https://www.um.edu.mt/library/oar/handle/123456789/94048 Sat, 04 Apr 2026 20:36:40 GMT 2026-04-04T20:36:40Z https://www.um.edu.mt/library/oar/handle/123456789/102762 Title: An investigation of the Saharan episodes predicted by the CAMS ensemble model Abstract: Air pollution caused by air particles is a global issue that has gotten a lot of attention because of the possible consequences for the environment and human health. Sources of particulate matter can be both natural and anthropogenic. A pollution source may only be called "natural" if it has not been polluted by human intervention. Anthropogenic particles, on the other hand, are created by human activities such as the use of fossil fuels in automobiles, power plants, home heating, and industrial operations. Arid-zone dust contributes greatly to global atmospheric aerosols. North Africa (Sahara and Sahel) is the most significant source, accounting for more than half of all worldwide dust emissions. Saharan dust mostly affects Mediterranean nations. It was calculated that in 2012–2013, it supplied over 20% (3.7 μg/m3) of the PM10 at a rural background site in Malta. The Environment and Resources Authority (ERA) of Malta is required to monitor air quality in compliance with EN 12341:2014. The Ambient Air Quality Directive (AAQD) specifies two PM10 limit levels. A daily restriction of 50 μg/m3 that cannot be exceeded more than 35 times per year, and an annual limit of 40 μg/m3. ERA is obligated by the European Commission to provide its measured data. In their Justification reports, EU Member States are expected to mention the days affected by Saharan dust. Satellite images, forecasts, and trajectories are used to do this. The CAMS Ensemble Model, however, is underutilised and understudied in the Maltese region. CAMS provides information on pollution concentrations caused by long-distance travel. It also offers free air quality dispersion forecasting for the whole European continent. As a result, if CAMS ensemble forecasting is used in Malta, it may result in more detailed forecasts. CAMS regional ensemble forecasting might potentially be used to forecast the Health Risk Index (HRI) and short-term air quality. The forecast will be used in the execution of such public accuracy since it is validated on a regular basis for the whole European region. Hence, the CAMS Ensemble Model can be a valuable tool for the ERA's verification process in identifying Saharan dust occurrences. The primary aim of this work was to validate the CAMS ensemble model. This was achieved by doing statistical testing using the Spearman correlation test with in-situ data (ERA ground data). In which any improvements or poor model performance were remarked. Moreover, the secondary aim of this dissertation was to compare forecasting data, in-situ measurements, and ground-based observations. This was achieved by doing a descriptive analysis using the Anaconda software (python tool). In which any trends of PM10/aerosol data derived from the CAMS ensemble model (forecasting data), with MODIS satellite data (in-situ measurements), and with Environment and Resources Authority (ERA) data (ground-based observations) were noted. The primary aim showed that the CAMS Ensemble model gave generally accurate data when compared to in-situ data, with a performance accuracy of 80.3%. The only time there was no relationship between CAMS and ground data (ERA) was in 2018, when the sample size was small to analyse. As a result, this demonstrates that the CAMS Ensemble Model is a reliable tool for Saharan dust forecasting and verification procedures. The secondary aim of this study showed that ground data is the most accurate data source for comparing predicted and observed data in Saharan dust forecasts. Furthermore, due to a lack of AOD data, MODIS satellite data proved to be the least trustworthy in-situ measurement to use in this analysis. However, as demonstrated in the daily/seasonal analysis section, the MODIS combined AOD algorithm outperformed the MODIS DB AOD algorithm and some dates of the ERA`s justification report results. Description: M.Sc.(Melit.) Sat, 01 Jan 2022 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/102762 2022-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/102761 Title: Saharan dust contributions to atmospheric aerosols in Malta Abstract: Particulate matter has a significant association to critical human health risks. European countries are well known to experience several episodes originating from Saharan dust episodes throughout the year that pose a risk to human health as well as lead to natural exceedances for the PM10 Daily Limit Value (DLV) of 50 µg/m3. As a result of this, Member States have been given the possibility to deduct contribution of natural sources from the measured PM10 values. This European Commission (2011) has established guidelines that Member States are expected to comply with for the deduction to be possible. By consulting the data compiled by the Maltese entity, the Environment and Resources Authority (ERA), it was possible to analyse the Saharan dust contribution from 2016 to 2020. The three stations that measure PM10 which were used for this study were Għarb, Gozo (rural background site), Msida, Malta (traffic site) and Żejtun, Malta (urban background site). Quantification of Saharan dust contribution from these three stations helped in analysing the spatial consistency across the Maltese islands. A combination of methods was put together for this research to be possible including the use of regimes, backward trajectories using HYSPLIT, and dust forecast models to help identify the dates that experienced Saharan dust episodes across the Maltese islands. Apart from the pairwise comparison between Għarb and Msida in 2019, overall, the Saharan dust contribution can be considered as very close to being identical with no statistical difference between the three stations across Malta. The results help address the limited information about this phenomenon and the importance of more awareness about the Saharan dust implications to human health. Description: M.Sc.(Melit.) Sat, 01 Jan 2022 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/102761 2022-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/102760 Title: Assessing the degree of consensus regarding key stakeholders’ interests to repurpose abandoned lands south of Ġnejna Bay, Mgarr Abstract: The phenomenon of Agricultural Land Abandonment (ALA) is defined as the cessation of agricultural activities as well as land management in agricultural lands. ALA has been occurring since the 1950s at a global scale, in which rural areas are affected the most by both social and environmental impacts. Moreover, this phenomenon is currently highly relevant within the European context, given the presence of EU agricultural lands being at high potential risk of abandonment. The fate of land abandonment is not easily resolved, seeing that various nuances need to be considered, that is, the local circumstances of a particular site, such as the pre-existing state of a land coupled with physical and social factors that actively condition the state of a land. In light of these issues, this study’s aim is to explore the variety of perspectives of key stakeholder figures that possess either interest and/or legislative influence regarding agricultural land abandonment repurposing in the Maltese Islands with special consideration of this project’s study site located in Ġnejna Bay, Mġarr. A stakeholder analysis was conducted in order to classify key actors according to their level of influence and interest in repurposing abandoned farmlands. Along with the stakeholder analysis, semi-structured interviews were carried out for the individual stakeholders in order to further explore the following themes from the obtained responses: level of interest, level of impact/influence, landscape components that are prioritised by the stakeholder and the willingness to commit to potential future projects to repurpose the land. The results of this study indicate that there is a general supportive sentiment by stakeholders towards the repurposing of the site featured in this project, either in order to preserve the Maltese countryside or to resume its original purpose, i.e. agricultural activities. However, several identified variables hinder repurposing plans to take place including: ownership status and inheritance laws, land fragmentation and values as well as perceptions held by groups regarding ALA and impacts deriving from it. Description: M.Sc.(Melit.) Sat, 01 Jan 2022 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/102760 2022-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/102759 Title: Investigation of accumulation zones in bays along the northern Maltese coastline Abstract: One of the most important, rapidly expanding, and deteriorating global environmental issues is marine litter. While many studies have been conducted on the accumulation and dispersion mechanisms of surface marine litter, studies which assess the accumulation zones of benthic marine litter are still lacking, especially in the Maltese islands. This study attempts to investigate if a relationship between bathymetry and benthic litter accumulations exists. Google Earth Engine was used to obtain the pseudo Satellite Derived Bathymetries (pSDB) for 10 scenes using a Blue:Green band ratio and a Blue:Red band ratio. Each scene was then modelled using two modelling techniques: Linear Regression model and Random Forest model and the results were then compared with in-situ LIDAR data to identify which combination of month, band ratio and modelling technique achieved the lowest Mean Average Error (MAE). The scene from July 2020 using the Blue:Green band ratio with the Random Forest modelling technique proved to be the most accurate and was utilised as a basis to interpolate SDB at each bay. Litter data from a previous study was then projected over the SDB interpolations, and the sample points of the litter data were compared to the bathymetry of the bay. Scatter plots comparing litter count with depth of the studied bays revealed that shallower depths had little to no litter counts, but once the 2-metre depth is exceeded, litter count substantially increases. Several visual instances also showed similar occurrences, with small amounts of litter in shallow depth and larger amounts of litter in deeper depths. However, when a Spearman’s Rank correlation was applied to the two variables, no statistical relationship could be identified. Description: M.Sc.(Melit.) Sat, 01 Jan 2022 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/102759 2022-01-01T00:00:00Z