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

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.

Ambient air quality assessment at the airports based on a meteorological perspective

Natural mineral dust episodes elevate particle concentrations and eventually decrease air quality. Air pollutant emissions from aircraft, airport ground operations, and long-range dust transport are producing problems for the aviation sector. Dust transport from the Sahara Desert, one of the primary dust sources globally, significantly affects the eastern Mediterranean basin, including Türkiye. This study investigates the effect of long-range dust transport on particulate matter (PM) concentrations at Turkish airports. Three different approaches were used to analyse dust episodes in the study area. Firstly, routine reports of meteorological conditions at the airports were investigated. For this purpose, airport routine meteorological reports (Metar) and aviation-selected special weather report (Speci) codes, recorded at 11 airports from 2012 to 2021, were used to determine the dust episode days. Secondly, the hourly PM measurement dataset was analyzed from the closest air quality monitoring stations to the airports. Finally, regional atmospheric model results and backward-trajectory analysis were used to validate the dust episodes and determine the dust origin. Results showed that 163 dust episodes occurred during the study period, 17% from North Africa and 12% from the Mediterranean region.

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%).

An investigation of the effects of sand and dust storms in the North East Sahara Desert on Turkish airports and PM10 values: 7 and 8 April, 2013 events

Between April 7 and April 10, 2013, a cyclone with a value of 995 hPa that developed in the central Mediterranean transported dust from the Sahara Desert towards Turkey. At 13 airports in Turkey, dust haze and widespread dust were seen during different occasions in this period and caused the observation of so-called "Blowing dust events." This cyclone blew dust towards the Cappadocia airport, and the prevailing visibility decreased to 3800 m, making it the lowest value measured during the transition of this cyclone. In this study, Aviation Routine Weather Report (Metar) and Aviation Selected Special Weather Report (Speci) observations of airports in North Africa and Turkey were evaluated for the period between April 3 and April 11, 2013. With this cyclone the prevailing visibility at Benina Airport in Libya decreased to 50 m on April 6, 2013. This study aims to evaluate long-distance dust transport's effects on meteorological visibility at airports in Turkey and examine the episodic changes of PM₁₀ values measured by air quality monitoring stations. Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model outputs were used to determine the trajectories of long-distance dust particles. Powder red, green, and blue (RGB) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images, Cloud-Aerosol LIDAR Infrared Pathfinder Satellite Observations (CALIPSO) images, the Barcelona Supercomputing Center-Dust Regional Atmosphere Model (BSC-DREAM8b) outputs, and Global Forecast System (GFS) synoptic maps were used for analysis. In addition, PM₁₀ values obtained from air quality monitoring stations were examined. According to the data obtained from the CALIPSO images, the dust concentration on the Eastern Mediterranean reaches up to 5 km. The episodic values obtained from certain air quality measurement stations are Adana 701, Gaziantep 629, Karaman 900, Nevşehir 1343, and Yozgat 782 µg/m³ on an hourly average.

The relationship between PM10 and meteorological variables in the mega city Istanbul

PM₁₀, one of the air pollutants, occurs regularly in İstanbul during the winter months, namely in December, January, and February. PM₁₀ pollutant is affected by numerous factors. Among these factors are various meteorological variables and climatological factors. This article aims to determine the relationship between PM₁₀ and meteorological variables (wind speed, wind direction, temperature, and relative humidity) and to interpret these results. PM₁₀ and meteorological data were examined between 2011 and 2018. To determine the relationship, multiple linear regression, Pearson's correlation coefficient (PCC), Spearman's rank correlation, Kendall Tau correlation, autocorrelation function (ACF), cross-correlation function (CCF), and visuals were determined using the R program (open-air) packages. In the study, the relationship between wind, temperature, and relative humidity with PM₁₀ was determined, and it was observed that the PM₁₀ concentration was maximum between January and February. PM₁₀ concentrations have a positive relationship with relative humidity and wind direction, while a negative relationship with wind speed and temperature was observed. The correlation values for relative humidity and temperature were found to be 0.01 and - 0.15, respectively. Furthermore, the relationship between wind speed and PM₁₀ was calculated from multiple linear regression model, and the estimated value was - 0.12 while looking at the wind direction value, it was approximately 0.03.

Modelling driving factors of PM2.5 concentrations in port cities of the Yangtze River Delta

PM_2.5 is one of the major air pollutants in port cities of the Yangtze River Delta (YRD) of China. Understanding the driving factors of PM_2.5 is essential to guide air pollution prevention and control. We selected 17 major port cities in YRD to study the driving factors of PM_2.5 in 2019 and 2020. Generalized Additive Models were built to model the non-linear effects of single, multiple and interactions of driving factors on the variations of PM_2.5. NO₂, SO₂ and the day of year are most strongly associated with the variation of PM_2.5 concentration when used alone. Anthropogenic emissions play complicated roles in regulating PM_2.5 concentration. Although the effect of cargo throughput (CT) on PM_2.5 concentration is non-monotonic, higher PM_2.5 levels are found to be associated with higher levels of SO₂ and CT. This work can potentially provide a scientific basis for formulating PM_2.5 prevention and control policies in the region.

Visibility, aerosol optical depth, and low-visibility events in Bangkok during the dry season and associated local weather and synoptic patterns

Visibility and aerosol optical depth (AOD) characterization, and their relationship with PM₁₀ and local and synoptic meteorology, were studied for January-March in 2014 and 2015 over Bangkok. Visibility degradation intensifies in the dry season as compared to the wet season due to increase in PM₁₀ and unfavorable meteorological conditions. The average visibility is lower in January and February as compared to the other months. Relatively higher AOD in March despite lower PM₁₀ is attributed to the synergetic effect of moderate relative humidity, secondary aerosols, elevated aerosol layer due to summertime convection, and biomass burning. Larger variability in visibility and PM₁₀ in winter months is due to more synoptic weather fluctuations while AOD shows similar variability for all months attributed partly to fires. Higher PM₁₀ and moderate-to-high relative humidity cause lower visibility in the morning while it improves in afternoon as PM₁₀ and relative humidity decrease. AOD is higher in the afternoon as compared to that in the morning and evening as it is less sensitive to diurnal change in aerosols and meteorology at the surface level. Visibility and AOD relationships with PM₁₀ are dependent on relative humidity. Weaker winds lead to lower visibility, higher PM₁₀, and higher AOD irrespective of wind direction. Stronger winds improve visibility and decrease PM₁₀ for all directions while AOD is higher for all directions except eastern and northeastern. The back-trajectory results show that the transport of pollutant and moist air is coupled with the synoptic weather and influence visibility and AOD. Two low-visibility events were investigated. The first event is potentially caused by the combined effect of local emissions and their accumulation due to stagnant weather conditions, secondary aerosols, and forest fires in the nearby regions. The second event can be attributed to the local emission and fires in the nearby area with hygroscopic growth of aerosols due to moist air from the Gulf of Thailand. Based on these findings, some policy implications have also been given.

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.

Selected Persistent Organic Pollutants in Ambient Air in Turkey: Regional Sources and Controlling Factors

As a result of its unique location, Turkey receives air masses from Europe, Russia, Middle East, and Africa, making it an important place in terms of long-range atmospheric transport (LRT) of contaminants. Atmospheric levels of 22 organochlorine pesticides (OCPs), 45 polychlorinated biphenyls (PCBs), and 14 polybrominated diphenyl ethers (PBDEs) were measured in two metropolitan cities, Istanbul and Izmir, on a weekly basis from May 2014 to May 2015. Dichlorodiphenyltrichloroethane (DDT) and its derivatives were dominant OCP species, followed by isomers of hexachlorocyclohexane (HCH) at both sites. The annual mean concentration of ∑DDX (sum of o,p'-DDT, p,p'-DDT, o,p'-DDD, p,p'-DDD, o,p'-DDE, and p,p'-DDE) was 82 pg/m³ for Istanbul and 89 pg/m³ for Izmir, while these levels were about 46 pg/m³ for ∑HCHs (sum of α-, β-, γ-, and δ-HCH) at both of the sites. At both stations, tri- and tetra-PCBs and tetra- and penta-PBDEs were dominant congeners. The temperature dependence indicates that both LRT and local contaminated areas contribute to the elevated levels. A Lagrangian particle dispersion model (FLEXPART) showed a few potential source regions in northern Africa and Middle East, southern-southwestern and eastern Europe including Russia, as well as from local domestic metropolitan areas.

Characterization of aerosol sources in León (Spain) using Positive Matrix Factorization and weather types

A one-year aerosol sampling campaign, between 2016 and 2017, was conducted in a suburban area of León city, Spain. An association between the Positive Matrix Factorization (PMF) results and air masses through circulation weather types was carried out, through the construction of linear models from the PM₁₀ concentrations and its chemical composition. The aerosol sources, identified by PMF six-factor solution, were: traffic (29%), aged sea salt (26%), secondary aerosols (16%), dust (13%), marine aerosol (7%) and biomass burning (3%). Traffic and secondary factors showed the highest PM₁₀ contribution in the hybrid cyclonic types with wind component from the first and second quadrant. Anticyclonic types with wind component from the first quadrant exhibited high values of secondary, aged sea salt and dust factors. The highest contributions of the dust factor were also associated with northerly types. The linear models built for estimating the source apportionment of PM₁₀, from aerosol chemical composition and geostrophic flow, showed positive coefficients for: westerly flows (WF) in marine factor, southerly flows (SF) in secondary and traffic factors, and shear southerly vorticities (ZS) in dust factor. Negative dependences were observed for ZS in aged sea salt factor and for SF in dust factor. The PM₁₀ mass concentration calculated by the linear models and by the PMF model were strongly correlated. This can be very useful to determine the contribution of a specific source to PM₁₀ in León, only by knowing some meteorological and chemical variables.