Monthly Average Concentration Research Articles

Aerosol Black Carbon Measurement at High Altitude Western Ghats Location of Ooty, Tami Nadu

The aerosol Black Carbon (BC) are particles formed from the incomplete combustion of fossil fuel and biomass combustion which was collected from high altitude location in Western Ghats, Ooty, Tamil Nadu using Aethalometer Instrument (model AE-31 of Magee Scientific, USA) during 2017. The monthly averaged BC concentration shows highest value of 1.88 ± 0.44 µg m-3 during April with the annual mean of 0.83 ± 0.20 µg m-3. The diurnal variation shows higher seasonality especially in winter and summer with highest peak in 17:00 to 22:00 hr. The aerosol optical depth derived from MERRA 2 model showed annual mean of 0.29 and it is in line with BC concentration. The results showed that the concentrations are varying within a day, month and season depends on the local meteorological conditions.

Characterization of multiple atmospheric pollutants during haze and non-haze episodes in Beijing, China: Concentration, chemical components and transport flux variations

Characteristics of submicron particulate matter, including its components, during December 5–30, 2016, were comprehensively investigated in Beijing. The surface transport flux was calculated as well as the cross-border transport influence of Beijing and the North China Plain (NCP) on Beijing University of Technology (BJUT) based on the non-refractory submicron particles (NR-PM1) and species, PM2.5, and gaseous pollutant observations, together with wind vectors. The Weather Research & Forecasting (WRF) and Comprehensive Air Quality Model with Extension (CAMx) were applied to demonstrate the vertical PM2.5 flux distribution. These results showed that the monthly average concentration of NR-PM1 was 86.1 ± 86.5 μg m−3, with organics forming the major fraction (49.2 ± 11.1%), followed by NO3− (19.1 ± 6.3%), SO42− (15.8 ± 6.4%), NH4+ (10.8 ± 2.6%), and Cl− (5.1 ± 2.9%). The accumulation and dissipation of pollutants were related to the wind vector, with higher concentrations in the southern and eastern directions with low wind speed (WS), and lower concentrations in the northwestern direction with high WS. The net flux intensities were stronger from WB to BJUT for particulate matter and species, from EB to BJUT for gaseous pollutants and from NB to BJUT for all pollutants, which might attribute to the mutual influence of the pollutant concentration and wind vector. All the pollutant flux intensities were generally stronger in the heavy pollution episodes (HPEs) and red alert episodes (RAEs) than those in the non-polluted episodes (NPEs). Moreover, the PM2.5 net flux varied with the height; the maximum total net flux occurred at a height of 252 m. The variations in PM2.5 flux at the high-altitude layer were similar to those at the low-altitude layer, in which the former was approximately 1.5–2 times the latter. Furthermore, the external transport could exert important influence before reaching the most severe stage of pollution, while the local emissions had a greater potential to form heavy pollution extremes. Overall, the aforementioned results could provide the scientific support for proposing effective joint control measures and mitigating the adverse effects of heavy pollution in NCP.

Atmospheric Air Pollution with Polycyclic Aromatic Hydrocarbons in the Krasnoyarsk Region Cities

The results of analysis of the content of benzo(a)pyrene and other high-molecular polycyclic aromatic hydrocarbons (PAH) in atmospheric air samples collected in 2018 in industrial cities of the Krasnoyarsk region at the state monitoring network of Roshydromet are presented. The PAH measurements were performed by the high-performance liquid chromatography method, using a fluorometric detector. The monthly average concentrations of benzo(a)pyrene in the atmospheric air exceeded 10 MPC in the cities of Minusinsk, Lesosibirsk, Krasnoyarsk, and Achinsk. The maximum monthly average content of benzo(a)pyrene during the observation period in 2018 was found in Minusinsk (January, 90 MPC) and Lesosibirsk (January, 59 MPC). The main reasons for the increased levels of air pollution with PAH are investigated. Seasonal variability in the content of benzo(a)pyrene and other PAH in the atmospheric air of the Krasnoyarsk region cities with a maximum in winter and a minimum in summer is shown. The annual average concentration of benzo(a)pyrene in the atmospheric air in 2018 decreased in the following series: Minusinsk (17.2 ng/m3), Lesosibirsk (12.4 ng/m3), Krasnoyarsk (6.5 ng/m3), Achinsk (3.6 ng/m3), and Norilsk (0.6 ng/m3). A similar decreasing concentration trend in this series of cities is typical for other PAH. The level of air pollution with benzo(a)pyrene in the cities of Minusinsk, Lesosibirsk, Krasnoyarsk in 2018 is characterized as “very high.” The pyrogenic nature of PAH in the atmosphere of the surveyed cities of the Krasnoyarsk region is shown using molecular ratios.

ATMOSPHERIC METHANE EMISSIONS FOR ARGENTINA. COMPARISON WITH TROPOMI SATELLITE MEASUREMENTS

Abstract. Methane emissions have very important effect on global radiative forcing. Therefore, reducing these emissions has been proposed as an effective short-term strategy to mitigate global warming, in parallel with reductions in long-lived carbon dioxide (CO2) for long- term temperature stabilizations. In this context, Argentina emits 3645 Gg of CH4 mainly from livestock production, biomass burning and natural gas production. Since 2018, TROPOMI instruments provide global coverage on methane column-average mole fraction of dry air (XCH4), and height profiles of methane concentrations. We compare two available methane inventory: a national (a high resolution of own ellaboration: GEAA) and an international (EDGAR) emissions database with TROPOMI measurements. By performing inverse satellite retrieval we evaluate the ability of remote sensing information to detect possible hotspot methane emissions and compare these results with the two inventories. From these analyzes, we observe that the latitudinal averages of the continental sector increase at a rate of 10 ppb/degree, from south to north, while the maritime sector remains constant. From a temporary perspective, the average monthly concentration amplitude range varies 40 to 50 ppb, with minimum values in March and maximum values in September.

Government environmental governance, structural adjustment and air quality: A quasi-natural experiment based on the Three-year Action Plan to Win the Blue Sky Defense War

Improving air quality is an era task for China to transform its economic development model and enhance its environmental governance capabilities. This article take the Chinese government's Three-year Action Plan to Win the Blue Sky Defense War (abbreviated as the Blue Sky Defense War) as a quasi-natural experiment and use regression discontinuity design (RDD) to evaluate the governance effect of this policy. The study found that the Blue Sky Defense War reduced the monthly average concentration of PM2.5 and PM10 in cities by 14.49 and 23.43, respectively. Heterogeneity analysis shows that the Blue Sky Defence War has a more prominent effect on urban air quality management based on PM10 assessment; Jing-Jin-Ji region and surrounding areas are the key points to ensure the achievement of air management. Consistent and effective environmental governance policies, transparent and timely information disclosure and structural adjustment are all powerful guarantees for the effectiveness of the Blue Sky Defense War. These research conclusions provide new ideas for developing countries to formulate practical environmental pollution control policies.

Low-cost air pollution monitoring system-an opportunity for reducing the health risk associated with physical activity in polluted air.

The issue of air pollution by particulate matter (PM) concerns many places in the world. At the same time, many residents undertake physical activity (recreation, rehabilitation, sport) in the open air. Generally, the amount of dust concentration depends on both the place (center or periphery of the city) and the time of day. In the present study we describe the outcome of monitoring of the state of air pollution by particle matter (PM10) in the Kraków agglomeration area in order to show that it can provide information concerning air quality in the area where people practice varied kinds of sports in the open air. The measurements of PM10 have been made by a few stations with identical construction working as one network. The details of the air pollution monitoring system and its data quality verification have been described. The network stations made multipoint observations across the Kraków Metropolitan Area during the year 2017 in eight locations. The locations selected represent a diverse spectrum of terrain conditions in which the Kraków agglomeration community undertakes physical activity. For most months of 2017, the minimum monthly average 4-hour PM10 concentrations were recorded between 10–14 h, regardless of location, whereas the maximum was between 18–22. We also noticed a huge differences in the average monthly value of PM10 in some locations within the Kraków agglomeration—ranging between 4.9–339.0 µg m−3. This indicates that some regions of the city are more suitable for performance of physical activity in the open air than others. In conclusion, we postulate that a low-cost air pollution monitoring system is capable of providing valuable information concerning air quality in a given region, which seems to be of importance also to people who practice varied sports activities in the open air.

Spatiotemporal Variation in Phytoplankton Community Driven by Environmental Factors in the Northern East China Sea

The East China Sea (ECS) is the largest marginal sea in the northern western Pacific Ocean. In comparison to various physical studies, little information on the seasonal patterns in community structure of phytoplankton is currently available. Based on high performance liquid chromatography (HPLC) pigment analysis, spatiotemporal variations in phytoplankton community compositions were investigated in the northern ECS. Water temperature and salinity generally decreased toward the western part of the study area but warmer conditions in August led to strong vertical stratification of the water column. In general, major inorganic nutrient concentrations were considerably higher in the western part with a shallow water depth, and consistent with previous results, had no discernable vertical pattern during our observation period except in August. This study also revealed PO4-limited environmental conditions in May and August. The monthly averaged integral chlorophyll-a concentration varied seasonally, highest (35.2 ± 20.22 mg m−2) in May and lowest (5.2 ± 2.54 mg m−2) in February. No distinct vertical differences in phytoplankton community compositions were observed for all the sampling seasons except in August when cyanobacteria predominated in the nutrient-deficient surface layer and diatoms prevailed at deep layer. Canonical correlation analysis results revealed that nutrient distribution and the water temperature were the major drivers of the vertical distribution of phytoplankton communities in August. Spatially, a noticeable difference in phytoplankton community structure between the eastern and western parts was observed in November with diatom domination in the western part and cyanobacteria domination in the eastern part, which were significantly (p < 0.01) correlated with water temperature, salinity, light conditions, and nutrient concentrations. Overall, the two major phytoplankton groups were diatoms (32.0%) and cyanobacteria (20.6%) in the northern ECS and the two groups were negatively correlated, which holds a significant ecological meaning under expected warming ocean conditions.

Pollution Characteristics, Transport Pathways, and Potential Source Regions of PM2.5 and PM10 in Changchun City in 2018

Air pollution has attracted increasing attention in recent years. Cluster analysis, scene analysis, and the potential source contribution function (PSCF), based on the backward trajectory model, were used to identify the transport pathways and potential source regions of PM2.5 and PM10 (particulate matter with an aerodynamic diameter of not more than 2.5 µm and 10 µm) in Changchun in 2018. In addition, the PSCF was slightly improved. The highest average monthly concentrations of PM2.5 and PM10 appeared in March and April, when they reached 53.9μg/m3 and 120.0 μg/m3, respectively. The main potential source regions of PM2.5 and PM10 were generally similar: western Jilin Province, northwestern Inner Mongolia, northeastern Liaoning Province, and the Yellow Sea region. The secondary potential source regions were southern Russia, central Mongolia, western Shandong Province, eastern Hebei Province, and eastern Jiangsu Province. The northwest and southwest directions were found to be the two pathways that mainly affect the air quality of Changchun City. Moreover, the northwestern pathway had a larger potential contribution source area than the southwestern pathway. The airflow in the southwest direction came from Liaoning Province, Shandong Province, and the Yellow Sea region. This mainly occurred in summer; its transmission distance was short; it had a relatively higher weight potential source contribution function (WPSCF) value; it can be regarded as a local source; and its representative pollutants were SO2 (sulfur dioxide), CO (carbon monoxide), and O3 (ozone). The northwestern pathway passed through Russia, Mongolia, and Inner Mongolia. The transmission distance of this pathway was longer; it had a relatively lower WPSCF value; it can be considered as a natural source to a certain extent; it mainly occurred in autumn and, especially, in winter; and the representative pollutants of this pathway were NO (nitric oxide), NOx (nitrogen oxide), PM2.5, and PM10.

Sazonalidade da Concentração de CO2 na camada limite atmosférica sobre o lago Curuá-Una, Santarém-Pará

Rivers and lakes play an essential role in the global carbon cycle, not just in the transport of organic and inorganic particles to the oceans. Recently, it has been discovered that they also contribute greatly to the emission of CO2 into the atmosphere, assuming a prominent role as a greenhouse gas. This work aims to study the seasonality of the CO2 concentration in the Atmospheric Limit Layer (CLA) over the artificial lake of Curuá-Una, during the period from June 2015 to June 2016. The study was carried out at the hydroelectric power plant of Curuá-una, located 70 km southwest of the city of Santarém, in the state of Pará. The data were obtained using a micrometeorological buoy contained by a system of covariance of turbulent vortices, where the concentration of CO2, temperature, wind speed were obtained, as well as variables that describe the turbulent flow of the atmosphere. The results show that the average monthly concentration of maximum CO2 was 405 ppm in June 2015, while the lowest average concentration was observed in December of the same year. An interesting result found in this study was the relationship between the CO2 concentration and the intensity of vertical atmospheric turbulence (σw).

The Great Smog Month and Spatial and Monthly Variation in Air Quality in Ambient Air in Delhi, India.

Background.In recent years, poor urban air quality in Delhi, India has gained significant attention. Episodic events including crop stubble burning and Diwali celebrations are considered major factors in the worsening quality of ambient air.Objective.This study aimed to investigate spatial and monthly variation as well as the role of episodic events in ambient air quality in Delhi, including the ‘Great Smog' month of November 2017.Methods.Monitoring of air pollutants (particulate matter (PM10, PM2.5, PM1) and nitrogen dioxide (NO2)) was carried out at three distinct locations of Delhi from April 2017–February 2018. The concentration of NO2 was measured using a modified Jacob and Hochheiser method and PM was measured using a GRIMM aerosol spectrometer. Air quality index was also determined to identify the effects of air pollution on human health.Results.Overall, the levels of air pollution were found to be approximately 2.1–3.2 times higher along a traffic intersection and about 1.4–2.0 times higher in a commercial area compared with an institutional area. The highest average monthly concentrations of PM10, PM2.5, PM1 and NO2 were 768, 374, 298 and 149 μg/m3, respectively, during the Great Smog month of November 2017. November and August were recorded as the most polluted and cleanest months, respectively, in the city. Generally, poor to severe categories of the air quality index (AQI) were obtained from October to February. Higher concentrations during November were attributed to stubble burning in the nearby states of Delhi with the additive effect of fireworks during Diwali celebrations.Conclusions.Severe ambient air quality as observed in the present study is a serious matter of concern for the health of Delhi's population. To control spikes in poor air quality during episodic events, it is imperative to raise awareness among farmers regarding the severe health hazards of stubble burning.Competing Interests.The authors declare no competing financial interests.

Measurements of surface air 7Be concentrations in Saudi Arabia

The main objective of this study is to identify the atmospheric 7Be concentrations in 130 surface air samples collected from three stations located in Riyadh, Haql and Khafji cities in Saudi Arabia between November 2012 and April 2014. Monthly variations as well as seasonal patterns of 7Be were studied using a medium-volume air sampler and a gamma spectroscopy system equipped with a high-purity germanium (HPGe) detector. 7Be exhibited one maximum specific activity in summer and one minimum in winter with average monthly concentrations of 12.4 ± 0.9, 15.4 ± 1.2, and 18.0 ± 1.3 mBq m−3 in Riyadh, Haql and Khafji, respectively. Overall, the average 7Be concentration in the three stations was 12.9 ± 1.0 mBq m−3, whereas the maximum value of 29.5 mBq m−3 was registered in Khafji city in August 2013. Besides 7Be, measurements indicate observations of 40 K, 137Cs, 226Ra radionuclides in surface air samples collected from the three stations. 40 K showed measurable concentrations, whereas the concentrations of 137Cs and 226Ra were only detected in a limited number of samples.

Impacts of water partitioning and polarity of organic compounds on secondary organic aerosol over eastern China

Abstract. Secondary organic aerosol (SOA) is an important component of fine particular matter (PM2.5). Most air quality models use an equilibrium partitioning method along with the saturation vapor pressure (SVP) of semivolatile organic compounds (SVOCs) to predict SOA formation. However, the models typically assume that the organic particulate matter (OPM) is an ideal mixture and ignore the partitioning of water vapor to OPM. In this study, the Community Multiscale Air Quality model (CMAQ) is updated to investigate the impacts of water vapor partitioning and nonideality of the organic–water mixture on SOA formation during winter (January) and summer (July) of 2013 over eastern China. The updated model treats the partitioning of water vapor molecules into OPM and uses the universal functional activity coefficient (UNIFAC) model to estimate the activity coefficients of species in the organic–water mixture. The modified model can generally capture the observed surface organic carbon (OC) with a correlation coefficient R of 0.7 and the surface organic aerosol (OA) with the mean fractional bias (MFB) and mean fractional error (MFE) of −0.28 and 0.54, respectively. SOA concentration shows significant seasonal and spatial variations, with high concentrations in the North China Plain (NCP), central China, and the Sichuan Basin (SCB) regions during winter (up to 25 µg m−3) and in the Yangtze River Delta (YRD) during summer (up to 16 µg m−3). In winter, SOA decreases slightly in the updated model, with a monthly averaged relative change of 10 %–20 % in the highly concentrated areas, mainly due to organic–water interactions. The monthly averaged concentration of SOA increases greatly in summer, by 20 %–50 % at the surface and 30 %–60 % in the whole column. The increase in SOA is mainly due to the increase in biogenic SOA in inland areas and anthropogenic SOA in coastal areas. As a result, the averaged aerosol optical depth (AOD) is increased by up to 10 %, and the cooling effect of aerosol radiative forcing (ARF) is enhanced by up to 15 % over the YRD in summer. The aerosol liquid water content associated with OPM (ALWorg) at the surface is relatively high in inland areas in winter and over the ocean in summer, with a monthly averaged concentration of 0.5–3.0 and 5–7 µg m−3, respectively. The hygroscopicity parameter κ of OA based on the κ–Köhler theory is determined using the modeled ALWorg. The correlation of κ with the O:C ratio varies significantly across different cities and seasons. Analysis of two representative cities, Jinan (in the NCP) and Nanjing (in the YRD), shows that the impacts of water partitioning and nonideality of the organic–water mixture on SOA are sensitive to temperature, relative humidity (RH), and the SVP of SVOCs. The two processes exhibit opposite impacts on SOA in eastern China. Water uptake increases SOA by up to 80 % in the organic phase, while including nonunity activity coefficients decreases SOA by up to 50 %. Our results indicate that both water partitioning into OPM and the activity coefficients of the condensed organics should be considered in simulating SOA formation from gas–particle partitioning, especially in hot and humid environments.

Temporal variations and source apportionment of volatile organic compounds at an urban site in Shijiazhuang, China

Shijiazhuang, the city with the worst air quality in China, is suffering from severe ozone pollution in summer. As the key precursors of ozone generation, it is necessary to control the Volatile Organic Compounds (VOCs) pollution. To have a better understanding of the pollution status and source contribution, the concentrations of 117 ambient VOCs were analyzed from April to August 2018 in an urban site in Shijiazhuang. Results showed that the monthly average concentration of total VOCs was 66.27 ppbv, in which, the oxygenated VOCs (37.89%), alkanes (33.89%), and halogenated hydrocarbons (13.31%) were the main composite on. Eight major sources were identified using Positive Matrix Factorization modeling with an accurate VOCs emission inventory as inter-complementary methods revealed that the petrochemical industry (26.24%), other industrial sources (15.19%), and traffic source (12.24%) were the major sources for ambient VOCs in Shijiazhuang. The spatial distributions of major industrial activities emissions were identified by using geographic information statistics system, which illustrated the VOCs was mainly from the north and southeast of Shijiazhuang. The inverse trajectory analysis using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and Potential Source Contribution Function (PSCF) clearly demonstrated the features of pollutant transport to Shijiazhuang. These findings can provide references for local governments regarding control strategies to reduce VOCs emissions.

Evaluation of the Seasonal Variability of Nutrient in Water of Kuibyshev Reservoir

On the basis of generalization and analysis of long-term data, the peculiarities of the processes of pollution by nutrients of the waters of the Kuibyshev reservoir were studied and the specificity of the seasonal variability of nutrients was revealed. It was revealed that all the nutrients in the water of the Kuibyshev reservoir are characterized by seasonal variability, which is most pronounced in nitrate ions. The results of the study show that in 2009-2015 yrs perennial average monthly concentrations of nutrients did not exceed the fishery standards in the water of the Kuibyshev reservoir.

Analysis of Characteristics and Meteorological Influence Factors of Ozone Pollution in Henan Province

The spatio-temporal characteristics of ozone (O3) pollution in the Henan Province in 2017 and its relationship with particulate matter, precursors, and meteorological factors were studied using the data obtained from the air quality monitoring station and national baseline ground climate station. Results showed that the annual mean O3 concentration of a maximum daily 8-h average (MDA8) was 108 μg·m-3 in the Henan Province with the trend of summer > spring > autumn > winter. Different levels of O3 were observed in various cities. The number of days exceeding the standard was up to 88 days in Anyang, while the lowest was found in Xinyang with 17 days. The most severe of O3 pollution occurred during late spring and early summer. During this period, the average monthly concentration of O3 MDA8 was above 140 μg·m-3, and peaked in June. The qualitative and quantitative analysis showed that the monthly average concentration of O3 MDA8 was negatively correlated with particulate matter, and the O3 hourly concentration was also negatively correlated with CO and NO2. The O3 MDA8 concentration and meteorological factors (sunshine duration, temperature, rainfall, visibility, humidity, and wind speed) had different correlations during different seasons and various cities.

High-Resolution Biomass Burning Aerosol Transport Simulations in the Tropics

This study evaluates the performance of the Weather Research and Forecasting Model with Chemistry (WRF-Chem) for simulating biomass burning aerosol transport at high resolution in the tropics using two different biomass burning emission inventories. Hourly, daily, and monthly average PM10 dry mass concentrations at 5 km resolution—simulated separately using the Brazilian Biomass Burning Emission Model (WRF-3BEM) and the Fire Inventory from NCAR (WRF-FINN) and their averages (WRF-AVG) for 3 months from February to April—are evaluated, using measurements from ground stations distributed in northern Thailand for 2014 and 2015. Results show that WRF-3BEM agrees well with observations and performs much better than WRF-FINN and WRF-AVG. WRF-3BEM simulations are almost unbiased, while those of WRF-FINN and WRF-AVG are significantly overestimated due to significant overestimates of FINN emissions. WRF-3BEM and the measured monthly average PM10 concentrations for all stations and both years are 89.22 and 87.20 μg m−3, respectively. The root mean squared error of WRF-3BEM simulated monthly average PM10 concentrations is 72.00 and 47.01% less than those of WRF-FINN and WRF-AVG, respectively. The correlation coefficient of WRF-3BEM simulated monthly PM10 concentrations and measurements is 0.89. WRF-3BEM can provide useful biomass burning aerosol transport simulations for the northern region of Thailand.

МЕТАН В ПРИПОВЕРХНОСТНОМ СЛОЕ АТМОСФЕРЫ: СОВРЕМЕННОЕ СОДЕРЖАНИЕ, МНОГОЛЕТНИЕ ТРЕНДЫ И ВНУТРИГОДОВАЯ ИЗМЕНЧИВОСТЬ

The article is devoted to the empirical analysis of series of monthly mean concentrations of methane in the near-surface layer of the atmosphere from the global network of monitoring stations. They operate within the Global Atmosphere Watch (GAW) under the auspices of the World Meteorological Organization (WMO). The data is freely available at the World Data Center for Greenhouse Gases GAW/WMO (WDCGG) on its website https://gaw.kishou.go.jp/ . The temporal coverage is from the 1980s. Data series from 69 stations are considered, of which 22 stations represent the global background conditions. The rest of the stations are regional. Long-term trends in concentrations and intraannual (inter-monthly) deviations of mean monthly concentrations from long-term trends were studied. The multi-year trend was estimated using a series of 12-month running averages. To exclude systematic differences in methane concentrations, these series were adjusted to the series for the high-latitude Arctic station Alert (82° 30' N, 62° 21' W). The analysis showed that long-term trends are non-linear (including with a known pause in the growth of methane levels in 1999-2006), but are similar at most of the stations under consideration. Exceptions are 6 regional stations classified as ‘abnormal’ for methane. A possible cause of the abnormality is being under the influence of certain sources of methane (anthropogenic or natural). Long-term trends at the rest of the stations are just slightly differ from the average trend for global stations. The series of intra-annual (inter-monthly) deviations of mean monthly concentrations from long-term trends for many stations, even those located at very significant distances from each other, show high correlative similarity. However, it manifests itself at an optimal time shift from 5 months. towards earlier dates up to 6 months. towards later dates. The results of the analysis are consistent with the assumption that the intra-annual variability in methane concentration is largely driven by seasonal factors that are significantly related to latitude, including vertical mixing in the atmosphere and destruction in the troposphere in reactions with hydroxyl. The root-mean-square values of the intra-annual (inter-monthly) fluctuations in methane concentration significantly depend on latitude. The higher the latitude, the greater the overall value. Maximum values are reached in the latitudinal belt 45-50° N, and further, to the north, the Кузовкин В.В., Семенов С.М. 20 values decrease. This character of intra-annual fluctuations in the level of methane content may be explained, among other things, by significant inter-seasonal fluctuations in anthropogenic methane emissions at the indicated latitudes in countries with developed economies located in North America and Western Europe. The estimates of correlations of the series of intra-annual (inter-monthly) fluctuations of the average monthly concentrations of CH4 and CO2 showed that at optimal time shifts, they are rather high, about 0.8. Moreover, this is observed both at some polar stations and at tropical ones. This confirms the assumption that natural seasonal biogeochemical and geophysical processes play a significant role in the formation of intra-annual (inter-monthly) deviations of the methane and carbon dioxide content in the near-surface layer from long-term trends, namely, vertical mixing of air, CO2 absorption on the Earth's surface, destruction of methane in the troposphere in reactions with hydroxyl.

Spatio-temporal variations of tropospheric nitrogen dioxide in Turkey based on satellite remote sensing

The satellite observations of NO2 acquire the total tropospheric column over an area while the current ground observations lack spatial and temporal coverage. In this study the Dutch Ozone Monitoring Instrument (OMI) NO2 (DOMINO) data product v2.0 for 2004 - 2019 period was used to analyze the spatial and temporal variations of NO2 in Turkey. Considering the seasonality characteristics of NO2, we have used pixel based Seasonal Kendall (S-K) test to investigate the trend of the change. The highest values of NO2 has been found at the metropolitan areas and perimeter of the high capacity power plants in the observed period. The monthly average concentrations of NO2 are higher in winter months due to the higher demand of heating and power usage. The S-K trend test results indicate a statistically negative trend at the largest cities such as Istanbul, Ankara and Izmir. However statistically significant positive trend has been found in some areas and Syrian border provinces in particular. Our results show that there is an abrupt change by 2011 in the tropospheric NO2 concentrations, same period when the first Syrian refugees have arrived after the political disorder. The dramatic change at the emission landscape of the NO2 in the region can be explained by changes in population concentration due to political circumstances.

Analysis of NOx Pollution Characteristics in the Atmospheric Environment in Changchun City

Nitrogen oxide (NOx) pollution has become one of the most challenging problems in China in the past 20 years. In this study, on the basis of the Jilin Province Atmospheric Environmental Quality Bulletin and hourly NOx data from the Atmospheric Environment Automatic Monitoring Station in Changchun, temporal and spatial variations in NOx concentration in the province and Changchun and their relationships with various pollutants and meteorological factors were analyzed. The results show that Changchun had the highest NOx concentration of all cities in the province, with a high concentration in the center and a low concentration in the east and west. The areas with high NOx concentrations in Changchun were mainly distributed in urban centers, and the concentration in the northern part of the city was higher than that in the south. The seasonal variation and average daily variation in NOx concentration in Changchun had a bimodal distribution, and the NOx concentration in autumn and winter was higher than that in spring and summer. The maximum monthly average concentrations of NOx and nitric oxide (NO) were reached in October, and the maximum monthly average concentration of nitrogen dioxide (NO2) was reached in March. The average daily variation in NOx concentration first peaked at 07:00–08:00 in the morning, and the second peak occurred between 20:00 and 22:00 at night. The NOx concentration in Changchun was positively correlated with NO2, NO, PM2.5 (fine particulate matter), PM10 (particulate matters), CO (carbon monoxide), and pressure, and it showed a significant negative correlation with O3, temperature, wind speed, and humidity.

The Content of High-Molecular Polycyclic Aromatic Hydrocarbons in Urban Air During FIFA World Cup 2018

Polycyclic aromatic hydrocarbons including benzo(a)pyrene have been determined on aerosol particles in air sampled in several cities of the European part of Russia hosting FIFA World Cup 2018. The average monthly concentrations of benzo(a)pyrene (BaP) in none of the samples in June–July 2018 exceeded the maximum permitted concentration. The maximum average monthly concentration of BaP during the observation period has been found in Kazan (station no 8, July–0.83 ng/m3). The average concentration of BaP in the considered cities decreased along the series: Kazan (0.45 ng/m3), Kaliningrad (0.38 ng/m3), Moscow (0.35 ng/m3), Saransk (0.32 ng/m3), Nizhny Novgorod (0.31 ng/m3), Samara (0.31 ng/m3), Rostov-on-Don (0.26 ng/m3), St. Petersburg (0.22 ng/m3), Volgograd (0.16 ng/m3), Sochi (0.01 ng/m3).