Technical note: New particle formation event forecasts during PEGASOS–Zeppelin Northern mission 2013 in Hyytiälä, Finland

Abstract

Abstract. New particle formation (NPF) occurs frequently in the global atmosphere. During recent years, detailed laboratory experiments combined with intensive field observations in different locations have provided insights into the vapours responsible for the initial formation of particles and their subsequent growth. In this regard, the importance of sulfuric acid, stabilizing bases such as ammonia and amines as well as extremely low volatile organics, have been proposed. The instrumentation to observe freshly formed aerosol particles has developed to a stage where the instruments can be implemented as part of airborne platforms, such as aircrafts or a Zeppelin-type airship. Flight measurements are technically more demanding and require a greater detail of planning than field studies at the ground level. The high cost of flight hours, limited time available during a single research flight for the measurements, and different instrument payloads in Zeppelin airship for various flight missions demanded an analysis tool that would forecast whether or not there is a good chance for an NPF event. Here we present a methodology to forecast NPF event probability at the SMEAR II site in Hyytiälä, Finland. This methodology was used to optimize flight hours during the PEGASOS (Pan-European Gas Aerosol Climate Interaction Study)-Zeppelin Northern mission in May-June 2013. Based on the existing knowledge, we derived a method for estimating the nucleation probability that utilizes forecast air mass trajectories, weather forecasts, and air quality model predictions. With the forecast tool we were able to predict the occurrence of NPF events for the next day with more than 90 % success rate (10 out of 11 NPF event days correctly predicted). To our knowledge, no similar forecasts of NPF occurrence have been developed for other sites. This method of forecasting NPF occurrence could be applied also at other locations, provided that long-term observations of conditions favouring particle formation are available.

Long-term analysis of clear-sky new particle formation events and nonevents in Hyytiälä

“…During the NPF event days, the measured air masses were found to originate mainly from the north and passed over Scandinavia before arriving at Hyytiälä. Similarly to previously reported results, air masses arriving from the north and north-west directions result in clean air with low pollutant (particulate matter and trace gas) concentrations (Nieminen et al, 2015). During NPF the nonevent days, air masses originated from more polluted areas in Europe and Russia, resulting in elevated levels of condensation sink and other air pollutants in Hyytiälä, as also seen in previous studies (Sogacheva et al, 2005).…”

“…In particular, Baranizadeh et al (2014) studied the effect of cloudiness on NPF events observed at SMEAR II in Hyytiälä. They concluded, in agreement with some other studies, that clouds tend to attenuate or interrupt NPF events Boulon et al, 2010;Baranizadeh et al, 2014;Nieminen et al, 2015). In this study, we eliminated one variable that limits NPF (cloudiness) in order to provide a better insight into the other quantities related to atmospheric NPF.…”

“…The difference in CS between NPF events and nonevents follows from the distinctly different air masses arriving at Hyytiälä. For instance, it has been shown that air masses originating from the north and passing over Scandinavia have, on average, lower values of CS than the air masses passing over Russia and central Europe (Sogacheva et al, 2005;Nieminen et al, 2015).…”

“…For instance, high concentrations of low-volatility vapors result in a higher probability for NPF (Nieminen et al, 2015), whereas a high relative humidity and condensation sink (CS) tend to suppress NPF (Hyvö-nen et al, 2005;Nieminen et al, 2014). Recent laboratory experiments have shown the importance of sulfuric acid and low-volatile oxidized organic vapors to NPF Kirkby et al, 2011;Petäjä et al, 2011;Kulmala et al, 2013;Ehn et al, 2014;Riccobono et al, 2014).…”

Identification of new particle formation events with deep learning

“…Hyvönen et al (2005) and Mikkonen et al (2006) applied discriminant analysis for multi-year datasets of aerosol size-distributions and several gas and meteorological parameters measured at Hyytiälä, Finland and San Pietro 20 Capofiume, Italy. Both of these studies were able to construct models to predict the probability of NPF occurrence with reasonable accuracy, and this approach has also been used in the day-to-day planning of a complex airborne measurement campaign (Nieminen et al, 2015). More recently, preliminary attempt at utilizing machine learning on big datasets have been reported (Zaidan et al, 2017).…”