77 citations as recorded by crossref.

1. Southern California megacity CO<sub>2</sub>, CH<sub>4</sub>, and CO flux estimates using ground- and space-based remote sensing and a Lagrangian model J. Hedelius et al. 10.5194/acp-18-16271-2018
2. Estimating vehicle carbon dioxide emissions from Boulder, Colorado, using horizontal path-integrated column measurements E. Waxman et al. 10.5194/acp-19-4177-2019
3. Development and deployment of a mid-cost CO2 sensor monitoring network to support atmospheric inverse modeling for quantifying urban CO2 emissions in Paris J. Lian et al. 10.5194/amt-17-5821-2024
4. Electrochemical sensors on board a Zeppelin NT: in-flight evaluation of low-cost trace gas measurements T. Schuldt et al. 10.5194/amt-16-373-2023
5. High-performance machine-learning-based calibration of low-cost nitrogen dioxide sensor using environmental parameter differentials and global data scaling S. Koziel et al. 10.1038/s41598-024-77214-y
6. Recovery of sparse urban greenhouse gas emissions B. Zanger et al. 10.5194/gmd-15-7533-2022
7. Observing local CO<sub>2</sub> sources using low-cost, near-surface urban monitors A. Shusterman et al. 10.5194/acp-18-13773-2018
8. An Interpolation Method to Reduce the Computational Time in the Stochastic Lagrangian Particle Dispersion Modeling of Spatially Dense XCO2 Retrievals D. Roten et al. 10.1029/2020EA001343
9. Tall tower eddy covariance measurements of CO2 fluxes in Vienna, Austria B. Matthews & H. Schume 10.1016/j.atmosenv.2022.118941
10. Integration and calibration of non-dispersive infrared (NDIR) CO<sub>2</sub> low-cost sensors and their operation in a sensor network covering Switzerland M. Müller et al. 10.5194/amt-13-3815-2020
11. The BErkeley Atmospheric CO<sub>2</sub> Observation Network: field calibration and evaluation of low-cost air quality sensors J. Kim et al. 10.5194/amt-11-1937-2018
12. Low-cost urban carbon monitoring network and implications for china: a comprehensive review H. Jiang et al. 10.1007/s11356-023-29836-4
13. Computationally efficient methods for large-scale atmospheric inverse modeling T. Cho et al. 10.5194/gmd-15-5547-2022
14. Observed decreases in on-road CO<sub>2</sub> concentrations in Beijing during COVID-19 restrictions D. Liu et al. 10.5194/acp-21-4599-2021
15. Background conditions for an urban greenhouse gas network in the Washington, DC, and Baltimore metropolitan region A. Karion et al. 10.5194/acp-21-6257-2021
16. Cost-Efficient measurement platform and machine-learning-based sensor calibration for precise NO2 pollution monitoring A. Pietrenko-Dabrowska et al. 10.1016/j.measurement.2024.115168
17. Monitoring of greenhouse gases and pollutants across an urban area using a light-rail public transit platform L. Mitchell et al. 10.1016/j.atmosenv.2018.05.044
18. A city-level comparison of fossil-fuel and industry processes-induced CO2 emissions over the Beijing-Tianjin-Hebei region from eight emission inventories P. Han et al. 10.1186/s13021-020-00163-2
19. Expected Performance of a Mobile e-nose platform for Real Time Victim Localization S. Blionas 10.1088/1742-6596/1730/1/012120
20. Evaluation and environmental correction of ambient CO<sub>2</sub> measurements from a low-cost NDIR sensor C. Martin et al. 10.5194/amt-10-2383-2017
21. Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM2.5 Monitoring in Accra, Ghana G. Raheja et al. 10.1021/acs.est.2c09264
22. On the Large Variation in Atmospheric CO2 Concentration at Shangdianzi GAW Station during Two Dust Storm Events in March 2021 X. Li et al. 10.3390/atmos14091348
23. Simulating atmospheric tracer concentrations for spatially distributed receptors: updates to the Stochastic Time-Inverted Lagrangian Transport model's R interface (STILT-R version 2) B. Fasoli et al. 10.5194/gmd-11-2813-2018
24. Spatial-Temporal Analysis of PM2.5 and NO2 Concentrations Collected Using Low-Cost Sensors in Peñuelas, Puerto Rico S. Reece et al. 10.3390/s18124314
25. A portable sensor for the determination of tree canopy air quality W. Berelson et al. 10.1039/D3EA00057E
26. Monitoring Urban Greenhouse Gases Using Open-Path Fourier Transform Spectroscopy B. Byrne et al. 10.1080/07055900.2019.1698407
27. Influence of dataset density on CO2 and CH4 trend calculation I. Pérez et al. 10.1007/s11869-019-00681-0
28. MUCCnet: Munich Urban Carbon Column network F. Dietrich et al. 10.5194/amt-14-1111-2021
29. Carbon dioxide and methane measurements from the Los Angeles Megacity Carbon Project – Part 1: calibration, urban enhancements, and uncertainty estimates K. Verhulst et al. 10.5194/acp-17-8313-2017
30. Challenges in Monitoring Atmospheric CO2 Concentrations in Seoul Using Low-Cost Sensors C. Park et al. 10.1007/s13143-020-00213-2
31. Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary) A. Clements et al. 10.3390/s17112478
32. Toward Establishing a Low-cost UAV Coordinated Carbon Observation Network (LUCCN): First Integrated Campaign in China D. Yang et al. 10.1007/s00376-023-3107-5
33. Statistical data pre-processing and time series incorporation for high-efficacy calibration of low-cost NO2 sensor using machine learning S. Koziel et al. 10.1038/s41598-024-59993-6
34. Towards a hygroscopic growth calibration for low-cost PM2.5 sensors M. Patel et al. 10.5194/amt-17-1051-2024
35. Stationary and portable multipollutant monitors for high-spatiotemporal-resolution air quality studies including online calibration C. Buehler et al. 10.5194/amt-14-995-2021
36. Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties K. Wu et al. 10.1525/elementa.138
37. COCAP: a carbon dioxide analyser for small unmanned aircraft systems M. Kunz et al. 10.5194/amt-11-1833-2018
38. Observing System Choice Can Minimize Interference of the Biosphere in Studies of Urban CO2 Emissions R. Lal & E. Kort 10.1029/2022JD037452
39. Using a gradient boosting model to improve the performance of low-cost aerosol monitors in a dense, heterogeneous urban environment N. Johnson et al. 10.1016/j.atmosenv.2018.04.019
40. Optimising Citizen-Driven Air Quality Monitoring Networks for Cities S. Gupta et al. 10.3390/ijgi7120468
41. An Analysis on the Performance of a Mobile Platform with Gas Sensors for Real Time Victim Localization A. Anyfantis & S. Blionas 10.3390/s21062018
42. Social Impact Assessment of HealthyAIR Tool for Real-Time Detection of Pollution Risk A. Moreno Cano et al. 10.3390/su12239856
43. Analysis of anthropogenic CO2 emission uncertainty and influencing factors at city scale in Yangtze River Delta region: One of the world's largest emission hotspots H. Liu et al. 10.1016/j.apr.2024.102281
44. Compact Non-Dispersive Infrared Multi-Gas Sensing Platform for Large Scale Deployment with Sub-ppm Resolution B. Wastine et al. 10.3390/atmos13111789
45. An overview of outdoor low-cost gas-phase air quality sensor deployments: current efforts, trends, and limitations K. Okorn & L. Iraci 10.5194/amt-17-6425-2024
46. Plume analysis from field evaluations of a portable air quality monitoring system J. Marto et al. 10.1080/10962247.2020.1834010
47. Evaluation of Low-Cost CO2 Sensors Using Reference Instruments and Standard Gases for Indoor Use Q. Cai et al. 10.3390/s24092680
48. Spatial Statistical Downscaling for Constructing High-Resolution Nature Runs in Global Observing System Simulation Experiments P. Ma et al. 10.1080/00401706.2018.1524791
49. Climate mitigation policies for cities must consider air quality impacts R. Commane & L. Schiferl 10.1016/j.chempr.2022.02.006
50. Spatial and temporal variations of CO<sub>2</sub> mole fractions observed at Beijing, Xianghe, and Xinglong in North China Y. Yang et al. 10.5194/acp-21-11741-2021
51. Long-term urban carbon dioxide observations reveal spatial and temporal dynamics related to urban characteristics and growth L. Mitchell et al. 10.1073/pnas.1702393115
52. Observed Impacts of COVID‐19 on Urban CO2 Emissions A. Turner et al. 10.1029/2020GL090037
53. On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction S. Koziel et al. 10.1016/j.knosys.2024.111564
54. Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing S. Koziel et al. 10.1016/j.jestch.2024.101729
55. Mapping pollution exposure and chemistry during an extreme air quality event (the 2018 Kīlauea eruption) using a low-cost sensor network B. Crawford et al. 10.1073/pnas.2025540118
56. Ventilation rates in California classrooms: Why many recent HVAC retrofits are not delivering sufficient ventilation W. Chan et al. 10.1016/j.buildenv.2019.106426
57. Characterization of a commercial lower-cost medium-precision non-dispersive infrared sensor for atmospheric CO<sub>2</sub> monitoring in urban areas E. Arzoumanian et al. 10.5194/amt-12-2665-2019
58. A Network of Field-Calibrated Low-Cost Sensor Measurements of PM2.5 in Lomé, Togo, Over One to Two Years G. Raheja et al. 10.1021/acsearthspacechem.1c00391
59. Detecting Urban Emissions Changes and Events With a Near‐Real‐Time‐Capable Inversion System J. Ware et al. 10.1029/2018JD029224
60. Constraining Sector‐Specific CO2 Fluxes Using Space‐Based XCO2 Observations Over the Los Angeles Basin D. Roten et al. 10.1029/2023GL104376
61. Calibrations of Low-Cost Air Pollution Monitoring Sensors for CO, NO2, O3, and SO2 P. Han et al. 10.3390/s21010256
62. A method for using stationary networks to observe long-term trends of on-road emission factors of primary aerosol from heavy-duty vehicles H. Fitzmaurice & R. Cohen 10.5194/acp-22-15403-2022
63. Estimation of cucumber net primary production using environmental and control information in a smart multi-span plastic greenhouse M. Kang et al. 10.1016/j.compag.2024.108819
64. Observing Annual Trends in Vehicular CO2 Emissions J. Kim et al. 10.1021/acs.est.1c06828
65. Proof of concept apparatus for the design of a simple, low cost, mobile e-nose for real-time victim localization (human presence) based on indoor air quality monitoring sensors A. Anyfantis & S. Blionas 10.1016/j.sbsr.2019.100312
66. Monitoring Excess Exposure to Air Pollution for Professional Drivers in London Using Low-Cost Sensors L. Frederickson et al. 10.3390/atmos11070749
67. A multi-city urban atmospheric greenhouse gas measurement data synthesis L. Mitchell et al. 10.1038/s41597-022-01467-3
68. An open-path observatory for greenhouse gases based on near-infrared Fourier transform spectroscopy T. Schmitt et al. 10.5194/amt-16-6097-2023
69. Modeling fine-grained spatio-temporal pollution maps with low-cost sensors S. Iyer et al. 10.1038/s41612-022-00293-z
70. Evaluation of version 3.0B of the BEHR OMI NO<sub>2</sub> product J. Laughner et al. 10.5194/amt-12-129-2019
71. The Berkeley Environmental Air-quality and CO<sub>2</sub> Network: field calibrations of sensor temperature dependence and assessment of network scale CO<sub>2</sub> accuracy E. Delaria et al. 10.5194/amt-14-5487-2021
72. Constraining Urban CO2 Emissions Using Mobile Observations from a Light Rail Public Transit Platform D. Mallia et al. 10.1021/acs.est.0c04388
73. Development of a small unmanned aircraft system to derive CO<sub>2</sub> emissions of anthropogenic point sources M. Reuter et al. 10.5194/amt-14-153-2021
74. Monitoring of hourly carbon dioxide concentration under different land use types in arid ecosystem K. Biro Turk et al. 10.1515/biol-2022-0534
75. High-Resolution Modeling and Apportionment of Diesel-Related Contributions to Black Carbon Concentrations S. Hamilton & R. Harley 10.1021/acs.est.1c03913
76. Assessing vehicle fuel efficiency using a dense network of CO<sub>2</sub> observations H. Fitzmaurice et al. 10.5194/acp-22-3891-2022
77. Network design for quantifying urban CO<sub>2</sub> emissions: assessing trade-offs between precision and network density A. Turner et al. 10.5194/acp-16-13465-2016