Articles | Volume 19, issue 19
https://doi.org/10.5194/acp-19-12531-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-19-12531-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note
| 
09 Oct 2019
Technical note |
| 09 Oct 2019
| 09 Oct 2019
Technical note: Effects of uncertainties and number of data points on line fitting – a case study on new particle formation
Department of Applied Physics, University of Eastern Finland,
Kuopio, Finland
Mikko R. A. Pitkänen
Department of Applied Physics, University of Eastern Finland,
Kuopio, Finland
Finnish Meteorological Institute, Atmospheric Research Centre of
Eastern Finland, Kuopio, Finland
Tuomo Nieminen
Department of Applied Physics, University of Eastern Finland,
Kuopio, Finland
currently at: Institute for Atmospheric and Earth System
Research, University of Helsinki, Helsinki, Finland
Antti Lipponen
Finnish Meteorological Institute, Atmospheric Research Centre of
Eastern Finland, Kuopio, Finland
Sini Isokääntä
Department of Applied Physics, University of Eastern Finland,
Kuopio, Finland
Antti Arola
Finnish Meteorological Institute, Atmospheric Research Centre of
Eastern Finland, Kuopio, Finland
Kari E. J. Lehtinen
Department of Applied Physics, University of Eastern Finland,
Kuopio, Finland
Finnish Meteorological Institute, Atmospheric Research Centre of
Eastern Finland, Kuopio, Finland
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15 citations as recorded by crossref.
- On the calibration of FIGAERO-ToF-CIMS: importance and impact of calibrant delivery for the particle-phase calibration A. Ylisirniö et al. 10.5194/amt-14-355-2021
- Upper-tropospheric pollutants observed by MIPAS: geographic and seasonal variations N. Glatthor et al. 10.5194/acp-25-1175-2025
- Constraining the Twomey effect from satellite observations: issues and perspectives J. Quaas et al. 10.5194/acp-20-15079-2020
- Observations on aerosol optical properties and scavenging during cloud events A. Ruuskanen et al. 10.5194/acp-21-1683-2021
- Spatiotemporal Dynamics of Suspended Sediments in the Negro River, Amazon Basin, from In Situ and Sentinel-2 Remote Sensing Data R. Marinho et al. 10.3390/ijgi10020086
- Formation and growth of sub-3-nm aerosol particles in experimental chambers L. Dada et al. 10.1038/s41596-019-0274-z
- Clumped isotope measurements reveal aerobic oxidation of methane below the Greenland ice sheet G. Adnew et al. 10.1016/j.gca.2024.11.009
- Quantifying the relationship between observed variables with censored values using Bayesian error-in-variables regression P. Vermeiren et al. 10.1016/j.chemosphere.2025.144269
- A biogenic secondary organic aerosol source of cirrus ice nucleating particles M. Wolf et al. 10.1038/s41467-020-18424-6
- High Particle Number Emissions Determined with Robust Regression Plume Analysis (RRPA) from Hundreds of Vehicle Chases M. Olin et al. 10.1021/acs.est.2c08198
- Challenges and solutions in determining dilution ratios and emission factors from chase measurements of passenger vehicles V. Leinonen et al. 10.5194/amt-16-5075-2023
- Constraining Water Depth Influence on Organic Paleotemperature Proxies Using Sedimentary Archives D. Varma et al. 10.1029/2022PA004533
- Multivariate model-based investigation of the temperature dependence of ozone concentration in Finnish boreal forest S. Isokääntä et al. 10.1016/j.atmosenv.2022.119315
- Significance of the organic aerosol driven climate feedback in the boreal area T. Yli-Juuti et al. 10.1038/s41467-021-25850-7
- A hybrid method for reconstructing the historical evolution of aerosol optical depth from sunshine duration measurements W. Wandji Nyamsi et al. 10.5194/amt-13-3061-2020
Latest update: 18 Apr 2025
Short summary
Atmospheric measurement data never come without measurement error. Too often, these errors are neglected when researchers make inferences from their data. We applied multiple line-fitting methods to simulated data mimicking two central variables in aerosol research. Our results show that an ordinary least squares fit, typically used to describe relationships, underestimates the slope of the fit and that methods taking the measurement uncertainty into account performed significantly better.
Atmospheric measurement data never come without measurement error. Too often, these errors are...
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