Does dust pollution play a role in creating aerosols?

Atmospheric aerosols originating from both natural and anthropogenic sources play a crucial role in various natural processes, affecting climate, ecosystems, and air quality on a global scale. These particles have the potential to profoundly influence our entire planet by both directly and indirectly interacting with the Earth’s radiation budget. Aerosols directly modify the planetary radiation budget by scattering and absorption of long- and shortwave radiation. Depending on their size and chemical composition, aerosols can act as cloud-condensation nuclei (CCN) and ice nuclei (IN) and impact cloud microphysical processes, which indirectly influence the global energy budget. The aerosol−cloud−radiation interaction also modifies precipitation processes, the hydrological cycle, and climate [1]. Aerosols originate from various sources and have significant impacts on climate, health, and the environment, thereby impacting human well-being. The inhalation of aerosols, particularly fine particulate matter (PM2.5), can lead to various adverse health effects, including respiratory and cardiovascular diseases, cancer, and premature death [2]. Consequently, it is essential to thoroughly investigate the physical properties of aerosols. Satellite-based remote sensing, alongside ground-based observations, plays a pivotal role in monitoring aerosol optical properties, improving our understanding of atmospheric processes. This comprehensive monitoring provides critical information on environmental pollution and helps in the analysis of the effects of aerosols and clouds on radiative fluxes [3]. Both spaceborne and ground-based observations offer a comprehensive assessment of long-term spatial, temporal, and seasonal variations in aerosol optical properties. For the investigation of atmospheric aerosol properties, satellite data have advantages and disadvantages compared to ground-based observations. Satellite data provide a global perspective with extensive coverage of aerosol distributions, while ground-based platforms have relatively small spatial coverage but deliver high temporal resolution. In contrast, space-borne observations have limited temporal resolution [4]. The necessity of verifying satellite data is underscored by the need to ensure accuracy and reliability in global aerosol observations for air-quality, environmental, and climate research. Global satellite observations of aerosol properties are invaluable for validating and refining model simulations across extensive spatial and temporal scales [5,6]. However, satellite data alone can have gaps and uncertainties. Integrating satellite observations with ground-based measurements helps to provide a more consistent and accurate picture of global aerosol distributions, ensuring that the satellite-derived data align well with the ground-based observations [5,6]. This verification process is crucial for constraining and validating the aerosol properties observed from space, ultimately leading to better climate models and environmental assessments.The significance of studies on air quality and mineral dust in the Levantine Region is highlighted by the influence of urbanization, increased industrial activities, climate change, and the region’s geographical proximity to deserts. The Eastern Mediterranean basin, including the Levantine Region, falls within the dust belt and is subjected to the presence of dust particles originating from two of the largest dust-source regions, namely the Sahara (North Africa) and the Middle East (the Arabian Peninsula and Syria), as reported by various studies [7,8]. Numerous investigations have focused on the air quality and dust composition in the region, highlighting the need for ongoing research and interventions to address the environmental and health impacts of aerosols. Those aerosol-monitoring studies have utilized space-borne observational platforms such as Advanced Very High Resolution Radiometer (AVHRR), Meteosat Visible and Infra-Red Imager (MVIRI) [9], Total Ozone Mapping Spectrometer (TOMS) [7,10,11], Moderate Resolution Imaging Spectroradiometer (MODIS) [11,12], and Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) [13]. The aerosol optical depth (AOD) data from MODIS have undergone comprehensive analysis and validation, as discussed in various studies [14,15]. These investigations focused on ensuring the accuracy and reliability of MODIS AOD data, particularly through comparisons with ground-based Aerosol Robotic Network (AERONET) measurements [7,16,17]. The validated MODIS AOD data have found extensive use in aerosol research, highlighting their significance in contributing to scientific studies in this field. While previous studies have often focused on shorter time frames or isolated periods over the Eastern Mediterranean, this study provides an extensive temporal analysis covering nearly two decades (2003–2023), offering a comprehensive view of aerosol trends and variations over time using the Seasonal−Trend decomposition using Loess (STL) method. This method allows for a detailed separation of seasonal patterns, trends, and irregular components. Although all the selected stations are located in the Levantine region, our detailed analysis will highlight the regional differences, providing a nuanced understanding of aerosol behaviors across different environments. Cloud-fraction analysis is incorporated to account for the impact of cloud cover on aerosol measurements, addressing potential biases and uncertainties in the data.Time-Series Analysis 3.4.1. Trend−Seasonality Analysis of MODIS STL was applied to examine the long-term trends, seasonal patterns, and residual variations in the MODIS data for four stations. The trend component captures the long-term trend in the dataset, removing short-term fluctuations. The seasonal component captures the repeating annual cycle within the dataset, representing changes that occur within a year. Figure A2 in Appendix A illustrates trend, seasonality and residue decompositions for four locations over the period from 2003 to 2023. The Mann−Kendall test and Sen’s slope estimator were applied. For the IMS-METU-ERDEMLI station, a statistically significant slight positive trend in AOD values can be observed, with a slope of approximately 0.0001. In contrast, no significant trends could be detected at the other stations, namely CUTTEPAK, Cairo_EMA_2, and SEDE_BOKER. The findings of Aslano˘glu et al. [13], using a 9-year CALIPSO-derived product (2007–2015), revealed the following station-specific trends: a slight positive trend at the IMS-METU-ERDEMLI, CUT-TEPAK, and Cairo_EMA_2 stations and a slight negative trend at the SEDE_BOKER station. The trend at Erdemli/Mersin (Figure A2a) shows a gradual change over time, with increases around 2005–2007 and 2017–2020 that are followed by decreases. AOD values rise from 2017 to 2020, reaching a maximum around 2019. The seasonal component shows clear monthly variations, with high AOD values during spring and summer, likely due to increased mineral-dust activities [49,50], and lower AOD values during winter. Between 2015 and 2017, peaks can be observed earlier in spring and late summer, with the spring peak starting to increase until 2018.The period between 2018 and 2020 shows peaks in AOD values, particularly around 2019, which is consistent with the trend of increased aerosol levels during these years. Starting from 2017, seasonal peaks can be observed during late spring and summer. Findings of seasonal pattern are consistent with the results from Kubilay et al. [10], which indicated that the northeastern Mediterranean receives significant dust particles from the Saharan desert in spring and from the central-eastern Sahara in summer. The region is affected by dust transported from Middle East—Arabian Peninsula in autumn.The study of Aldabash et al. [12] also concluded that AOD from MODIS observations peaks in the summer and reaches its lowest levels in the winter across the region. The increase in aerosol loadings over Turkey during the summer is due to the long-range transport of dust particles from the Middle East and North Africa. Tutsak and Koçak [49] suggested that the set of aerosol types was more diverse in spring compared to winter, summer, and fall. The trend−seasonality analysis for Cyprus over the same period shows increases in AOD values between 2006–2009, 2010–2012, 2014–2016, and 2020–2022, with peaks around 2008 (the highest peak), 2011–2012 2016, and 2022 (Figure A2b). The seasonal component of the STL reveals a clear annual cycle, with peaks in late spring and summer. Lower AOD values can be observed in winter. Between 2003 and 2006, higher AOD values can be observed in the spring aerosol season. Despite these fluctuations, our analysis, utilizing MODIS data spanning from 2003 to 2023, did not identify any statistically significant trend at the CUT-TEPAK station. In Cairo, from 2008 (a low point) to 2012 (peak), there is an increasing trend standing out in the analysis (Figure A2c). High AOD levels in 2006 might be attributed to the numerous fire events during the “black cloud” season [29]. Overall, the greatest value can be observed in 2012. After 2012, there is a decline in AOD values until 2019. High AOD values can be observed in late spring and summer (April to August), suggesting that seasonal dust transport is more active during these months [46]. Spring aerosol levels consistently higher than AOD values in summer. The lowest AOD value occured in winter (December to February), likely due to atmospheric cleansing by precipitation or reduced emissions. Moreover, between 2007 and 2015, two spring peaks can be observed, suggesting seasonal aerosol events during this period. Since 2019, spring peaks have been increasing while summer peaks have been declining, indicating a shift in seasonal aerosol dynamics.Analysis of Farahat et al. [46] with MODIS Aqua data from 2002 to 2014 revealed a positive trend, with a slope value of 0.001 per year. Findings of El-Metwally et al. [48] align with our results, with dust-like aerosols with high AOD and low AE values observed in spring, indicating the presence of mineral dust from the southwest region, specifically the Saharan desert. The maximum AOD value in April includes both a mineral-dust component and background aerosol. High AOD values in summer might be due to pollution-like aerosols (fine-mode aerosols). At the Sede-Boker station (Figure A2d), the trends indicate relatively stable AOD values from 2003 to 2006, and from 2015 to 2019. A period of increasing AOD values can be observed between 2007 and 2012, peaking around 2012. The lowest AOD values occurred around 2020.The dominance of spring peaks over summer peaks is noticeable from 2006 onward. Since 2017, spring maxima have remained steady, while summer peaks have been decreasing. From 2003 to 2012, spring peaks start to increase, with the highest AOD values observed in spring 2012, coinciding with the overall maxima. Consistent with other stations, lower aerosol concentrations can be observed in winter. From 2012 onwards, the winter minimum values started to increase, while the summer peaks increased from 2012 to 2018 and then decreased. Both Cairo and Sede Boker experienced peaks in AOD values around 2012, with those peaks followed by a decreasing trend in AOD values and a new peak around 2022. This indicates that these two stations, situated in the southern part of the Levantine region, may have been influenced by similar regional factors such as meteorological conditions, dust-transport mechanisms, and changes in local emission sources 3.4.2. Comparative Trend Analysis of MODIS and AERONET AOD Measurements MODIS and AERONET observations across all stations were compared to assess how well they capture general climatological patterns and trends in AOD using the STL method (Figure 13). In each station, quality-assured measurements start and end on different dates. For this reason, different time windows are presented for each station, but evaluations have also been carried out for the concurrent measurements. Over the period from 2004 to 2019 at the IMS-METU-ERDEMLI station (Figure 13a), both datasets capture major peaks and general trends, although AERONET tends to show higher AOD values. The trend between 2006 and 2011 closely matches, showing similar patterns during this period. The trend analysis reveals an AERONET peak in 2012; however, this peak is not reflected in the MODIS data. The highest value observed in the AERONET data is in 2014, whereas this peak is not the highest in the MODIS data. Moreover, the MODIS trend overestimates AOD values compared to the AERONET trend in 2019. Over the period from 2010 to 2023 at the CUT-TEPAK station (Figure 13b), MODIS data shows higher peaks and greater variability compared to the more subdued trends observed in AERONET data. On the other hands, at the Cairo_EMA_2 station over the same period (Figure 13c), the AERONET data includes higher peaks and more apparent fluctuations compared to the MODIS data. The maximum in 2013 is remarkably more pronounced than in the MODIS data. Over the period from 2003 to 2023 at the SEDE_BOKER station (Figure 13d), excluding the year 2020, MODIS AOD values are predominantly higher than AERONET values. Both the MODIS and the AERONET data show similar peaks and fluctuations, particularly around 2016–2023.