Air pollution is affected by the atmospheric dynamics. This study aims to determine that air pollution concentration values in İstanbul increased significantly and reached peak values due to atmospheric blocking between the 30th of December 2022 and the 5th of January 2023. In this study, hourly pollutant data was obtained from 16 air quality monitoring stations (AQMS), the exact reanalysis data was extracted from ERA5 database, and inversion levels and meteorological and synoptic analyses were used to determine the effects of atmospheric blocking on air pollution. Also, cloud base heights and vertical visibility measurements were taken with a ceilometer. Statistical calculations and data visualizations were performed using the R and Grads program. Omega-type blocking, which started in İstanbul on December 30, 2022, had a significant impact on the 1st and 2nd of January 2023, and PM10 and PM2.5 concentration values reached their peak values at 572.8 and 254.20 µg/m3, respectively. In addition, it was found that the average concentration values in the examined period in almost all stations were higher than the averages for January and February. As a result, air quality in İstanbul was determined as \"poor\" between these calendar dates. It was found that the blocking did not affect the ozone (µg/m3) concentration. It was also found that the concentrations of particulate matter (PM) 10 µm or less in diameter (PM10) and PM 2.5 µm or less in diameter (PM2.5) were increased by the blocking effect in the İstanbul area. Finally, according to the data obtained using the ceilometer, cloud base heights decreased to 30 m and vertical visibility to 10 m.

Accurately determining the spatiotemporal variability of ozone on a regional to intercontinental scale is essential for air quality studies. In the present study, a first systematic evaluation and analysis of long-term (2009-2020) gridded datasets (0.5° × 0.625°) of total columnar ozone (TCO) retrieved from Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2TCO) is evaluated for the Indian region. The MERRA-2TCO is first validated with observations (IMDTCO) and then further compared with the Atmospheric Infrared Sounder (AIRSTCO) satellite datasets. For an in-depth comparison and statistical analysis, the dataset has been segregated into seven distinct regions, i.e., Western Himalaya (WH), North East (NE), North Central (NC), North West (NW), West Peninsula India (WPI), East Peninsula India (EPI), and South Peninsula India (SPI). Descriptive statistics (NMSE, FB, R, FA2, and d) reveals a significant correlation of MERRA-2TCO against IMDTCO for Delhi with NMSE (0.0013), FB (- 0.029) and Varanasi NMSE (0.0008), FB (- 0.014). The results of simple linear regression analysis show an increasing TCO trend value of 0.31% and 0.44% per decade in both the cities, respectively. A comparison of MERRA-2TCO with AIRSTCO shows a significant correlation of 0.62-0.87 in different regions of India. Furthermore, in support of Brewer\'s circulation pattern, an increasing shift of columnar ozone from low (SPI) to high (WH) latitudinal regions is observed. Our results show that the MERRA-2 ozone dataset can be effectively used for ozone air quality studies over India and this analysis may strengthen the need for independent, high-quality, and consistent ozone measurements with small uncertainties.

The focus of this study is to evaluate the influence of intertropical discontinuity (ITD) on the variation of total column ozone (TCO). Relevant information is supplied on the temporal and spatial variability of TCO along the ITD zone, which is an important factor influencing the earth\'s atmosphere. Several studies over the years have established the relationship and have influence several atmospheric processes on TCO. However, the relationship between intertropical discontinuity and TCO over West Africa has a gap. This study tends to examine the influence ITD has on TCO variation using the West African region as a case study. The study used wind, ozone, and dewpoint temperature data for the period between 1980 and 2019. To assess the variability and trend over the study region, several statistical methods were used, including Pearson correlation, Mann-Kendall, and linear regression model. The Mann-Kendall test shows an increasing trend throughout the months over the study region. Spatial analysis also revealed that regions north of the ITD have a higher concentration of TCO than the southern region of the ITD between April and September. However, ITD influence was more visible during the wet months of June to August (JJA) as the highest concentration of TCO was observed during this period across all latitude, but more deviation was observed between latitude 10 to 18° N, while the least occurrence is observed when ITD is at its minimum position in the month of December to February (DJF). The ACRV shows that 14° N exhibit the highest variation with a value of 4.84, while the deviation is also at its highest with value of 13.65. The monthly position of ITD for 40 years was also analysed to observe the monthly deviation along the ITD region 40 years, and the spatial distribution of TCO was analysed from January to December. It is of note that during the cause of this study, low-ozone values of 220DU are not found in the study region. The highest and the lowest value of TCO is 295 DU and 227 DU, respectively, with an average range of 68DU.

Ozone plays an important role in the thermal structure and chemical composition of the atmosphere. The present study compares the temporal and spatial distributions of Total Column Ozone (TCO) over the Indian sub-continent retrieved from a geostationary Indian National Satellite (INSAT-3D) and Atmospheric Infrared Sounder (AIRS). The INSAT-3D TCO values are also evaluated against the Dobson spectrophotometer observations at two locations. The inter-comparison results reveal a good correlation of 0.8, the bias of -5 DU, and Root Mean Square Error (RMSE) of 15 DU approximately between the TCO retrieved from INSAT-3D and AIRS. The lowest RMSE and highest correlation coefficient were found in the pre-monsoon season. The INSAT-3D and AIRS show reasonable agreement with the RMSE varying between 10 and 30 DU. On the other hand, evaluation of the INSAT-3D TCO with the ground-based observations from Dobson spectrophotometers located at New Delhi and Varanasi showed fair agreement with a maximum monthly mean correlation coefficient of 0.68 and 0.76, respectively, and RMSE varying from 11 to 16 DU for both the stations. The seasonal distribution of TCO and its variation over the Indian region has also been studied using INSAT-3D and AIRS data. The analysis exhibits strong seasonal variations, with higher values in pre-monsoon season and minimum values in winter season. The noticeable seasonal variability of TCO can be attributed to complex combination of photochemical and dynamical processes in the troposphere and stratosphere. The main objectives of the study are to compare the INSAT-3D TCO with two independent ground-based Dobson spectrophotometer observations and Atmospheric Infrared Sounder (AIRS) aboard NASA\'s Aqua satellite.

An analysis is presented for both ground- and satellite-based retrievals of total column ozone and nitrogen dioxide levels from the Washington, D.C., and Baltimore, Maryland, metropolitan area during the NASA-sponsored July 2011 campaign of Deriving Information on Surface COnditions from Column and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Satellite retrievals of total column ozone and nitrogen dioxide from the Ozone Monitoring Instrument (OMI) on the Aura satellite are used, while Pandora spectrometers provide total column ozone and nitrogen dioxide amounts from the ground. We found that OMI and Pandora agree well (residuals within ±25 % for nitrogen dioxide, and ±4.5 % for ozone) for a majority of coincident observations during July 2011. Comparisons with surface nitrogen dioxide from a Teledyne API 200 EU NOx Analyzer showed nitrogen dioxide diurnal variability that was consistent with measurements by Pandora. However, the wide OMI field of view, clouds, and aerosols affected retrievals on certain days, resulting in differences between Pandora and OMI of up to ±65 % for total column nitrogen dioxide, and ±23 % for total column ozone. As expected, significant cloud cover (cloud fraction >0.2) was the most important parameter affecting comparisons of ozone retrievals; however, small, passing cumulus clouds that do not coincide with a high (>0.2) cloud fraction, or low aerosol layers which cause significant backscatter near the ground affected the comparisons of total column nitrogen dioxide retrievals. Our results will impact post-processing satellite retrieval algorithms and quality control procedures.