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

2015 ◽  
Vol 15 (21) ◽  
pp. 12385-12396 ◽  
Author(s):  
T. Nieminen ◽  
T. Yli-Juuti ◽  
H. E. Manninen ◽  
T. Petäjä ◽  
V.-M. Kerminen ◽  
...  
Keyword(s):  
Ground Level ◽  
Field Studies ◽  
Particle Formation ◽  
Technical Note ◽  
Analysis Tool ◽  
New Particle Formation ◽  
Air Quality Model ◽  
Quality Model ◽  
Weather Forecasts

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.

scholarly journals Technical Note: New particle formation event forecasts during PEGASOS-Zeppelin Northern mission 2013 in Hyytiälä, Finland

2015 ◽  
Vol 15 (2) ◽  
pp. 2459-2485
Author(s):  
T. Nieminen ◽  
T. Yli-Juuti ◽  
H. E. Manninen ◽  
T. Petäjä ◽  
V.-M. Kerminen ◽  
...  
Keyword(s):  
Ground Level ◽  
Field Studies ◽  
Particle Formation ◽  
Technical Note ◽  
Analysis Tool ◽  
New Particle Formation ◽  
Air Quality Model ◽  
Quality Model ◽  
Weather Forecasts ◽  
Model Predictions

Abstract. New particle formation (NPF) occurs frequently in the global atmosphere. During recent years detailed laboratory experiments together 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 sulphuric 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 a NPF event. Here we present a generalized methodology to derive NPF event probability that was used to optimise flying hours during Zeppelin campaign in Finland during the PEGASOS-Zeppelin Northern mission in 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).

scholarly journals Hourly Ground-Level PM2.5 Estimation Using Geostationary Satellite and Reanalysis Data via Deep Learning

2021 ◽  
Vol 13 (11) ◽  
pp. 2121
Author(s):  
Changsuk Lee ◽  
Kyunghwa Lee ◽  
Sangmin Kim ◽  
Jinhyeok Yu ◽  
Seungtaek Jeong ◽  
...  
Keyword(s):  
Cross Validation ◽  
Ground Level ◽  
Reanalysis Data ◽  
Training Dataset ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Air Quality Model ◽  
Quality Model ◽  
Near Surface

This study proposes an improved approach for monitoring the spatial concentrations of hourly particulate matter less than 2.5 μm in diameter (PM2.5) via a deep neural network (DNN) using geostationary ocean color imager (GOCI) images and unified model (UM) reanalysis data over the Korean Peninsula. The DNN performance was optimized to determine the appropriate training model structures, incorporating hyperparameter tuning, regularization, early stopping, and input and output variable normalization to prevent training dataset overfitting. Near-surface atmospheric information from the UM was also used as an input variable to spatially generalize the DNN model. The retrieved PM2.5 from the DNN was compared with estimates from random forest, multiple linear regression, and the Community Multiscale Air Quality model. The DNN demonstrated the highest accuracy compared to that of the conventional methods for the hold-out validation (root mean square error (RMSE) = 7.042 μg/m3, mean bias error (MBE) = −0.340 μg/m3, and coefficient of determination (R2) = 0.698) and the cross-validation (RMSE = 9.166 μg/m3, MBE = 0.293 μg/m3, and R2 = 0.49). Although the R2 was low due to underestimated high PM2.5 concentration patterns, the RMSE and MBE demonstrated reliable accuracy values (<10 μg/m3 and 1 μg/m3, respectively) for the hold-out validation and cross-validation.

scholarly journals Long-term analysis of clear-sky new particle formation events and non-events in Hyytiälä

2016 ◽  
Author(s):  
Lubna Dada ◽  
Pauli Paasonen ◽  
Tuomo Nieminen ◽  
Stephany Buenrostro Mazon ◽  
Jenni Kontkanen ◽  
...  
Keyword(s):  
Formation Rate ◽  
Threshold Value ◽  
Particle Formation ◽  
New Particle Formation ◽  
Organic Vapors ◽  
Clear Sky ◽  
Sky Conditions ◽  
Oxidized Products ◽  
Condensation Sink

Abstract. New particle formation (NPF) events have been observed all around the world and are known to be a major source of atmospheric aerosol particles. Here we combine 20 years of observations in a boreal forest at the SMEAR II station (Station for Measuring Ecosystem-Atmosphere Relations) in Hyytiälä, Finland, by utilizing previously accumulated knowledge, and by focusing on clear-sky (non-cloudy) conditions. We first investigated the effect of cloudiness on NPF and then compared the NPF event and non-event days during clear-sky conditions. In this comparison we considered, for example, the effects of calculated particle formation rates, condensation sink, trace gas concentrations and various meteorological quantities. The formation rate of 1.5 nm particles was calculated by using proxies for gaseous sulfuric acid and oxidized products of low volatile organic compounds. As expected, our results indicate an increase in the frequency of NPF events under clear-sky conditions. Also, focusing on clearsky conditions enabled us to find a clear separation of many variables related to NPF. For instance, oxidized organic vapors showed higher concentration during the clear-sky NPF event days, whereas the condensation sink (CS) and some trace gases had higher concentrations during the non-event days. The calculated formation rate of 3 nm particles showed a notable difference between the NPF event and non-event days during clear-sky conditions, especially in winter and spring. For spring time, we are able to find a threshold value for the combined values of ambient temperature and CS, above which practically no clear-sky NPF event could be observed. Finally, we present a probability distribution for the frequency of NPF events at a specific CS and temperature.

scholarly journals Direct observation of molecular clusters and nucleation mode particles in the Amazon

2017 ◽  
Author(s):  
Daniela Wimmer ◽  
Stephany Buenrostro Mazon ◽  
Hanna Elina Manninen ◽  
Juha Kangasluoma ◽  
Alessandro Franchin ◽  
...  
Keyword(s):  
Growth Rates ◽  
Ground Level ◽  
Particle Formation ◽  
New Particle Formation ◽  
Wet Season ◽  
Ion Concentrations ◽  
Nucleation Mode ◽  
Rain Events ◽  
20 Nm ◽  
Spectrometer Data

Abstract. We investigated atmospheric new particle formation (NPF) in the Amazon rainforest using direct measurement methods. The occurrence of NPF on ground level in the Amazon region has not been observed previously in pristine conditions. Our measurements extended to two field sites and two tropical seasons (wet and dry). We measured the variability of air ion concentrations (0.8–20 nm) with an ion spectrometer between 2011 and 2014 at the T0t site and between February and October 2014 at the GoAmazon 2014/5 T3 site. The main difference between the two sites is their geographical location. Both sites are influenced by the Manaus pollution plume yet with different frequencies. T0t is reached by the pollution about 1 day in 7, where the T3 site is about 15 % of the time affected by Manaus. The sampling was performed at ground level at both sites. At T0t the instrumentation was located inside the rainforest, whereas the T3 site was an open pasture site. T0t site is mostly parallel wind to Manaus, whereas T3 site is downwind of Manaus. No NPF events were observed inside the rainforest canopy (site T0t) at ground level during the period Sep 2011–Jan 2014. However, rain-induced ion and particle bursts (hereafter, “rain events”) occurred frequently (306/529 days) at T0t throughout the year but most frequently between January and April (wet season). Rain events increased nucleation mode (2–20 nm) particle and ion concentrations on the order of 104 cm−3. We observed 8 NPF events at the pasture site during the wet season. We calculated the growth rates (GR) and formation rates of neutral particles and ions for the size ranges 2–3 nm, 3–7 nm and 7–20 nm using the ion spectrometer data. One explanation for the absence of new particle formation events at the T0t site could be a combination of cleaner airmasses and the rainforest canopy acting as an ‘umbrella’, hindering the mixing of the airmasses down to the measurement height. Neutral particle growth rates in the 3–7 nm regime showed two phenomena. Growth rates were either about 2 nm h−1 or about 14 nm h−1. There was no clear difference in the sulfuric acid concentrations for NPF days vs days without NPF. Back trajectory calculations show different airmass origin for the NPF days compared to non NPF days.

scholarly journals Evidence of an elevated source of nucleation based on model simulations and data from the NIFTy experiment

2012 ◽  
Vol 12 (17) ◽  
pp. 8021-8036 ◽  
Author(s):  
P. Crippa ◽  
T. Petäjä ◽  
H. Korhonen ◽  
G. S. El Afandi ◽  
S. C. Pryor
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Ultrafine Particle ◽  
Ground Level ◽  
Particle Formation ◽  
Atmospheric Conditions ◽  
New Particle Formation ◽  
Near Surface ◽  
Nocturnal Inversion

Abstract. New particle formation has been observed at a number of ground-based measurement sites. Prior research has provided evidence that this new particle formation, while observed in the near-surface layer, is actually occurring in atmospheric layers above the surface and appears to be focused in or close to the residual layer formed by the nocturnal inversion. Here, we present both observations and modeling for southern Indiana which support this postulate. Based on simulations with a detailed aerosol dynamics model and the Weather Research and Forecasting model, along with data from ground-based remote sensing instruments and detailed gas and particle phase measurements, we show evidence that (i) the maximum rate change of ultrafine particle concentrations as observed close to the surface is always preceded by breakdown of the nocturnal inversion and enhancement of vertical mixing and (ii) simulated particle size distributions exhibit greatest accord with surface observations during and subsequent to nucleation only when initialized with a particle size distribution representative of clear atmospheric conditions, rather than the in situ (ground-level) particle size distribution.

scholarly journals Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data

2016 ◽  
Vol 16 (24) ◽  
pp. 15629-15652 ◽  
Author(s):  
Ioannis Kioutsioukis ◽  
Ulas Im ◽  
Efisio Solazzo ◽  
Roberto Bianconi ◽  
Alba Badia ◽  
...  
Keyword(s):  
Air Quality ◽  
Deterministic Model ◽  
Ensemble Methods ◽  
Ground Level ◽  
Chemical Mechanism ◽  
Second Phase ◽  
Air Quality Model ◽  
Quality Model ◽  
Deterministic Models ◽  
Ensemble Mean

Abstract. Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four ensemble methods were applied to two different datasets, and their performance was compared for ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10). Apart from the unconditional ensemble average, the approach behind the other three methods relies on adding optimum weights to members or constraining the ensemble to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme) and AirBase databases. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill over the single models and the ensemble mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional ensemble mean achieves higher skill compared to each station's best deterministic model at no more than 60 % of the sites, indicating a combination of members with unbalanced skill difference and error dependence for the rest. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way. The skill improvements were higher for O3 and lower for PM10, associated with the extent of potential changes in the joint distribution of accuracy and diversity in the ensembles. The skill enhancement was superior using the weighting scheme, but the training period required to acquire representative weights was longer compared to the sub-selecting schemes. Further development of the method is discussed in the conclusion.

scholarly journals Technical note: The enhancement limit of coagulation scavenging of small charged particles

2021 ◽  
Vol 21 (5) ◽  
pp. 3827-3832
Author(s):  
Naser G. A. Mahfouz ◽  
Neil M. Donahue
Keyword(s):  
Survival Probability ◽  
Charged Particles ◽  
Particle Growth ◽  
Particle Formation ◽  
Technical Note ◽  
New Particle Formation ◽  
Neutral Case

Abstract. We show that the limit of the enhancement of coagulation scavenging of charged particles is 2, that is, doubled compared to the neutral case. Because the particle survival probability decreases exponentially as the coagulation sink increases, everything else being equal, the doubling of the coagulation sink can amount to a dramatic drop in survival probability – squaring the survival probability, p2, where p≤1 is the survival probability in the neutral case. Thus, it is imperative to consider this counterbalancing effect when studying ion-induced new-particle formation and ion-enhanced new-particle growth in the atmosphere.

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