Browsing by master's degree program "Ilmakehätieteiden maisteriohjelma"

Atmospheric aerosol particles absorb and scatter solar radiation, directly altering the Earth’s radiation budget. These particles also have a complex role in weather and climate by changing cloud physical properties such as reflectivity by acting as cloud condensation nuclei or ice nuclei. Aerosol particles in the boundary layer are important because they pose a negative impact on air quality and human health. In addition, elevated aerosol from volcanic dust or desert dust present an imminent threat to aviation safety. To improve our understanding of the role of aerosol in influencing climate and the capability to detect volcanic ash, a ground-based network of Halo Doppler lidars at a wavelength of 1565 nm is used to collect data of atmospheric vertical profiles across Finland. By comparing the theoretical values of depolarization ratio of liquid clouds with the observed values, bleed through of each lidar is detected and corrected to improve data quality. The background noise levels of these lidars are also collected to assess their stability and durability. A robust classification algorithm is created to extract aerosol depolarization ratios from the data to calculate overall statistics. This study finds that bleed through is at 0.017 ± 0.0072 for the Uto-32 lidar and 0.0121 ± 0.0071 for the Uto-32XR lidar. By examining the time series of background noise level, these instruments are also found to be stable and durable. The results from the classification algorithm show that it successfully classified aerosol, cloud, and precipitation even on days with high turbulence. Depolarization ratios of aerosol across all the sites are extracted and their means are found to be at 0.055 ± 0.076 in Uto, 0.076 ± 0.090 in Hyytiala, 0.076 ± 0.071 in Vehmasmaki and 0.041 ± 0.089 in Sodankyla. These mean depolarization ratios are found to vary by season and location. They peak during summer, when pollen is abundant, but they remain at the lowest in the winter. As Sodankylä is located in the Artic, it has aerosols with lower depolarization ratio than other sites in most years. This study found that in summer, aerosol depolarization ratio is positively correlated with relative humidity and negatively correlated with height. No conclusion was drawn as to what processes play a more important role in these correlations. This study offers an overview of depolarization ratio for aerosol at a wavelength of 1565 nm, which is not commonly reported in literature. This opens a new possibility of using Doppler lidars for aerosol measurements to support air quality and the safety of aviation. Further research can be done test the capability of depolarization ratio at this wavelength to differentiate elevated aerosol such as dust, pollution, volcanic ash from boundary layer aerosol.

The Arctic is warming faster than any other region on Earth due to climate change. The characteristics of the air masses overlying the Arctic play a key role when assessing the magnitude and implications of global warming in the region, but comprehensive studies of Arctic air mass properties covering long time series of measurements are scarce. The aim of this study is to use such a data set to quantify the key characteristics of Arctic air masses prior to transport to the human-habited Eurasian continent, and the typical conditions leading to Arctic events in Värriö. HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model was employed to calculate backward atmospheric trajectories arriving at SMEAR I (Station for Measuring Ecosystem-Atmosphere Relations) in Värriö for every hour in 1998-2017. An air mass was classified as Arctic if the backward trajectory arriving at Värriö was located north of 78 °N 72 hours before the arrival time. Data from SMEAR I, including meteorological variables and trace gas and aerosol concentrations, were then gathered in order to compare Arctic and non-Arctic air masses. Of all the hours that were analysed, 15.0 % were classified as associated with an Arctic air mass. The typically cyclonic curvature of the trajectories and the median duration of 10 hours per individual Arctic event were hypothesised to be due to Arctic air mass events being linked to passing low pressure systems. Arctic air masses were found to be colder and have lower moisture content in summer, when the difference at surface level was 5.6 °C and 1.7 g m-3 respectively, compared to non-Arctic air masses. In other seasons the differences were less pronounced, but average particle and trace gas concentrations were found to be notably lower for Arctic air masses than for non-Arctic air masses. An exception to this was ozone, which had 24.6 % higher average concentration in Arctic air masses in months between November and February, compared to non-Arctic air masses. The annual median aerosol particle concentration in Arctic air masses was found to be 308 cm-3 and only 129 cm-3 between November and March, on average. During a median year, the value of condensation sink (CS) was on average 65 % smaller in Arctic air masses than in the non-Arctic. The Kola Peninsula industry was observed to increase concentrations of SO2 and aerosol particles, particularly Aitken mode (25-90 nm) particles, of affected air masses. Overall, Arctic air masses were found to have several unique characteristics compared to other air masses arriving at SMEAR I, Värriö. As expected, Arctic air masses are colder and drier than non-Arctic air masses, but the difference is pronounced only in summer months. Other air mass characteristics, especially aerosol particle and trace gas concentration were generally found to be lower, unless the air mass was influenced by the industrial sites in the Kola Peninsula.

Biogenic Volatile Organic Compounds play a major role in the atmosphere by acting as precursors in the formation of secondary organic aerosols and by also affecting the concentration of ozone. The chemical diversity of BVOCs is vast but global emissions are dominated by isoprene and monoterpenes. The emissions of BVOCs from plants are affected by environmental parameters with temperature and light having significant impacts on the emissions. The Downy birch and Norway spruce trees consist of heavy and low volatile compounds but published results are limited up to observing sesquiterpenoid emissions from these two trees. In this study, the Vocus proton-transfer-reaction time-of-flight mass spectrometer is deployed in the field to examine BVOC emissions from Downy birch and Norway spruce trees. With higher mass resolution, shorter time response and lower limits of detection than conventional PTR instruments, the Vocus can effectively measure a broader range of VOCs. For the first time, real-time emissions of diterpenes and 12 different oxygenated compounds were observed from birch and spruce trees. The emission spectrum of birch was dominated by C10H17+, while for spruce C5H9+ contributed the most. The sum emissions of oxygenated compounds contributed significantly to the observed total emissions from both the trees. The emission rates of all compounds varied dramatically throughout the period due to fluctuations in temperature and light. Due to lack of data from spruce, conclusive results for temperature and light response on terpene emissions could not be drawn. For birch, the emission rates were well explained by the temperature and temperature-light algorithms. The terpene emissions modelled using both algorithms correlated similarly with experimental data making it difficult to decisively conclude if the emissions originated from synthesis or pools.

International shipping is globally a major source of atmospheric nitrogen oxides (NOx). It has been widely recognized that these emissions have negative effects on maritime air quality and human health. For a long time, shipping was the least regulated NOx emission source, but now first regulations for ship exhaust NOx emissions started as of January 2021. Shipping emissions must be monitored so the obedience of these regulations can be followed. Different measurement techniques are developed to address the problems related to shipping emission monitoring. The purpose of this thesis is to demonstrate how tropospheric nitrogen dioxide (NO2) concentration measurements by TROPOspheric Monitoring Instrument (TROPOMI) onboard Copernicus Sentinel 5 Precursor (S5P) satellite can be used to characterize signatures of shipping emissions. The capability of TROPOMI to detect busy shipping lanes and port areas was first tested with a large study area of the whole Eastern Mediterranean Sea. Analysis was supported with shipping emission data inventory from the Ship Traffic Assessment Model (STEAM). Results showed elevated NO2 concentrations close to major port areas, especially if the dominant wind direction on the water area was from the continent. These elevated concentrations were most likely a result of both transported urban emissions and shipping emissions. STEAM and TROPOMI grid cell comparison was done over the busiest shipping lane area over the open sea, and the results showed that if the monthly summed shipping emission amount was either small or very large, the signal of shipping emissions was affected by background concentrations. More detailed shipping emission study was done at port Piraeus and the surrounding sea area. There, satellite measurement analysis was done by selecting three smaller study areas for comparison, one over the city of Athens, the second one close to the port Piraeus and the third one over the open sea. Relation between the satellite observations of NO2 and modelled shipping emissions of NOx was obtained in the study area that was over the open sea, the center of the area being 35 km from the coast. The signal of shipping emissions was not detected close to the port, most likely because of the influence of other emission sources. Lastly, spring and summer 2020 were analysed separately in more detail, as they were included in the overall study period of this thesis but the air pollution patterns at that time were affected by the extraordinary COVID-19 pandemic restrictions. The results showed unusually small average NO2 concentrations over the city of Athens during spring 2020. Meteorological observations from that time period did not show anything that could fully explain the decrease. Observations over the sea close to Piraeus showed no clear difference between 2019 and 2020 average concentrations, so the pandemic possibly had only a minor impact on the shipping emissions in the port area.

In atmospheric sciences, measurements provided by remote-sensing instruments are crucial in observing the state of atmosphere. The associated uncertainties are important in nearly all data analyses. Random uncertainties reported by satellite instruments are typically estimated by inversion algorithms (ex-ante). They can be incomplete due to simplified or incomplete modelling of atmospheric processes used in the retrievals, and thus validating random uncertainties is important. However, such validation of uncertainties (or their estimates from statistical analysis afterwards, i.e. ex-post) is not a trivial task, because atmospheric measurements are obtained from the ever-changing atmosphere. This Thesis aims to explore the structure function method – an important approach in spatial statistics – and apply it to total ozone column measurements provided by the nadir-viewing satellite instrument TROPOMI. This method allows us to simultaneously perform validation of reported ex-ante random uncertainties and to explore of local-scale natural variability of atmospheric parameters. Two-dimensional structure functions of total ozone column have been evaluated based on spatial separations in latitudinal and longitudinal directions over selected months and latitude bands. Our results have indicated that the ex-post random uncertainties estimated agree considerably well with the reported ex-ante random uncertainties, which are within 1-2 DU. Discrepancies between them are very small in general. The morphology of ozone natural variability has also been illustrated: ozone variability is minimal in the tropics throughout the year, whereas in middle latitudes and polar regions they attain maxima in local spring and winter. In every scenario, the ozone structure functions are anisotropic with a stronger variability in the latitudinal direction, except at specific seasons in polar regions where isotropic behaviour is observed. Our analysis has demonstrated that the structure function method is a remarkable and promising tool for validating random uncertainties and exploring natural variability. It has a high potential for applications in other remote sensing measurements and atmospheric model data.

Gulf of Bothnia was simulated with NEMO sea model and LIM3 sea ice model. The results were used to count ice area, ice thickness, ice season length and the dates for freezing ang thawing. Results contained years from 1975 to 2059 but only years from 2006 were mostly used. Before 2006 the model was forced with a statistical history run. It was compared to thickness observations and the ice model was considered reliable enough. Atmospheric forcings became from three earth system models and two emission scenarios. With smaller emissions results about ice conditions and its trends vary between model runs with different focings a lot more than with higher emissions. In many case a propability distribution was used on results unlike on earlier similar researches which have mostly used only medians of ice parameters. Propability distribution for ice area was made using cumulative Gumbel probability distribution which enabled counting time periods longer than the time series. It also increased the reliability of extreme results. According to the results the northen part of the Bay of Bothnia freezes in every winter at 2050s. Ice thickness is 80cm at the most and median is 50cm. In almost every result southern part of the Bothnian Sea has over 50% chance for ice to occur and the median of thickness is more than 10cm. Length of the ice season close to 2050s can exeed 150 days often at the northen Bay of Bothnia but elsewhere it is closer to 100 days and varies a lot. The counted propability distributions for ice area let us suspect that a part of the Bay of Bothnia would remain unfreezed at least once every 30 years or more propably every 20 years in years from 2006 to 2059. In contradiction, not much can be said about large areas, because results vary a lot about wheter the whole Gulf of Bothnia can be expected to freeze close to 2050s.

Mixing processes under a seasonal ice cover in boreal lakes have received little attention from the physical limnological community. Even though the water is calm under the ice cover, many different phenomena are still able to cause mixing in the water column, which in turn affects the gas fluxes as well as physical and chemical properties of the water. Lakes in the boreal zone are very numerous. Understanding their behaviour helps us predict the effects of climate change in the boreal zone. In my thesis I present the various mechanisms that reign under the ice cover, and attempt to see these mechanisms in action in lake Kuivajärvi. Emphasis was placed on internal waves and the various components of the energy balance that can induce mixing. Data was collected with thermistor chains and a measurement raft between 24.1. – 3.5.2017. Two types of internal waves were observed during the ice-on season of 2016 – 2017. Short period barotropic seiches were observed during the whole ice-on season and transient long period baroclinic seiches were observed on two occasions. Other mixing processes seen in the lake were sediment heating in the dead of winter, penetrative convection caused by short wave radiation in the spring and diurnal stratification and mixing during spring caused by the daily heating and nightly cooling. Some mixing under the ice cover was found to depend on the meteorological conditions prevailing over the lake during the previous summer and just before the ice-on in late autumn, while others were more predictable. Long period internal waves and sediment heating are set in motion by meteorological conditions, while the spring mixing and overturn are more stable, due them being more a function of the orbital mechanics of our planet than the prevailing weather. Varying surface conditions of the lake ice cover make the measurement of especially the surface temperature complicated. Snow and ice are under a continuous metamorphosis due to the weather. This makes surface emissivity difficult to estimate, causing significant errors in the measurement of the outgoing longwave radiation. This in turn causes problems in defining the surface temperature from it. Also, the precipitation heat flux is difficult to estimate due to the lack of knowledge on the surface temperature.

Ocean reanalysis products (ORAs) can provide information on the state of the ocean. Although the different data sources, model configurations, forcing choices and assimilation methods cause the ORAs to deviate from each other, the ensemble approach has been previously found to produce realistic mean states. This raises the question if ORAs could be used for studying temporal and spatial changes in the Arctic Ocean, where measurements are generally sparse. Such study has not been previously published. In this thesis, the changes in the hydrography of the Arctic Ocean are examined over the previous decades based on selected ORAs. Eleven ORAs, TOPAZ4, C-GLORS025v5, ECDA3, GECCO2, GLORYS2v4, GloSea5-GO5, MOVE-G2i, ORAP5, SODA3.3.1, UR025.4 and ORAS5, were chosen for this study due to their overlap over 1993–2010 and the multimodel ensemble (MMM) was formulated based on the products, excluding ECDA3. The data were divided into depth layers and layer-average salinities and temperatures were used to calculate basin-average anomaly time series and trends to study the observed temporal changes. Per-grid trends were also produced to study both spatial and temporal changes in more detail. To assess their reliability, trends from the MMM and individual ORAs were compared to an observational product, EN4.2.0.g10 and the variability in the products and the MMM was assessed using statistical measures. The Eurasian Basin was found to be warming across all layers (up to 0.3 ◦ C decade −1 ) accompanied by salinification, except for localised cooling in the top 100 meters in the western basin, near the Fram Strait (-0.2 ◦ C decade −1 ). This indicates additional heat uptake by the surface 0–100 meters and also increasing heat and salinity content of the AW inflow, while the transport of sea ice out of the AO has increased. The Amerasian Basin, on the other hand, showed a strong freshening trend culminating at the Beaufort Gyre. This is most likely due to the anticyclonic wind forcing and increasing freshwater inflow to the Beaufort Sea. The Amerasian Basin also showed a warming trend in the 300–700 m layers but a cooling trend in the 100–300 m layer north of the Chukchi Sea. The ensemble approach worked well in dampening the extremities of singular ORAs, but some trends observed in the literature were missed due to disagreements between ORAs, especially in the Fram Strait and Beaufort Sea, which suggest that further improvements in both models and measurements are needed in those areas. Furthermore, improvements in deep ocean observations, how models handle the deeper ocean and assimilation methods are needed in order to study trends in the deeper depths in the AO. All in all, as the improvements come, the ORA MMM shows great potential for studies in the AO.

The impacts of dust aerosols on human health and climate change are increasing as the particulate matter (PM) mass concentrations and frequency of Sand and Dust Storm (SDS) episodes have shown an increasing trend in recent studies, especially for the Middle East and North Africa (MENA). In this thesis, particulate matter (PM10 and PM2.5) concentrations were measured during May 2018–March 2019 in the urban atmosphere of Amman, Jordan. The PM sampling was 24-hours every 6 days. The overall mean PM10 mass concentration was 64±39 μg/m3 with the median (+interquartile range) value of 49.2+53.5 μg/m3, the PM2.5 mass concentration varied between 15 μg/m3 and 190 μg/m3 with an annual average 47±32 μg/m3 and with the median (+interquartile range) value of 35.8+26.3 μg/m3. The PM2.5 / PM10 ratio was 0.8±0.2. According to the Jordanian Air Quality standards, the annual mean PM10 needs to be below a limit value of 120 μg/m3, which was true in this work. However, the PM2.5 mass concentration was three times higher the corresponding limit value (65 μg/m3). However, both exceeded the World Health Organization (WHO) air quality annual guideline of 20 μg/m3 for PM10 and 10 μg/m3 for PM2.5. The results show that the observed PM10 mass concentrations in Jordan were lower than what was reported in other cities in the Middle East but were higher when compared to other Mediterranean cities. During the measurement period, Jordan was affected by Sand and Dust Storms (SDS), which were observed on 14 sampling days. The source origins of these SDS were traced back to North Africa, the Arabian Peninsula, and the Levant. The 24-hour PM10 concentrations during these SDS episodes ranged between 108.1 μg/m3 and 187.3 μg/m3. In the future, measurements with a higher time resolution (one sample per day) are recommended for a more precise seasonal trend interpretation.

Sand and dust storms are one of the major regional environmental problems that affect human health. Many environmental studies have focused on airborne dust concentrations observed at different regions and have tried to connect the observations to specific dust source regions. This thesis aims to provide a new dust classifications scheme for the Eastern Mediterranean region, specifically observed in Amman, Jordan. I utilized a combination of a long-term data-base consisting of aerosol particle number concentration in coarse mode (1–10 µm) during November 2013 – July 2018 and air mass back trajectories analysis to visually identify the Sand and Dust Storm (SDS) episodes. The classification included three main source regions of for the submicron dust, namely Sahara, Arabia, and Levant. I also classified the data according to the, episode intensity according to their corresponding number concentrations as no-dust, mild, intermediate, and strong intensities and further classified the range of back trajectories as short, intermediate, long, and very long, which indicates the distance between the observation site and the source region.. The results showed that majority of the dust events and an elevated number of dust days are influenced by a source in Levant and Sahara source region. These events which dominated during 70 days in 2016. The Levant source governed during 60 days during the same period. Other dust sources contributed less to the dusty days, and the lowest dusty days number was due to emissions from Levant & Arabia (19 days). The episode intensity varied censurably and underlined variability from the different source areas. The maximum intensity in the dust episode concentration was linked to Levant & Sahara with a max number concentration of 95 /cm3. The classification method was successful and it was able to establish a dust source database in the Eastern Mediterranean region based on the long-term observations performed in Amman with variable dust concentration and dust periods in different seasons and different meteorological circumstances.