: First in air quality, https://www.iqair.com/, last access: 17 September 2023.
IQAir: AirVisual Platform, https://www.iqair.com/us/commercial-
air-quality-monitors/airvisual-platform, last access: 9 March 2024a.
IQAir: Live animated air quality map, https://www.iqair.com/us/air-quality-map, last access: 9 March 2024b.
Jaafar, W., Xu, J., Farrar, E., Jeong, C., Ganji, A., Evans, G., and Hatzopoulou, M.: Challenges and opportunities of low-cost sensors in capturing the impacts of construction activities on neighborhood air quality, Build. Environ., 254, 111363, https://doi.org/10.1016/j.buildenv.2024.111363, 2024.
Jain, S., Presto, A. A., and Zimmerman, N.: Spatial modeling of daily PM2.5, NO2, and CO concentrations measured by a low-cost sensor network: Comparison of linear, machine learning, and hybrid land use models, Environ. Sci. Technol., 55, 8631–8641, https://doi.org/10.1021/acs.est.1c02653, 2021.
Jang, Y.-W. and Jung, G.-W.: Temporal characteristics and sources of PM2.5 in Porto Velho of Amazon region in Brazil from 2020 to 2022, Sustainability, 15, 14012, https://doi.org/10.3390/su151814012, 2023.
Jayaratne, R., Liu, X., Thai, P., Dunbabin, M., and Morawska, L.: The influence of humidity on the performance of a low-cost air particle mass sensor and the effect of atmospheric fog, Atmos. Meas. Tech., 11, 4883–4890, https://doi.org/10.5194/amt-11-4883-2018, 2018.
Jayaratne, R., Kuhn, T., Christensen, B., Liu, X., Zing, I., Lamont, R., Dunbabin, M., Maddox, J., Fisher, G., and Morawska, L.: Using a network of low-cost particle sensors to assess the impact of ship emissions on a residential community, Aerosol Air Qual. Res., 20, 2754, https://doi.org/10.4209/aaqr.2020.06.0280, 2020.
Jayaratne, R., Thai, P., Christensen, B., Liu, X., Zing, I., Lamont, R., Dunbabin, M., Dawkins, L., Bertrand, L., and Morawska, L.: The effect of cold-start emissions on the diurnal variation of carbon monoxide concentration in a city centre, Atmos. Environ., 245, 118035, https://doi.org/10.1016/j.atmosenv.2020.118035, 2021.
Jeong, J. I. and Park, R. J.: Effects of the meteorological variability on regional air quality in East Asia, Atmos. Environ., 69, 46–55, https://doi.org/10.1016/j.atmosenv.2012.11.061, 2013.
Jiao, W., Hagler, G. S. W., Williams, R. W., Sharpe, R. N., Weinstock, L., and Rice, J.: Field assessment of the village green project: An autonomous community air quality monitoring system, Environ. Sci. Technol., 49, 6085–6092, https://doi.org/10.1021/acs.est.5b01245, 2015.
Jiao, W., Hagler, G., Williams, R., Sharpe, R., Brown, R., Garver, D., Judge, R., Caudill, M., Rickard, J., Davis, M., Weinstock, L., Zimmer-Dauphinee, S., and Buckley, K.: 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, 5281–5292, https://doi.org/10.5194/amt-9-5281-2016, 2016.
Jing, P., Schusler, T., Dahal, D., Zhang, B., Fischer, E., Pollack, I. B., and Sablan, O. M.: Community air research experience (Care): Engaging undergraduate students underrepresented in stem fields in research on air pollution in chicago communities, in: AGU Fall Meeting, Chicago, IL, 12–16 December 2022, ED42C-0608, https://ui.adsabs.harvard.edu/abs/2022AGUFMED42C0608J (last access: 8 March 2024), 2022.
Johnston, J. E., Enebish, T., Eckel, S. P., Navarro, S., and Shamasunder, B.: Respiratory health, pulmonary function and local engagement in urban communities near oil development, Environ. Res., 197, 111088, https://doi.org/10.1016/j.envres.2021.111088, 2021.
Jovašević-Stojanović, M., Bartonova, A., Topalović, D., Lazović, I., Pokrić, B., and Ristovski, Z.: On the use of small and cheaper sensors and devices for indicative citizen-based monitoring of respirable particulate matter, Environ. Pollut., 206, 696–704, https://doi.org/10.1016/j.envpol.2015.08.035, 2015.
Kampa, M. and Castanas, E.: Human health effects of air pollution, Environ. Pollut., 151, 362–367, https://doi.org/10.1016/j.envpol.2007.06.012, 2008.
Karagulian, F., Barbiere, M., Kotsev, A., Spinelle, L., Gerboles, M., Lagler, F., Redon, N., Crunaire, S., and Borowiak, A.: Review of the performance of low-cost sensors for air quality monitoring, Atmosphere, 10, 506, https://doi.org/10.3390/atmos10090506, 2019.
Karaoghlanian, N., Noureddine, B., Saliba, N., Shihadeh, A., and Lakkis, I.: Low cost air quality sensors “PurpleAir” calibration and inter-calibration dataset in the context of Beirut, Lebanon, Data in Brief, 41, 108008, https://doi.org/10.1016/j.dib.2022.108008, 2022.
Kelly, K. E., Whitaker, J., Petty, A., Widmer, C., Dybwad, A., Sleeth, D., Martin, R., and Butterfield, A.: Ambient and laboratory evaluation of a low-cost particulate matter sensor, Environ. Pollut., 221, 491–500, https://doi.org/10.1016/j.envpol.2016.12.039, 2017.
Khader, A. and Martin, R. S.: Use of low-cost ambient particulate sensors in Nablus, Palestine with application to the assessment of regional dust storms, Atmosphere, 10, 539, https://doi.org/10.3390/atmos10090539, 2019.
Khan, T. R. and Meranger, J. C.: Recent advances in SO2, NOx, and O3 personal monitoring, Environ. Int., 9, 195–206, https://doi.org/10.1016/0160-4120(83)90037-5, 1983.
Khuriganova, O. I., Obolkin, V. A., Golobokova, L. P., Bukin, Y. S., and Khodzher, T. V.: Passive sampling as a low-cost method for monitoring air pollutants in the Baikal region (Eastern Siberia), Atmosphere, 10, 470, https://doi.org/10.3390/atmos10080470, 2019.
Kim, J., Shusterman, A. A., Lieschke, K. J., Newman, C., and Cohen, R. C.: The BErkeley Atmospheric CO2 Observation Network: field calibration and evaluation of low-cost air quality sensors, Atmos. Meas. Tech., 11, 1937–1946, https://doi.org/10.5194/amt-11-1937-2018, 2018.
Korotchenkov, G. S., Dmitriev, S. V., and Brynzari, V. I.: Processes development for low cost and low power consuming SnO2 thin film gas sensors (Tfgs), Sensor. Actuat. B-Chem., 54, 202–209, https://doi.org/10.1016/S0925-4005(99)00017-9, 1999.
Kotzagianni, M., Hassani, A., Morresi, N., Udina, S., Kyfonidis, C., Roussos, A., Casaccia, S., Revel, G. M., and Noriega-Ortega, B.: Calibration strategies for low-cost compact field sensors in Citizen Science Air Quality measurements: Insights from SOCIO-BEE project, in: 2023 8th International Conference on Smart and Sustainable Technologies (SpliTech), Split/Bol, Croatia, 20–23 June 2023, IEEE, 1–6, https://doi.org/10.23919/SpliTech58164.2023.10193423, 2023.
Kuhn, T., Jayaratne, R., Thai, P. K., Christensen, B., Liu, X., Dunbabin, M., Lamont, R., Zing, I., Wainwright, D., Witte, C., Neale, D., and Morawska, L.: Air quality during and after the Commonwealth Games 2018 in Australia: Multiple benefits of monitoring, J. Aerosol Sci., 152, 105707, https://doi.org/10.1016/j.jaerosci.2020.105707, 2021.
Kumar, T. and Doss, A.: Airo: Development of an intelligent IOT-based air quality monitoring solution for urban areas, Procedia Comput. Sci., 218, 262–273, https://doi.org/10.1016/j.procs.2023.01.008, 2023.
Kunak AIR Cloud: Air quality software for data analysis, http://kunakair.com/air-quality-software/, last access: 10 March 2024.
Kurtenbach, R., Ulianova, K., Gibilisco, R. G., Villena, G., and Wiesen, P.: Validation of low cost sensors for gases and particulate matter in the city centre of Wuppertal, Germany, in: Proceedings of the 24th International Transport and Air Pollution (TAP) Conference, https://data.europa.eu/doi/10.2760/019404, 2022.
Labzovskii, L. D., Vande Hey, J., Romanov, A. A., Golovatina-Mora, P., Belikov, D. A., Lashkari, A., Takele Kenea, S., and Hekman, E.: Who should measure air quality in modern cities? The example of decentralization of urban air quality monitoring in Krasnoyarsk (Siberia, Russia), Environ. Sci. Policy, 140, 93–103, https://doi.org/10.1016/j.envsci.2022.11.016, 2023.
Lassman, W., Pierce, J. R., Bangs, E. J., Sullivan, A. P., Ford, B., Mengistu Tsidu, G., Sherman, J. P., Collett, J. L., and Bililign, S.: Using low-cost measurement systems to investigate air quality: A case study in Palapye, Botswana, Atmosphere, 11, 583, https://doi.org/10.3390/atmos11060583, 2020.
Lee, Y.-M., Lin, G.-Y., Le, T.-C., Hong, G.-H., Aggarwal, S. G., Yu, J.-Y., and Tsai, C.-J.: Characterization of spatial-temporal distribution and microenvironment source contribution of PM2.5 concentrations using a low-cost sensor network with artificial neural network/kriging techniques, Environ. Res., 244, 117906, https://doi.org/10.1016/j.envres.2023.117906, 2024.
Li, H. Z., Gu, P., Ye, Q., Zimmerman, N., Robinson, E. S., Subramanian, R., Apte, J. S., Robinson, A. L., and Presto, A. A.: Spatially dense air pollutant sampling: Implications of spatial variability on the representativeness of stationary air pollutant monitors, Atmospheric Environment: X, 2, 100012, https://doi.org/10.1016/j.aeaoa.2019.100012, 2019.
Li, J., Zhang, H., Chao, C.-Y., Chien, C.-H., Wu, C.-Y., Luo, C. H., Chen, L.-J., and Biswas, P.: Integrating low-cost air quality sensor networks with fixed and satellite monitoring systems to study ground-level PM2.5, Atmos. Environ., 223, 117293, https://doi.org/10.1016/j.atmosenv.2020.117293, 2020.
Liang, L., Daniels, J., Bailey, C., Hu, L., Phillips, R., and South, J.: Integrating low-cost sensor monitoring, satellite mapping, and geospatial artificial intelligence for intra-urban air pollution predictions, Environ. Pollut., 331, 121832, https://doi.org/10.1016/j.envpol.2023.121832, 2023.
Lin, C., Labzovskii, L. D., Leung Mak, H. W., Fung, J. C. H., Lau, A. K. H., Kenea, S. T., Bilal, M., Vande Hey, J. D., Lu, X., and Ma, J.: Observation of PM2.5 using a combination of satellite remote sensing and low-cost sensor network in Siberian urban areas with limited reference monitoring, Atmos. Environ., 227, 117410, https://doi.org/10.1016/j.atmosenv.2020.117410, 2020.
Liu, B. and Zimmerman, N.: Fleet-based vehicle emission factors using low-cost sensors: Case study in parking garages, Transportation Res. D-Tr. E., 91, 102635, https://doi.org/10.1016/j.trd.2020.102635, 2021.
Liu, J., Banerjee, S., Oroumiyeh, F., Shen, J., del Rosario, I., Lipsitt, J., Paulson, S., Ritz, B., Su, J., Weichenthal, S., Lakey, P., Shiraiwa, M., Zhu, Y., and Jerrett, M.: Co-kriging with a low-cost sensor network to estimate spatial variation of brake and tire-wear metals and oxidative stress potential in Southern California, Environ. Int., 168, 107481, https://doi.org/10.1016/j.envint.2022.107481, 2022.
Liu, M., Barkjohn, K., Norris, C., Schauer, J., Zhang, J., Zhang, Y., Hu, M., and Bergin, M.: Using low-cost sensors to monitor indoor, outdoor, and personal ozone concentrations in Beijing, China, Environ. Sci.-Proc. Imp., 22, 131–143, https://doi.org/10.1039/C9EM00377K, 2020.
Liu, N., Bu, Z., Liu, W., Kan, H., Zhao, Z., Deng, F., Huang, C., Zhao, B., Zeng, X., Sun, Y., Qian, H., Mo, J., Sun, C., Guo, J., Zheng, X., Weschler, L. B., and Zhang, Y.: Health effects of exposure to indoor volatile organic compounds from 1980 to 2017: A systematic review and meta-analysis, Indoor Air, 32, e13038, https://doi.org/10.1111/ina.13038, 2022.
Liu, S., Yang, X., and Zhou, X.: Development of a low-cost UAV-based system for CH4 monitoring over oil fields, Environ. Technol., 42, 3154–3163, https://doi.org/10.1080/09593330.2020.1724199, 2020.
Liu, X., Jayaratne, R., Thai, P., Kuhn, T., Zing, I., Christensen, B., Lamont, R., Dunbabin, M., Zhu, S., Gao, J., Wainwright, D., Neale, D., Kan, R., Kirkwood, J., and Morawska, L.: Low-cost sensors as an alternative for long-term air quality monitoring, Environ. Res., 185, 109438, https://doi.org/10.1016/j.envres.2020.109438, 2020.
Local Haze [Mobile App]: https://localhaze.humanlogic.com/, last access: 17 September 2023.
Lopez-Restrepo, S., Yarce, A., Pinel, N., Quintero, O. L., Segers, A., and Heemink, A. W.: Urban air quality modeling using low-cost sensor network and data assimilation in the Aburrá Valley, Colombia, Atmosphere, 12, 91, https://doi.org/10.3390/atmos12010091, 2021.
Love my air: https://denver.lovemyair.com, last access: 10 March 2024.
Lu, T., Liu, Y., Garcia, A., Wang, M., Li, Y., Bravo-Villasenor, G., Campos, K., Xu, J., and Han, B.: Leveraging citizen science and low-cost sensors to characterize air pollution exposure of disadvantaged communities in southern california, Int. J. Env. Res. Pub. He., 19, 8777, https://doi.org/10.3390/ijerph19148777, 2022.
Ma, Y., Richards, M., Ghanem, M., Guo, Y., and Hassard, J.: Air pollution monitoring and mining based on sensor grid in London, Sensors, 8, 3601–3623, https://doi.org/10.3390/s80603601, 2008.
Mahfuz, M. U. and Ahmed, K.: A review of micro-nano-scale wireless sensor networks for environmental protection: Prospects and challenges, Sci. Technol. Adv. Mat., 6, 302–306, https://doi.org/10.1016/j.stam.2005.02.008, 2005.
Malings, C., Tanzer, R., Hauryliuk, A., Kumar, S. P. N., Zimmerman, N., Kara, L. B., Presto, A. A., and R. Subramanian: Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring, Atmos. Meas. Tech., 12, 903–920, https://doi.org/10.5194/amt-12-903-2019, 2019a.
Malings, C., Tanzer, R., Hauryliuk, A., Saha, P. K., Robinson, A. L., Presto, A. A., and Subramanian, R.: Fine particle mass monitoring with low-cost sensors: Corrections and long-term performance evaluation, Aerosol Sci. Technol., 54, 160–174, https://doi.org/10.1080/02786826.2019.1623863, 2019b.
Malings, C., Knowland, K. E., Keller, C. A., and Cohn, S. E.: Sub-city scale hourly air quality forecasting by combining models, satellite observations, and ground measurements, Earth and Space Science, 8, e2021EA001743, https://doi.org/10.1029/2021EA001743, 2021.
Martinez, A., Hernandez-Rodríguez, E., Hernandez, L., Schalm, O., González-Rivero, R. A., and Alejo-Sánchez, D.: Design of a low-cost system for the measurement of variables associated with air quality, IEEE Embedded Systems Letters, 15, 105–108, https://doi.org/10.1109/LES.2022.3196543, 2023.
Mead, M. I., Popoola, O. A. M., Stewart, G. B., Landshoff, P., Calleja, M., Hayes, M., Baldovi, J. J., McLeod, M. W., Hodgson, T. F., Dicks, J., Lewis, A., Cohen, J., Baron, R., Saffell, J. R., and Jones, R. L.: The use of electrochemical sensors for monitoring urban air quality in low-cost, high-density networks, Atmos. Environ., 70, 186–203, https://doi.org/10.1016/j.atmosenv.2012.11.060, 2013.
Meixner, H. and Lampe, U.: Metal oxide sensors, Sensor. Actuat. B-Chem., 33, 198–202, https://doi.org/10.1016/0925-4005(96)80098-0, 1996.
Meixner, H., Gerblinger, J., Lampe, U., and Fleischer, M.: Thin-film gas sensors based on semiconducting metal oxides, Sensor. Actuat. B-Chem., 23, 119–125, https://doi.org/10.1016/0925-4005(94)01266-K, 1995.
Metreveli, Y. Y.: The Internet of things and indoor air quality on ship, IOP Conf. Ser.: Earth Environ. Sci., 872, 012015, https://doi.org/10.1088/1755-1315/872/1/012015, 2021.
Miranda, M. L., Edwards, S. E., Keating, M. H., and Paul, C. J.: Making the environmental justice grade: The relative burden of air pollution exposure in the united states, Int. J. Env. Res. Pub. He., 8, 1755–1771, https://doi.org/10.3390/ijerph8061755, 2011.
Miskell, G., Salmond, J., and Williams, D. E.: Low-cost sensors and crowd-sourced data: Observations of siting impacts on a network of air-quality instruments, Sci. Total Environ., 575, 1119–1129, https://doi.org/10.1016/j.scitotenv.2016.09.177, 2017.
MKE FreshAir Collective: https://www.mkefreshair.com/, last access: 10 March 2024.
Mo, X., Peters, D., and Lei, C.: Low Cost Autonomous UAV Swarm Application in Wildfire Surveillance and Suppression, Proceedings of the 2021 6th International Conference on Machine Learning Technologies, Jeju Island, Republic of Korea, 23–25 April 2021, Association for Computing Machinery, 164–169, https://doi.org/10.1145/3468891.3468916, 2021.
Moltchanov, S., Levy, I., Etzion, Y., Lerner, U., Broday, D. M., and Fishbain, B.: On the feasibility of measuring urban air pollution by wireless distributed sensor networks, Sci. Total Environ., 502, 537–547, https://doi.org/10.1016/j.scitotenv.2014.09.059, 2015.
Morawska, L., Thai, P. K., Liu, X., Asumadu-Sakyi, A., Ayoko, G., Bartonova, A., Bedini, A., Chai, F., Christensen, B., Dunbabin, M., Gao, J., Hagler, G. S. W., Jayaratne, R., Kumar, P., Lau, A. K. H., Louie, P. K. K., Mazaheri, M., Ning, Z., Motta, N., Mullins, B., Rahman, M. M., Ristovski, Z., Shafiei, M., Tjondronegoro, D., Westerdahl, D., and Williams, R.: Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?, Environ. Int., 116, 286–299, https://doi.org/10.1016/j.envint.2018.04.018, 2018.
Morel, P.: Gramm: Grammar of graphics plotting in Matlab, Journal of Open Source Software, 3, 568, https://doi.org/10.21105/joss.00568, 2018.
Morgan, M. G. and Morris, S. C.: Individual air pollution monitors: An assessment of national research needs, Brookhaven National Laboratory, BNL-50482, https://doi.org/10.2172/7293144, 1976.
Mullen, C. J., Grineski, S. E., Collins, T. W., and Flores, A. B.: Air quality sensors and distributional environmental justice: A case study of Salt Lake County, Utah, Environmental Sociology, 10, 179–191, https://doi.org/10.1080/23251042.2023.2295099, 2023.
Müller, M., Graf, P., Meyer, J., Pentina, A., Brunner, D., Perez-Cruz, F., Hüglin, C., and Emmenegger, L.: Integration and calibration of non-dispersive infrared (NDIR) CO2 low-cost sensors and their operation in a sensor network covering Switzerland, Atmos. Meas. Tech., 13, 3815–3834, https://doi.org/10.5194/amt-13-3815-2020, 2020.
Munir, S., Mayfield, M., Coca, D., Jubb, S. A., and Osammor, O.: Analysing the performance of low-cost air quality sensors, their drivers, relative benefits and calibration in cities – A case study in Sheffield, Environ. Monit. Assess., 191, 94, https://doi.org/10.1007/s10661-019-7231-8, 2019.
Narayana, M. V., Jalihal, D., and Nagendra, S. M. S.: Establishing a sustainable low-cost air quality monitoring setup: A survey of the state-of-the-art, Sensors, 22, 394, https://doi.org/10.3390/s22010394, 2022.
NASA: Ames INSTEP, https://www.nasa.gov/inexpensive-
network-sensor-technology-exploring-pollution-instep/, last access: 10 March 2024.
NASA HAQAST (NASA Health and Air Quality Applied Sciences Team): Past Meetings, https://haqast.org/get-involved/meetings/, last access: 17 September 2023.
National Research Council (US) Committee on Indoor Pollutants: VI Monitoring and modeling of indoor air pollution, in: Indoor Pollutants, National Academies Press, US, https://www.ncbi.nlm.nih.gov/books/NBK234059/ (last access: 8 March 2024), 1981.
National Association of Clean Air Agencies: https://www.4cleanair.org/, last access: 17 September 2023.
Ndamuzi, E., Akimana, R., Gahungu, P., and Bimenyimana, E.: Modelling and characterization of fine Particulate Matter dynamics in Bujumbura using low cost sensors, arXiv [preprint], https://doi.org/10.48550/arXiv.2312.12003, 19 December 2023.
Ngo, N. S., Asseko, S. V. J., Ebanega, M. O., Allo'o Allo'o, S. M., and Hystad, P.: The relationship among PM2.5, traffic emissions, and socioeconomic status: Evidence from Gabon using low-cost, portable air quality monitors, Transport. Res. D-Tr. E., 68, 2–9, https://doi.org/10.1016/j.trd.2018.01.029, 2019.
Ngom, B., Seye, M. R., Diallo, M., Gueye, B., and Drame, M. S.: A hybrid measurement kit for real-time air quality monitoring across senegal cities. 2018 1st International Conference on Smart Cities and Communities (SCCIC), Ouagadougou, Burkina Faso, 24–26 July 2018, IEEE, 1–6, https://doi.org/10.1109/SCCIC.2018.8584551, 2018.
Nori-Sarma, A., Thimmulappa, R. K., Venkataramana, G. V., Fauzie, A. K., Dey, S. K., Venkareddy, L. K., Berman, J. D., Lane, K. J., Fong, K. C., Warren, J. L., and Bell, M. L.: Low-cost NO2 monitoring and predictions of urban exposure using universal kriging and land-use regression modelling in Mysore, India, Atmos. Environ., 226, 117395, https://doi.org/10.1016/j.atmosenv.2020.117395, 2020.
Oizom: https://oizom.com/, last access: 10 March 2024.
Okorn, K. and Hannigan, M.: Applications and limitations of quantifying speciated and source-apportioned vocs with metal oxide sensors, Atmosphere, 12, 1383, https://doi.org/10.3390/atmos12111383, 2021.
Okorn, K., Jimenez, A., Collier-Oxandale, A., Johnston, J., and Hannigan, M.: Characterizing methane and total non-methane hydrocarbon levels in Los Angeles communities with oil and gas facilities using air quality monitors, Sci. Total Environ., 777, 146194, https://doi.org/10.1016/j.scitotenv.2021.146194, 2021.
Omokungbe, O. R., Fawole, O. G., Owoade, O. K., Popoola, O. A. M., Jones, R. L., Olise, F. S., Ayoola, M. A., Abiodun, P. O., Toyeje, A. B., Olufemi, A. P., Sunmonu, L. A., and Abiye, O. E.: Analysis of the variability of airborne particulate matter with prevailing meteorological conditions across a semi-urban environment using a network of low-cost air quality sensors, Heliyon, 6, e04207, https://doi.org/10.1016/j.heliyon.2020.e04207, 2020.
Omokungbe, O. R., Olufemi, A. P., Toyeje, A. B., and Abiodun, P. O.: Investigating the evolution of gaseous air pollutants with prevailing meteorology across selected sites within a pollution hotspot in Ile-Ife, Southwestern Nigeria, Discover Environment, 1, 5, https://doi.org/10.1007/s44274-023-00006-0, 2023.
OpenAQ: https://openaq.org/, last access: 10 March 2024.
Ott, W. R.: Concepts of human exposure to air pollution, Environ. Int., 7, 179–196, https://doi.org/10.1016/0160-4120(82)90104-0, 1982.
Outpost Environmental: https://outpostenvironmental.com/, last access: 10 March 2024.
Ouyang, B., Popoola, L., Jones, R., Li, C., and Chen, J.: Portable and low-cost sensors in monitoring air qualities in China, EGU General Assembly, Vienna, Austria, 17–22 April 2016, EGU2016-16213, 2016.
Owoade, O. K., Abiodun, P. O., Omokungbe, O. R., Fawole, O. G., Olise, F. S., Popoola, O. O. M., Jones, R. L., and Hopke, P. K.: Spatial-temporal variation and local source identification of air pollutants in a semi-urban settlement in Nigeria using low-cost sensors, Aerosol Air Qual. Res., 21, 200598, https://doi.org/10.4209/aaqr.200598, 2021.
Oyola, P., Carbone, S., Timonen, H., Torkmahalleh, M., and Lindén, J.: Editorial: Rise of low-cost sensors and citizen science in air quality studies, Frontiers in Environmental Science, 10, 868543, https://doi.org/10.3389/fenvs.2022.868543, 2022.
Ozler, S.: Field applications of low-cost air quality monitors for PM2.5 studies, MS thesis, https://minds.wisconsin.edu/handle/1793/78604 (last access: 8 March 2024), 2018.
Paku for PurpleAir: https://paku.app, last access: 9 March 2024.
Panzitta, A., Bax, C., Lotesoriere, B. J., Ratti, C., and Capelli, L.: Realisation of a multi-sensor system for real-tim emonitoring of odour emissions at a waste treatment plant, Chem. Engineer. Trans., 95, 139–144, https://doi.org/10.3303/CET2295024, 2022.
Papaconstantinou, R., Demosthenous, M., Bezantakos, S., Hadjigeorgiou, N., Costi, M., Stylianou, M., Symeou, E., Savvides, C., and Biskos, G.: Field evaluation of low-cost electrochemical air quality gas sensors under extreme temperature and relative humidity conditions, Atmos. Meas. Tech., 16, 3313–3329, https://doi.org/10.5194/amt-16-3313-2023, 2023.
Papadopoulos, C. A., Vlachos, D. S., and Avaritsiotis, J. N.: Comparative study of various metal-oxide-based gas-sensor architectures, Sensor. Actuat. B-Chem., 32, 61–69, https://doi.org/10.1016/0925-4005(96)80110-9, 1996.
Park, C., Jeong, S., Park, H., Woo, J.-H., Sim, S., Kim, J., Son, J., Park, H., Shin, Y., Shin, J., Kwon, S.-M., and Lee, W.: Challenges in monitoring atmospheric CO2 concentrations in Seoul using low-cost sensors, Asia-Pac. J. Atmos. Sci., 57, 547–553, https://doi.org/10.1007/s13143-020-00213-2, 2021.
Patwardhan, I., Sara, S., and Chaudhari, S.: Comparative evaluation of new low-cost particulate matter sensors, in: 2021 8th International Conference on Future Internet of Things and Cloud (FiCloud), Rome, Italy, 23–25 August 2021, 192–197, https://doi.org/10.1109/FiCloud49777.2021.00035, 2021.
Penza, M., Suriano, D., Villani, M. G., Spinelle, L., and Gerboles, M.: Towards air quality indices in smart cities by calibrated low-cost sensors applied to networks, 2014 IEEE SENSORS, Valencia, Spain, 2–5 November 2014, IEEE, 2012–2017, https://doi.org/10.1109/ICSENS.2014.6985429, 2014.
Penza, M., Suriano, D., Cassano, G., Pfister, V., Amodio, M., Trizio, L., Brattoli, M., and De Gennaro, G.: A case-study of microsensors for landfill air-pollution monitoring applications, Urban Climate, 14, 351–369, https://doi.org/10.1016/j.uclim.2014.09.002, 2015.
Penza, M., Suriano, D., Pfister, V., Prato, M., and Cassano, G.: Urban air quality monitoring with networked low-cost sensor-systems, Proceedings, 1, 573, https://doi.org/10.3390/proceedings1040573, 2017.
Pereira-Rodrigues, N., Guillot, J. M., Fanlo, J. L., Renner, C., and Aubert, B.: Miniature and low-cost devices for the precise and reliable monitoring of low concentrations of H2s in changing environments, Chem. Engineer. Trans., 23, 237–242, https://doi.org/10.3303/CET1023040, 2010.
Perello, J.: Bettair, https://www.miteco.gob.es/content/dam/miteco/es/calidad-y-evaluacion-ambiental/formacion/ateknea_bettair_jornada_sensores_20180605_tcm30-457716.pdf (last access: 8 March 2024), 2018.
Piedrahita, R., Xiang, Y., Masson, N., Ortega, J., Collier, A., Jiang, Y., Li, K., Dick, R. P., Lv, Q., Hannigan, M., and Shang, L.: The next generation of low-cost personal air quality sensors for quantitative exposure monitoring, Atmos. Meas. Tech., 7, 3325–3336, https://doi.org/10.5194/amt-7-3325-2014, 2014.
Pochwala, S., Gardecki, A., Lewandowski, P., Somogyi, V., Anweiler, S.: Developing of Low-Cost Air Pollution Sensor – Measurements with the Unmanned Aerial Vehicles in Poland, Sensors, 20, 3582, https://doi.org/10.3390/s20123582, 2020.
Pope, C. A. and Dockery, D. W.: Health effects of fine particulate air pollution: Lines that connect, J. Air Waste Manage., 56, 709–742, https://doi.org/10.1080/10473289.2006.10464485, 2006.
Pope, F. D., Gatari, M., Ng'ang'a, D., Poynter, A., and Blake, R.: Airborne particulate matter monitoring in Kenya using calibrated low-cost sensors, Atmos. Chem. Phys., 18, 15403–15418, https://doi.org/10.5194/acp-18-15403-2018, 2018.
Popoola, O. A. M., Carruthers, D., Lad, C., Bright, V. B., Mead, M. I., Stettler, M. E. J., Saffell, J. R., and Jones, R. L.: Use of networks of low cost air quality sensors to quantify air quality in urban settings, Atmos. Environ., 194, 58–70, https://doi.org/10.1016/j.atmosenv.2018.09.030, 2018.
Postolache, O. A., Pereira, J. M. D., and Girao, P. M. B. S.: Smart sensors network for air quality monitoring applications, IEEE T. Instrum. Meas., 58, 3253–3262, https://doi.org/10.1109/TIM.2009.2022372, 2009.
Prana Air: https://pranaair.com, last access: 9 March 2024.
Prathibha, P. S., Cross, E. S., Strehl, R. L., Yeager II, R. A., Bhatnagar, A., and Turner, J. R.: Green heart louisville: Community-level assessment of exposure to air pollution, AGU, A206-02, https://ui.adsabs.harvard.edu/abs/2020AGUFMA206...02P (last access: 8 March 2024), 2020.
Puget Sound Clean Air Agency: Air quality sensors: https://www.pscleanair.gov/539/Air-Quality-Sensors#:~:text=One%20of%20the%20most%20popular,regulatory%20monitors%20and%20comparing%20measurements, last access: 17 September 2023.
PurpleAir: New API dashboard and data download tool release, https://www2.purpleair.com/blogs/blog-home/purpleair-s-new-api-dashboard-data-download-tool-release, last access: 11 November 2023.
PurpleAir: Real-time air quality map, https://map.purpleair.com/, last access: 9 March 2024.
PurpleAir Community: Is there an Introductory guide on how to utilize the API to analyze historical data?, https://community.purpleair.com/t/is-there-an-introductory-
guide-on-how-to-utilise-the-api-to-analyse-historical-data/3148/3, last access: 10 March 2024.
QuantAQ: https://quant-aq.com/, last access: 10 March 2024.
Queensland University of Technology: Koala sensors, https://research.qut.edu.au/ilaqh/projects/koala-sensors/, last access: 10 March 2024.
Quevedo, D., Gao, Z., Do, K., Bahreini, R., Collins, D., and Ivey, C.: Multidecadal analysis of meteorological and emissions regimes for PM2.5 across california, ACS ESandT Air, 1, 33–42, https://doi.org/10.1021/acsestair.3c00019, 2024.
Quintero, E., González, J., García, F., Sáez, Y., and Collado, E.: IoT-based system prototype for particulate matter monitoring in the city of Chitre, Panama, https://laccei.org/LACCEI2023-BuenosAires/meta/FP847.html (last access: 8 March 2024), 2023.
Raheja, G., Harper, L., Hoffman, A., Gorby, Y., Freese, L., O'Leary, B., Deron, N., Smith, S., Auch, T., Goodwin, M., and Westervelt, D. M.: Community-based participatory research for low-cost air pollution monitoring in the wake of unconventional oil and gas development in the Ohio River Valley: Empowering impacted residents through community science, Environ. Res. Lett., 17, 065006, https://doi.org/10.1088/1748-9326/ac6ad6, 2022a.
Raheja, G., Sabi, K., Sonla, H., Gbedjangni, E. K., McFarlane, C. M., Hodoli, C. G., and Westervelt, D. M.: A network of field-calibrated low-cost sensor measurements of PM2.5 in Lomé, Togo, over one to two years, ACS Earth Space Chem., 6, 1011–1021, https://doi.org/10.1021/acsearthspacechem.1c00391, 2022b.
Rai, A. C., Kumar, P., Pilla, F., Skouloudis, A. N., Di Sabatino, S., Ratti, C., Yasar, A., and Rickerby, D.: End-user perspective of low-cost sensors for outdoor air pollution monitoring, Sci. Total Environ., 607–608, 691–705, https://doi.org/10.1016/j.scitotenv.2017.06.266, 2017.
Ramakrishna, J., Durgaprasad, M. B., and Smith, K. R.: Cooking in India: The impact of improved stoves on indoor air quality, Environ. Int., 15, 341–352, https://doi.org/10.1016/0160-4120(89)90047-0, 1989.
Real-Time Air Quality Sensor Networks: The world air quality index project, https://aqicn.org/network/, last access: 10 March 2024.
Ren, Y., Qu, Z., Du, Y., Xu, R., Ma, D., Yang, G., Shi, Y., Fan, X., Tani, A., Guo, P., Ge, Y., and Chang, J.: Air quality and health effects of biogenic volatile organic compounds emissions from urban green spaces and the mitigation strategies, Environ. Pollut., 230, 849–861, https://doi.org/10.1016/j.envpol.2017.06.049, 2017.
Ribbit Network: https://www.ribbitnetwork.org/, last access: 10 March 2024.
RIVM data portal: https://samenmeten.rivm.nl/dataportaal/, last access: 10 March 2024.
Rodríguez, E. H., Schalm, O., and Martínez, A.: Development of a low-cost measuring system for the monitoring of environmental parameters that affect air quality for human health, ITEGAM-JETIA, 6, 22–27, https://itegam-jetia.org/journal/index.php/jetia/article/view/648 (last access: 8 March 2024), 2020.
Rosmarin, A., Curtis, L., and Brown, D. R.: Weather-based evaluation of exposure to airborne toxins to nearby residents, Environmental Advances, 13, 100415, https://doi.org/10.1016/j.envadv.2023.100415, 2023.
Sablan, O. M., Gargulinski, E., Slater, K., Rosen, Z., Henery, G., Ford, B., Magzamen, S., Soja, A. J., Pierce, J. R., and Fischer, E.: Monitoring smoke from landscape fires in the flint hills region of Kansas during the 2022 burning season, in: AGU Fall Meeting, Chicago, IL, 12–16 December 2022, GH42A-33, https://ui.adsabs.harvard.edu/abs/2022AGUFMGH42A..33S (last access: 8 March 2024), 2022.
Sahu, R., Dixit, K. K., Mishra, S., Kumar, P., Shukla, A. K., Sutaria, R., Tiwari, S., and Tripathi, S. N.: Validation of low-cost sensors in measuring real-time PM10 concentrations at two sites in Delhi national capital region, Sensors, 20, 1347, https://doi.org/10.3390/s20051347, 2020.
Sahu, R., Nagal, A., Dixit, K. K., Unnibhavi, H., Mantravadi, S., Nair, S., Simmhan, Y., Mishra, B., Zele, R., Sutaria, R., Motghare, V. M., Kar, P., and Tripathi, S. N.: Robust statistical calibration and characterization of portable low-cost air quality monitoring sensors to quantify real-time O3 and NO2 concentrations in diverse environments, Atmos. Meas. Tech., 14, 37–52, https://doi.org/10.5194/amt-14-37-2021, 2021.
Saleh, T. and Khader, A.: Urban particulate matter hazard mapping and monitoring site selection in Nablus, palestine, Atmosphere, 13, 1134, https://doi.org/10.3390/atmos13071134, 2022.
Saúco, L., Pradas, P., Ibarrola, E., Martín, J., and Lardín, C.: Early alert system for odour management in WWTP, in: 2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN), Aveiro, Portugal, 29 May–1 June 2022, IEEE, 1–2, https://doi.org/10.1109/ISOEN54820.2022.9789637, 2022.
Sayahi, T., Kaufman, D., Becnel, T., Kaur, K., Butterfield, A. E., Collingwood, S., Zhang, Y., Gaillardon, P.-E., and Kelly, K. E.: Development of a calibration chamber to evaluate the performance of low-cost particulate matter sensors, Environ. Pollut., 255, 113131, https://doi.org/10.1016/j.envpol.2019.113131, 2019.
Sayahi, T., Garff, A., Quah, T., Lê, K., Becnel, T., Powell, K. M., Gaillardon, P.-E., Butterfield, A. E., and Kelly, K. E.: Long-term calibration models to estimate ozone concentrations with a metal oxide sensor, Environ. Pollut., 267, 115363, https://doi.org/10.1016/j.envpol.2020.115363, 2020.
Sberveglieri, G., Hellmich, W., and Müller, G.: Silicon hotplates for metal oxide gas sensor elements, Microsyst. Technol., 3, 183–190, https://doi.org/10.1007/s005420050078, 1997.
Schalm, O., Carro, G., Lazarov, B., Jacobs, W., and Stranger, M.: Reliability of Lower-Cost Sensors in the Analysis of Indoor Air Quality on Board Ships, Atmosphere, 13, 1579, https://doi.org/10.3390/atmos13101579, 2022.
Shankar, S., Abbas, G., Nithyaprakash, R., Naveenkumar, R., Rakesh Mohanty, S., Sabarinathan, A., and Karthick, S.: Study on the impact of firecrackers on atmospheric pollutants during Diwali festival in Tamil Nadu, India, E3S Web Conf., 453, 01004, https://doi.org/10.1051/e3sconf/202345301004, 2023.
Schneider, P., Bartonova, A., Castell, N., Dauge, F. R., Gerboles, M., Hagler, G., Hüglin, C., Jones, R. L., Khan, S., Lewis, A. C., Mijling, B., Müller, M., Penza, M., Spinelle, L., Stacey, B., Vogt, M., Wesseling, J., and Williams, R. W.: Toward a Unified Terminology of Processing Levels for Low-Cost Air-Quality Sensors, Environ. Sci. Technol., 53, 8485–8487, https://doi.org/10.1021/acs.est.9b03950, 2019.
Sherwood, R. J. and Greenhalgh, D. M.: A personal air sampler, Ann. Occup. Hyg., 2, 127–132, https://doi.org/10.1093/annhyg/2.2.127, 1960.
Shi, Z., Vu, T., Kotthaus, S., Harrison, R. M., Grimmond, S., Yue, S., Zhu, T., Lee, J., Han, Y., Demuzere, M., Dunmore, R. E., Ren, L., Liu, D., Wang, Y., Wild, O., Allan, J., Acton, W. J., Barlow, J., Barratt, B., Beddows, D., Bloss, W. J., Calzolai, G., Carruthers, D., Carslaw, D. C., Chan, Q., Chatzidiakou, L., Chen, Y., Crilley, L., Coe, H., Dai, T., Doherty, R., Duan, F., Fu, P., Ge, B., Ge, M., Guan, D., Hamilton, J. F., He, K., Heal, M., Heard, D., Hewitt, C. N., Hollaway, M., Hu, M., Ji, D., Jiang, X., Jones, R., Kalberer, M., Kelly, F. J., Kramer, L., Langford, B., Lin, C., Lewis, A. C., Li, J., Li, W., Liu, H., Liu, J., Loh, M., Lu, K., Lucarelli, F., Mann, G., McFiggans, G., Miller, M. R., Mills, G., Monk, P., Nemitz, E., O'Connor, F., Ouyang, B., Palmer, P. I., Percival, C., Popoola, O., Reeves, C., Rickard, A. R., Shao, L., Shi, G., Spracklen, D., Stevenson, D., Sun, Y., Sun, Z., Tao, S., Tong, S., Wang, Q., Wang, W., Wang, X., Wang, X., Wang, Z., Wei, L., Whalley, L., Wu, X., Wu, Z., Xie, P., Yang, F., Zhang, Q., Zhang, Y., Zhang, Y., and Zheng, M.: Introduction to the special issue “In-depth study of air pollution sources and processes within Beijing and its surrounding region (APHH-Beijing)”, Atmos. Chem. Phys., 19, 7519–7546, https://doi.org/10.5194/acp-19-7519-2019, 2019.
Shibata, K., Yokoo, T., Takeuchi, K., Tanaka, T., Kamino, M., Nishikawa, S., Nakano, S., and Kuwano, Y.: A new-structure ir gas sensor, Jpn. J. Appl. Phys., 26, 1898, https://doi.org/10.1143/JJAP.26.1898, 1987.
Shusterman, A. A., Teige, V. E., Turner, A. J., Newman, C., Kim, J., and Cohen, R. C.: The BErkeley Atmospheric CO2 Observation Network: initial evaluation, Atmos. Chem. Phys., 16, 13449–13463, https://doi.org/10.5194/acp-16-13449-2016, 2016.
Si, M., Xiong, Y., Du, S., and Du, K.: Evaluation and calibration of a low-cost particle sensor in ambient conditions using machine-learning methods, Atmos. Meas. Tech., 13, 1693–1707, https://doi.org/10.5194/amt-13-1693-2020, 2020.
Singh, A., Ng'ang'a, D., Gatari, M. J., Kidane, A. W., Alemu, Z. A., Derrick, N., Webster, M. J., Bartington, S. E., Thomas, G. N., Avis, W., and Pope, F. D.: Air quality assessment in three East African cities using calibrated low-cost sensors with a focus on road-based hotspots, Environmental Research Communications, 3, 075007, https://doi.org/10.1088/2515-7620/ac0e0a, 2021.
Sivaraman, V., Carrapetta, J., Hu, K., and Luxan, B. G.: HazeWatch: A participatory sensor system for monitoring air pollution in Sydney, in: 38th Annual IEEE Conference on Local Computer Networks - Workshops, Sydney, NSW, Australia, 21–24 October 2013, IEEE, 56–64, https://doi.org/10.1109/LCNW.2013.6758498, 2013.
Smart Citizen: Map of smartcitizen kits, https://smartcitizen.me/kits, last access: 10 March 2024.
Smart Citizen Kit: https://www.seeedstudio.com/Smart-Citizen-Kit-p-2864.html, last access: 10 March 2024.
Soares, A. R. and Silva, C.: Review of ground-level ozone impact in respiratory health deterioration for the past two decades, Atmosphere, 13, 434, https://doi.org/10.3390/atmos13030434, 2022.
Sonkar, S. K., Kumar, P., George, R. C., Philip, D. and Ghosh, A. K.: Detection and Estimation of Natural Gas Leakage Using UAV by Machine Learning Algorithms, IEEE Sens. J., 22, 8041–8049, https://doi.org/10.1109/JSEN.2022.3157872, 2022.
Spinelle, L., Aleixandre, M., and Gerboles, M.: Protocol of evaluation and calibration of low-cost gas sensors for the monitoring of air pollution, JRC Publications Repository, https://doi.org/10.2788/9916, 2013.
Spinelle, L., Gerboles, M., Kok, G., Persijn, S., and Sauerwald, T.: Review of portable and low-cost sensors for the ambient air monitoring of benzene and other volatile organic compounds, Sensors, 17, 1520, https://doi.org/10.3390/s17071520, 2017.
Subramanian, R., Ellis, A., Torres-Delgado, E., Tanzer, R., Malings, C., Rivera, F., Morales, M., Baumgardner, D., Presto, A., and Mayol-Bracero, O. L.: Air quality in Puerto Rico in the aftermath of hurricane maria: A case study on the use of lower cost air quality monitors, ACS Earth and Space Chemistry, 2, 1179–1186, https://doi.org/10.1021/acsearthspacechem.8b00079, 2018.
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.: Development and application of a next generation air sensor network for the Hong Kong marathon 2015 air quality monitoring, Sensors, 16, 211, https://doi.org/10.3390/s16020211, 2016.
Suriano, D., Cassano, G., and Penza, M.: A portable gas sensor system for air quality monitoring, in: Sensors and Microsystems, edited by: Di Natale, C., Ferrari, V., Ponzoni, A., Sberveglieri, G., and Ferrari, M., Springer International Publishing, 155–158, https://doi.org/10.1007/978-3-319-00684-0_29, 2014.
Suriano, D., Prato, M., Pfister, V., Cassano, G., Dipinto, S., and Penza, M.: 20 - the case-study of the res-novae national project: Low-cost sensor-systems for urban air quality monitoring, in: Sixth Scientific Meeting EuNetAir, Academy of Sciences, Prague, Czech Republic, 5–7 October 2016, Proceedings, 77–80, https://doi.org/10.5162/6EuNetAir2016/20, 2016.
Tagle, M., Rojas, F., Reyes, F., Vásquez, Y., Hallgren, F., Lindén, J., Kolev, D., Watne, Å. K., and Oyola, P.: Field performance of a low-cost sensor in the monitoring of particulate matter in Santiago, Chile, Environ. Monit. Assess., 192, 171, https://doi.org/10.1007/s10661-020-8118-4, 2020.
Tanzer, R., Malings, C., Hauryliuk, A., Subramanian, R., and Presto, A. A.: Demonstration of a low-cost multi-pollutant network to quantify intra-urban spatial variations in air pollutant source impacts and to evaluate environmental justice, Int. J. Env. Res. Pub. He., 16, 2523, https://doi.org/10.3390/ijerph16142523, 2019.
Tanzer-Gruener, R., Li, J., Eilenberg, S. R., Robinson, A. L., and Presto, A. A.: Impacts of modifiable factors on ambient air pollution: A case study of COVID-19 shutdowns, Environ. Sci. Tech. Let., 7, 554–559, https://doi.org/10.1021/acs.estlett.0c00365, 2020.
Taylor, J. K.: Sampling and calibration for atmospheric measurements: A symposium sponsored by ASTM committee d-22 on sampling and analysis of atmospheres. ASTM International, 1987.
Tékouabou, S. C. K., Chenal, J., Azmi, R., Diop, E. B., Toulni, H., and de Nsegbe, A. P.: Towards air quality particulate-matter monitoring using low-cost sensor data and visual exploration techniques: Case study of Kisumu, Kenya, Procedia Comput. Sci., 215, 963–972, https://doi.org/10.1016/j.procs.2022.12.099, 2022.
TELLUS: AirView Map, https://airview.tellusensors.com/, last access: 17 September 2023.
Thriving Earth Exchange: Projects Archive, https://thrivingearthexchange.org/projects/, last access: 17 September 2017.
Tryner, J., L'Orange, C., Mehaffy, J., Miller-Lionberg, D., Hofstetter, J. C., Wilson, A., and Volckens, J.: Laboratory evaluation of low-cost PurpleAir PM monitors and in-field correction using co-located portable filter samplers, Atmos. Environ., 220, 117067, https://doi.org/10.1016/j.atmosenv.2019.117067, 2020.
Tsujita, W., Yoshino, A., Ishida, H., and Moriizumi, T.: Gas sensor network for air-pollution monitoring, Sensor. Actuat. B-Chem., 110, 304–311, https://doi.org/10.1016/j.snb.2005.02.008, 2005.
Turner, A. J., Kim, J., Fitzmaurice, H., Newman, C., Worthington, K., Chan, K., Wooldridge, P. J., Köehler, P., Frankenberg, C., and Cohen, R. C.: Observed impacts of covid-19 on urban CO2 emissions, Geophys. Res. Lett., 47, e2020GL090037, https://doi.org/10.1029/2020GL090037, 2020.
U.S. Department of Energy: Environmental Justice History, https://www.energy.gov/lm/environmental-justice-history, last access: 7 March 2024.
U.S. EPA (Environmental Protection Agency): NAAQS Table [Other Policies and Guidance], https://www.epa.gov/criteria-air-pollutants/naaqs-table (last access: 17 September 2023), 2014a.
U.S. EPA (Environmental Protection Agency): Village Green Project – Overviews and Factsheets, https://www.epa.gov/air-research/village-green-project (last access: 17 September 2023), 2014b.
U.S. EPA (Environmental Protection Agency): Biden-Harris Administration Announces $53 Million for 132 Community Air Pollution Monitoring Projects Across the Nation, https://www.epa.gov/newsreleases/biden-harris-administration-
announces-53-million-132-community-air-pollution (last access: 24 October 2024), 2022.
U.S. EPA (Environmental Protection Agency) Office of Research and Development: Air Sensor Guidebook, https://cfpub.epa.gov/si/si_public_record_Report.cfm?Lab=NERLanddirEntryId=277996, last access: 7 March 2024.
Vajs, I., Drajic, D., and Cica, Z.: Covid-19 lockdown in Belgrade: Impact on air pollution and evaluation of a neural network model for the correction of low-cost sensors' measurements, Appl. Sci., 11, 10563, https://doi.org/10.3390/app112210563, 2021.
Valenzuela, A. A., Schwab, M., Silnik, A. A., Debattista, A. F., and Kiessling, R. A.: Low power wireless sensor node platform for agriculture monitoring in Argentina, in: 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), Zhengzhou, China, 18–20 October 2018, IEEE, 101–1014, https://doi.org/10.1109/CyberC.2018.00029, 2018.
van Bree, B.: Innovative Monitoring Network - Ambient Urban Air Quality, Netherlands Organisation for Applied Scientific Research (TNO), https://resolver.tno.nl/uuid:7e12cbaa-0ad0-47f4-9bd6-2682992b8d2a, last access: 25 October 2024.
van Zoest, V. M.: Spatio-temporal modelling of urban sensor network data: Mapping air quality risks in Eindhoven, PhD thesis, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, the Netherlands, ISBN 978-90-365-4929-5, https://library.itc.utwente.nl/papers_2020/phd/vanzoest.pdf (last access: 5 November 2024), 2020.
Velásquez, R. M. A., Acevedo, D. M. V., Paredes, M. G. S. P., and Vargas, C. Z.: Implementation and analysis of low-cost network for air pollution in Lima and Arequipa, in: 2022 IEEE XXIX International Conference on Electronics, Electrical Engineering and Computing (INTERCON), Lima, Peru, 11–13 August 2022, IEEE, 1–4, https://doi.org/10.1109/INTERCON55795.2022.9870052, 2022.
Villa, T. F., Gonzalez, F., Miljievic, B., Ristovski, Z. D., and Morawska, L.: An Overview of Small Unmanned Aerial Vehicles for Air Quality Measurements: Present Applications and Future Prospectives, Sensors-Basel, 16, 1072, https://doi.org/10.3390/s16071072, 2016.
Vrijheid, M., Basagaña, X., Gonzalez, J. R., et al.: Advancing tools for human early life course exposome research and translation, Environmental Epidemiology, 5, e166, https://doi.org/10.1097/EE9.0000000000000166, 2021.
Wallace, L., Zhao, T., and Klepeis, N. E.: Calibration of PurpleAir PA-I and PA-II monitors using daily mean PM2.5 concentrations measured in California, Washington, and Oregon from 2017 to 2021, Sensors-Basel, 22, 4741, https://doi.org/10.3390/s22134741, 2022.
Ware, J. H., Spengler, J. D., Neas, L. M., Samet, J. M., Wagner, G. R., Coultas, D., Ozkaynak, H., and Schwab, M.: Respiratory and irritant health effects of ambient volatile organic compounds, Am. J. Epidemiol., 137, 1287–1301, https://doi.org/10.1093/oxfordjournals.aje.a116639, 1993.
Washington University in St. Louis: BKH Outdoor Sensor Network, https://sites.wustl.edu/mongoliaproject/bkh-outdoor-network/, last access: 10 March 2024.
Wen, T.-H., Jiang, J.-A., Sun, C.-H., Juang, J.-Y., and Lin, T.-S.: Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (Wsn) framework, Int. J. Env. Res. Pub. He., 10, 6380–6396, https://doi.org/10.3390/ijerph10126380, 2013.
Weppner, W.: Solid-state electrochemical gas sensors, Sensor. Actuator., 12, 107–119, https://doi.org/10.1016/0250-6874(87)85010-2, 1987.
Wesseling, J., de Ruiter, H., Blokhuis, C., Drukker, D., Weijers, E., Volten, H., Vonk, J., Gast, L., Voogt, M., Zandveld, P., van Ratingen, S., and Tielemans, E.: Development and implementation of a platform for public information on air quality, sensor measurements, and citizen science, Atmosphere, 10, 445, https://doi.org/10.3390/atmos10080445, 2019.
Whitty, R., Pfeffer, M., Ilyinskaya, E., Roberts, T., Schmidt, A., Barsotti, S., Strauch, W., Crilley, L., Pope, F., Bellanger, H., Mendoza, E., Mather, T., Liu, E., Peters, N., Taylor, I., Francis, H., Hernández Leiva, X., Lynch, D., Nobert, S., and Baxter, P.: Effectiveness of low-cost air quality monitors for identifying volcanic SO2 and PM downwind from Masaya volcano, Nicaragua, Volcanica, 5, 33–59, https://doi.org/10.30909/vol.05.01.3359, 2022.
Williams, R., Duvall, R., Kilaru, V., Hagler, G., Hassinger, L., Benedict, K., Rice, J., Kaufman, A., Judge, R., Pierce, G., Allen, G., Bergin, M., Cohen, R. C., Fransioli, P., Gerboles, M., Habre, R., Hannigan, M., Jack, D., Louie, P., Martin, N. A., Penza, M., Polidori, A., Subramanian, R., Ray, K., Schauer, J., Seto, E., Thurston, G., Turner, J., Wexler, A. S., and Ning, Z.: Deliberating performance targets workshop: Potential paths for emerging PM2.5 and O3 air sensor progress, Atmospheric Environment: X, 2, 100031, https://doi.org/10.1016/j.aeaoa.2019.100031, 2019.
Windy: https://www.windy.com/, last access: 10 March 2024.
Wyzga, R. E. and Rohr, A. C.: Long-term particulate matter exposure: Attributing health effects to individual PM components, J. Air Waste Manage., 65, 523–543, https://doi.org/10.1080/10962247.2015.1020396, 2015.
World Meteorological Organization: 2021 WMO Report No. 1215 – An update on low-cost sensors for the measurement of atmospheric composition, ISBN 978-92-63-11215-6, https://library.wmo.int/idurl/4/37465 (last access: 8 March 2024), 2021.
Xi, X., Johnson, M. S., Jeong, S., Fladeland, M., Pieri, D., Diaz, J. A., and Bland, G. L.: Constraining the sulfur dioxide degassing flux from Turrialba volcano, Costa Rica using unmanned aerial system measurements, J. Volcanol. Geoth. Res., 325, 110–118, https://doi.org/10.1016/j.jvolgeores.2016.06.023, 2016.
Yaacoub, E., Kadri, A., Mushtaha, M., and Abu-Dayya, A.: Air quality monitoring and analysis in Qatar using a wireless sensor network deployment, in: 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC), Sardinia, Italy, 1–5 July 2013, IEEE, 596–601, https://doi.org/10.1109/IWCMC.2013.6583625, 2013.
Yang, L. H., Hagan, D. H., Rivera-Rios, J. C., Kelp, M. M., Cross, E. S., Peng, Y., Kaiser, J., Williams, L. R., Croteau, P. L., Jayne, J. T., and Ng, N. L.: Investigating the sources of urban air pollution using low-cost air quality sensors at an urban Atlanta site, Environ. Sci. Technol., 56, 7063–7073, https://doi.org/10.1021/acs.est.1c07005, 2022.
Yavus, E., Kuzu, S. L., and Saral, A.: Investigation of vertical particulate matter distribution using low-cost sensors in Istanbul, Turkey, BL2ES2-21, BABES-21 and BISET-21, Barcelona, Spain, 13–15 October 2021, https://doi.org/10.17758/EIRAI10.F1021210, 2021.
Yoo, E.-H., Zammit-Mangion, A., and Chipeta, M. G.: Adaptive spatial sampling design for environmental field prediction using low-cost sensing technologies, Atmos. Environ., 221, 117091, https://doi.org/10.1016/j.atmosenv.2019.117091, 2020.
Zaidan, M. A., Hossein Motlagh, N., Fung, P. L., Lu, D., Timonen, H., Kuula, J., Niemi, J. V., Tarkoma, S., Petäjä, T., Kulmala, M., and Hussein, T.: Intelligent calibration and virtual sensing for integrated low-cost air quality sensors, IEEE Sens. J., 20, 13638–13652, https://doi.org/10.1109/JSEN.2020.3010316, 2020.
Zaldei, A., Vagnoli, C., Di Lonardo, S., Gioli, B., Gualtieri, G., Toscano, P., Martelli, F., and Matese, A.: AIRQino, a low-cost air quality mobile platform, EGU General Assembly, Vienna, Austria, 12–17 April 2015, EGU2015-6158, 2015.
Zampolli, S., Elmi, I., Ahmed, F., Passini, M., Cardinali, G. C., Nicoletti, S., and Dori, L.: An electronic nose based on solid state sensor arrays for low-cost indoor air quality monitoring applications, Sensor. Actuat. B-Chem., 101, 39–46, https://doi.org/10.1016/j.snb.2004.02.024, 2004.
Zeb, A., Soininen, J.-P., and Sozer, N.: Data harmonisation as a key to enable digitalisation of the food sector: A review, Food Bioprod. Process., 127, 360–370, https://doi.org/10.1016/j.fbp.2021.02.005, 2021.
Zhou, F., Liu, J., Zhu, H., Yang, X., and Fan, Y.: A Real-Time Measurement-Modeling System for Ship Air Pollution Emission Factors, J. Mar. Sci. Eng.-Basel, 10, 760, https://doi.org/10.3390/jmse10060760, 2022.
Zimmerman, N., Presto, A. A., Kumar, S. P. N., Gu, J., Hauryliuk, A., Robinson, E. S., Robinson, A. L., and R. Subramanian: A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring, Atmos. Meas. Tech., 11, 291–313, https://doi.org/10.5194/amt-11-291-2018, 2018.
Executive editor
I agree with the handling aditor that this is a very useful and comprehensive study and deserves wide attention.
I agree with the handling aditor that this is a very useful and comprehensive study and deserves...
Short summary
We reviewed 60 sensor networks and 17 related efforts (sensor review papers and data accessibility projects) to better understand the landscape of stationary low-cost gas-phase sensor networks deployed in outdoor environments worldwide. Gaps in monitoring efforts include the availability of gas-phase measurements compared to particulate matter (PM) and geographic coverage gaps (the Global South, rural areas). We conclude with a summary of cross-network unification and quality control efforts.
We reviewed 60 sensor networks and 17 related efforts (sensor review papers and data...