cpc > Condensation Particle CounterInstrument Type(s) > Baseline • Evaluation • External • Guest

The condensation particle counter (CPC) measures sub-micron aerosol particle number concentration by condensing fluid onto particles and causing them to grow to sizes that are easily detectable by optical scattering. The condensing liquid is typically an alcohol (e.g., butanol) or water.

Depending on the CPC type, typical CPC instruments can count particles with sizes that range from 3 to 3000 nanometers (ultrafine CPC) or from 10 to 3000 nanometers (fine CPC). The CPC is part of the aerosol observing system (AOS).


The data set has been developed to provide regionally representative total particle number concentration one-minute-time-resolution data from the condensation particle counter (CPC) at ENA.

Primary Measurements


  • Fixed
  • AMF1
  • AMF2
  • AMF3

Data Details

Developed By Francesca Gallo | Allison Aiken
Contact Francesca Gallo
Resource(s) Data Directory
Data format Text
Site ENA
Content time range 14 October 2010 - 29 November 2022
Attribute accuracy The Eastern North Atlantic (ENA) Aerosol Mask (ENA-AM) included in this data set is a mathematical algorithm that identifies and masks high-concentration aerosol events using the one-minute-resolution Aerosol Observing System (AOS) fine concentration particle counter (CPC) data at ENA. ENA-AM was previously developed and validated during the ACE-ENA IOP in 2017, and based on the agreement between ENA Central site (C1) and ENA temporary Supplementary site (S1) masked CPC data sets.
Positional accuracy No formal positional accuracy tests were conducted.
Data Consistency and Completeness Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details.
Access Restriction No access constraints are associated with this data.
Use Restriction No use constraints are associated with this data.
Citations Gallo, F, J Uin, SR Springston, J Wang, G Zheng, C Kuang, E Azevedo, R Wood, A McComiskey, F Mei, J Kyrouac, and AC Aiken. 2020. "Identifying a regional aerosol baseline in the Eastern North Atlantic using collocated measurements and a mathematical algorithm to mask high submicron number concentration aerosol events." Atmospheric Chemistry and Physics 20, 7553-7573, https://doi.org/10.5194/acp-20-7553-2020.

Aiken, AC, F Gallo, J Uin, SR Springston, J Wang, G Zheng, C Kuang, A McComiskey, R Wood, C Flynn, A Theisen, E Azevedo, P Ortega, and H Powers. 2019. Eastern North Atlantic (ENA) Aerosol Supplementary Site (S1) Data Analysis Report. Ed. by Robert Stafford, ARM user facility. DOE/SC-ARM-TR-229.

Gallo, F, and AC Aiken. 2020. Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Summer 2017, US, N. p., https://doi.org/10.5439/1579567.

Gallo, F, and AC Aiken, 2020. Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Winter 2017, US, N. p., https://doi.org/10.5439/1579568.

Aiken, AC, and F Gallo. 2020. Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Supplementary Facility (S01), US, N. p., https://doi.org/10.5439/1581730.


Barrett P, S Abel, H Coe, I Crawford, A Dobracki, J Haywood, S Howell, A Jones, J Langridge, G McFarquhar, G Nott, H Price, J Redemann, Y Shinozuka, K Szpek, J Taylor, R Wood, H Wu, P Zuidema, S Bauguitte, R Bennett, K Bower, H Chen, S Cochrane, M Cotterell, N Davies, D Delene, C Flynn, A Freedman, S Freitag, S Gupta, D Noone, T Onasch, J Podolske, M Poellot, S Schmidt, S Springston, A Sedlacek III, J Trembath, A Vance, M Zawadowicz, and J Zhang. 2022. "Intercomparison of airborne and surface-based measurements during the CLARIFY, ORACLES and LASIC field experiments." Atmospheric Measurement Techniques, 15(21), 10.5194/amt-15-6329-2022.

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Beck I, H Angot, A Baccarini, L Dada, L Quéléver, T Jokinen, T Laurila, M Lampimäki, N Bukowiecki, M Boyer, X Gong, M Gysel-Beer, T Petäjä, J Wang, and J Schmale. 2022. "Automated identification of local contamination in remote atmospheric composition time series." Atmospheric Measurement Techniques, 15(14), 10.5194/amt-15-4195-2022.

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