## A.4 Aerosol in situ measurements

<table><thead><tr><th>ACTRIS variable</th><th>NF requirements Mandatory - M Specializing - S Optimum - O</th><th>Associated Topical Centre</th><th>Data producer L1, L2</th><th>RRT-O= operational in RRT now RRT-S = scheduled from 2020</th><th>Integrating Nephelometer</th><th>Mobility Particle Size Spectrometer</th><th>Aerodynamic & Optical Particle Size Spectrometer</th><th>Absorption Photometer</th><th>Condensation Particle Counter</th><th>Scanning PSM, (N)AIS, N-MPSS</th><th>Particle Size Magnifier (PSM)</th><th>Cloud Condensation Nuclei Counter</th><th>Filter sampling</th><th>Thermal-optical analyser</th><th>Offline filter-based IC GC-MS HDLC-MS LC/MS</th><th>Aerosol Mass Spectrometer</th><th>X-Ray Fluorescence, Particle Induced X-ray Emission</th></tr></thead><tbody><tr><td>Particle light scattering and backscattering coefficients</td><td>M</td><td>CAIS</td><td>NF</td><td>NRT-O</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Particle number size distribution - mobility diameter</td><td>M</td><td>CAIS</td><td>NF</td><td>NRT-O</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Particle number size distribution - optical and aerodynamic diameter</td><td>S</td><td>CAIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Particle light absorption coefficient and equivalent black carbon concentration</td><td>M</td><td>CAIS</td><td>NF</td><td>NRT-O</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Particle number concentration</td><td>S</td><td>CAIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Nanoparticle number size distribution</td><td>S</td><td>CAIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
## A.4 Aerosol in situ measurements

<table><thead><tr><th>ACTRIS variable</th><th>NF requirements Mandatory - M Specializing - S Optimum - O</th><th>Associated Topical Centre</th><th>Data producer L1, L2</th><th>RRT-O= operational in RRT now RRT-S = scheduled from 2020</th><th>Integrating Nephelometer</th><th>Mobility Particle Size Spectrometer</th><th>Aerodynamic & Optical Particle Size Spectrometer</th><th>Absorption Photometer</th><th>Condensation Particle Counter</th><th>Scanning PSM, (N)AIS, N-MPSS</th><th>Particle Size Magnifier (PSM)</th><th>Cloud Condensation Nuclei Counter</th><th>Filter sampling</th><th>Thermal-optical analyser</th><th>Offline filter-based IC GC-MS HDLC-MS LC/MS</th><th>Aerosol Mass Spectrometer</th><th>X-Ray Fluorescence, Particle Induced X-ray Emission</th></tr></thead><tbody><tr><td>Particle light scattering and backscattering coefficients</td><td>M</td><td>CAIS</td><td>NF</td><td>NRT-O</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Particle number size distribution - mobility diameter</td><td>M</td><td>CAIS</td><td>NF</td><td>NRT-O</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Particle number size distribution - optical and aerodynamic diameter</td><td>S</td><td>CAIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Particle light absorption coefficient and equivalent black carbon concentration</td><td>M</td><td>CAIS</td><td>NF</td><td>NRT-O</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Particle number concentration</td><td>S</td><td>CAIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Nanoparticle number size distribution</td><td>S</td><td>CAIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><thead><tr><th>ACTRIS variable</th><th>NF requirements Mandatory - M Specializing - S Optimum - O</th><th>Associated Topical Centre</th><th>Data producer L1, L2</th><th>RRT-O= operational in RRT now RRT-S = scheduled from 2020</th><th>Integrating Nephelometer</th><th>Mobility Particle Size Spectrometer</th><th>Aerodynamic & Optical Particle Size Spectrometer</th><th>Absorption Photometer</th><th>Condensation Particle Counter</th><th>Scanning PSM, (N)AIS, N-MPSS</th><th>Particle Size Magnifier (PSM)</th><th>Cloud Condensation Nuclei Counter</th><th>Filter sampling</th><th>Thermal-optical analyser</th><th>Offline filter-based IC GC-MS HDLC-MS LC/MS</th><th>Aerosol Mass Spectrometer</th><th>X-Ray Fluorescence, Particle Induced X-ray Emission</th></tr></thead><tbody><tr><td>Nanoparticle number concentration</td><td>S</td><td>CAIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cloud condensation nuclei number concentration</td><td>S</td><td>CAIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mass concentration of particulate organic and elemental carbon</td><td>S</td><td>CAIS</td><td>NF</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mass concentration of particulate organic tracers</td><td>S</td><td>CAIS</td><td>NF</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mass concentration of non-refractory particulate organics and inorganics</td><td>S</td><td>CAIS</td><td>NF/TC</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mass concentration of particulate elements</td><td>S</td><td>CAIS</td><td>NF</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><thead><tr><th>ACTRIS variable</th><th>NF requirements Mandatory - M Specializing - S Optimum - O</th><th>Associated Topical Centre</th><th>Data producer L1, L2</th><th>RRT-O= operational in RRT now RRT-S = scheduled from 2020</th><th>Integrating Nephelometer</th><th>Mobility Particle Size Spectrometer</th><th>Aerodynamic & Optical Particle Size Spectrometer</th><th>Absorption Photometer</th><th>Condensation Particle Counter</th><th>Scanning PSM, (N)AIS, N-MPSS</th><th>Particle Size Magnifier (PSM)</th><th>Cloud Condensation Nuclei Counter</th><th>Filter sampling</th><th>Thermal-optical analyser</th><th>Offline filter-based IC GC-MS HDLC-MS LC/MS</th><th>Aerosol Mass Spectrometer</th><th>X-Ray Fluorescence, Particle Induced X-ray Emission</th></tr></thead><tbody><tr><td>Nanoparticle number concentration</td><td>S</td><td>CAIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cloud condensation nuclei number concentration</td><td>S</td><td>CAIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mass concentration of particulate organic and elemental carbon</td><td>S</td><td>CAIS</td><td>NF</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mass concentration of particulate organic tracers</td><td>S</td><td>CAIS</td><td>NF</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mass concentration of non-refractory particulate organics and inorganics</td><td>S</td><td>CAIS</td><td>NF/TC</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Mass concentration of particulate elements</td><td>S</td><td>CAIS</td><td>NF</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><thead><tr><td>ACTRIS variable</td><td>Comment</td></tr></thead><tbody><tr><td>Particle light scattering and backscattering coefficients</td><td>multi-wavelength</td></tr><tr><td>Particle number size distribution - mobility diameter</td><td>0.01 - 0.8 µm</td></tr><tr><td>Particle number size distribution - optical and aerodynamic diameter</td><td>0.7 - 10 µm</td></tr><tr><td>Particle light absorption coefficient and equivalent black carbon concentration</td><td></td></tr><tr><td>Particle number concentration</td><td>> 0.01 µm</td></tr><tr><td>Nanoparticle number size distribution</td><td>0.001 - 0.02 µm</td></tr><tr><td>Nanoparticle number concentration</td><td>&lt; 0.01 µm</td></tr><tr><td>Cloud condensation nuclei number concentration</td><td>at various supersaturations</td></tr><tr><td>Mass concentration of particulate organic and elemental carbon</td><td></td></tr><tr><td>Mass concentration of particulate organic tracers</td><td></td></tr><tr><td>Mass concentration of non-refractory particulate organics and inorganics</td><td></td></tr><tr><td>Mass concentration of particulate elements</td><td></td></tr></tbody></table>
<table><thead><tr><td>ACTRIS variable</td><td>Comment</td></tr></thead><tbody><tr><td>Particle light scattering and backscattering coefficients</td><td>multi-wavelength</td></tr><tr><td>Particle number size distribution - mobility diameter</td><td>0.01 - 0.8 µm</td></tr><tr><td>Particle number size distribution - optical and aerodynamic diameter</td><td>0.7 - 10 µm</td></tr><tr><td>Particle light absorption coefficient and equivalent black carbon concentration</td><td></td></tr><tr><td>Particle number concentration</td><td>> 0.01 µm</td></tr><tr><td>Nanoparticle number size distribution</td><td>0.001 - 0.02 µm</td></tr><tr><td>Nanoparticle number concentration</td><td>&lt; 0.01 µm</td></tr><tr><td>Cloud condensation nuclei number concentration</td><td>at various supersaturations</td></tr><tr><td>Mass concentration of particulate organic and elemental carbon</td><td></td></tr><tr><td>Mass concentration of particulate organic tracers</td><td></td></tr><tr><td>Mass concentration of non-refractory particulate organics and inorganics</td><td></td></tr><tr><td>Mass concentration of particulate elements</td><td></td></tr></tbody></table>
## A.5 Cloud in situ measurements

<table><thead><tr><th>ACTRIS variable</th><th>NF requirements<br>Mandatory - M<br>Specializing - S<br>Optimum - O</th><th>Associated<br>Topical<br>Centre</th><th>Data<br>producer<br>L1, L2</th><th>RRT-O=<br>operational in<br>RRT now<br>RRT-S =<br>scheduled from<br>2020</th><th>Mobility Particle<br>Size Spectrometer</th><th>Condensation Particle<br>Counter</th><th>Integrating Cloud Probe</th><th>Cloud Droplet Probe</th><th>Cloud Ice Probe</th><th>Aerosol Particle Sampler</th><th>Bulk collectors</th><th>INP instrument</th></tr></thead><tbody><tr><td>Liquid Water Content</td><td>M</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Droplet effective diameter</td><td>M</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Droplet number concentration</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Droplet size distribution</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Interstitial aerosol number concentration</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Interstitial aerosol size distribution</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Total aerosol number concentration</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Total aerosol size distribution</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cloud residuals number concentration</td><td>O</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cloud residuals composition</td><td>O</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ice particle number concentration</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ice particle size distribution</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ice nucleating particle number concentration</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ice nucleating particle temperature spectrum</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Bulk cloud water chemical composition</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
## A.5 Cloud in situ measurements

<table><thead><tr><th>ACTRIS variable</th><th>NF requirements<br>Mandatory - M<br>Specializing - S<br>Optimum - O</th><th>Associated<br>Topical<br>Centre</th><th>Data<br>producer<br>L1, L2</th><th>RRT-O=<br>operational in<br>RRT now<br>RRT-S =<br>scheduled from<br>2020</th><th>Mobility Particle<br>Size Spectrometer</th><th>Condensation Particle<br>Counter</th><th>Integrating Cloud Probe</th><th>Cloud Droplet Probe</th><th>Cloud Ice Probe</th><th>Aerosol Particle Sampler</th><th>Bulk collectors</th><th>INP instrument</th></tr></thead><tbody><tr><td>Liquid Water Content</td><td>M</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Droplet effective diameter</td><td>M</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Droplet number concentration</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Droplet size distribution</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Interstitial aerosol number concentration</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Interstitial aerosol size distribution</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Total aerosol number concentration</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Total aerosol size distribution</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cloud residuals number concentration</td><td>O</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cloud residuals composition</td><td>O</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ice particle number concentration</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ice particle size distribution</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ice nucleating particle number concentration</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Ice nucleating particle temperature spectrum</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Bulk cloud water chemical composition</td><td>S</td><td>CIS</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
## A.6 Reactive trace gases in situ measurements

<table><thead><tr><th>ACTRIS variable</th><th>NF requirements Mandatory - M Specializing - S Optimum - O</th><th>Associated Topical Centre</th><th>Data producer L1, L2</th><th>RRT-O= operational in RRT now RRT-S = scheduled from 2020</th><th>On-line GC-FID</th><th>On-line GC-MS</th><th>On-line GC-FID/MS</th><th>On-line GC-Medusa</th><th>On-line PTR-MS</th><th>On-line Hantzsch</th><th>Off-line traps: ads-tubes</th><th>Off-line traps: DNPH-cartridge-HPLC</th><th>Off-line steel canister</th><th>Off-line glass flask</th><th>NO-O<sub>3</sub> chemiluminescence</th><th>Potentially other measurement technique supported by the TC</th><th>Cavity Attenuated Phase Shift Spectroscopy (CAPS)</th><th>CI-API-TOF</th></tr></thead><tbody><tr><td>NMHCs</td><td>M*, O</td><td>CGas-SiM</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>OVOCs</td><td>M*, O</td><td>CGas-SiM</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Terpenes</td><td>M*, O</td><td>CGas-SiM</td><td>NF</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NO</td><td>M</td><td>CGas-SiM</td><td>NF/TC</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NO<sub>2</sub></td><td>M</td><td>CGas-SiM</td><td>NF/TC</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Condensable vapours</td><td>O*, S</td><td>CGas-SiM</td><td>NF/TC</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
A.6 Reactive trace gases in situ measurements

<table><thead><tr><th>ACTRIS variable</th><th>NF requirements Mandatory - M Specializing - S Optimum - O</th><th>Associated Topical Centre</th><th>Data producer L1, L2</th><th>RRT-O= operational in RRT now RRT-S = scheduled from 2020</th><th>On-line GC-FID</th><th>On-line GC-MS</th><th>On-line GC-FID/MS</th><th>On-line GC-Medusa</th><th>On-line PTR-MS</th><th>On-line Hantzsch</th><th>Off-line traps: ads-tubes</th><th>Off-line traps: DNPH-cartridge-HPLC</th><th>Off-line steel canister</th><th>Off-line glass flask</th><th>NO-O<sub>3</sub> chemiluminescence</th><th>Potentially other measurement technique supported by the TC</th><th>Cavity Attenuated Phase Shift Spectroscopy (CAPS)</th><th>CI-API-TOF</th></tr></thead><tbody><tr><td>NMHCs</td><td>M*, O</td><td>CGas-SiM</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>OVOCs</td><td>M*, O</td><td>CGas-SiM</td><td>NF</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Terpenes</td><td>M*, O</td><td>CGas-SiM</td><td>NF</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NO</td><td>M</td><td>CGas-SiM</td><td>NF/TC</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NO<sub>2</sub></td><td>M</td><td>CGas-SiM</td><td>NF/TC</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Condensable vapours</td><td>O*, S</td><td>CGas-SiM</td><td>NF/TC</td><td>NRT-S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><thead><tr><td>ACTRIS variable</td><td>Comments</td></tr></thead><tbody><tr><td>NMHCs</td><td>NMHCs (C<sub>2</sub>-C<sub>9</sub>, detailed list available). Time resolution depends on sampling frequency, typical maximum 1/hour. M*: At least 6 different VOCs (NMHCs, OVOCs, terpenes) have to be measured at an NF, can be partly NMHCs.</td></tr><tr><td>OVOCs</td><td>Oxidised volatile organic compounds (detailed list available). Time resolution depends on sampling frequency, typical maximum 1/hour, less for PTR-MS. M*: At least 6 different VOCs (NMHCs, OVOCs, terpenes) have to be measured at an NF, can be partly OVOCs.</td></tr><tr><td>Terpenes</td><td>Monoterpenes (detailed list available). Time resolution depends on sampling frequency, typical maximum 1/hour, M*: At least 6 different VOCs (NMHCs, OVOCs, terpenes) have to be measured at an NF, can be partly terpenes.</td></tr><tr><td>NO</td><td>Needs to be accomplished by water vapour and ozone measurements, ideally also global radiation or J(NO2)</td></tr><tr><td>NO<sub>2</sub></td><td>Needs to be accomplished by water vapour and ozone measurements, ideally also global radiation or J(NO2)</td></tr><tr><td>Condensable vapours</td><td>Sulfuric acid, highly oxygenated molecules (HOM)</td></tr></tbody></table>
<table><thead><tr><td>ACTRIS variable</td><td>Comments</td></tr></thead><tbody><tr><td>NMHCs</td><td>NMHCs (C<sub>2</sub>-C<sub>9</sub>, detailed list available). Time resolution depends on sampling frequency, typical maximum 1/hour. M*: At least 6 different VOCs (NMHCs, OVOCs, terpenes) have to be measured at an NF, can be partly NMHCs.</td></tr><tr><td>OVOCs</td><td>Oxidised volatile organic compounds (detailed list available). Time resolution depends on sampling frequency, typical maximum 1/hour, less for PTR-MS. M*: At least 6 different VOCs (NMHCs, OVOCs, terpenes) have to be measured at an NF, can be partly OVOCs.</td></tr><tr><td>Terpenes</td><td>Monoterpenes (detailed list available). Time resolution depends on sampling frequency, typical maximum 1/hour, M*: At least 6 different VOCs (NMHCs, OVOCs, terpenes) have to be measured at an NF, can be partly terpenes.</td></tr><tr><td>NO</td><td>Needs to be accomplished by water vapour and ozone measurements, ideally also global radiation or J(NO2)</td></tr><tr><td>NO<sub>2</sub></td><td>Needs to be accomplished by water vapour and ozone measurements, ideally also global radiation or J(NO2)</td></tr><tr><td>Condensable vapours</td><td>Sulfuric acid, highly oxygenated molecules (HOM)</td></tr></tbody></table>
# Annex B: References

## B.1 Applicable ACTRIS-PPP Documents

ACTRIS Glossary: https://www.actris.eu/About/ACTRIS/ACTRISglossary.aspx

D2.3: ACTRIS Data Policy

D2.6: ACTRIS Access and Service Policy

D3.1: ACTRIS Cost Book

D4.1: Concept document on ACTRIS Central Facilities structure and services

D4.2: ACTRIS Data Management Plan

D5.2: Documentation on technical concepts and requirements for ACTRIS Exploratory Platforms

D5.3: Documentation on ACTRIS National Facility labelling principles

D6.3: Report on access rules and modalities and recommendations for ACTRIS access policy

## B.2 Publications

Anttila, T., Vaattovaara, P., Komppula, M., Hyvärinen, A. P., Lihavainen, H., Kerminen, V. M., and Laaksonen, A., 2009: Size-dependent activation of aerosols into cloud droplets at a subarctic background site during the second Pallas Cloud Experiment (2nd PaCE): method development and data evaluation, Atmos. Chem. Phys., 9, 4841–4854, doi: 10.5194/acp-9-4841-2009.

Anttila, T., Brus, D., Jaatinen, A., Hyvärinen, A. P., Kivekäs, N., Romakkaniemi, S., Komppula, M., and Lihavainen, H., 2012: Relationships between particles, cloud condensation nuclei and cloud droplet activation during the third Pallas Cloud Experiment, Atmos. Chem. Phys., 12, 11435–11450, doi: 10.5194/acp-12-11435-2012.

Asmi, E., Freney, E., Hervo, M., Picard, P., Rose, C., Colomb, A., and Sellegri, K., 2012: Aerosol cloud activation in summer and winter at Puy-de-Dôme high altitude site in France, Atmos. Chem. Phys., 12, 11589–11607, doi: 10.5194/acp-12-11589-2012.

Barreto, A., Cuevas, E., Damiri, B., Guirado, C., Berkoff, T., Berjón, A. J., Hernández, Y., Almansa, F., and Gil, M., 2013a: A new method for nocturnal aerosol measurements with a lunar photometer prototype, Atmos. Meas. Tech., 6, 585–598, doi: 10.5194/amt-6-585-2013.

Barreto, A., Cuevas, E., Damiri, B., Romero, P. M., and Almansa, F., 2013b: Column water vapor determination in night period with a lunar photometer prototype, Atmos. Meas. Tech., 6, 2159–2167, doi: 10.5194/amt-6-2159-2013.

Barreto, Á., et al., 2016: The new sun-sky-lunar Cimel CE318-T multiband photometer – a comprehensive performance evaluation, Atmos. Meas. Tech., 9, 631–654, doi: 10.5194/amt-9-631-2016.
# Annex B: References

## B.1 Applicable ACTRIS-PPP Documents

ACTRIS Glossary: https://www.actris.eu/About/ACTRIS/ACTRISglossary.aspx

D2.3: ACTRIS Data Policy

D2.6: ACTRIS Access and Service Policy

D3.1: ACTRIS Cost Book

D4.1: Concept document on ACTRIS Central Facilities structure and services

D4.2: ACTRIS Data Management Plan

D5.2: Documentation on technical concepts and requirements for ACTRIS Exploratory Platforms

D5.3: Documentation on ACTRIS National Facility labelling principles

D6.3: Report on access rules and modalities and recommendations for ACTRIS access policy

## B.2 Publications

Anttila, T., Vaattovaara, P., Komppula, M., Hyvärinen, A. P., Lihavainen, H., Kerminen, V. M., and Laaksonen, A., 2009: Size-dependent activation of aerosols into cloud droplets at a subarctic background site during the second Pallas Cloud Experiment (2nd PaCE): method development and data evaluation, Atmos. Chem. Phys., 9, 4841–4854, doi: 10.5194/acp-9-4841-2009.

Anttila, T., Brus, D., Jaatinen, A., Hyvärinen, A. P., Kivekäs, N., Romakkaniemi, S., Komppula, M., and Lihavainen, H., 2012: Relationships between particles, cloud condensation nuclei and cloud droplet activation during the third Pallas Cloud Experiment, Atmos. Chem. Phys., 12, 11435–11450, doi: 10.5194/acp-12-11435-2012.

Asmi, E., Freney, E., Hervo, M., Picard, P., Rose, C., Colomb, A., and Sellegri, K., 2012: Aerosol cloud activation in summer and winter at Puy-de-Dôme high altitude site in France, Atmos. Chem. Phys., 12, 11589-11607, doi: 10.5194/acp-12-11589-2012.

Barreto, A., Cuevas, E., Damiri, B., Guirado, C., Berkoff, T., Berjón, A. J., Hernández, Y., Almansa, F., and Gil, M., 2013a: A new method for nocturnal aerosol measurements with a lunar photometer prototype, Atmos. Meas. Tech., 6, 585–598, doi: 10.5194/amt-6-585-2013.

Barreto, A., Cuevas, E., Damiri, B., Romero, P. M., and Almansa, F., 2013b: Column water vapor determination in night period with a lunar photometer prototype, Atmos. Meas. Tech., 6, 2159–2167, doi: 10.5194/amt-6-2159-2013.

Barreto, Á., et al., 2016: The new sun-sky-lunar Cimel CE318-T multiband photometer – a comprehensive performance evaluation, Atmos. Meas. Tech., 9, 631–654, doi: 10.5194/amt-9-631-2016.
Barreto, Á., et al., 2017: Assessment of nocturnal aerosol optical depth from lunar photometry at the Izaña high mountain observatory, Atmos. Meas. Tech., 10, 3007-3019, doi: 10.5194/amt-10-3007-2017.

Berner, A., 1988: The collection of fog droplets by a jet impaction stage, Science of The Total Environment, 73, 217–228, doi: 10.1016/0048-9697(88)90430-5.

Boulter, J. E., Cziczo, D. J., Middlebrook, A. M., Thomson, D. S., and Murphy, D. M., 2006: Design and performance of a pumped counterflow virtual impactor, Aerosol. Sci. Technol., 40, 969–976, doi: 10.1080/02786820600840984.

Clémer, K., Van Roozendael, M., Fayt, C., Hendrick, F., Hermans, C., Pinardi, G., Spurr, R. J. D., Wang, P., and De Mazière, M., 2010: Multiple wavelength retrieval of tropospheric aerosol optical properties from MAXDOAS measurements in Beijing, Atmos. Meas. Tech., 3, 863–878, doi: 10.5194/amt-3-863-2010.

Collett, J. L., Daube, B. C., Gunz, D., and Hoffmann, M. R., 1990: Intensive studies of Sierra Nevada cloud water chemistry and its relationship to precursor aerosol and gas concentrations, Atmospheric Environment Part A, General Topics 24, 1741–1757, doi: 10.1016/0960-1686(90)90507-J.

Cziczo, D. J., et al., 2009: Inadvertent climate modification due to anthropogenic lead, Nat. Geosci., 2, 333–336, doi: 10.1038/NGEO499.

Dammers, E., et al., 2016: An evaluation of IASI-NH3 with ground-based Fourier transform infrared spectroscopy measurements, Atmos. Chem. Phys., 16, 10351–10368, doi: 10.5194/acp-16-10351-2016.

De Mazière, M., et al., 2018: The Network for the Detection of Atmospheric Composition Change (NDACC): History, status and perspectives, Atmos. Chem. Phys., 18, 4935–4964, doi: 10.5194/acp-18-4935-2018.

Demoz, B. B., Collett, J. L., and Daube, B. C., 1996: On the Caltech Active Strand Cloudwater Collectors, Atmospheric Research, 41, 1, 47–62, doi: 10.1016/0169-8095(95)00044-5.

Ditas, F., Shaw, R. A., Siebert, H., Simmel, M., Wehner, B., and Wiedensohler, A., 2012: Aerosols-cloud microphysics-thermodynamics-turbulence: Evaluating supersaturation in a marine stratocumulus cloud, Atmos. Chem. Phys. 12, 2459–2468, doi: 10.5194/acp-12-2459-2012.

Dubovik, O., and M. D. King, 2000: A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements, J. Geophys. Res., 105, 20 673–20 696, doi: 10.1029/2000JD900282.

Dubovik, O., A. Smirnov, B. N. Holben, M. D. King, Y. J. Kaufman, T. F. Eck, and I. Slutsker, 2000: Accuracy assessments of aerosol optical properties retrieved from AERONET sun and sky-radiance measurements, J. Geophys. Res., 105, 9791-9806, doi: 10.1029/2000JD900040.

Franco B., et al., 2015a: Retrieval of ethane from ground-based FTIR solar spectra using improved spectroscopy: recent burden increase above Jungfraujoch, J. Quant. Spectrosc. Radiat. Transfer, 160, 36–49, doi: 10.1016/j.jqsrt.2015.03.017.
Barreto, Á., et al., 2017: Assessment of nocturnal aerosol optical depth from lunar photometry at the Izaña high mountain observatory, Atmos. Meas. Tech., 10, 3007-3019, doi: 10.5194/amt-10-3007-2017.

Berner, A., 1988: The collection of fog droplets by a jet impaction stage, Science of The Total Environment, 73, 217–228, doi: 10.1016/0048-9697(88)90430-5.

Boulter, J. E., Cziczo, D. J., Middlebrook, A. M., Thomson, D. S., and Murphy, D. M., 2006: Design and performance of a pumped counterflow virtual impactor, Aerosol. Sci. Technol., 40, 969–976, doi: 10.1080/02786820600840984.

Clémer, K., Van Roozendael, M., Fayt, C., Hendrick, F., Hermans, C., Pinardi, G., Spurr, R. J. D., Wang, P., and De Mazière, M., 2010: Multiple wavelength retrieval of tropospheric aerosol optical properties from MAXDOAS measurements in Beijing, Atmos. Meas. Tech., 3, 863–878, doi: 10.5194/amt-3-863-2010.

Collett, J. L., Daube, B. C., Gunz, D., and Hoffmann, M. R., 1990: Intensive studies of Sierra Nevada cloud water chemistry and its relationship to precursor aerosol and gas concentrations, Atmospheric Environment Part A, General Topics 24, 1741–1757, doi: 10.1016/0960-1686(90)90507-J.

Cziczo, D. J., et al., 2009: Inadvertent climate modification due to anthropogenic lead, Nat. Geosci., 2, 333–336, doi: 10.1038/NGEO499.

Dammers, E., et al., 2016: An evaluation of IASI-NH3 with ground-based Fourier transform infrared spectroscopy measurements, Atmos. Chem. Phys., 16, 10351–10368, doi: 10.5194/acp-16-10351-2016.

De Mazière, M., et al., 2018: The Network for the Detection of Atmospheric Composition Change (NDACC): History, status and perspectives, Atmos. Chem. Phys., 18, 4935–4964, doi: 10.5194/acp-18-4935-2018.

Demoz, B. B., Collett, J. L., and Daube, B. C., 1996: On the Caltech Active Strand Cloudwater Collectors, Atmospheric Research, 41, 1, 47–62, doi: 10.1016/0169-8095(95)00044-5.

Ditas, F., Shaw, R. A., Siebert, H., Simmel, M., Wehner, B., and Wiedensohler, A., 2012: Aerosols-cloud microphysics-thermodynamics-turbulence: Evaluating supersaturation in a marine stratocumulus cloud, Atmos. Chem. Phys. 12, 2459–2468, doi: 10.5194/acp-12-2459-2012.

Dubovik, O., and M. D. King, 2000: A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements, J. Geophys. Res., 105, 20 673–20 696, doi: 10.1029/2000JD900282.

Dubovik, O., A. Smirnov, B. N. Holben, M. D. King, Y. J. Kaufman, T. F. Eck, and I. Slutsker, 2000: Accuracy assessments of aerosol optical properties retrieved from AERONET sun and sky-radiance measurements, J. Geophys. Res., 105, 9791-9806, doi: 10.1029/2000JD900040.

Franco B., et al., 2015a: Retrieval of ethane from ground-based FTIR solar spectra using improved spectroscopy: recent burden increase above Jungfraujoch, J. Quant. Spectrosc. Radiat. Transfer, 160, 36–49, doi: 10.1016/j.jqsrt.2015.03.017.
Franco, B., et al., 2015b: Retrievals of formaldehyde from ground-based FTIR and MAX-DOAS observations at the Jungfraujoch station and comparisons with GEOS-Chem and IMAGES model simulations, Atmos. Meas. Tech., 8, 1733–1756, doi:10.5194/amt-8-1733-2015.

Freudenthaler, V., Linné, H., Chaikovski, A., Rabus, D., and Groß, S., 2018: EARLINET lidar quality assurance tools, Atmos. Meas. Tech. Discuss., doi: 10.5194/amt-2017-395, in review.

Freudenthaler, V., 2016: About the effects of polarising optics on lidar signals and the Δ90 calibration, Atmos. Meas. Tech., 9, 4181–4255, doi: 10.5194/amt-9-4181-2016.

Frieß, U., Monks, P. S., Remedios, J. J., Rozanov, A., Sinreich, R., Wagner, T., and Platt, U., 2006: MAX-DOAS O₄ measurements: A new technique to derive information on atmospheric aerosols: 2. Modeling studies, J. Geophys. Res., 111, D14203, doi: 10.1029/2005JD006618.

Gaussiat, N., R.J. Hogan, and A.J. Illingworth, 2007: Accurate liquid water path retrieval from low-cost microwave radiometers using additional information from a lidar ceilometer and operational forecast models, J. Atmos. Oceanic Technol., 24, 1562–1575, doi: 10.1175/JTECH2053.1.

Gerber, H., Arends, B. G., and Ackerman, A. S., 1994: New microphysics sensor for aircraft use, Atmos. Res., 31, 235–252, doi: 10.1016/0169-8095(94)90001-9.

Guyot, G., Gourbeyre, C., Febvre, G., Shcherbakov, V., Burnet, F., Dupont, J. C., Sellegri, K., and Jourdan, O., 2015: Quantitative evaluation of seven optical sensors for cloud microphysical measurements at the Puy-de-Dôme Observatory, France, Atmos. Meas. Tech., 8, 4347–4367, doi: 10.5194/amt-8-4347-2015.

Hammer, E., Bukowiecki, N., Gysel, M., Jurányi, Z., Hoyle, C. R., Vogt, R., Baltensperger, U., and Weingartner, E., 2014: Investigation of the effective peak supersaturation for liquid-phase clouds at the high-alpine site Jungfraujoch, Switzerland (3580m a.s.l.), Atmos. Chem. Phys., 14, 1123–1139, doi: 10.5194/acp-14-1123-2014.

Hendrick, F., et al., 2011: NDACC/SAOZ UV-visible total ozone measurements: improved retrieval and comparison with correlative ground-based and satellite observations, Atmos. Chem. Phys., 11, 5975–5995, doi: 10.5194/acp-11-5975-2011.

Hendrick, F., et al., 2012: Analysis of stratospheric NO₂ trends above Jungfraujoch using ground-based UV-visible, FTIR, and satellite nadir observations, Atmos. Chem. Phys., 12, 8851–8864, doi: 10.5194/acp-12-8851-2012.

Hendrick, F., et al., 2014: Four years of ground-based MAX-DOAS observations of HONO and NO₂ in the Beijing area, Atmos. Chem. Phys., 14, 765–781, doi: 10.5194/acp-14-765-2014.

Henning, S., Weingartner, E., Schmidt, S., Wendisch, M., Gäggeler, H. W., and Baltensberger, U., 2002: Size-dependent aerosol activation at the high-alpine site Jungfraujoch (3580 m asl), Tellus B, 54, 82–95, doi: 10.3402/tellusb.v54i1.16650.

Herman, J. R., Cede, A., Spinei, E., Mount, G., Tzortziou, M., and Abuhassan, N., 2009: NO₂ column amounts from ground-based Pandora and MFDOAS spectrometers using the direct-sun DOAS technique:
Franco, B., et al., 2015b: Retrievals of formaldehyde from ground-based FTIR and MAX-DOAS observations at the Jungfraujoch station and comparisons with GEOS-Chem and IMAGES model simulations, Atmos. Meas. Tech., 8, 1733–1756, doi:10.5194/amt-8-1733-2015.

Freudenthaler, V., Linné, H., Chaikovski, A., Rabus, D., and Groß, S., 2018: EARLINET lidar quality assurance tools, Atmos. Meas. Tech. Discuss., doi: 10.5194/amt-2017-395, in review.

Freudenthaler, V., 2016: About the effects of polarising optics on lidar signals and the Δ90 calibration, Atmos. Meas. Tech., 9, 4181–4255, doi: 10.5194/amt-9-4181-2016.

Frieß, U., Monks, P. S., Remedios, J. J., Rozanov, A., Sinreich, R., Wagner, T., and Platt, U., 2006: MAX-DOAS O₄ measurements: A new technique to derive information on atmospheric aerosols: 2. Modeling studies, J. Geophys. Res., 111, D14203, doi: 10.1029/2005JD006618.

Gaussiat, N., R.J. Hogan, and A.J. Illingworth, 2007: Accurate liquid water path retrieval from low-cost microwave radiometers using additional information from a lidar ceilometer and operational forecast models, J. Atmos. Oceanic Technol., 24, 1562–1575, doi: 10.1175/JTECH2053.1.

Gerber, H., Arends, B. G., and Ackerman, A. S., 1994: New microphysics sensor for aircraft use, Atmos. Res., 31, 235–252, doi: 10.1016/0169-8095(94)90001-9.

Guyot, G., Gourbeyre, C., Febvre, G., Shcherbakov, V., Burnet, F., Dupont, J. C., Sellegri, K., and Jourdan, O., 2015: Quantitative evaluation of seven optical sensors for cloud microphysical measurements at the Puy-de-Dôme Observatory, France, Atmos. Meas. Tech., 8, 4347–4367, doi: 10.5194/amt-8-4347-2015.

Hammer, E., Bukowiecki, N., Gysel, M., Jurányi, Z., Hoyle, C. R., Vogt, R., Baltensperger, U., and Weingartner, E., 2014: Investigation of the effective peak supersaturation for liquid-phase clouds at the high-alpine site Jungfraujoch, Switzerland (3580m a.s.l.), Atmos. Chem. Phys., 14, 1123–1139, doi: 10.5194/acp-14-1123-2014.

Hendrick, F., et al., 2011: NDACC/SAOZ UV-visible total ozone measurements: improved retrieval and comparison with correlative ground-based and satellite observations, Atmos. Chem. Phys., 11, 5975–5995, doi: 10.5194/acp-11-5975-2011.

Hendrick, F., et al., 2012: Analysis of stratospheric NO₂ trends above Jungfraujoch using ground-based UV-visible, FTIR, and satellite nadir observations, Atmos. Chem. Phys., 12, 8851–8864, doi: 10.5194/acp-12-8851-2012.

Hendrick, F., et al., 2014: Four years of ground-based MAX-DOAS observations of HONO and NO₂ in the Beijing area, Atmos. Chem. Phys., 14, 765–781, doi: 10.5194/acp-14-765-2014.

Henning, S., Weingartner, E., Schmidt, S., Wendisch, M., Gäggeler, H. W., and Baltensberger, U., 2002: Size-dependent aerosol activation at the high-alpine site Jungfraujoch (3580 m asl), Tellus B, 54, 82–95, doi: 10.3402/tellusb.v54i1.16650.

Herman, J. R., Cede, A., Spinei, E., Mount, G., Tzortziou, M., and Abuhassan, N., 2009: NO₂ column amounts from ground-based Pandora and MFDOAS spectrometers using the direct-sun DOAS technique:
Intercomparisons and application to OMI validation, J. Geophys. Res., 114, D13307, doi: 10.1029/2009JD011848.

Herman, J., Evans, R., Cede, A., Abuhassan, N., Petropavlovskikh, I., and McConville, G., 2015: Comparison of ozone retrievals from the Pandora spectrometer system and Dobson spectrophotometer in Boulder, Colorado, Atmos. Meas. Tech., 8, 3407–3418, doi: 10.5194/amt-8-3407-2015.

Hiranuma, N., et al., 2016: Development and characterization of an ice-selecting pumped counterflow virtual impactor (IS-PCVI) to study ice crystal residuals, Atmos. Meas. Tech., 9, 3817–3836, doi: 10.5194/amt-9-3817-2016.

Hirsikko, A., et al., 2014: Observing wind, aerosol particles, cloud and precipitation: Finland's new ground-based remote-sensing network, Atmos. Meas. Tech., 7, 1351–1375, doi: 10.5194/amt-7-1351-2014.

Hoerger, C.C., et al., 2015: ACTRIS non-methane hydrocarbon intercomparison experiment in Europe to support WMO GAW and EMEP observation networks, Atmos. Meas. Tech. 8, 2715–2736, doi: 10.5194/amt-8-2715-2015.

Hogan, R. J., and E. J. O'Connor, 2004: Facilitating cloud radar and lidar algorithms: The Cloudnet Instrument Synergy/Target Categorization product, Cloudnet documentation, available online at [cloudnet.fmi.fi/data/products/categorization.pdf](https://cloudnet.fmi.fi/data/products/categorization.pdf).

Hogan, R. J., D. P. Donovan, C. Tinel, M. A. Brooks, A. J. Illingworth, and J. P. V. Poiares Baptista, 2006: Independent evaluation of the ability of spaceborne radar and lidar to retrieve the microphysical and radiative properties of ice clouds, J. Atmos. Oceanic Technol., 23, 211–227, doi: 10.1175/JTECH1837.1.

Holben, B. N., T. F. Eck, I. Slutsker, A. Smirnov, A. Sinyuk, J. Schafer, D. Giles, and O. Dubovik, 2006: Aeronet's Version 2.0 quality assurance criteria, Proc. SPIE 6408, Remote Sensing of the Atmosphere and Clouds, 64080Q, doi: 10.1117/12.706524.

Holben, B. N., et al., 2001: An emerging ground-based aerosol climatology: Aerosol Optical Depth from AERONET, J. Geophys. Res., 106, 12067–12097, doi: 10.1029/2001JD900014.

Holben, B. N., et al., 1998: AERONET - A federated instrument network and data archive for aerosol characterization, Rem. Sens. Environ., 66, 1–16, doi: 10.1016/S0034-4257(98)00031-5.

Hönninger, G., C. von Friedeburg, and U. Platt, 2004: Multi axis differential optical absorption spectroscopy, Atmos. Chem. Phys., 4, 231–254, doi: 10.5194/acp-4-231-2004.

Illingworth, A. J., et al., 2007: Cloudnet: Continuous evaluation of cloud profiles in seven operational models using ground-based observations, Bull. Am. Meteorol. Soc., 88, 883–898, doi: 10.1175/BAMS-88-6-88.

Karol, Y., D. Tanre, P. Goloub, C. Vervaerde, J. Y. Balois, L. Blarel, T. Podvin, A. Mortier, and A. Chaikovsky, 2013: Airborne sunphotometer PLASMA: concept, measurements, comparison of aerosol extinction vertical profile with lidar, Atmos. Meas. Tech., 6, 2383–2389, doi: 10.5194/amt-6-2383-2013.
Intercomparisons and application to OMI validation, J. Geophys. Res., 114, D13307, doi: 10.1029/2009JD011848.

Herman, J., Evans, R., Cede, A., Abuhassan, N., Petropavlovskikh, I., and McConville, G., 2015: Comparison of ozone retrievals from the Pandora spectrometer system and Dobson spectrophotometer in Boulder, Colorado, Atmos. Meas. Tech., 8, 3407–3418, doi: 10.5194/amt-8-3407-2015.

Hiranuma, N., et al., 2016: Development and characterization of an ice-selecting pumped counterflow virtual impactor (IS-PCVI) to study ice crystal residuals, Atmos. Meas. Tech., 9, 3817–3836, doi: 10.5194/amt-9-3817-2016.

Hirsikko, A., et al., 2014: Observing wind, aerosol particles, cloud and precipitation: Finland's new ground-based remote-sensing network, Atmos. Meas. Tech., 7, 1351–1375, doi: 10.5194/amt-7-1351-2014.

Hoerger, C.C., et al., 2015: ACTRIS non-methane hydrocarbon intercomparison experiment in Europe to support WMO GAW and EMEP observation networks, Atmos. Meas. Tech. 8, 2715–2736, doi: 10.5194/amt-8-2715-2015.

Hogan, R. J., and E. J. O'Connor, 2004: Facilitating cloud radar and lidar algorithms: The Cloudnet Instrument Synergy/Target Categorization product, Cloudnet documentation, available online at [cloudnet.fmi.fi/data/products/categorization.pdf](https://cloudnet.fmi.fi/data/products/categorization.pdf).

Hogan, R. J., D. P. Donovan, C. Tinel, M. A. Brooks, A. J. Illingworth, and J. P. V. Poiares Baptista, 2006: Independent evaluation of the ability of spaceborne radar and lidar to retrieve the microphysical and radiative properties of ice clouds, J. Atmos. Oceanic Technol., 23, 211–227, doi: 10.1175/JTECH1837.1.

Holben, B. N., T. F. Eck, I. Slutsker, A. Smirnov, A. Sinyuk, J. Schafer, D. Giles, and O. Dubovik, 2006: Aeronet's Version 2.0 quality assurance criteria, Proc. SPIE 6408, Remote Sensing of the Atmosphere and Clouds, 64080Q, doi: 10.1117/12.706524.

Holben, B. N., et al., 2001: An emerging ground-based aerosol climatology: Aerosol Optical Depth from AERONET, J. Geophys. Res., 106, 12067–12097, doi: 10.1029/2001JD900014.

Holben, B. N., et al., 1998: AERONET - A federated instrument network and data archive for aerosol characterization, Rem. Sens. Environ., 66, 1–16, doi: 10.1016/S0034-4257(98)00031-5.

Hönninger, G., C. von Friedeburg, and U. Platt, 2004: Multi axis differential optical absorption spectroscopy, Atmos. Chem. Phys., 4, 231–254, doi: 10.5194/acp-4-231-2004.

Illingworth, A. J., et al., 2007: Cloudnet: Continuous evaluation of cloud profiles in seven operational models using ground-based observations, Bull. Am. Meteorol. Soc., 88, 883–898, doi: 10.1175/BAMS-88-6-88.

Karol, Y., D. Tanre, P. Goloub, C. Vervaerde, J. Y. Balois, L. Blarel, T. Podvin, A. Mortier, and A. Chaikovsky, 2013: Airborne sunphotometer PLASMA: concept, measurements, comparison of aerosol extinction vertical profile with lidar, Atmos. Meas. Tech., 6, 2383–2389, doi: 10.5194/amt-6-2383-2013.
Krämer, M., and Schütz, L., 1994: On the collection efficiency of a rotating ARM collector and its applicability to cloud- and fogwater sampling, J. Aerosol Sci., 25, 137–148, doi: 10.1016/0021-8502(94)90186-4.

Krüger, M. L., Mertes, S., Klimach, T., Cheng, Y. F., Su, H., Schneider, J., Andreae, M. O., Pöschl, U., and Rose, D., 2014: Assessment of cloud supersaturation by size-resolved aerosol particle and cloud condensation nuclei (CCN) measurements, Atmos. Meas. Tech., 7, 2615–2629, doi: 10.5194/amt-7-2615-2014.

Lance, S., Brock, C. A., Rogers, D., and Gordon, J. A., 2010: Water droplet calibration of the Cloud Droplet Probe (CDP) and in-flight performance in liquid, ice and mixed-phase clouds during ARCPAC, Atmos. Meas. Tech., 3, 1683–1706, doi: 10.5194/amt-3-1683-2010.

Leblanc, T., Sica, R. J., van Gijsel, J. A. E., Godin-Beekmann, S., Haefele, A., Trickl, T., Payen, G., and Gabarrot, F., 2016a.: Proposed standardized definitions for vertical resolution and uncertainty in the NDACC lidar ozone and temperature algorithms – Part 1: Vertical resolution, Atmos. Meas. Tech., 9, 4029–4049, doi: 10.5194/amt-9-4029-2016.

Leblanc, T., Sica, R. J., van Gijsel, J. A. E., Godin-Beekmann, S., Haefele, A., Trickl, T., Payen, G., and Liberti, G., 2016b: Proposed standardized definitions for vertical resolution and uncertainty in the NDACC lidar ozone and temperature algorithms – Part 2: Ozone DIAL uncertainty budget, Atmos. Meas. Tech., 9, 4051–4078, doi: 10.5194/amt-9-4051-2016.

Leblanc, T., Sica, R. J., van Gijsel, J. A. E., Haefele, A., Payen, G., and Liberti, G., 2016c: Proposed standardized definitions for vertical resolution and uncertainty in the NDACC lidar ozone and temperature algorithms – Part 3: Temperature uncertainty budget, Atmos. Meas. Tech., 9, 4079–4101, doi: 10.5194/amt-9-4079-2016.

Li, L., Z. Li, K. Li, L. Blarel, and M. Wendisch, 2014: A method to calculate Stokes parameters and angle of polarization of skylight from polarized CIMEL sun/sky radiometers, J. Quant. Spectrosc. Radiat. Transfer, 149, 334–346, doi: 10.1016/j.jqsrt.2014.09.003.

Li, Z., et al., 2013: Method to intercalibrate sunphotometer constants using an integrating sphere as a light source in the laboratory, Appl. Opt., 52, 2226–2234, doi: 10.1364/AO.52.002226.

Li, Z., L. Blarel, T. Podvin, and P. Goloub, 2010: Calibration of the degree of linear polarization using solar light, Appl. Opt., 49, 1249–1256, doi: 10.1364/AO.49.001249.

Lihavainen, H., et al., 2008: Measurements of the relation between aerosol properties and microphysics and chemistry of low level liquid water clouds in Northern Finland, Atmos. Chem. Phys., 8, 6925–6938, doi: 10.5194/acp-8-6925-2008.

Lloyd, G., et al., 2015: The origins of ice crystals measured in mixed-phase clouds at the high-alpine site Jungfraujoch, Atmos. Chem. Phys., 15, 12953–12969, doi: 10.5194/acp-15-12953-2015.

Lopatin, A., O. Dubovik, A. Chaikovsky, P. Goloub, T. Lapyonok, D. Tanré, and P. Litvinov, 2013: Enhancement of aerosol characterization using synergy of lidar and sun – photometer coincident
Krämer, M., and Schütz, L., 1994: On the collection efficiency of a rotating ARM collector and its applicability to cloud- and fogwater sampling, J. Aerosol Sci., 25, 137–148, doi: 10.1016/0021-8502(94)90186-4.

Krüger, M. L., Mertes, S., Klimach, T., Cheng, Y. F., Su, H., Schneider, J., Andreae, M. O., Pöschl, U., and Rose, D., 2014: Assessment of cloud supersaturation by size-resolved aerosol particle and cloud condensation nuclei (CCN) measurements, Atmos. Meas. Tech., 7, 2615–2629, doi: 10.5194/amt-7-2615-2014.

Lance, S., Brock, C. A., Rogers, D., and Gordon, J. A., 2010: Water droplet calibration of the Cloud Droplet Probe (CDP) and in-flight performance in liquid, ice and mixed-phase clouds during ARCPAC, Atmos. Meas. Tech., 3, 1683–1706, doi: 10.5194/amt-3-1683-2010.

Leblanc, T., Sica, R. J., van Gijsel, J. A. E., Godin-Beekmann, S., Haefele, A., Trickl, T., Payen, G., and Gabarrot, F., 2016a.: Proposed standardized definitions for vertical resolution and uncertainty in the NDACC lidar ozone and temperature algorithms – Part 1: Vertical resolution, Atmos. Meas. Tech., 9, 4029–4049, doi: 10.5194/amt-9-4029-2016.

Leblanc, T., Sica, R. J., van Gijsel, J. A. E., Godin-Beekmann, S., Haefele, A., Trickl, T., Payen, G., and Liberti, G., 2016b: Proposed standardized definitions for vertical resolution and uncertainty in the NDACC lidar ozone and temperature algorithms – Part 2: Ozone DIAL uncertainty budget, Atmos. Meas. Tech., 9, 4051–4078, doi: 10.5194/amt-9-4051-2016.

Leblanc, T., Sica, R. J., van Gijsel, J. A. E., Haefele, A., Payen, G., and Liberti, G., 2016c: Proposed standardized definitions for vertical resolution and uncertainty in the NDACC lidar ozone and temperature algorithms – Part 3: Temperature uncertainty budget, Atmos. Meas. Tech., 9, 4079–4101, doi: 10.5194/amt-9-4079-2016.

Li, L., Z. Li, K. Li, L. Blarel, and M. Wendisch, 2014: A method to calculate Stokes parameters and angle of polarization of skylight from polarized CIMEL sun/sky radiometers, J. Quant. Spectrosc. Radiat. Transfer, 149, 334–346, doi: 10.1016/j.jqsrt.2014.09.003.

Li, Z., et al., 2013: Method to intercalibrate sunphotometer constants using an integrating sphere as a light source in the laboratory, Appl. Opt., 52, 2226–2234, doi: 10.1364/AO.52.002226.

Li, Z., L. Blarel, T. Podvin, and P. Goloub, 2010: Calibration of the degree of linear polarization using solar light, Appl. Opt., 49, 1249–1256, doi: 10.1364/AO.49.001249.

Lihavainen, H., et al., 2008: Measurements of the relation between aerosol properties and microphysics and chemistry of low level liquid water clouds in Northern Finland, Atmos. Chem. Phys., 8, 6925–6938, doi: 10.5194/acp-8-6925-2008.

Lloyd, G., et al., 2015: The origins of ice crystals measured in mixed-phase clouds at the high-alpine site Jungfraujoch, Atmos. Chem. Phys., 15, 12953–12969, doi: 10.5194/acp-15-12953-2015.

Lopatin, A., O. Dubovik, A. Chaikovsky, P. Goloub, T. Lapyonok, D. Tanré, and P. Litvinov, 2013: Enhancement of aerosol characterization using synergy of lidar and sun – photometer coincident
observations: the GARRLiC algorithm, Atmos. Meas. Tech., 6, 2065-2088, doi: 10.5194/amt-6-2065-2013.

Manninen, A. J., E.J. O'Connor, V. Vakkari, and T. Petäjä, 2016: A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland, Atmos. Meas. Tech., 9, 817-827, doi: 10.5194/amt-9-817-2016.

Marinoni, A., Laj, P., Sellegri, K., and Mailhot, G., 2004: Cloud chemistry at the Puy de Dome: variability and relationships with environmental factors, Atmos. Chem. Phys., 4, 715-728, doi: 10.5194/acp-4-715-2004.

Mertes, S., Schwarzenböck, A., Laj, P., Wobrock, W., Pichon, J. M., Orsi, G., and Heintzenberg, J., 2001: Changes of cloud microphysical properties during the transition from supercooled to mixed-phase conditions during CIME, Atmos. Res., 58, 267-294, doi: 10.1016/S0169-8095(01)00095-3.

Miles, N. L., Verlinde, J., and Clothiaux, E. E., 2000: Cloud droplet size distributions in low-level stratiform clouds, J. Atmos. Sci., 5, 295-311, doi: 10.1175/1520-0469(2000)057<0295:cdsdil>2.0.co;2.

Noone, K., Ogren, J. A., Heintzenberg, J., Charlson, R. J., and Covert, D. S., 1988: Design and calibration of a counterflow virtual impactor for sampling of atmospheric fog and cloud droplets, Aerosol Sci. Technol., 8, 235-244, doi: 10.1080/02786828808959186.

O'Connor, E. J., A. J. Illingworth, and R. J. Hogan, 2004: A Technique for Autocalibration of Cloud Lidar. J. Atmos. Oceanic Technol., 21, 777-786, doi: 10.1175/1520-0426(2004)021<0777:ATFAOC>2.0.CO;2.

O'Connor, E. J., A. J. Illingworth, I. M. Brooks, C. D. Westbrook, R. J. Hogan, F. Davies, and B. J. Brooks, 2010: A method for estimating the turbulent kinetic energy dissipation rate from a vertically-pointing Doppler lidar, and independent evaluation from balloon-borne in-situ measurements, J. Atmos. Ocean. Technol., 27, 1652-1664, doi: 10.1175/2010JTECHA1455.1.

Ogren, J. A., J. Heintzenberg, and R. J. Charlson, 1985: In-situ sampling of clouds with a droplet to aerosol converter, Geophys. Res. Lett., 12, 121-124, doi: 10.1029/GL012i003p00121.

Pommereau, J. P., and F. Goutail, 1988: O₃ and NO₂ ground-based measurements by visible spectrometry during Arctic winter and spring 1988, Geophys. Res. Lett., 15, 891-894, doi: 10.1029/GL015i008p00891.

Protat, A., A. Armstrong, M. Haeffelin, Y. Morille, J. Pelon, J. Delanoë, and D. Bouniol, 2006: The impact of conditional sampling and instrumental limitations on the statistics of cloud properties derived from cloud radar and lidar at SIRTA, Geophys. Res. Lett., 33, L11805, doi: 10.1029/2005GL025340.

Reutter, P., Su, H., Trentmann, J., Simmel, M., Rose, D., Gunthe, S. S., Wernli, H., Andreae, M. O., and Pöschl, U., 2009: Aerosol- and updraft-limited regimes of cloud droplet formation: influence of particle number, size and hygroscopicity on the activation of cloud condensation nuclei (CCN), Atmos. Chem. Phys., 9, 7067-7080, doi: 10.5194/acp-9-7067-2009.

Reynolds, B., Fowler, D., and Thomas, S., 1996: Chemistry of cloud water at an upland site in mid-Wales, Science of The Total Environment, 188, 115-125, doi: 10.1016/0048-9697(96)05165-0.
observations: the GARRLiC algorithm, Atmos. Meas. Tech., 6, 2065-2088, doi: 10.5194/amt-6-2065-2013.

Manninen, A. J., E.J. O'Connor, V. Vakkari, and T. Petäjä, 2016: A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland, Atmos. Meas. Tech., 9, 817-827, doi: 10.5194/amt-9-817-2016.

Marinoni, A., Laj, P., Sellegri, K., and Mailhot, G., 2004: Cloud chemistry at the Puy de Dome: variability and relationships with environmental factors, Atmos. Chem. Phys., 4, 715-728, doi: 10.5194/acp-4-715-2004.

Mertes, S., Schwarzenböck, A., Laj, P., Wobrock, W., Pichon, J. M., Orsi, G., and Heintzenberg, J., 2001: Changes of cloud microphysical properties during the transition from supercooled to mixed-phase conditions during CIME, Atmos. Res., 58, 267-294, doi: 10.1016/S0169-8095(01)00095-3.

Miles, N. L., Verlinde, J., and Clothiaux, E. E., 2000: Cloud droplet size distributions in low-level stratiform clouds, J. Atmos. Sci., 5, 295-311, doi: 10.1175/1520-0469(2000)057<0295:cdsdil>2.0.co;2.

Noone, K., Ogren, J. A., Heintzenberg, J., Charlson, R. J., and Covert, D. S., 1988: Design and calibration of a counterflow virtual impactor for sampling of atmospheric fog and cloud droplets, Aerosol Sci. Technol., 8, 235-244, doi: 10.1080/02786828808959186.

O'Connor, E. J., A. J. Illingworth, and R. J. Hogan, 2004: A Technique for Autocalibration of Cloud Lidar. J. Atmos. Oceanic Technol., 21, 777-786, doi: 10.1175/1520-0426(2004)021<0777:ATFAOC>2.0.CO;2.

O'Connor, E. J., A. J. Illingworth, I. M. Brooks, C. D. Westbrook, R. J. Hogan, F. Davies, and B. J. Brooks, 2010: A method for estimating the turbulent kinetic energy dissipation rate from a vertically-pointing Doppler lidar, and independent evaluation from balloon-borne in-situ measurements, J. Atmos. Ocean. Technol., 27, 1652-1664, doi: 10.1175/2010JTECHA1455.1.

Ogren, J. A., J. Heintzenberg, and R. J. Charlson, 1985: In-situ sampling of clouds with a droplet to aerosol converter, Geophys. Res. Lett., 12, 121-124, doi: 10.1029/GL012i003p00121.

Pommereau, J. P., and F. Goutail, 1988: O₃ and NO₂ ground-based measurements by visible spectrometry during Arctic winter and spring 1988, Geophys. Res. Lett., 15, 891-894, doi: 10.1029/GL015i008p00891.

Protat, A., A. Armstrong, M. Haeffelin, Y. Morille, J. Pelon, J. Delanoë, and D. Bouniol, 2006: The impact of conditional sampling and instrumental limitations on the statistics of cloud properties derived from cloud radar and lidar at SIRTA, Geophys. Res. Lett., 33, L11805, doi: 10.1029/2005GL025340.

Reutter, P., Su, H., Trentmann, J., Simmel, M., Rose, D., Gunthe, S. S., Wernli, H., Andreae, M. O., and Pöschl, U., 2009: Aerosol- and updraft-limited regimes of cloud droplet formation: influence of particle number, size and hygroscopicity on the activation of cloud condensation nuclei (CCN), Atmos. Chem. Phys., 9, 7067-7080, doi: 10.5194/acp-9-7067-2009.

Reynolds, B., Fowler, D., and Thomas, S., 1996: Chemistry of cloud water at an upland site in mid-Wales, Science of The Total Environment, 188, 115-125, doi: 10.1016/0048-9697(96)05165-0.
Rose, D., Gunthe, S. S., Mikhailov, E., Frank, G. P., Dusek, U., Andreae, M. O., and Pöschl, U., 2008: Calibration and measurement uncertainties of a continuous-flow cloud condensation nuclei counter (DMT-CCNC): CCN activation of ammonium sulfate and sodium chloride aerosol particles in theory and experiment, Atmos. Chem. Phys., 8, 1153–1179, doi: 10.5194/acp-8-1153-2008.

Schwarzenböck, A., Heintzenberg, J., and Mertes, S., 2000: Incorporation of aerosol particles between 25 and 850 nanometers into cloud elements: Measurement with a new complementary sampling system, Atmos. Res., 52, 241–260.

Smirnov, A., B. N. Holben, T. F. Eck, O. Dubovik, and I. Slutsker, 2000: Cloud screening and quality control algorithms for the AERONET database, Rem. Sens. Env., 73, 337-349.

Spiegel, J. K., Zieger, P., Bukowiecki, N., Hammer, E., Weingartner, E., and Eugster, W., 2012: Evaluating the capabilities and uncertainties of droplet measurements for the fog droplet spectrometer (FM-100), Atmos. Meas. Tech., 5, 2237–2260, doi: 10.5194/amt-5-2237-2012.

Torres, B., et al., 2017: Advanced characterisation of aerosol size properties from measurements of spectral optical depth using the GRASP algorithm, Atmos. Meas. Tech., 10, 3743–3781, doi: 10.5194/amt-10-3743-2011.

Twohy, C. H., Schanot, A. J., and Cooper, W. A., 1997: Measurement of condensed water content in liquid and ice clouds using an airborne counterflow virtual impactor, J. Atmos. Oceanic Technol., 14, 197–202, doi: 10.1175/1520-0426(1997)014<0197:MOCWCI>2.0.CO;2.

van Pinxteren, D., et al., 2005: Schmücke hill cap cloud and valley stations aerosol characterisation during FEBUKO (II): Organic compounds, Atmos. Env., 39, 4305–4320, doi: 10.1016/j.atmosenv.2005.02.014.

Verheggen, B., Cozic, J., Weingartner, E., Mertes, S., Bower, K., Flynn, M., Connolly, P., Gallagher, M., and Baltensperger, U., 2007: Aerosol activation in liquid and mixed-phase clouds at the high alpine site Jungfraujoch, J. Geophys. Res., 112, D23202, doi: 10.1029/2007JD008714.

Vigouroux, C., et al., 2015: Trends of ozone total columns and vertical distribution from FTIR observations at 8 NDACC stations around the globe, Atmos. Chem. Phys., 15, 2915–2933, doi: 10.5194/acp-15-2915-2015.

Vigouroux, C., et al., 2018: NDACC harmonized formaldehyde time-series from 21 FTIR stations covering a wide range of column abundances, Atmos. Meas. Tech. Discuss., doi: 10.5194/amt-2018-22, in review.

Vlemmix, T., et al., 2015: MAX-DOAS observations of aerosols, formaldehyde and nitrogen dioxide in the Beijing area: comparison of two profile retrieval approaches, Atmos. Meas. Tech., 8, 941–963, doi: 10.5194/amt-8-941-2015.

Wagner, T., Dix, B., Friedeburg, C. v., Frieß, U., Sanghavi, S., Sinreich, R., and Platt, U., 2004: MAX-DOAS O4 measurements - A new technique to derive information on atmospheric aerosols. (I) Principles and information content, J. Geophys. Res., 109, D22205, doi: 10.1029/2004JD004904.
Rose, D., Gunthe, S. S., Mikhailov, E., Frank, G. P., Dusek, U., Andreae, M. O., and Pöschl, U., 2008: Calibration and measurement uncertainties of a continuous-flow cloud condensation nuclei counter (DMT-CCNC): CCN activation of ammonium sulfate and sodium chloride aerosol particles in theory and experiment, Atmos. Chem. Phys., 8, 1153–1179, doi: 10.5194/acp-8-1153-2008.

Schwarzenböck, A., Heintzenberg, J., and Mertes, S., 2000: Incorporation of aerosol particles between 25 and 850 nanometers into cloud elements: Measurement with a new complementary sampling system, Atmos. Res., 52, 241–260.

Smirnov, A., B. N. Holben, T. F. Eck, O. Dubovik, and I. Slutsker, 2000: Cloud screening and quality control algorithms for the AERONET database, Rem. Sens. Env., 73, 337-349.

Spiegel, J. K., Zieger, P., Bukowiecki, N., Hammer, E., Weingartner, E., and Eugster, W., 2012: Evaluating the capabilities and uncertainties of droplet measurements for the fog droplet spectrometer (FM-100), Atmos. Meas. Tech., 5, 2237–2260, doi: 10.5194/amt-5-2237-2012.

Torres, B., et al., 2017: Advanced characterisation of aerosol size properties from measurements of spectral optical depth using the GRASP algorithm, Atmos. Meas. Tech., 10, 3743–3781, doi: 10.5194/amt-10-3743-2011.

Twohy, C. H., Schanot, A. J., and Cooper, W. A., 1997: Measurement of condensed water content in liquid and ice clouds using an airborne counterflow virtual impactor, J. Atmos. Oceanic Technol., 14, 197–202, doi: 10.1175/1520-0426(1997)014<0197:MOCWCI>2.0.CO;2.

van Pinxteren, D., et al., 2005: Schmücke hill cap cloud and valley stations aerosol characterisation during FEBUKO (II): Organic compounds, Atmos. Env., 39, 4305–4320, doi: 10.1016/j.atmosenv.2005.02.014.

Verheggen, B., Cozic, J., Weingartner, E., Mertes, S., Bower, K., Flynn, M., Connolly, P., Gallagher, M., and Baltensperger, U., 2007: Aerosol activation in liquid and mixed-phase clouds at the high alpine site Jungfraujoch, J. Geophys. Res., 112, D23202, doi: 10.1029/2007JD008714.

Vigouroux, C., et al., 2015: Trends of ozone total columns and vertical distribution from FTIR observations at 8 NDACC stations around the globe, Atmos. Chem. Phys., 15, 2915–2933, doi: 10.5194/acp-15-2915-2015.

Vigouroux, C., et al., 2018: NDACC harmonized formaldehyde time-series from 21 FTIR stations covering a wide range of column abundances, Atmos. Meas. Tech. Discuss., doi: 10.5194/amt-2018-22, in review.

Vlemmix, T., et al., 2015: MAX-DOAS observations of aerosols, formaldehyde and nitrogen dioxide in the Beijing area: comparison of two profile retrieval approaches, Atmos. Meas. Tech., 8, 941–963, doi: 10.5194/amt-8-941-2015.

Wagner, T., Dix, B., Friedeburg, C. v., Frieß, U., Sanghavi, S., Sinreich, R., and Platt, U., 2004: MAX-DOAS O4 measurements - A new technique to derive information on atmospheric aerosols. (I) Principles and information content, J. Geophys. Res., 109, D22205, doi: 10.1029/2004JD004904.
Wandinger, U., et al., 2016: EARLINET instrument intercomparison campaigns: overview on strategy and results, Atmos. Meas. Tech., 9, 1001–1023, doi: 10.5194/amt-9-1001-2016.

Weingartner, E., Nyeki, S., and Baltensperger, U., 1999: Seasonal and diurnal variation of aerosol size distributions (10<d<750 nm) at a high-alpine site (Jungfraujoch 3580 m asl), J. Geophys. Res., 104, 26809–26820, doi: 10.1029/1999JD900170.

Westbrook, C. D., Illingworth, A. J., O'Connor, E. J., and Hogan, R. J., 2010: Doppler lidar measurements of oriented planar ice crystals falling from supercooled and glaciated layer clouds, Q. J. Roy. Meteorol. Soc., 136, 260–276, doi: 10.1002/qj.528.

Wiedensohler, A., et al., 2012: Mobility particle size spectrometers: Harmonization of technical standards and data structure to facilitate high quality long-term observations of atmospheric particle number size distributions, Atmos. Meas. Tech., 5, 657–685, doi: 10.5194/amt-5-657-2012.

Wiedensohler, A., et al., 2017: Mobility particle size spectrometers: Calibration procedures and measurement uncertainties, Aerosol Science and Technology, doi: 10.1080/02786826.2017.1387229.

Wiegner, M., and A. Geiß, 2012: Aerosol profiling with the Jenoptik ceilometer CHM15kx, Atmos. Meas. Tech., 5, 1953–1964, doi: 10.5194/amt-5-1953-2012.

WMO, 2007: A WMO/GAW Expert Workshop on Global Long-Term Measurements of VOCs, Geneva, Switzerland, http://library.wmo.int/pmb_ged/wmo-td_1373.pdf.

Worringen, A., et al., 2015: Single particle characterization of ice-nucleating particles and ice particle residuals sampled by three different techniques, Atmos. Chem. Phys., 15, 4161–4178, doi: 10.5194/acp-15-4161-2015.
Wandinger, U., et al., 2016: EARLINET instrument intercomparison campaigns: overview on strategy and results, Atmos. Meas. Tech., 9, 1001–1023, doi: 10.5194/amt-9-1001-2016.

Weingartner, E., Nyeki, S., and Baltensperger, U., 1999: Seasonal and diurnal variation of aerosol size distributions (10<d<750 nm) at a high-alpine site (Jungfraujoch 3580 m asl), J. Geophys. Res., 104, 26809–26820, doi: 10.1029/1999JD900170.

Westbrook, C. D., Illingworth, A. J., O'Connor, E. J., and Hogan, R. J., 2010: Doppler lidar measurements of oriented planar ice crystals falling from supercooled and glaciated layer clouds, Q. J. Roy. Meteorol. Soc., 136, 260–276, doi: 10.1002/qj.528.

Wiedensohler, A., et al., 2012: Mobility particle size spectrometers: Harmonization of technical standards and data structure to facilitate high quality long-term observations of atmospheric particle number size distributions, Atmos. Meas. Tech., 5, 657–685, doi: 10.5194/amt-5-657-2012.

Wiedensohler, A., et al., 2017: Mobility particle size spectrometers: Calibration procedures and measurement uncertainties, Aerosol Science and Technology, doi: 10.1080/02786826.2017.1387229.

Wiegner, M., and A. Geiß, 2012: Aerosol profiling with the Jenoptik ceilometer CHM15kx, Atmos. Meas. Tech., 5, 1953–1964, doi: 10.5194/amt-5-1953-2012.

WMO, 2007: A WMO/GAW Expert Workshop on Global Long-Term Measurements of VOCs, Geneva, Switzerland, http://library.wmo.int/pmb_ged/wmo-td_1373.pdf.

Worringen, A., et al., 2015: Single particle characterization of ice-nucleating particles and ice particle residuals sampled by three different techniques, Atmos. Chem. Phys., 15, 4161–4178, doi: 10.5194/acp-15-4161-2015.