Analysing of atmospheric conditions and their effects on air quality in Istanbul using SODAR and CEILOMETER

Yavuz, Veli; Özen, Cem; Çapraz, Özkan; Özdemir, Emrah Tuncay; Deniz, Ali; akbayır, ibrahim; Temur, Hande

doi:10.1007/s11356-021-16958-w

Cited by 22 publications

(10 citation statements)

References 42 publications

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“…Although the differences between before and during the lockdowns are prominent for the vast majority of stations, it has been determined that these results cannot be evaluated reasonably because the compared periods do not include the same seasonal cycle, which is essential for the evaluation of the wind patterns [ 11 ]. However, in addition to the variability in wind direction, other meteorological factors, such as high-pressure systems [ 17 ] and Saharan dust storms [ 57 ], which cause PM 10 to change significantly, are also affected by yearly differences. Therefore, all these meteorological factors must be excluded [ 16 ] to estimate the net effect of lockdowns on air pollution improvement.…”

Section: Resultsmentioning

confidence: 99%

“…In addition to population density, the factors that cause air pollution are complex [ 9 ], and meteorological aspects have an essential role in their alteration [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 ], depending on the location. Moreover, disaggregating and quantifying the characteristics to improve air quality is challenging.…”

Section: Introductionmentioning

confidence: 99%

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The Long-Term Impact of COVID-19 Lockdowns in Istanbul

Tan

2022

IJERPH

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The World Health Organization (WHO) have set sustainability development goals to reduce diseases, deaths, and the environmental impact of cities due to air pollution. In Istanbul, although average pollutant concentrations have been on a downward trend in recent years, extreme values and their annual exceedance numbers are high based on the air quality standards of WHO and the EU. Due to COVID-19 lockdowns, statistically significant reductions in emissions were observed for short periods. However, how long the effect of the lockdowns will last is unknown. For this reason, this study aims to investigate the impact of long-term lockdowns on Istanbul’s air quality. The restriction period is approximated to the same periods of the previous years to eliminate seasonal effects. A series of paired t-tests (p-value < 0.05) were applied to hourly data from 12 March 2016, until 1 July 2021, when quarantines were completed at 36 air quality monitoring stations in Istanbul. The findings reveal that the average air quality of Istanbul was approximately 17% improved during the long-term lockdowns. Therefore, the restriction-related changes in emission distributions continued in the long-term period of 476 days. However, it is unknown how long this effect will continue, which will be the subject of future studies. Moreover, it was observed that the emission probability density functions changed considerably during the lockdowns compared to the years before. Accordingly, notable decreases were detected in air quality limit exceedances in terms of both excessive pollutant concentrations and frequency of occurrence, respectively, for PM10 (−13% and −13%), PM2.5 (−16% and −30%), and NO2 (−3% and −8%), but not for O3 (+200% and +540%) and SO2 (−10% and +2.5%).

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Long-Term Impact of COVID-19 Lockdowns in Istanbul

Tan

2022

IJERPH

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“…The city, which has a bosphorus connecting the Asian and European continents, has coasts to the Marmara Sea in the south and the Black Sea in the north. The effects of the Black Sea climate are seen in the north of the city and the Mediterranean climate is seen in the south (Yavuz et al 2022c). There are three airports in the city, two on the European continent and one on the Asian continent.…”

Section: Study Areamentioning

confidence: 99%

Performance analyzes of thermodynamic indices and atmospheric parameters in thunderstorm and non-thunderstorm days in Istanbul, Turkey

Yavuz

2023

Preprint

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This study aims to analyze the thunderstorm (TS) events in the megacity Istanbul by using thermodynamic indices and atmospheric stability parameters for the period of 2001-2022. It was determined that TS events did not show any trend on an annual basis, mostly occurred in the warm season (May to September), and mostly lasted for a few hours. The thermodynamic indices and atmospheric stability parameters used in the study are Showalter Index (SI), Lifted Index (LI), Severe Weather Threat Index (SWEAT), K-Index (KI), Totals Totals Index (TTI), Convective Available Potential Energy (CAPE), Convective Inhibition (CIN), and Bulk Richardson Number (BRN). Annual and seasonal analyzes of all indices and parameters were performed for TS and non-TS events. Significant differences were found in both average, maximum, and minimum values. The Probability of Detection (POD), False Alarm Ratio (FAR), Miss Rate (MR), Critical Success Index (CIS), Hiedke Skill Score (HSS), and True Skill Score (TSS) were used to analyze the success of the threshold values presented in the literature in detecting TS events. Then, the seasonal successes of these threshold values were tested. It was found that the best predictions were mostly in the summer season and the worst predictions in the winter season. The ideal threshold values were determined for indices and parameters by increasing or decreasing the existing threshold values at certain rates. Success increases of up to 15% in skill scores for the proposed threshold values.

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“…Many scienti c studies have proven that the spatial and temporal changes of pollutants that reduce AQ are signi cantly affected by meteorological events and the dynamic structure of the atmosphere. (Galindo et al, 2011;Unal et al, 2011;Fortelli et al, 2016;Lana et al, 2016;Özdemir et al, 2020;Yavuz et al, 2022). Zhang (2019), in his article examining the dynamic effects of meteorological conditions on air pollution in Beijing, found that the most important meteorological factors are excessive wind speed (dynamic) and sunshine duration (thermal), respectively.…”

Section: Introductionmentioning

confidence: 99%

An Urban Air Quality Assessment Based on a Meteorological Perspective

Kaya

Özdemir

Çapraz

et al. 2023

Preprint

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An integrated approach to understanding all measured pollutants with multi-discipline in different time scales and understanding the mechanisms hidden under low Air Quality conditions are essential for tackling potential air pollution issues. Sivas is a province located in the Eastern region of Türkiye with a developing industry and a growing population, and its climate is known as arid and cold. Since the end of 2016, the province has started to replace the habit of using coal for domestic heating and industry with natural gas. Despite this development, especially in Fine Particulate Matter (PM2.5), the province reaches very high pollution values every winter, threatening public health. In this study, the air pollution of Sivas province was analysed with meteorological and PM2.5 data over six years. It was found that the winter period (January-February-November-December) of every year except 2019 -which has missing data- is the period with the highest air pollution in the province. In addition, the fact that the days exceeding the daily PM2.5 limit values in 2016, 2017, 2020 and 2021 were also seen in the spring and summer months caused the study to focus on additional emission sources such as long-range dust transport and road vehicles. The year 2017, which has the highest values, was analysed in detail. Pollution periods with the highest episodes in 2018 were analysed with the HYSPLIT and DREAM models. As a result of the study, the average PM2.5 values in 2017 were found to be 31.66 ± 19.2 µg/m3 and a correlation of -0.49 between temperature and PM2.5. As a result of model outputs, it was observed that the inversion is intensely observed in the province, which is associated with an increase of PM2.5 during the episodes. Especially on days with daily average PM2.5 values above 100 µg/m3, dust transport from the Arabian Peninsula is observed. Additionally, analysis of Planetary Boundary Layer (PBL) data and PM pollution revealed a significant negative correlation (r=-0.61). It was noted that pollution persisted over the province during low PBL hours, particularly during high PM2.5 concentration periods.

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Analysing of atmospheric conditions and their effects on air quality in Istanbul using SODAR and CEILOMETER

Cited by 22 publications

References 42 publications

The Long-Term Impact of COVID-19 Lockdowns in Istanbul

The Long-Term Impact of COVID-19 Lockdowns in Istanbul

Performance analyzes of thermodynamic indices and atmospheric parameters in thunderstorm and non-thunderstorm days in Istanbul, Turkey

An Urban Air Quality Assessment Based on a Meteorological Perspective

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