Browsing by Subject "aerosol"
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(2023)Atmospheric aerosol particles play a significant role in urban air pollution, and understanding their size distribution is essential for assessing pollution sources and urban aerosol dynamics. In this study, we use a novel method developed by Kontkanen et al. (2020) to determine size-resolved particle number emissions in the particle size range of 3-800 nm at an urban background site and a street canyon site in Helsinki. Our results show overall higher particle number emissions in the street canyon compared to the urban background. On non-NPF event days, the particle number emissions of 3-6 nm particles in the urban background are highest in the noon. The emissions to the size range of 6-30 nm are highest during the morning or afternoon at both sites, indicating traffic is the main particle source in this size range. The emissions of larger particles are relatively low. Seasonal analysis suggests higher emissions during the summer in comparison to the winter which might be linked to higher product of mixing layer height (MLH) and particle number concentration in summer. Further investigations into particle emissions from different wind sectors suggest higher particle emissions from the urban sector than from the road sector in the urban background, contrary to the results for NOx concentrations. More research is needed to better understand the underlying factors. In addition, a comparison between particle number emissions estimated using FMI measurement MLH data and ERA5 model MLH data reveals that FMI data provides a more reliable representation of the MLH in the study area. Overall, the methods show limitations in accurately capturing particle dynamics in Helsinki. Future studies should address these limitations by employing more accurate NPF event classification and refining sector division methods.
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(2021)Cloud condensation nuclei (CCN) participate in controlling the climate, and a better understading of their number concentrations is needed to constrain the current uncertainties in Earth’s energy budget. However, estimating the global CCN concentrations is difficult using only localised in-situ measurements. To overcome this, different proxies and parametrisations for CCN have been developed. In this thesis, accumulation mode particles were used as a substitute for CCN, and continental proxy for number concentration of N100 was developed with CO and temperature as tracers for anthropogenic and biogenic emissions. The data utilised in the analysis contained N100 measurements from 22 sites from 5 different continents as well as CO and temperature from CAMS reanalysis dataset. The thesis aimed to construct a global continental proxy. In addition to this, individual proxies for each site (the site proxy) and proxies trained with other sites’ data (the site excluded proxy) were developed. The performance of these proxies was evaluated using a modified version of K-fold cross-validation, which allowed estimating the effect of dataset selection on the results. Additionally, time series, seasonal variation, and parameter distributions for developed proxies were analysed and findings compared against known characteristics of the sites. Global proxy was developed, but no single set of parameters, that would achieve the best performance at all sites, was found. Therefore, two versions of global proxy were selected and their results analysed. For most of the sites, the site proxy performed better than the global proxies. Additionally, based on the analysis from the site excluded proxy, extrapolating the global proxy to new locations produced results with varying accuracy. Best results came from sites with low concentrations and occasional anthropogenic transport episodes. Additionally, some European rural sites performed well, whereas in mountainous sites the proxy struggled. Comparing the proxy to literature, it performed generally less well or similarly as proxies from other studies. Longer datasets and additional measurement sites could improve the proxy performance.
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(2024)Fog has a significant impact on society, by making transportation and aviation industries difficult to operate as planned due to reduced visibility. Studies have estimated that 32 % of marine accidents, worldwide, and 40 %, in the Atlantic Ocean, took place during dense sea fog. Therefore forecasting fog accurately, and allowing society to function, would help mitigate financial losses associated with possible accidents and delays. However, forecasting the complex fog with numerical weather prediction (NWP) models remains difficult for the modelling community. A NWP model typically operates in the resolution of kilometres, when the multiple processes associated with fog (turbulence, cloud droplet microphysics, thermal inversion) have a smaller spatial scale than that. Consequently, some processes need to be simplified and parametrised, increasing the uncertainty, or more computational power is needed to be allocated for them. One of these NWP models is HARMONIE-AROME, which the Finnish Meteorological Institute develops in collaboration with its European colleague institutes. To improve the associated accuracy, a brand new, more complex and expensive, option for processing aerosols in HARMONIE-AROME, is presented. This near-real-time (NRT) aerosol option integrates aerosol concentrations from Copernicus Atmospheric Monitoring Services' NRT forecast into HARMONIE-AROME. The statistical performance of the model's sea fog forecast in the Baltic Sea was studied in a case study using marine observations. The quantitative metric, proportion score, was studied. As a result, a forecast using the NRT option showed a slight deterioration in visibility (0.52 versus 0.59), a neutral improvement in cloud base height (0.52 versus 0.51), and a slight deterioration in 2-meter relative humidity (0.73 versus 0.76) forecasts with respect to the reference option. Furthermore, the score in general remained weak against observations in the case of visibility and cloud base height. In addition, based on qualitative analysis, the spatial coverage of the forecasted sea fog in both experiments was similar to the one observed by the NWCSAF Cloud Type-product. In total, the new aerosol option showed neutral or slightly worse model predictability. However, no strong conclusions should be made from this single experiment sample and more evaluations should be carried out.
Now showing items 1-3 of 3