Spatial and Temporal Variation of the Extreme Saharan Dust Event over Turkey in March 2016

Elevating hourly PM2.5 forecasting in Istanbul, Türkiye: Leveraging ERA5 reanalysis and genetic algorithms in a comparative machine learning model analysis

Rapid urbanization and industrialization have intensified air pollution, posing severe health risks and necessitating accurate PM2.5 predictions for effective urban air quality management. This study distinguishes itself by utilizing high-resolution ERA5 reanalysis data for a grid-based spatial analysis of Istanbul, Türkiye, a densely populated city with diverse pollutant sources. It assesses the predictive accuracy of advanced machine learning (ML) models-Multiple Linear Regression (MLR), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting (LGB), Random Forest (RF), and Nonlinear Autoregressive with Exogenous Inputs (NARX). Notably, it introduces genetic algorithm optimization for the NARX model to enhance its performance. The models were trained on hourly PM2.5 concentrations from twenty monitoring stations across 2020-2021. Istanbul was divided into seven regions based on ERA5 grid distributions to examine PM2.5 spatial variability. Seventeen input variables from ERA5, including meteorological, land cover, and vegetation parameters, were analyzed using the Neighborhood Component Analysis (NCA) method to identify the most predictive variables. Comparative analysis showed that while all models provided valuable insights (RF > LGB > XGB > MLR), the NARX model outperformed them, particularly with the complex dataset used. The NARX model achieved a high R-value (0.89), low RMSE (5.24 μg/m³), and low MAE (2.94 μg/m³). It performed best in autumn and winter, with the highest accuracy in Region-1 (R-value 0.94) and the lowest in Region-5 (R-value 0.75). This study's success in a complex urban setting with limited monitoring underscores the robustness of the NARX model and the methodology's potential for global application in similar urban contexts. By addressing temporal and spatial variability in air quality predictions, this research sets a new benchmark and highlights the importance of advanced data analysis techniques for developing targeted pollution control strategies and public health policies.

The role of large-scale atmospheric circulations on long-term variations of PM10 concentrations over Turkey

PM10 is widely identified as an important atmospheric pollutant posing a serious threat to human health and environment as well as it influences the climate system. To unearth the mechanism involved in its sources and circulation behavior in environment, this study focuses on the role of large-scale atmospheric circulation on the long-term variability of PM10 over Turkey by applying rotated empirical orthogonal functions (REOF) analysis. As a result of the implementation of REOF to the daily PM10 data for 80 air quality stations throughout the period 2010-2020, first REOF mode (REOF1 44.9% in winter, 43.2% in spring, 39.5% in summer and 31.6% in fall) for all the four seasons indicated the role of local emission sources on the variations of PM10, which show high PM10 values in different geographical regions. The results of the second mode (REOF2, 17.9% in winter, 14.0% in spring, 14.0% in summer and 16.3% in fall) indicate the role of large-scale atmospheric circulations on the values of PM10. From the REOF2 analysis and extracted synoptic composite maps, the strength of southerly winds and the presence of southwesterly winds at low levels are very important in transporting of dust pollutants from the Arabian Peninsula and Northern Africa, respectively, to the eastern (EAR) and southeastern (SEAR) regions of Turkey during winter. In spring, sand particles in the interior terrestrial part of the country are carried to the northern regions by the effect of large-scale southerly winds, which cause above-normal PM10 concentrations in the Black Sea region of Turkey. In summer, dust particles together with warm dry air intrusion to the eastern region of Turkey by strong easterly winds are sourced by Caspian Sea and result in high PM10 values. Our findings emphasize that the long-term variations in air quality over Turkey are affected secondary by the variations in the large-scale atmospheric circulations with primary contributions from the changes in local emission sources.

Impact of desert dust storms, PM10 levels and daily temperature on mortality and emergency department visits due to stroke

Objective

It is known that the inhalation of air pollutants adversely affects human health. These air pollutants originated from natural sources such as desert storms or human activities including traffic, power generating, domestic heating, etc. This study aimed to investigate the impacts of desert dust storms, particulate matter ≤10 μm (PM10) and daily maximum temperature (MT) on mortality and emergency department (ED) visits due to stroke in the city of Gaziantep, Southeast Turkey.

Method

The data on mortality and ED visits due to stroke were retrospectively recruited from January 1, 2009, to March 31, 2014, in Gaziantep City Centre.

Results

PM10 levels did not affect ED visits or mortality due to stroke; however, MT increased both ED visits [adjusted odds ratio (OR) = 1.002, 95% confidence interval (CI) = 1.001-1.003] and mortality (OR = 1.006, 95% CI = 0.997-1.014) due to stroke in women. The presence of desert storms increased ED visits due to stroke in the total population (OR = 1.219, 95% CI = 1.199-1.240), and all subgroups. It was observed that desert dust storms did not have an increasing effect on mortality.

Conclusion

Our findings suggest that MT and desert dust storms can induce morbidity and mortality due to stroke.

An analysis of atmospheric stability indices and parameters under air pollution conditions

The stability of the atmosphere plays an important role in changes in air pollutant concentrations. Stable atmospheric conditions cause pollutant concentrations to reach high values, which degrades the air quality in a particular region. This study aims to reveal the relationship between atmospheric stability indices/parameters (thermodynamic indices) and changes in air pollutant concentrations. Pollutant concentrations of PM10, PM2.5, SO2, NO2, CO, and O3 were statistically analyzed for a 10-year (2013-2022) period for nine air quality stations located in the megacity Istanbul. Based on national and international air quality standards, 145 episode days were determined for the days when these parameters exceeded the threshold values. Five stability indices (Showalter Index - SI, Lifted Index - LI, Severe Weather Index - SWEAT, K Index - KI, Totals Totals Index - TTI), and three stability parameters (Convective Available Potential Energy - CAPE, Convective Inhibition - CIN, Bulk Richardson Number - BRN) were used to determine the stability of the atmosphere for episode days. It has been found that in cases where air pollutant concentrations are high, the stability parameters reveal the stability of the atmosphere better than the stability indices. It was also found that there was at least one vertical inversion layer on 122 of the 145 episode days, these layers mostly (84%) occurred between the surface and 850 hPa levels, and the layer thicknesses were mostly between 0-250 m (84%).

The effect of military conflict zone in the Middle East on atmospheric persistent organic pollutant contamination in its north

This study aimed to investigate long-range atmospheric transport of selected POPs released due to the effects of military conflicts in regions to the south of Turkey's borders. Ten locations were selected to deploy passive air samplers at varying distances to the border on a southeast-west transect of the country, proximity-grouped as close, middle, and far. Sampling campaign included winter and transition months when desert dust transport events occur. Hypothesis of the study was that a decreasing trend would be observed with increasing distance to the border. Group comparisons based on statistical testing showed that PBDE-183, Σ₄₅PCB, and dieldrin in winter; PBDE-28, PBDE-99, PBDE-154, p,p'-DDE, Σ₁₄PBDE, and Σ₂₅OCP in the transition period; and PBDE-28, PBDE-85, PBDE-99, PBDE-154, PBDE-190, PCB-52, Σ₄₅PCB, p,p'-DDE, and Σ₂₅OCP over the whole campaign had a decreasing trend on the transect. An analysis of concentration ratio to the background showed that long-range atmospheric transport impacted the study sites, especially those of close group in comparison to the local sources. Back-trajectory analyses indicated that there was transport from the conflict areas to sites in the close-proximity group, while farther sampling locations mostly received air masses from Europe, Russia, and former Soviet Union countries, followed by North Africa, rather than the military conflict areas. In consequence, decrease in concentrations with distance and its relation to molecular weight through proportions, diagnostic ratios, analysis of concentration ratio to the background, and back-trajectory analyses support the effect of transport from the military-conflict area to its north.

Air quality improvement and its relation to mobility during COVID-19 lockdown in Marmara Region, Turkey

The outbreak of the novel coronavirus SARS-CoV-2 (hereafter COVID-19) has changed the daily routines of people around the world. When the first case was confirmed on 11 March 2020 in Turkey, the number of cases reached 4500 per day by 10 April in Turkey. Afterwards, the government declared more restrictive lockdown measures for 31 metropolitan cities starting 10 April, and it was implemented for the following weekends, national, and religious holidays. The change in concentrations of PM₁₀, PM_2.5, and NO₂ during these measures with respect to the pre-lockdown period, the same period in the previous years and for different levels of measures for the cities in the Marmara Region of Turkey was investigated in this study. The daily mean concentrations of PM₁₀, PM_2.5, and NO₂ obtained from 11 stations operated by the Ministry of Environment and Urbanization and Google mobility data are used in this study. Average PM_2.5 and NO₂ concentrations during the lockdown period declined with respect to the pre-lockdown period and the previous year for all stations. Average PM₁₀ concentrations during the lockdown of 8 of 11 stations declined, while the rest of the stations increased with respect to the pre-lockdown period. In 9 of the 11 stations, the average concentration of PM₁₀ decreased compared to the previous four years. In 7 of the 11 stations, the number of days exceeding WHO limit for PM₁₀ was decreased during the lockdown period with respect to the pre-lockdown period. For PM_2.5, the number of days exceeding WHO limit was decreased during the lockdown period compared to the pre-lockdown period for all the stations. For NO₂, the number of days exceeding WHO limit was decreased during the lockdown period compared to the pre-lockdown period for 7 of the 8 stations. There is a significant relationship between mobility decrease and NO₂ concentrations in large cities. The correlation coefficients are generally lower in small cities in the study region.

Characterization of atmospheric mechanisms that cause the transport of Arabian dust particles to the southeastern region of Turkey

The Southeastern Anatolia Region (SEAR), the third-lowest mean annual precipitation region in Turkey, has semi-arid climate and plateau characteristics. The proximity of the region to North Africa and the Middle East dust source areas enables long-range transport of desert dust particles toward the SEAR by strong winds. Among the other dust source regions, the Arabian Peninsula has a crucial role in terms of affecting the SEAR with a high-annual frequency and high dust concentration values. We investigated the atmospheric patterns of three extreme Arabian dust episodes that affect the SEAR in this study. Dust episodes were determined using present weather (SYNOP) codes of ten stations in the SEAR during the 2014-2019 period. The source regions were found using HYSPLIT backward trajectory analysis. In this study, we benefited from synoptic maps, in situ PM₁₀ observations, numerical simulations of the WRF-Chem model, and MODIS satellite images to analyze the extreme dust episodes. The results showed that the surface low pressure over the Persian Gulf and strong southerly winds at the 700-hPa level enabled the transport of dust particles from the surface to the mid-atmospheric levels. If the center of the upper-level ridge extended from Saudi Arabia to southern Turkey, the atmospheric blocking mechanism prevented the dispersion of dense dust particles from the SEAR to its surrounding, which caused the observation of high dust concentrations in the SEAR. In general, the WRF-Chem model outputs are in good agreement with ground-based PM₁₀ concentrations and MODIS true-color images in terms of temporal and spatial distributions of dust concentrations.

The effects of desert dust storms, air pollution, and temperature on morbidity due to spontaneous abortions and toxemia of pregnancy: 5-year analysis

Epidemiological studies have suggested an association between particulate air pollution, increased temperatures, and morbidity related to pregnancy outcomes. However, the roles of desert dust storms and climatological factors have not been fully addressed. The objectives of the present study were to investigate the association between desert dust storms, particulate matter with a diameter ≤10 μm (PM₁₀), daily temperatures, and toxemia of pregnancy and spontaneous abortion in Gaziantep, South East Turkey. The study was conducted retrospectively at emergency department of two hospitals in Gaziantep city. Data from January 1, 2009, to March 31, 2014, were collected. Patients, who were diagnosed with toxemia of pregnancy and spontaneous abortion by radiological imaging modalities, were included in the study. Daily temperature ranges, mean temperature values, humidity, pressure, wind speed, daily PM10 levels, and records of dust storms were collected. A generalized additive regression model was designed to assess variable effects on toxemia of pregnancy and spontaneous abortion, while adjusting for possible confounding factors. Our findings demonstrated that presence of dust storms was positively associated with the toxemia of pregnancy both in outpatient admissions (OR=1.543 95% CI=1.186-2.009) and inpatient hospitalizations (OR=1.534; 95% CI=1.162-2.027). However, neither PM₁₀ nor maximum temperature showed a marked association with spontaneous abortion or toxemia of pregnancy in our study population. Our findings suggest that desert dust storms may have an impact on the risk for adverse pregnancy outcomes such as toxemia of pregnancy. Health authorities should take necessary measures to protect pregnant women against detrimental effects of these storms.

Impact of the COVID-19 outbreak on air pollution levels in East Asia

This study leverages satellite remote sensing to investigate the impact of the coronavirus outbreak and the resulting lockdown of public venues on air pollution levels in East Asia. We analyze data from the Sentinel-5P and the Himawari-8 satellites to examine concentrations of NO₂, HCHO, SO₂, and CO, and the aerosol optical depth (AOD) over the BTH, Wuhan, Seoul, and Tokyo regions in February 2019 and February 2020. Results show that most of the concentrations of pollutants are lower than those of February 2019. Compared to other pollutants, NO₂ experienced the most significant reductions by almost 54%, 83%, 33%, and 19% decrease in BTH, Wuhan, Seoul, and Tokyo, respectively. The greatest reductions in pollutants occurred in Wuhan, with a decrease of almost 83%, 11%, 71%, and 4% in the column densities of NO₂, HCHO, SO₂, and CO, respectively, and a decrease of about 62% in the AOD. Although NO₂, CO, and formaldehyde concentrations decreased in the Seoul and Tokyo metropolitan areas compared to the previous year, concentrations of SO₂ showed an increase in these two regions due to the effect of transport from polluted upwind regions. We also show that meteorological factors were not the main reason for the dramatic reductions of pollutants in the atmosphere. Moreover, an investigation of the HCHO/NO₂ ratio shows that in many regions of East China, particularly in Wuhan, ozone production in February 2020 is less NO_X saturated during the daytime than it was in February 2019. With large reductions in the concentrations of NO₂ during lockdown situations, we find that significant increases in surface ozone in East China from February 2019 to February 2020 are likely the result of less reaction of NO and O₃ caused by significantly reduced NO_X concentrations and less NO_X saturation in East China during the daytime.

The influence of meteorological conditions and atmospheric circulation types on PM10 levels in western Turkey

High levels of atmospheric pollutants have been frequently measured in Turkey during the last decade. Specifically, the occurrence of these high particulate matter concentrations is often related to either local-scale conditions or regional-scale transport. In order to better understand the atmospheric factors that trigger poor air quality, further research investigating the relationship between air pollution and meteorological variables or atmospheric circulation patterns is needed. In this study, the influence of synoptic-scale weather types on PM₁₀ levels over the Aegean region of Turkey is investigated for the period 2008-2015. First of all, hourly PM₁₀ concentrations of 13 air quality stations are respectively converted to daily, seasonal, and regional averages. The seasonal variability of PM₁₀ values in the region indicates that high particulate matter concentrations are registered in winter, fall, spring, and summer months with mean values at 90.6 (± 38.3 standard deviation), 66.9 (± 28.3), 61.6 (± 23.4), and 54.1 (± 12.8) μg m^-3, respectively. In regard to the synoptic-scale approach, eight directional and two vorticity types of the Lamb weather type (LWT) method are used in the analysis. Based on the results, poor air quality conditions are observed in all seasons during active southeasterly (SE, interaction between a low pressure over Italy and a high pressure over the Caspian Sea) circulation types (CTs). In winter, mainly easterly (E), SE, southerly (S), and anticyclonic (A) weather patterns result in above normal PM₁₀ concentrations. In addition to these four CTs, southwesterly (SW) types also cause higher PM₁₀ values in the spring season. During summer, SE, SW, westerly (W), and cyclonic (C) CTs are associated with above-normal PM₁₀ values. During fall, obvious higher PM₁₀ concentrations are found during SE, S, and A types.