An examination of Köhler theory resulting in an accurate expression for the equilibrium radius ratio of a hygroscopic aerosol particle valid up to and including relative humidity 100%

2008 ◽  
Vol 113 (D3) ◽  
Author(s):  
Ernie R. Lewis
Keyword(s):  
Relative Humidity ◽  
Aerosol Particle ◽  
Radius Ratio ◽  
Kohler Theory ◽  
Accurate Expression ◽  
Equilibrium Radius

scholarly journals 60 years of UK visibility measurements: impact of meteorology and atmospheric pollutants on visibility

2017 ◽  
Vol 17 (3) ◽  
pp. 2085-2101 ◽  
Author(s):  
Ajit Singh ◽  
William J. Bloss ◽  
Francis D. Pope
Keyword(s):  
Relative Humidity ◽  
Aerosol Particle ◽  
Urban Areas ◽  
Land Use Changes ◽  
Gas Absorption ◽  
Atmospheric Pollutants ◽  
Light Extinction ◽  
The Impact ◽  
Aerosol Hygroscopicity

Abstract. Reduced visibility is an indicator of poor air quality. Moreover, degradation in visibility can be hazardous to human safety; for example, low visibility can lead to road, rail, sea and air accidents. In this paper, we explore the combined influence of atmospheric aerosol particle and gas characteristics, and meteorology, on long-term visibility. We use visibility data from eight meteorological stations, situated in the UK, which have been running since the 1950s. The site locations include urban, rural and marine environments. Most stations show a long-term trend of increasing visibility, which is indicative of reductions in air pollution, especially in urban areas. Additionally, the visibility at all sites shows a very clear dependence on relative humidity, indicating the importance of aerosol hygroscopicity on the ability of aerosol particles to scatter radiation. The dependence of visibility on other meteorological parameters, such as wind speed and wind direction, is also investigated. Most stations show long-term increases in temperature which can be ascribed to climate change, land-use changes (e.g. urban heat island effects) or a combination of both; the observed effect is greatest in urban areas. The impact of this temperature change upon local relative humidity is discussed. To explain the long-term visibility trends and their dependence on meteorological conditions, the measured data were fitted to a newly developed light-extinction model to generate predictions of historic aerosol and gas scattering and absorbing properties. In general, an excellent fit was achieved between measured and modelled visibility for all eight sites. The model incorporates parameterizations of aerosol hygroscopicity, particle concentration, particle scattering, and particle and gas absorption. This new model should be applicable and is easily transferrable to other data sets worldwide. Hence, historical visibility data can be used to assess trends in aerosol particle properties. This approach may help constrain global model simulations which attempt to generate aerosol fields for time periods when observational data are scarce or non-existent. Both the measured visibility and the modelled aerosol properties reported in this paper highlight the success of the UK's Clean Air Act, which was passed in 1956, in cleaning the atmosphere of visibility-reducing pollutants.

scholarly journals 60 years of UK visibility measurements: impact of meteorology and atmospheric pollutants on visibility

2016 ◽  
Author(s):  
Ajit Singh ◽  
William J. Bloss ◽  
Francis D. Pope
Keyword(s):  
Relative Humidity ◽  
Aerosol Particle ◽  
Urban Areas ◽  
Land Use Changes ◽  
Gas Absorption ◽  
Atmospheric Pollutants ◽  
Light Extinction ◽  
The Impact ◽  
Aerosol Hygroscopicity

Abstract. Reduced visibility is an indicator of poor air quality. Moreover, degradation in visibility can be hazardous to human safety; for example, low visibility can lead to road, rail, sea and air accidents. In this paper, we explore the combined influence of atmospheric aerosol particle and gas characteristics, and meteorology, on long-term visibility. We use visibility data from eight meteorological stations, situated in the UK, which have been running since the 1950s. The site locations include urban, rural and marine environments. Most stations show a long term trend of increasing visibility which is indicative of reductions in air pollution, especially in urban areas. Additionally, the visibility at all sites show a very clear dependence on relative humidity indicating the importance of aerosol hygroscopicity on the ability of aerosol particles to scatter radiation. The dependence of visibility on other meteorological parameters, such as wind speed and wind direction is also investigated. Most stations show long term increases in temperature which can be ascribed to either climate change, land-use changes (e.g. urban heat island effects) or a combination of both; the observed effect is greatest in urban areas. The impact of this temperature change upon local relative humidity is discussed. To explain the long term visibility trends and their dependence on meteorological conditions, the measured data were fitted to a newly developed light extinction model to generate predictions of historic aerosol and gas scattering and absorbing properties. In general, an excellent fit was achieved between measured and modelled visibility for all 8 sites. The model incorporates parameterizations of aerosol hygroscopicity, particle concentration, particle scattering, and particle and gas absorption. This new model should be applicable and is easily transferrable to other data sets worldwide. Hence, historical visibility data can be used to assess trends in aerosol particle properties. This approach may help constrain global model simulations which attempt to generate aerosol fields for time periods when observational data are scarce or non-existent. Both the measured visibility and the modelled aerosol properties reported in this paper highlight the success of the UK’s Clean Air Act, which was passed in 1956, in cleaning the atmosphere of visibility reducing pollutants.

scholarly journals Classifying previously undefined days from eleven years of aerosol-particle-size distribution data from the SMEAR II station, Hyytiälä, Finland

2009 ◽  
Vol 9 (2) ◽  
pp. 667-676 ◽  
Author(s):  
S. Buenrostro Mazon ◽  
I. Riipinen ◽  
D. M. Schultz ◽  
M. Valtanen ◽  
M. Dal Maso ◽  
...  
Keyword(s):  
Particle Size ◽  
Relative Humidity ◽  
Size Distribution ◽  
Aerosol Particle ◽  
Particle Formation ◽  
Number Concentration ◽  
Aerosol Size Distribution ◽  
Distribution Data ◽  
Back Trajectories ◽  
Condensation Sink

Abstract. Studies of secondary aerosol-particle formation depend on identifying days in which new particle formation occurs and, by comparing them to days with no signs of particle formation, identifying the conditions favourable for formation. Continuous aerosol size distribution data has been collected at the SMEAR II station in a boreal forest in Hyytiälä, Finland, since 1996, making it the longest time series of aerosol size distributions available worldwide. In previous studies, the data have been classified as particle-formation event, nonevent, and undefined days, with almost 40% of the dataset classified as undefined. In the present study, eleven years (1996–2006) of undefined days (1630 days) were reanalyzed and subdivided into three new classes: failed events (37% of all previously undefined days), ultrafine-mode concentration peaks (34%), and pollution-related concentration peaks (19%). Unclassified days (10%) comprised the rest of the previously undefined days. The failed events were further subdivided into tail events (21%), where a tail of a formation event presumed to be advected to Hyytiälä from elsewhere, and quasi events (16%) where new particles appeared at sizes 3–10 nm, but showed unclear growth, the mode persisted for less than an hour, or both. The ultrafine concentration peaks days were further subdivided into nucleation-mode peaks (24%) and Aitken-mode peaks (10%), depending on the size range where the particles occurred. The mean annual distribution of the failed events has a maximum during summer, whereas the two peak classes have maxima during winter. The summer minimum previously found in the seasonal distribution of event days partially offsets a summer maximum in failed-event days. Daily-mean relative humidity and condensation sink values are useful in discriminating the new classes from each other. Specifically, event days had low values of relative humidity and condensation sink relative to nonevent days. Failed-event days possessed intermediate condensation sink and relative humidity values, whereas both ultrafine-mode peaks and, to a greater extent, pollution-related peaks had high values of both, similar to nonevent days. Using 96-h back trajectories, particle-size concentrations were plotted as a function of time the trajectory spent over land. Increases in particle size and number concentration during failed-event days were similar to that during the later stages of event days, whereas the particle size and number concentration for both nonevent and peaks classes did not increase as fast as for event and failed events days.

scholarly journals A look at aerosol formation using data mining techniques

2005 ◽  
Vol 5 (12) ◽  
pp. 3345-3356 ◽  
Author(s):  
S. Hyvönen ◽  
H. Junninen ◽  
L. Laakso ◽  
M. Dal Maso ◽  
T. Grönholm ◽  
...  
Keyword(s):  
Data Mining ◽  
Relative Humidity ◽  
Aerosol Particle ◽  
Atmospheric Aerosol ◽  
Particle Surface ◽  
Particle Formation ◽  
High Water Content ◽  
Aerosol Formation ◽  
Data Mining Techniques ◽  
Condensation Sink

Abstract. Atmospheric aerosol particle formation is frequently observed throughout the atmosphere, but despite various attempts of explanation, the processes behind it remain unclear. In this study data mining techniques were used to find the key parameters needed for atmospheric aerosol particle formation to occur. A dataset of 8 years of 80 variables collected at the boreal forest station (SMEAR II) in Southern Finland was used, incorporating variables such as radiation, humidity, SO2, ozone and present aerosol surface area. This data was analyzed using clustering and classification methods. The aim of this approach was to gain new parameters independent of any subjective interpretation. This resulted in two key parameters, relative humidity and preexisting aerosol particle surface (condensation sink), capable in explaining 88% of the nucleation events. The inclusion of any further parameters did not improve the results notably. Using these two variables it was possible to derive a nucleation probability function. Interestingly, the two most important variables are related to mechanisms that prevent the nucleation from starting and particles from growing, while parameters related to initiation of particle formation seemed to be less important. Nucleation occurs only with low relative humidity and condensation sink values. One possible explanation for the effect of high water content is that it prevents biogenic hydrocarbon ozonolysis reactions from producing sufficient amounts of low volatility compounds, which might be able to nucleate. Unfortunately the most important biogenic hydrocarbon compound emissions were not available for this study. Another effect of water vapour may be due to its linkage to cloudiness which may prevent the formation of nucleating and/or condensing vapours. A high number of preexisting particles will act as a sink for condensable vapours that otherwise would have been able to form sufficient supersaturation and initiate the nucleation process.

scholarly journals New representation of water activity based on a single solute specific constant to parameterize the hygroscopic growth of aerosols in atmospheric models

2012 ◽  
Vol 12 (12) ◽  
pp. 5429-5446 ◽  
Author(s):  
S. Metzger ◽  
B. Steil ◽  
L. Xu ◽  
J. E. Penner ◽  
J. Lelieveld
Keyword(s):  
Relative Humidity ◽  
Water Activity ◽  
Atmospheric Chemistry ◽  
Reference Model ◽  
Climate Modeling ◽  
Cloud Condensation Nuclei ◽  
Hygroscopic Growth ◽  
Wide Range ◽  
Kohler Theory ◽  
Key Factor

Abstract. Water activity is a key factor in aerosol thermodynamics and hygroscopic growth. We introduce a new representation of water activity (aw), which is empirically related to the solute molality (μs) through a single solute specific constant, νi. Our approach is widely applicable, considers the Kelvin effect and covers ideal solutions at high relative humidity (RH), including cloud condensation nuclei (CCN) activation. It also encompasses concentrated solutions with high ionic strength at low RH such as the relative humidity of deliquescence (RHD). The constant νi can thus be used to parameterize the aerosol hygroscopic growth over a wide range of particle sizes, from nanometer nucleation mode to micrometer coarse mode particles. In contrast to other aw-representations, our νi factor corrects the solute molality both linearly and in exponent form x · ax. We present four representations of our basic aw-parameterization at different levels of complexity for different aw-ranges, e.g. up to 0.95, 0.98 or 1. νi is constant over the selected aw-range, and in its most comprehensive form, the parameterization describes the entire aw range (0–1). In this work we focus on single solute solutions. νi can be pre-determined with a root-finding method from our water activity representation using an aw−μs data pair, e.g. at solute saturation using RHD and solubility measurements. Our aw and supersaturation (Köhler-theory) results compare well with the thermodynamic reference model E-AIM for the key compounds NaCl and (NH4)2SO4 relevant for CCN modeling and calibration studies. Envisaged applications include regional and global atmospheric chemistry and climate modeling.

scholarly journals Closure of In-Situ Measured Aerosol Backscattering and Extinction Coefficients with Lidar Accounting for Relative Humidity

2021 ◽  
Author(s):  
Sebastian Düsing ◽  
Albert Ansmann ◽  
Holger Baars ◽  
Joel C. Corbin ◽  
Cyrielle Denjean ◽  
...  
Keyword(s):  
Optical Properties ◽  
Relative Humidity ◽  
Aerosol Particle ◽  
Light Absorption ◽  
Aerosol Particles ◽  
Light Extinction ◽  
Mixing State ◽  
Carbon Mass ◽  
Lidar Ratio

Abstract. Aerosol particles contribute to the climate forcing through their optical properties. Measuring these optical aerosol particle properties is still challenging, especially considering the hygroscopic growth of aerosol particles, which alters their optical properties. Lidar and in-situ techniques can derive a variety of aerosol optical properties, like aerosol particle light extinction, backscattering, and absorption. But these techniques are subject to some limitations and uncertainties. Within this study, we compared airborne in-situ based and, on Mie-theory based, modeled optical properties at dry state. At ambient state, modeled optical properties were compared with lidar-based estimates. Also, we examined the dependence of the aerosol particle light extinction-to-backscatter ratio, also lidar ratio, to relative humidity. The used model was fed with measured physicochemical aerosol properties and ambient atmospheric conditions. The model considered aerosol particles in an internal core-shell mixing state with constant volume fractions of the aerosol components over the entire observed aerosol particle size-range. The underlying set of measurements was conducted near the measurement site Melpitz, Germany, during two campaigns in summer, 2015, and winter, 2017, and represent Central European background aerosol conditions. Two airborne payloads deployed on a helicopter and a balloon provided measurements of microphysical and optical aerosol particle properties and were complemented by the polarization Raman lidar system PollyXT as well as by a holistic set of microphysical, chemical and optical aerosol measurements derived at ground level. Comparisons of calculated optical aerosol properties with ground-based in-situ measured aerosol optical properties at dry state showed an agreement of the model within 13 % (3 %) in terms of scattering at 450 nm wavelength during the winter (summer) campaign. The model also represented the aerosol particle light absorption at 637 nm within 8 % (18 %) during the winter (summer) campaign and agreed within 13 % with the airborne in-situ aerosol particle light extinction measurements during summer. During winter, in a comparatively clean case with equivalent black carbon mass-concentrations of around 0.2 µg m−3 the modeled airborne measurement-based aerosol particle light absorption, was up to 32–37 % larger than the measured values during a relatively clean period. However, during a high polluted case, with an equivalent black carbon mass concentration of around 4 µg m−3, the modeled aerosol particle light absorption coefficient was, depending on the wavelength, 13–32 % lower than the measured values. Spread and magnitude of the disagreement highlighted the importance of the aerosol mixing state used within the model, the requirement of the inclusion of brown carbon, and a wavelength-dependent complex refractive index of black and brown carbon when such kind of model is used to validate aerosol particle light absorption coefficient estimates of, e.g., lidar systems. Besides dry state comparisons, ambient modeled aerosol particle light extinction, as well as aerosol particle light backscattering, were compared with lidar estimates of these measures. During summer, on average, for four of the twelve conducted measurement flights, the model calculated lower aerosol particle light extinction (up to 29 % lower) as well as backscattering (up to 32 % lower) than derived with the lidar. In winter, the modeled aerosol particle light extinction coefficient was 17 %–41 % lower, the aerosol particle light backscattering coefficient 14 %–42 % lower than the lidar estimates. For both, the winter and summer cases, the Mie-model estimated reasonable extinction-to-backscatter (LR) ratios. Measurement-based Mie-modeling showed evidence of the dependence of the lidar ratio on relative humidity (RH). With this result, we presented a fit for lidar wavelengths of 355, 532, and 1064 nm with an underlying equation of fLR (RH,γ(λ)) = fLR (RH = 0,λ) × (1 − RH)(−γ(λ)) and estimates of γ(355 nm) = 0.29 (±0.01), γ(532 nm) = 0.48 (±0.01), and γ(1064 nm) = 0.31 (±0.01). However, further measurements are required to entangle the behavior of the lidar ratio with respect to different aerosol types, to set up a climatology, and to assess the influence of the aerosol mixing state. This comprehensive study combining airborne and ground-based in-situ and remote sensing measurements, which simulated multiple aerosol optical coefficients in the ambient and dry state, is with its complexity unique of its kind.

Structural Change of Aerosol Particle Aggregates with Exposure to Elevated Relative Humidity

2015 ◽  
Vol 49 (20) ◽  
pp. 12054-12061 ◽  
Author(s):  
James F. Montgomery ◽  
Steven N. Rogak ◽  
Sheldon I. Green ◽  
Yuan You ◽  
Allan K. Bertram
Keyword(s):  
Structural Change ◽  
Relative Humidity ◽  
Aerosol Particle ◽  
Particle Aggregates

scholarly journals A look at aerosol formation using data mining techniques

2005 ◽  
Vol 5 (4) ◽  
pp. 7577-7611 ◽  
Author(s):  
S. Hyvönen ◽  
H. Junninen ◽  
L. Laakso ◽  
M. Dal Maso ◽  
T. Grönholm ◽  
...  
Keyword(s):  
Data Mining ◽  
Relative Humidity ◽  
Aerosol Particle ◽  
Atmospheric Aerosol ◽  
Particle Surface ◽  
Particle Formation ◽  
High Water Content ◽  
Aerosol Formation ◽  
Data Mining Techniques ◽  
Condensation Sink

Abstract. Atmospheric aerosol particle formation is frequently observed throughout the atmosphere, but despite various attempts of explanation, the processes behind it remain unclear. In this study data mining techniques were used to find the key parameters needed for atmospheric aerosol particle formation to occur. A dataset of 8 years of 80 variables collected at the boreal forest station (SMEAR II) in Southern Finland was used, incorporating variables such as radiation, humidity, SO2, ozone and present aerosol surface area. Data analysis were done using clustering and classification methods. The aim of this approach was to gain new parameters independent of any subjective interpretation. This resulted in two key parameters, relative humidity and preexisting aerosol particle surface (condensation sink), capable in explaining 88% of the nucleation events. The inclusion of any further parameters did not improve the results notably. Using these two variables it was possible to derive a nucleation probability function. Interestingly, the two most important variables are related to mechanisms that prevent the nucleation from starting and particles from growing, while parameters related to initiation of particle formation seemed to be less important. Nucleation occurs only with low relative humidity and condensation sink values. One possible explanation for the effect of high water content is that it prevents biogenic hydrocarbon ozonolysis reactions from producing sufficient amounts of low volatility compounds, which might be able to nucleate. Unfortunately the most important biogenic hydrocarbon compound emissions were not available for this study. Another effect of water vapour may be due to its linkage to cloudiness which may prevent the formation of nucleating and/or condensing vapours. A high number of preexisting particles will act as a sink for condensable vapours that otherwise would have been able to form sufficient supersaturation and initiate the nucleation process.

Sign in / Sign up

Export Citation Format

Share Document