PM10 Values Research Articles

The Impact of Air Pollution on Frequent Exacerbations among COPD Patients: An Observational Study on the Population of Western Romania

Patients with respiratory pathologies are the risk group most affected by air pollution, being directly exposed, especially those diagnosed with chronic obstructive pulmonary disease (COPD). In this observational study, which included 79 patients, we evaluated whether COPD patients with the frequent exacerbating phenotype or the infrequent exacerbating phenotype live in residences with higher values of air pollution. An air quality monitoring station was installed in each patient’s house for at least 24 h and PM 1.0, PM 2.5, and PM 10 were measured. Average PM 1.0, PM 2.5, and PM 10 values were lower in the group of infrequently exacerbating patients compared to the frequently exacerbating ones. For every 1 µg/m3 increase in the average values of PM 1.0, PM 2.5, and PM 10, there is an increase of 1.7%, 1.8% and 1%, respectively, in the risk of developing exacerbations. More importantly, an average value of PM 1.0, PM 2.5, and PM 10 above 32.21 µg/m3, 82.32 µg/m3 and 42.89 µg/m3 increases the probability of developing an exacerbation by 3.83, 10.14, and 4.12 times, respectively. Our analysis showed that COPD patients with a frequently exacerbating phenotype live in residences with high levels of air pollution compared to infrequently exacerbating ones.

Analysis of Increasing Case of Acute Respiratory Infections (ARI) in Nickel Mining Environment in Pomalaa District, Kolaka Regency, Southeast Sulawesi

Introduction: The mining process that has been carried out for a long time in large quantities often ignores environmental sustainability which in the end can result in various negative impacts that are felt in the short and long term. The purpose of the study was to determine the level of air pollution by Nickel dust and to analyze the relationship between exposure to Nickel dust and ARI disease in people living around the Nickel mining industry in Pomalaa District.
 Method: This study uses a cross-sectional design using a non-interventional type of research conducted in residential areas around the mining area of ​​PT Aneka Tambang Tbk, Kolaka Regency, Southeast Sulawesi Province as a mining designation area, namely in Pomalaa District.
 Result: The results showed that the average outdoor air quality for the S02 parameter in the designated area was higher than in the non-designated area, as well as for the N02 parameter, for the H2S parameter in both areas the average value was the same, but for the PM10 value in the designated area is higher than in the non-designated area, while the temperature, humidity, and wind speed in the two areas are almost the same.
 Conclusion: This is in line with the results of research conducted by Qomariyatus S (in 2007) conducted around the coal mine of PT Aneka Tambang,Southeast Sulawesi showed that the level of respirable dust in the field slightly exceeded the normal threshold value of 2.19 mg/m3.

Mega Asian dust event over China on 27–31 March 2021 observed with space-borne instruments and ground-based polarization lidar

Under the background of global climate change, the frequency of extreme weather events is ever-increasing. Climatic anomaly in dust source areas and intensive Mongolian cyclones jointly cause the reoccurrence of super dust storms in spring 2021. A mega dust storm broke out in southeast Mongolia on 27 March and significantly impacted air quality in China until 31 March. However, neither intensity nor affected areas are well depicted by the forecasting model. Here we report the horizontal distribution, transport path, dissipation, and influence on surface air quality of this event with the combination of space-borne and ground-based observations. Prudent analysis indicates a longer duration (5 days) and farther-south affected areas (25°N) than the previous report. Dust plumes were first transported to North and Northeast China, the Bohai Sea, and the Yellow Sea (28 March), and then respectively moved eastward to Korea-Japan regions and southward over mainland China (29 March), with PM10 values > 500 μg m−3 in 64 cities. Dust aerosols over the Yellow Sea retraced to the coastal areas of East China on 29 March, resulting in severe degradation of air quality over mainland China (25–40°N and 105–120°E) during 29–31 March. On 31 March, dust particles in this region were gradually removed, attributed to the wet removal and the enhanced south branch of westerlies. In central China, ground-based polarization lidar observed dust ∼26 h earlier (1600 LT, 27 March) than surface PM10 measurements. The dust plume showed a triple-layer vertical structure. The bottom layer mixed with local anthropogenic aerosols, concentrating most dust particles (>100 μg m−3); the upper two were composed of pure dust particles with lower mass concentration (<50 μg m−3). This study reveals the capacity of comprehensive observations with multiple approaches from both space and ground in real-time monitoring of mega dust storms and validating the sand storm forecasting.

A Novel Tree Ensemble Model to Approximate the Generalized Extreme Value Distribution Parameters of the PM2.5 Maxima in the Mexico City Metropolitan Area

We introduce a novel spatial model based on the distribution of generalized extreme values (GEVs) and tree ensemble models to analyze the maximum concentrations levels of particulate matter with a diameter of less than 2.5 microns (PM2.5) in the Mexico City metropolitan area during the period 2003–2021. Spatial trends were modeled through a decision tree in the context of a non-stationary GEV model. We used a tree ensemble model as a predictor of GEV parameters to approximate nonlinear trends. The decision tree was built by using a greedy stagewise approach, the objective function of which was the log-likelihood. We verified the validity of our model by means of the likelihood and Akaike’s information criterion (AIC). The maps of the generalized extreme value parameters on the spatial plane show the existence of differentiated local trends in the extreme values of PM2.5 in the study area. The results indicated strong evidence of an increase in the west–east direction of the study area. A spatial map of risk with maximum concentration levels of PM2.5 in a period of 25 years was built.

Meat quality in broiler chickens fed on cowpea (Vigna unguiculata [L.] Walp) seeds

The study aimed to evaluate the effects of a diet containing untreated cowpea (CWP; Aura 26 variety) seeds as a protein source on quality parameters of chickens’ breast (PM; Pectoralis major) and thigh muscles (BF; Biceps femoris). A total of 240 Ross 308 broiler chickens were randomly allotted to two groups: a control group fed with soybean meal (SBM) and an experimental group fed with CWP included at 200 g/kg as a replacement of SBM. Each group consisted of six pens as replicates, with 20 chicks per pen. At 6 weeks of age, twelve birds/group were slaughtered. Compared to SBM group, the group fed CWP had higher (P < 0.0001) lightness (L*) and redness (a*) values of PM and BF muscles, the latter had also higher yellowness (b*, P < 0.0001). The collagen and protein contents were significantly higher in CWP group in both PM and BF muscles, while fat was lower (P < 0.001) only in BF muscle. The use of CWP into broilers’ diets did not negatively impact the textural properties, i.e., hardness, adhesiveness, cohesiveness, springiness, gumminess, chewiness, and resilience of PM and BF, showing similar values in both groups. Also, PM and BF muscles of birds fed CWP had significantly higher (P < 0.05) levels of C:18:3n-3 and C:20:5n-3 compared with birds fed SBM. The n-6/n-3 PUFA ratio was significantly lower in CWP group (11.72 and 7.00) compared to SBM (13.47 and 12.63) for both PM and BF muscles. These results indicate that CWP can be considered a promising protein source for broiler chickens’ feed.

Sources identification of ammonium in PM2.5 during monsoon season in Dhaka, Bangladesh

Ammonia (NH3) is taken up by fine particulate matter (PM2.5), and there are concerns about its impact on the environment and health. The source of NH3, which was thought to be of agricultural sources, has recently been suspected to be non-agricultural sources in urban areas. Here, we collected PM2.5 during the monsoon season in Dhaka, Bangladesh, the most polluted city in the world, and analyzed the δ15N-NH4+ in PM2.5. As the result, the δ15N-NH4+ ranged from 9.2 ‰ to 34.4 ‰ (average: 20.7 ± 4.8 ‰), the highest of any of the averaged values annual reported in previous researches. In order to perform source analysis, the NH3 concentrations were estimated using the thermodynamic model ISORROPIA-II. The estimated concentration of NH3 gas averaged 40.8 μg/m3 (3.0–154.6 μg/m3). The contributions calculated with the mixing model to the δ15N-NH4+ values in PM2.5 in Dhaka, Bangladesh averaged 25.3 ± 14 %, 22.8 ± 10 %, 26.5 ± 15 %, and 25.4 ± 10 % for waste, fertilizer, NH3 slip, and fossil fuel combustion, respectively. Non-agricultural sources (NH3 slip, and fossil fuel combustion) accounted for almost half (51.9 %) of the contributions. In addition, the several validation tests of the isotope mixing model were also performed. For validating the uncorrected and corrected source data for δ15N-NH3, the contribution of non-agricultural sources with uncorrected source data would have been very high (>80 %), much higher than the corrected source data.

Linear and nonlinear framework for interval-valued PM2.5 concentration forecasting based on multi-factor interval division strategy and bivariate empirical mode decomposition

To forecast possible air pollution risks, a large number of models have been built to predict the daily average or hourly value of PM2.5 concentrations. In fact, due to the complexity of PM2.5 formation and the diversity of its influencing factors, PM2.5 concentrations may fluctuate greatly during a certain period, single-valued methods cannot present this uncertainty and variability. Therefore, this paper develops a hybrid modeling framework that combines the elastic net (EN) and multivariate relevance vector machine (MVRVM) for interval-valued PM2.5 time series (IPMTS) forecasting. Following the philosophy of the “linear and nonlinear” modeling framework, the EN and MVRVM are applied to capture the linear and nonlinear patterns hidden in the IPMTS. Different from existing studies that directly model linear and nonlinear patterns of time series, we introduce the multi-factor interval division (MFID) strategy and bivariate empirical mode decomposition (BEMD) algorithm into linear and nonlinear pattern modeling, respectively. This enhanced linear and nonlinear framework (termed MFID-EN-BEMD-MVRVM) can consider the possible linear relationship between PM2.5 and its related factors within the intervals and model the nonlinear pattern of IPMTS at multiple scales. The IPMTS extracted from four municipalities in China are used to validate the efficiency of the proposed model. Experimental results show that the MFID-EN-BEMD-MVRVM model achieves better forecasting performance than some benchmarks and state-of-the-art models in terms of comprehensive evaluation criteria. In addition, from the application analysis, the proposed interval-valued PM2.5 modeling architecture has the possibility of real-time forecasting.

A Suitable Model for Spatiotemporal Particulate Matter Concentration Prediction in Rural and Urban Landscapes, Thailand

Spatiotemporal particulate matter (PM) concentration prediction using MODIS AOD with significant PM factors in rural and urban landscapes in Thailand is necessary for public health and has been complicated by the limitations of PM monitoring stations. The research objectives were (1) to identify significant factors affecting PM10 concentrations in rural landscapes and PM2.5 in urban landscapes; (2) to predict spatiotemporal PM10 and PM2.5 concentrations using geographically weighted regression (GWR) and mixed-effect model (MEM), and (3) to evaluate a suitable spatiotemporal model for PM10 and PM2.5 concentration prediction and validation. The research methodology consisted of four stages: data collection and preparation, the identification of significant spatiotemporal factors affecting PM concentrations, the prediction of spatiotemporal PM concentrations, and a suitable spatiotemporal model for PM concentration prediction and validation. As a result, the predicted PM10 concentrations using the GWR model varied from 50.53 to 85.79 µg/m3 and from 36.92 to 51.32 µg/m3 in winter and summer, while the predicted PM10 concentrations using the MEM model varied from 50.68 to 84.59 µg/m3 and from 37.08 to 50.81 µg/m3 in both seasons. Likewise, the PM2.5 concentration prediction using the GWR model varied from 25.33 to 44.37 µg/m3 and from 16.69 to 24.04 µg/m3 in winter and summer, and the PM2.5 concentration prediction using the MEM model varied from 25.45 to 44.36 µg/m3 and from 16.68 and 23.75 µg/m3 during the two seasons. Meanwhile, according to Thailand and U.S. EPA standards, the monthly air quality index (AQI) classifications of the GWR and MEM were similar. Nevertheless, the derived average corrected Akaike Information Criterion (AICc) values of the GWR model for PM10 and PM2.5 predictions during both seasons were lower than that of the MEM model. Therefore, the GWR model was chosen as a suitable model for spatiotemporal PM10 and PM2.5 concentration predictions. Furthermore, the result of spatial correlation analysis for GWR model validation based on a new dataset provided average correlation coefficient values for PM10 and PM2.5 concentration predictions with a higher than the expected value of 0.5. Subsequently, the GWR model with significant monthly and seasonal factors could predict spatiotemporal PM 10 and PM2.5 concentrations in rural and urban landscapes in Thailand.

Statistical analysis of the temporal change of PM10 levels in the city of Sivas (Turkey).

The objective of this study is to statistically examine the variation of PM10 values measured at three stations in the center of Sivas between the years 2016 and 2020. Hourly PM10 measurement values were taken from three different stations (İstasyon Kavşağı, Meteoroloji, and Başöğretmen AQMSs) in the city center. Then the mean values of the measurements obtained between 2016 and 2020 were compared according to the years and the stations, as well as with the limit values given in the Regulation on Air Quality Assessment and Management(RAQAM). Analyses of variance were conducted to determine any differences between PM10 levels and 24-h limit values of PM10 for Turkey and between PM10 values of stations over the years. Considering the 5-year mean values, the mean value of all PM10 concentrations measured in the city center was calculated as 56.36 µg/m3. No statistical difference was found between the PM10 values measured in 2017 and 2018 at the İstasyon Kavşağı AQMS, and the comparisons of PM10 between stations over the years showed no difference between the Meteoroloji AQMS and the Başöğretmen AQMS in 2019 and 2020. The Spearman’s rank-order correlation results of PM10 over the years among the stations in the city showed that the strongest relationship was a moderate one between the years 2019 and 2020 with regard to the İstasyon Kavşağı AQMS. Probable dust transports were examined for the days when PM10 was at its highest, and the conclusion was that desert dust coming from the continent of Africa (south) to the center of Sivas had been effective.

Levels of indoor particulate matter and association with asthma in children in Benin City, Nigeria.

The relationship between indoor particulate matter and asthma in children was assessed in this study. Forty-five (45) locations were randomly selected across the five local government areas in Benin City, Edo State, for air quality assessment. Indoor and outdoor particulates (PM1.0, PM2.5, and PM10) were monitored monthly using a handheld BLATN particulate sampler (Br-Smart-126S series). Reported clinical cases of asthma in children from 2008 to 2017 were collected from two major hospitals in the metropolis. The data obtained were analysed with SPSS for Windows version 21.0. The average concentrations of indoor and ambient PM ranged between 10.7-26.2 and 19.0-49.4µg/m3 (PM1.0), 27.4-59.6 and 45.6-93.0µg/m3 (PM2.5), and 33.5-67.9 and 60.9-106.1µg/m3 (PM10) in the wet and dry seasons. PM2.5 and PM10 concentrations were observed above the WHO standards. Indoor particulate concentration was significantly (p = 0.001-0.012) higher in the dry season across the locations. Outdoor PM correlated positively (R = 0.568-0.855, p < 0.05; R2 = 0.322-0.724, p < 0.001) with their corresponding indoor PM concentration. The hazard ratio (HR) values of PM2.5 and PM10 exceeded 1 in all the sampling locations during the dry season, while the mean total hazard ratio (THR) of both PM metrics was considerably higher during the dry season than in the wet season. Indoor PM concentrations showed a significant positive correlation with reported cases of asthma (R = 0.498-0.542, p < 0.001) and accounted for 40.6% of the asthma cases during the dry season. The study showed that children in the selected households are at risk of increased asthma exacerbation due to exposure to particulate matter pollution.

Inventory of Commercial Cooking Activities and Emissions in a Typical Urban Area in Greece

The pollutants emitted during meal preparation in restaurants deteriorate the air quality. Thus, it is an environmental issue that needs to be addressed, especially in areas where these activities are densely located. The purpose of this study is to examine the impact on air quality from commercial cooking activities by performing a qualitative and quantitative analysis of the related parameters. The area of interest is located in the southeastern Mediterranean (Greater Athens area in Greece). Due to the lack of the necessary activity information, a survey was conducted. Emissions from the fuel burnt during the cooking procedures were calculated and it was found that, overall, 940.1 tonnes are attributed to commercial cooking activities annually (generated by classical pollutants, heavy metals, particulates and polycyclic aromatic hydrocarbon emissions). Comparing the contribution of different sources to the pollutants emitted, it was found that commercial cooking is responsible for about 0.6%, 0.8% and 1.0% of the total CO, NOx and PM10 values. Cooking organic aerosol (COA) and volatile organic compound (VOC) emissions from grilled meat were also calculated, accounting for 724.9 tonnes and 37.1 tonnes, respectively. Monthly, daily and hourly profiles of the cooking activities were developed and emissions were spatially disaggregated, indicating the city center as the area with higher values. Numerical simulations were performed with the WRF/CAMx modeling system and the results revealed a contribution of about 6% to the total PM10 concentrations in the urban center, where the majority of restaurants are located.

Experimental investigation on utilization of distillery sludge mixed with coal as a Low-grade fuel in brick kiln industry and product analysis

Energy demand has been considerably increasing since the last few decades. This trend is expected to continue in the coming years and hence alternative energy sources look more attractive and practically feasible. Distillery sludge has emerged as an alternative promising renewable energy source due to its high calorific value, carbon content and volatile matter. Distillery sludge after mixing with coal in different proportion (3:1, 3:2, 1:1 and 1:3) was used in the brick kiln industry as a combustion fuel for the different time of baking. The study results showed that 60 % of coal mixed with 40 % sludge i.e. 3:2 ratio with 4 h baking time was found suitable for the operation of brick kiln plant due to optimum compressive strength (5.35 MPa) and water absorption (17.09 %). On analyzing the flue gas emission characteristics during the operation value of PM (482 mg/Nm3) for coal mixed sludge at the ratio of 3:2, the flue gas emission values were within the prescribed limit of regulatory authority. The other mineralogical properties of bottom ash indicated that it is rich in calcium sulphate and aluminates which can further be used in cement and construction industries. It is recommended that coal mixed sludge in the ratio 3:2 may be utilized as a fuel for partial replacement of coal in the brick kiln industry.

Promoting Pedestrian Transportation to Reducing Air Pollution from Urban Transport

Increasing air pollution around the world causes many problems, especially in the field of health. Air pollution affects not only human health but also other living things' health. The factors that cause air pollution the most are heating, industry, and transportation. Many countries in the world carry out various studies to reduce the effect of these factors on air pollution. Especially in the field of transportation, studies have been done quite a lot in recent years. In this study, air pollution caused by transportation in Erzurum, Turkey has been investigated. Emission amounts of NOX, PM10, and SO2 values have been calculated according to the types of vehicles in the city. Then, the amount of emissions from transportation in the total sector has been revealed. The transportation structure of the city has examined in general terms and the missing aspects in terms of pedestrian transportation have been revealed. Finally, some solution proposals aiming to encourage the use of pedestrian transportation and micro mobility vehicles in order to reduce motor land vehicles are presented.

Air quality change and public perception during the COVID-19 lockdown in India

This study aims at analyzing the change in air quality following the COVID-19 lockdown in India and its perception by the general public. Air quality data for 100 days recorded at 193 stations throughout India were analyzed between 25th March to 17th May 2020. A nationwide online survey was conducted to obtain public perceptions of air quality improvement (n = 1750). On average, approximately 40% improvement in the air quality index was observed, contributed by a reduction in 40% of PM10, 44% of PM2.5, 51% of NO2 and 21% of SO2. There was a significant difference between the levels of all the pollutants before and after the lockdown (p < 0.05), except ozone. The correlation between PM10 and PM2.5 with ozone was significant after the lockdown period, indicating that a significant portion of the particulates present in the atmosphere after the lockdown period is secondary. The values of PM2.5/PM10 were found to be >0.5 in North East states and this observation points to the long-distance transport of PM2.5 from other places. The survey for public perception showed that 60% of the respondents perceived improvement in air quality. Household emissions were perceived to be a significant source of pollution after the lockdown. An odds ratio (OR) of 17 (95%, CI: 6.42, 47.04) indicated a very high dependence of perception on actual air quality. OR between air quality and health improvement was 5.2 (95%, CI: 2.69, 10.01), indicating significant health improvement due to air quality improvement. Google Trends analysis showed that media did not influence shaping the perception. There was a significant improvement in the actual and perceived air quality in India after the COVID-19-induced lockdown. PM10 levels had the most decisive influence in shaping public perception.

Spatial Analysis of Acute Respiratory Infection (ARI) Based On the Air Pollution Standard Index (PSI) at DKI Jakarta Region in 2018-2019

Introduction: Acute respiratory infection (ARI) is a health problem causing global morbidity and mortality in Indonesia, with 18.8 billion cases and more than six million deaths observed in 2016. Between 2013 and 2018, the diagnosis of ARI prevalence reportedly experienced a 10% decrease from 12.5-2.5%, within 10 provinces, including DKI Jakarta, Indonesia. Methods: This study aims to identify the spatial analysis of ARI events using an ecological method, based on the Air Pollution Standard Index (PSI) at DKI Jakarta between 2018 and 2019. Results and Discussion: Data analysis was performed by mapping case description through Quantum GIS, correlation assessment, as well as linear regression with SPSS scatter plot. Based on the bivariate analysis, the correlation assessment and linear regression of the ARI event with PM10 had positive regression in 2018 and 2019, at (R)0.649 and (R)0.0630, respectively. Conclusion: The highest PM10 values in Kelapa Gading and Cipayung districts increased the case of ARI fluctuations within two years. Therefore, the environmental health service office focused on the air quality evaluation and prevention control of ARI cases.

Estimation of Atmospheric PM10 Concentration in China Using an Interpretable Deep Learning Model and Top‐of‐the‐Atmosphere Reflectance Data From China’s New Generation Geostationary Meteorological Satellite, FY‐4A

AbstractThe rapid urbanization in China and the long‐range transport dust (LRTD) from arid and semi‐arid areas has resulted in an increase of PM10 concentration. In this study, an interpretable deep learning model [deep forest (DF)] with FY‐4A top‐of‐the‐atmosphere reflectance (TOAR) data were used to obtain the hourly PM10 in China. The optimal hourly average R2 of 10‐fold cross validation can achieve 0.85 (13:00 Beijing time); The R2 (RMSE, μg/m³) of the daily, monthly, and annual averages were 0.82 (24.16), 0.97 (6.53), and 0.99 (2.30), respectively. Using TOAR data, the DF model performed better than other machine learning models. The feature importance of the TOAR‐PM10 model showed that TOAR and meteorological elements both contributed significantly to the model. In spring, the PM10 in northern China was greater than that in southern China, which may be related to the LRTD. Excluding the dust weather periods, the areas with high PM10 values in China were mainly in cities and their suburbs, where were correlated with human activities. During a dust weather process, LRTD increased PM10 in northern China by 80.4%. During a mixture haze and dust weather process, the PM10 increased by 130.2% in northern China, of which LRTD led to an increase of 73.7%. The sources (from the Taklimakan Desert in China) and transmission paths of these two LRTD processes were similar. The contribution of LRTD to PM10 was related to dust intensity and meteorological conditions. The results showed that LRTD and local pollution to PM10 was both important in haze periods.

Stable C and N isotopes of PM2.5 and size-segregated particles emitted from incense stick and cigarette burning

This work measured the δ13C and δ15N signatures in PM2.5 and size-segregated particles emitted from incense stick and cigarette burning in different brands or nicotine contents for pollution source identification indoors. Three popular brands of incense stick and cigarette were selected for experiments. A personal environmental monitoring sampler and a Sioutas cascade impactor were used to collect PM2.5 and size-segregated particles, respectively, for isotopic signatures analyses. Our data showed that both δ13C and δ15N values were heavier from incense stick burning (δ13C: 27.3 ± 0.5; δ15N: 8.63 ± 1.35) than cigarette (δ13C: 28.5 ± 0.2; δ15N: 4.15 ± 0.69). The scatter plots of δ13C and TC/PM2.5 and of δ15N and TN/PM2.5 can be applied to distinguish particle pollution sources and assess the influence of cigarette burning to PM2.5 according to different nicotine contents. The δ13C values in size-segregated particles were similar to incense stick or cigarette burning; the δ13C values in PM2.5 were significantly higher than those in size-segregated particles. However, the nitrogen amount was too low in most of the size-segregated particles to analyze δ15N from incense stick and cigarette burning. These results suggest that the δ13C signatures on PM2.5 cannot represent the isotopic characteristics of size-segregated particles and δ15N has limitation for pollution source identification of different particle sizes.

A holistic approach to the air quality of Konya City, Turkey.

Considering an integrated approach to assess all of the measured pollutants in a diurnal, monthly, seasonal, and annual time scales and understanding the mechanisms hidden under low air quality conditions are essential for tackling potential air pollution issues. Konya, located in central Anatolia, is the largest province of Turkey with a surface area of 40,838 km2 and has different industrial activities. The lack of recent detailed studies limits our information on the underlying air pollution levels in Konya and obscuring policymakers to develop applicable mitigation measures. In this study, we used hourly monitored air quality data of CO, NO2, NOx, PM10, PM2.5, and SO2 from five stations in Konya and investigated the temporal and spatial variabilities for the 2008–2018 period via statistical analysis. Upon analysis, particulate matter was found to be the dominant pollutant deteriorating the air quality of Konya. The highest 2008–2018 periodic mean value of PM10 was found in Karatay Belediye as 70.5 µg/m3, followed by 67.4 µg/m3 in Meram, 58.7 µg/m3 in Selçuklu, and 43.7 µg/m3 in Selçuklu Belediye. The 24-h limit value of PM10 given as 50 µg/m3 in the legislation was violated in all of the stations, mainly during winter and autumn. High positive correlations were found among the stations, and the highest correlation was obtained between Selçuklu Belediye and Karatay Belediye with a Pearson correlation coefficient of 0.77. Long-term data showed a decreasing trend in PM10 concentrations. Diurnal variability is found to be more pronounced than weekly variability. For almost all of the pollutants, except for photochemical pollutants like O3, a prominent result was the nighttime and morning rush hours high-pollutant levels. A case study done for the January 29, 2018 to February 05, 2018 episode showed the importance of meteorology and topography on the high levels of pollution. Limitation of the pollutant transport and dilution by meteorological conditions and the location of Konya on a plain surrounded by high hills are believed to be the main reasons for having low air quality in the region.

Влияние тетрациклинов на патологию митоза в клетках образовательной ткани корней Allium cepa L.

The effect of tetracyclines (tetracycline and doxycycline) on genetic apparatus damage in the cells of root meristem Allium сера L. in the first metaphase after processing and after finishing the recovery period is investigated. Research methods: Allium test, cytogenetic analysis, statistical analysis. The experiment was conducted on a batch of the Stuttgarten variety which is genetically unstable as the result of micronucleus test. It’s indicated that the reaction of the tested material to the effect of tetracyclines depends on the concentration and duration of antibiotics. Aneugenic type aberrations such as mitosis, chromatic agglutination up to the formation of clots were prevailing in the cycling cells. An increase in the proportion of PM (chromatic agglutination, various bridges), the result of which is nucleus pycnosis and cell death was indicated for this genotype after the recovery period. It’s observed that after the recovery period there is a significant increase of cells with mitosis under the influence of tetracycline in the concentration of 20.0 mg/l, on exposure of 23 and 48 hours. The negative influence of tetracycline in the concentration of 100.0 mg/l was investigated, PM value reached 64.2%; the decrease of cells with PM wasn’t observed after the recovery period. In both cases cells with mitosis and chromatic agglutination were dominating. Doxycycline effect in the concentration of 20.0 and 100.0 mg/l caused the doubling of PM in comparison with control. After the recovery period a number of cells regardless of experienced concentration grew due to the increased number of cells with mitosis and chromatic agglutination. It’s necessary to mention different effects of meristematic cells of onion roots under the action of structural isomer which are tetracycline and doxycycline. It’s worth mentioning that the increase in concentration of bacteriostatic antibiotic (tetracycline and doxycycline) is necessary for maximum inactivation on the one hand. On the other hand, negative processes increase in the cells of eukaryotic organisms during the passage of the cell cycle, particularly, mitosis.

Role of core-shell structure in binary mixture of amino sulfonate amphoteric surfactant with nonionic surfactant in solubilization behavior of pyrene

In order to understand the role of core-shell structure of mixed surfactant micelle and the effect of hydrophilicity of amphiphile in the enhanced remediation of contaminated soils and water, a novel amphoteric sodium 3-(N-dodecylethylenediamino)− 2-hydroxypropyl sulfonate (C12AS), three nonionic octylphenol polyoxyethylated ethers with unit number n of oxyethylene glycol ether (OP-n, n = 4, 7 and 10) and these binary mixtures of C12AS/OP-n were adopted to probe the solubilization behavior of pyrene by both the UV–vis spectrometric and the 1H NMR techniques. Some parameters including the molar solubilization ratio (MSR), the partition coefficient (Pm), the standard free energy change (∆Gp) of partition, the interaction parameter (B) based on regular solution theory and the ratio (K1/n) of first stepwise association coefficient (K1) and aggregation number (n) in mixed micelle were estimated using different models. In these single surfactants, the values of MSR and Pm depend mainly on the hydrophilic-lipophilic balance (HLB) of amphiphiles for the homologues of OP surfactants. The solubilization behavior in these mixtures, however, does not again follow the HLB effect, but is subjected to the mixing ratio of component in mixed micelle and the micellar structure. The data from these B and K1/n values can gain some understanding in tune with these parameters, e.g., MSR, Pm, R, etc. Based on the chemical shift of hydroxyl group, the core-shell structure of mixed micelle assumed in this investigation is proposed to demonstrate the solubilization locus and rationally describe the spontaneous process of solubilization and the related behaviors. These findings will help with understanding the solubilization behavior of hydrophobic organic compounds in these surfactants with a core-shell structure of micelle and designing the surfactant formulations in the surfactant enhanced remediation of contaminated soils and water.