Total Ozone Content Research Articles

Effective technology of disinfecting ozonation of hatching chicken eggs

Relevance. The positive aspects of disinfecting ozonation of hatching eggs allow us to expect successful application of the method not only in large but also in small-scale farms, as well as for experimental and industrial purposes in laboratories and bio-enterprises related to the technological process based on the incubation of a small number of eggs. This determines the importance of expanding the range of ozonizers due to numerous portable devices. There are no clear recommendations for these devices and this causes the need to search for the most effective and harmless modes for the embryo, and schemes of disinfecting ozonation.Methods. The study used fertilized chicken eggs “Hysex Brown” and a portable ozonizer “OZON-OviV”. Ozone concentration 2.0 mg / l. Eggs were treated in a specially made chamber. Technology-1: twice for 30 minutes before incubation and on the 3rd day of incubation. Technology-2: three times for 30 minutes before incubation, on days 3 and 5. The range of studies included: assessment of total microbial contamination (densitometry); identification of microorganisms (MALDI-TOF-spectrometry); biological control of incubation (fertility, hatchability, mortality, developmental abnormalities); assessment of the adequacy of the internal organs (MicroCT); embryo morphometry (weight, length, chest circumference) and calculation of development proportionality indices; histological assessment of the liver.Results. The total ozone concentration during treatment by two methods was 240 mg/l and 360 mg/l, respectively. The disinfecting efficiency of ozonation has been proven, providing a decrease in the level of total microbial contamination by 30% and 40% with double and triple treatment. A tendency to maintain a low total microbial contamination, compared to intact eggs, up to 14 days of incubation has been revealed. The dynamics of the microbial landscape indicate the bacteriostatic effect of ozone in the concentrations used on a wide range of microorganisms. Microtomographic and histological methods confirmed the harmlessness of the technologies used. Along with the more pronounced antibacterial effect of technology-2, the presence of a stimulating effect on the body of the developing embryo was revealed, which determines the preference for its choice.

ДИНАМІЧНІ УМОВИ ФОРМУВАННЯ ПРОСТОРОВИХ ЕКСТРЕМУМІВ ОЗОНОВОГО ШАРУ НАД ТЕРИТОРІЄЮ УКРАЇНИ

The paper examines the conditions for the formation of spatial extremes in total ozone content (TOC) over the territory of Ukraine caused by dynamic factors. The study used satellite observations of TOC and meteorological parameters (u,v components of wind and geopotential height) from the ERA5 reanalysis in the Northern Hemisphere. We describe the processes of air advection with significant TOC deviations and implement its classification into the main types. Seventy cases of spatial extremes were identified, 86% of which were observed under air advection with a western component. The intense westerly flow in the lower stratosphere is responsible for both the advection of air with high TOC (total ozone content) and its local formation. Under a well-developed polar vortex, most ozone extremes are transported by the main flow and reach the territory of Ukraine from the west and northwest, forming significant positive deviations. In this case, the polar vortex itself must be displaced into the Eastern Hemisphere for Ukraine to be closer to its outer boundary. When the integrity of the polar vortex is disrupted, it takes on a wavelike structure, leading to greater variability in the processes forming ozone extremes over Ukraine, including TOC advection from the north and local formation. With the breakdown of the polar vortex and the onset of a rapid TOC decrease in late March to April, the likelihood of positive ozone deviations from the north increases, though their recurrence does not exceed 7% of the total number of extremes. Significant negative TOC deviations spread over Ukraine during the period of seasonal minima under two conditions: advection from the northwest when the stratospheric polar vortex is absent (until November), and advection from the west in the early stages of vortex formation (in December). The established and described dynamic conditions for the formation of ozone layer extremes are important for extending the lead time in forecasting ozone anomalies over Ukraine.

Variations of Planetary Wave Activity in the Lower Stratosphere in February as a Predictor of Ozone Depletion in the Arctic in March

This study is dedicated to the investigation of the relationship between the wave activity in February and temperature variations in the Arctic lower stratosphere in March. To study this relationship, the correlation coefficients (CCs) between the minimum temperature of the Arctic lower stratosphere in March (Tmin) and the amplitude of the planetary wave with zonal number 1 (PW1) in February were calculated. Tmin determines the conditions for the formation of polar stratospheric clouds (PSCs) following the chemical destruction of the ozone layer. The NCEP and ERA5 reanalysis data and the modern and future climate simulations of the Earth system models INM CM5 and SOCOLv4 were employed. It is shown that the maximum significant CC value between Tmin at 70 hPa in the polar region in March and the amplitude of the PW1 in February in the reanalysis data in the lower stratosphere is 0.67 at the pressure level of 200 hPa. The CCs calculated using the model data are characterized by maximum values of ~0.5, also near the same pressure level. Thus, it is demonstrated that the change in the planetary wave activity in the lower extratropical stratosphere in February can be one of the predictors of the Tmin. For further analysis of the dynamic structure in the lower stratosphere, composites of 10 seasons with the lowest and highest Tmin of the Arctic lower stratosphere in March were assembled. For these composites, differences in the vertical distribution and total ozone content, surface temperature, and residual meridional circulation (RMC) were considered, and features of the spatial distribution of wave activity fluxes were investigated. The obtained results may be useful for the development of forecasting of the Arctic winter stratosphere circulation, especially for the late winter season, when substantial ozone depletion occurs in some years.

Differential Responses of Total Ozone Content to Solar Activity Parameters at Two Saudi Arabian Locations

This study examines the correlations between Total Ozone Content (TOC) at two locations in Saudi Arabia—Abha and Jeddah—and various solar activity indicators (sunspot numbers, solar radio flux) and cosmic rays, using data spanning from 1979 to 2023. The research employs correlation analyses and spectral techniques, such as Fast Fourier Transform and wavelet analysis, to explore these relationships.The results reveal significant non-zero correlations between changes in TOC at both Saudi sites and the studied solar activity indicators and cosmic rays, with these correlations varying in strength and significance across different solar cycles and seasons.Spectral analysis suggests the presence of several periodicities in the TOC data from both sites, including cycles of 3.9 years, 2.63 years, 1.65 years, 1.1-1.2 years, 325 days (∼0.88 years), 285-293 days (∼0.78-0.80 years), 273 days (∼0.75 years), 249-232 days (∼0.68 years), and 202-188 days (∼0.52 years). Notable shared periodicities between TOC and solar activity and cosmic rays data include ∼ 2.6 years, 3.8-3.9 years, 1.56 years, 325 days, 273 days, and 166 days.The findings from both correlation and spectral analyses suggest a potential connection between variations in TOC and solar activity at the specific locations studied. This aligns with previous research indicating that increased UV radiation during periods of high solar activity enhances ozone production, particularly at lower latitudes, and that increased magnetic activity reduces the influx of cosmic rays into the heliosphere, impacting atmospheric ionization.

Measurements of total ozone content in the 4.7 µm region with a medium-resolution FTIR spectrometer and comparison with satellite data

The total ozone content (TOC) measurements results by the ground-based MR-32 instrument in 2015–2022 at the Obninsk station (55.11N; 36.60E) are presented. Solar radiation was measured by the FTIR spectrometer of medium resolution of 0.12 cm−1. Based on the analysis of the absorption spectra the relevant spectral intervals in the region of 4.7 microns were determined. The SFIT4 program was applied to retrieve total ozone content. A comparison of the results of TOC measurements by the MR-32 instrument with satellite data of OMPS, OMI, and SBUV(MOD) showed good agreement. The correlation coefficients are 0.93–0.97. According to spectral and cross-correlation wavelet analysis, ground and satellite oscillations with periods from 4 to 60 months occur of almost synchronously. The systematic discrepancies between daily average ground-based and satellite TO measurements are (−0.8 ± 3.6)%, (−0.2 ± 3.7)% and (−2 ± 5)% for OMPS, OMI and SBUV(MOD), respectively.

Projected changes in ultraviolet index and UV doses over the twenty-first century: impacts of ozone and aerosols from CMIP6.

This study evaluated the health-related weighted ultraviolet radiation (UVR) due to the total ozone content (TOC) and the aerosol optical depth (AOD) changes. Clear-sky Ultraviolet Index (UVI), daily doses, and exposure times for erythema induction (Dery and Tery) and vitamin D synthesis (DvitD and TvitD) were computed by a radiative transfer estimator. TOC and AOD data were provided by six Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). For projections, we consider four Shared Socioeconomic Pathways scenarios-SSPs (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5)-and two time-slices (near: 2041-2060 and far future: 2081-2100). UVR projections showed pronounced changes for the summer hemispheres in the far future. TOC increases in mid- and high latitudes of the Southern Hemisphere caused decreases in UVR at the summer solstice. However, projections did not indicate sun-safe exposure conditions in South America, Australia, and Southern Africa. On the contrary, exposure around solar noon from 10 to 20min will still be sufficient to induce erythema in skin type III individuals throughout this century. In southern Argentina and Chile, the UVR insufficiency for vitamin D synthesis at solar noon in skin type III remains the same during this century at the winter solstice. In the Northern Hemisphere, UVI and Dery at the summer solstice should remain high (UVI ≥ 8; Dery ~ 7.0kJm-2) in highly populated locations. Above 45 °N, UVR levels cannot be enough to synthesize vitamin D in skin type III during the boreal winter. Our results show that climate change will affect human health through excess or lack of solar UVR availability.

WRF-Chem Modeling of Tropospheric Ozone in the Coastal Cities of the Gulf of Finland

Ozone in the troposphere is a pollutant and greenhouse gas. Atmospheric models can add valuable information to observations for studying the spatial and temporal variations in tropospheric ozone content. The present study is intended to evaluate the variability in tropospheric ozone and its precursors near the Gulf of Finland with a focus on St. Petersburg (Russia) and Helsinki (Finland) in 2016–2019, using the WRF-Chem 3-D numerical model with a spatial resolution of 10 km, together with observations. The diurnal cycle of the near-surface ozone concentrations (NSOCs) in both cities is caused by the variability in NO2 emissions, planetary boundary layer height, and local meteorological conditions. The seasonal variations in NSOCs and tropospheric ozone content (TrOC) are caused by the variability in total ozone content and in ozone formation in the troposphere. The model reveals a VOC-limited regime in the ~0–1 km layer around St. Petersburg, Helsinki, and the Gulf of Finland and a pronounced NOx-limited regime in the 0–2 km layer in the forests of southern Finland, Karelia, some Russian regions, and the Baltic countries in July. The WRF-Chem model overestimates the measured NSOCs by 10.7–43.5% and the TrOC by 7–10.4%. The observed differences are mainly caused by the errors in chemical boundary conditions and emissions of ozone precursors and by the coarse spatial resolution of the modeling.

An investigation of the relationship between surface temperature and total ozone over New Delhi, India, using a frequency domain technique and binary fuzzy relation

ABSTRACT This work has explored spectral analysis to view the relationship between the time series of surface temperature and total ozone concentration (TOC) over New Delhi from 1995 to 2005. The time series has a discernible spectral density when analysed using harmonic analysis. Between the surface temperature and TOC, a common cycle of period of 10 months has been noted for the years under investigation. In addition, a binary fuzzy relation method has been used to examine the relationship between surface temperature and TOC using membership matrices produced by max-min composition. Overall, a fuzzy set theoretic approach has established a connectivity between surface temperature and TOC, and a spectral analysis approach which falls under the category of frequency domain approach has established the existence of a common cycle between these two time series.

Multifractal detrended fluctuation analysis approach to the monthly total ozone concentration over New Delhi, India

Multifractal detrended fluctuation analysis approach to the monthly total ozone concentration over New Delhi, India

Total ozone content, total cloud cover, and aerosol optical depth in CMIP6: simulations performance and projected changes

Total ozone content, total cloud cover, and aerosol optical depth in CMIP6: simulations performance and projected changes

Additive singular spectral model of a dendrochronological signal

Relevance. Allocation of structural components in a dendrochronological signal of annual rings of coniferous trees expands the possibilities of the bioindication method and allows obtaining information about changes in environmental conditions in the past for extended territories. Aim. Creation of an additive singular spectral model based on the frequency trigonometric components of the dendrochronological signal; reconstruction of changes in the total ozone content in the atmosphere in the past, affecting the level of ultraviolet radiation in the B range radiation. Objects. Time series of total ozone content in the atmosphere (data from 1932), width and density of annual rings (data from 1686–2004) on the example of the territory near the observatory in Arosa, Switzerland, time series of stable oxygen isotopes δ18Oc, France. Methods. Time series analysis (decomposition of a time series, identification of model parameters, prediction of a time series), statistical analysis (F-criterion, χ2 – Pearson criterion), experimental measurements of the percentage components of the wood of annual rings, correlation analysis, spectral singular analysis. Results. Decomposition of the dendrochronological signal of individual chronologies into trigonometric components in the Caterpillar program. Correlation analysis of the sensitivity of trees to atmospheric effects. Reconstruction of the ozone level in the stratosphere using the first trigonometric component of the dendrochronological signal. In cellulose, the first low-frequency component of the signal and the structural component of wood, a reliable response of trees to long-period fluctuations in the total ozone content is recorded. This allows assessment of the impact of the stress factor on conditions of exploitation of forest resources. The use of data on the width of the annual rings allows you to expand the territorial boundaries of the method.

The spatiotemporal variations of total column ozone concentration over Ethiopia

We have studied spatiotemporal characteristics of ozone concentration over Ethiopia using data from the Ozone Mapper and Profiling Suite-Nadir Mapper (OMPS-NM). Daily total column ozone data of 108 observation points with spatial resolution 1° × 1° over the study area for the period of 2012–2019 have been analyzed. The spatial variations over the region have been studied by considering longitudinal and latitudinal bands separately through the sample mean difference among different bands using multi-comparison analysis of variance technique in order to identify the clusters in the region. For the temporal variability, we model the total column ozone timeseries observation as a sum of seasonal, trend, and temporally correlated noise components. We have found that the total column ozone concentration has a maximum value of 301DU during summer on August 18, 2013 and a minimum value of 216DU during winter on January 03, 2013 over the study period. The 95% confidence level of the overall mean of the total column ozone concentration during the study period was found to be (261.35 ± 2.38)DU. Our spatial data analysis revealed that the spatial distribution of ozone over Ethiopia can be classified into three clusters: southern cluster (4.5°N–8.5°N and 33.5°E–47.5°E), north-eastern cluster (9.5°N to 14.5°N and 41.5°E–47.5°E), and north-western cluster (9.5°N–14.5°N and 33.5°E–40.5°E). We have checked the coefficient of determination among bands in the same cluster to see if the concentration of ozone in one band can be explained by the concentration in another band for each cluster and confirmed the reliability of the classification. In order to capture temporal characteristics, we have computed the spectral periodogram for each cluster and obtained a power peak at frequency f = 0.002 768 Hz, which indicates that the ozone concentration over the region exhibits an annual cyclic behavior. A truncated Fourier series fit is used to determine the annual seasonal component. The non-parametric Mann–Kendall’s trend test with a 95% confidence level of significant has indicated a decreasing linear trend with a depletion rate of 0.77, 0.73, and 0.43 DU/yr over north-western, north-eastern, and southern clusters, respectively. The analysis of residuals for each cluster indicated that the residuals are normally distributed with no significant outliers, and the model explains 85%, 86%, and 79% of the variance in the north-western, north-eastern, and southern clusters, respectively, demonstrating the reliability of the model considered in this study.

UVBoost: An erythemal weighted ultraviolet radiation estimator based on a machine learning gradient boosting algorithm

This article presents UVBoost, an ultraviolet radiation (UVR) estimator based on a Supervised Machine Learning (SML) regression model powered by high precision calculations provided by a conventional Radiative Transfer Model (RTM). The proposed regression model takes UVR as a dependent variable, and the Solar Zenith Angle (SZA), Total Ozone Content (TOC), and Aerosol Optical Depth (AOD), as the independent predictive variables. UVBoost was developed to increase computational speed for conducting calculations with large databases, without sacrificing accuracy. Furthermore, this method employs a user-friendly code, which can be used by laymen or researchers in other areas. UVBoost can be employed to disseminate UVR data in different spatiotemporal scales, or for climatological projection studies on a global scale. UVBoost was developed by comparing seven regression SML tools via cross validation. Results were validated using non-parametric statistical tests. Of all the tested tools, the Categorical Boosting (CatBoost) method showed the best accuracy at the lowest computational cost. Two additional studies were carried out, one at the global scale, and another at the local scale, to compare the traditional RTM vs. the UVBoost results. The first study simulated a global UVR field (1°x1°) with 64,800 gridpoints. The differences between RTM and UVBoost were less than ±5% for approximately 95% of all points, except for high SZA datapoints. The computational speed of UVBoost surpassed that of the RTM by more than three orders of magnitude. The second study simulated the daily UVR at eight different locations on Earth. The results showed that the UVBoost was very efficient in simulating accumulated UVR doses during the day, with negligible differences (< ±3%), which means it can be used in studies on UVR and human health. In the future, UVBoost will include other geophysical parameters and be extended to other bands in the electromagnetic spectrum.

Comparison of ground-based and satellite observations of total ozone content over Tomsk for 2006-2020

Comparison of ground-based and satellite observations of total ozone content over Tomsk for 2006-2020

Determination of the Total Ozone Content in Atmospheric Column according to the Data of Electro-L No. 3 Spacecraft Using Neural Networks Satellite

Determination of the Total Ozone Content in Atmospheric Column according to the Data of Electro-L No. 3 Spacecraft Using Neural Networks Satellite

Interactions of Biosphere and Atmosphere within Longleaf Pine Restoration Areas

Longleaf pine forests are economically and culturally valued ecosystems in the southeastern United States. Efforts to restore the longleaf pine ecosystem have risen dramatically over the past three decades. Longleaf pine restoration generally involves varying degrees of forest harvesting and frequent applications of prescribed fire. Thus, it is important to understand their interactions with the atmosphere on a large scale. In this study, we analyzed 14 parameters of aerosols, gasses, and energy from three areas with longleaf pine restoration (named Bladen in eastern NC, Escambia in southern AL and northern FL, and Kisatchie in central LA, USA) from 2000 to 2021 using multiple satellites. Averaged across the areas, the monthly aerosol optical depth at 483.5 nm was about 0.022, and the monthly aerosol single scattering albedo was 0.97. Black carbon column mass density averaged 7.46 × 10−7 kg cm−2 across these areas, but Kisatchie had a higher monthly dust column mass density (2.35 × 10−4 kg cm−2) than Bladen or Escambia. The monthly total column ozone and CO concentration averaged about 285 DU and 135 ppbv across the three areas. Monthly SO2 column mass density was significantly higher in Bladen (4.42 × 10−6 kg cm−2) than in Escambia and Kisatchie. The monthly surface albedo in Escambia (0.116) was significantly lower than in the other areas. The monthly total cloud area fraction averaged about 0.456 across the three areas. Sensible and latent heat net flux and Bowen ratios significantly differed among the three areas. Bowen ratio and total cloud area fraction were not significantly correlated. Net shortwave of the forest surface averaged about 182.62 W m−2 across the three areas. The monthly net longwave was much lower in Bladen (−90.46 W m−2) than in Escambia and Kisatchie. These results provide the baseline information on the spatial and temporal patterns of interactions between longleaf pine forests under restoration and the atmosphere and can be incorporated into models of climate change.

Forecasting of Total Column Ozone using Regression Analysis and LSTM-RNN Machine Learning Approach

Objectives: Atmospheric Ozone plays an important role in global climate change, human health and environmental conditions. Accurate and timely prediction of variation in Total Column Ozone (TCO) concentration is very important for both climatology and environment. In this context, the present study aims to utilize the advancement of Artificial Intelligence in Machine learning and a conventional method to develop models for the prediction of TCO concentration using historical time series data over a tropical region, India. Methods: Long Short-Term Memory (LSTM) deep learning networks are very useful in classifying, processing and making predictions based on time series data. In this work, Multiple Linear Regression (MLR) model, Long Short-Term Memory (LSTM) models are developed for forecasting TCO over a tropical region. The Statistical Parameters such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) were used to analyze and evaluate the performance of the proposed models. Findings: In the present study the TCO concentration varied between 217.4 DU and 288.6 DU. The performances of MLR and LSTM model were compared. From the results, it is evident that the values of RMSE, MAE and MAPE of the MLR model are 3.807924, 2.93766, 1.15 respectively whereas the values for LSTM model are 3.074492, 2.574, 1.01 respectively. LSTM was found to be the accurate model for the study data set and the predicted TCO concentration has a very good correlation with the actual observations and it does not rely on the meteorological parameters. Novelty: The LSTM models are usually employed in the field of machine translation, speech recognition and for the prediction of traffic levels, stock levels and air pollutants. This work utilizes the fast numerical machine learning computing library Tensorflow and a high level neural network library Keras that runs on top of Tensorflow to develop a LSTM network model for the prediction of the concentration levels of TCO. Keywords: Total Column Ozone; Regression; Forecasting; Climate Change; Long Short-Term Memory

Latitude Dependence of the Total Ozone Trends for the Period 2005–2020: TOC for Bulgaria in the Period 1996–2020

The present study examines a long-term statistical trend analysis of Total Ozone Content (TOC) data from the AURA satellite for latitudes 60° and 60° S. A methodology for eliminating the strong dependence on the season has been applied by introducing the relative deviation of the average monthly TOC from the climatological average. The analysis presents comparisons of the trends of the zonal average values of TOC and its relative values. In addition, the standard error of both parameters is calculated. The course of the obtained mass of Ozone (O3) and its trend for the period 2005–2020 is presented, and a division is made into three areas: (i) from 30° S to 30° N, (ii) from 30° S to 60° S, and (iii) from 30° N to 60° N. The last part of this study demonstrates the trends of TOC and relative TOC for Bulgaria in the period 1996–2020. The main results of this study show that (a) in the considered latitude range, a slow but steady increase in O3 prevails, (b) the main part of the O3 mass is in low and mid-latitudes, and (c) the general trend in O3 mass for both hemispheres is determined by the positive trend in the southern hemisphere.

A Deep-Neural-Network-Based Aerosol Optical Depth (AOD) Retrieval from Landsat-8 Top of Atmosphere Data

The 30 m resolution Landsat data have been used for high resolution aerosol optical depth (AOD) retrieval based on radiative transfer models. In this paper, a Landsat-8 AOD retrieval algorithm is proposed based on the deep neural network (DNN). A total of 6390 samples were obtained for model training and validation by collocating 8 years of Landsat-8 top of atmosphere (TOA) data and aerosol robotic network (AERONET) AOD data acquired from 329 AERONET stations over 30°W–160°E and 60°N–60°S. The Google Earth Engine (GEE) cloud-computing platform is used for the collocation to avoid a large download volume of Landsat data. Seventeen predictor variables were used to estimate AOD at 500 nm, including the seven bands TOA reflectance, two bands TOA brightness (BT), solar and viewing zenith and azimuth angles, scattering angle, digital elevation model (DEM), and the meteorological reanalysis total columnar water vapor and ozone concentration. The leave-one-station-out cross-validation showed that the estimated AOD agreed well with AERONET AOD with a correlation coefficient of 0.83, root-mean-square error of 0.15, and approximately 61% AOD retrievals within 0.05 + 20% of the AERONET AOD. Theoretical comparisons with the physical-based methods and the adaptation of the developed DNN method to Sentinel-2 TOA data with a different spectral band configuration are discussed.

A probe into the behaviour of total ozone time series through multifractal detrended fluctuation analysis

The present study reports a multifractal detrended fluctuation analysis (MF-DFA) of total ozone time series. Considering daily total ozone concentration (TOC) data ranging from 2015 to 2019, derived from Ozone Monitoring Instrument (OMI)/Aura observations, we have created a new profile by subtracting the trend. Subsequently, we have divided the profile \({X}_{i}\) into non-intersecting segments of equal time scale varying from 25 to 30. Fitting a second order polynomial, we have eliminated the local trend from each segment, and thereafter, we have computed the detrended variance. Finally, the multifractal behaviour has been identified, and the singularity spectra has helped us in obtaining the generalised Hurst exponent which in this case has come out to be greater than 0.5.