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The western Pacific continental sea significantly influences the regulation of climate‐active gases budget and the burden of sulfate aerosols. An underway shipboard measurement device was used to determine the dimethyl sulfide (DMS) in the surface seawater and overlying atmosphere in the East China Continental Sea. The average concentration of DMS in atmosphere and seawater was 122.8 ± 86.2pptv and 6.47 ± 3.58 nmol L−1, respectively. The variation trend of surface water DMS in the western Pacific continental sea was influenced by the abundance and composition of phytoplankton under different ocean current systems, with a significant impact from eddies on DMS production in the South China Sea. By eliminating the influence of terrestrial sources and limiting air mass transport within the marine boundary layer, strong correlations were established between atmospheric DMS and air mass exposure to chlorophyll (Echl), as well as between aerosol methanesulfonic acid (MSA) and Echl. During the aerosol sampling period, the atmospheric DMS levels (1,057 ± 371 ng/m3) were significantly higher than MSA levels (46.3 ± 59.8 ng/m3) in the East China Sea, where the conversion of DMS to MSA was not affected by changes in DMS concentration. The sea‐to‐air fluxes of DMS varied over a wide range, from 0.02 to 156.0 μmol m−2 d−1, with an average of 14.35 ± 18.58 μmol m−2 d−1. Marine DMS emissions play a critical role in the formation of sulfur aerosols on the western Pacific continental shelf, accounting for 24.6 ± 7.6% (14.8%–37.8%) of the total sulfate aerosols. Plain Language Summary: The western Pacific continental sea plays a crucial role in controlling climate‐active gas budgets and sulfate aerosol loads. We investigated the distribution, sources, and control factors of dimethyl sulfide in surface seawater and the overlying atmosphere using underway observations in the western Pacific continental sea. By removing the influence of land sources and limiting air mass transport within the marine boundary layer, we discovered strong correlations between atmospheric dimethyl sulfide and air mass exposure to chlorophyll, as well as between aerosol methanesulfonic acid and air mass exposure to chlorophyll. Marine dimethyl sulfide emissions are vital for sulfur aerosol formation on the western Pacific continental shelf. This study provides valuable insights into understanding dimethyl sulfide dynamics in the western Pacific continental sea while highlighting its role in sulfur cycling and aerosol formation. Key Points: Phytoplankton and eddies influenced dimethyl sulfide (DMS) distribution in the western Pacific continental seaThe atmospheric DMS and Echl exhibit a strong positive correlation, as well as MSA and EchlMarine DMS emissions accounted for 25% of total sulfate aerosols in the East China Sea [ABSTRACT FROM AUTHOR]

Fungal aerosols, as significant biocomponents of inhalable particulate matter, encompass a variety of allergens and pathogens. However, comprehensive knowledge regarding their composition, sources, and opportunistic pathogens present in severe air pollution remains limited. In this study, PM2.5 samples were collected from January to March 2018 in a northern Chinese city, during the winter heating and spring sandstorm seasons. The fungal community characteristics within three distinct haze and haze‐dust composite pollution were examined. The concentration of fungal aerosols was found to be significantly higher in dust samples. This was evidenced by a strong positive correlation with Ca2+, temperature, and wind speed (p < 0.05). Human and animal pathogens, such as Candida, were more prevalent in haze samples. Conversely, allergens and plant pathogens, like Alternaria, were found in higher concentration in dust samples. The primary ecological function shifted from being saprophytic to becoming human‐animal pathogenic or plant‐animal pathogenic. This shift was observed from non‐pollution, haze, to haze‐dust composite pollution. The dispersion of fungal aerosols was influenced by factors such as dust events and meteorological conditions, including increased temperature and wind speed. In the spring dust episodes, dust‐related pollutants, such as soil Ca2+ and PM10, accounted for 51.39% of the variation in the fungal community. This research explored the dynamics of fungal communities, potential pathogens, and factors influencing fungal communities in regional air pollution. The insights garnered from this research provide a robust foundation for subsequent human health exposure assessments. Plain Language Summary: Fungal aerosols, comprising spores, mycelium, and metabolites, harbor a variety of pathogens, and allergens of medical significance. These aerosols have been observed to increase in concentration during regional severe air pollution, necessitating further exploration of their potential harmful effects. This study aimed to elucidate the concentration, community structure, pathogens, and ecological functions of fungal aerosols during severe air pollution. To achieve this, particulate matter samples were collected in the typical periods of heightened pollution (winter heating and spring sandstorm seasons) in a northern China city. During this period, three severe pollution episodes‐defined as haze, haze‐dust synchronous composite pollution, and haze‐dust asynchronous composite pollution‐were identified. Our findings revealed that fungal concentrations were notably high in dust samples. High wind speed and temperature facilitated the dispersion of fungal spores. Winter haze samples were enriched with highly animal pathogenic fungi, while spring dust samples exhibited an elevated abundance of allergens and plant pathogens. Notably, meteorological conditions exerted a more pronounced impact on the fungal community during haze pollution, whereas dust‐related pollutants were the primary factors affecting the distribution and variation of fungal communities in the spring dust episodes. This research offers foundational data for evaluating human health exposure to fungal aerosols. Key Points: Meteorological conditions and air pollutants modulate fungal communitiesHuman pathogenic fungi were enriched in haze samples (Candida)Allergens and plant pathogens (Alternaria) were abundant in dust samples [ABSTRACT FROM AUTHOR]

Local air pollution is strongly affected by synoptic weather systems, such as fronts, troughs, low-altitude vortices, or high-altitude ridges. Nevertheless, few studies have analyzed the meteorological properties of cold or warm air masses associated to these systems and their impact on local air quality. In this study, hourly observations of fine particulate matter (diameter of up to 2.5 µm, i.e., PM2.5), wind (V), temperature (T), pressure (P), and precipitation (R), acquired in Hangzhou in 2014–2020, were analyzed. From this analysis, weather patterns were categorized into 27 types; 89 and 94 cases illustrating the passage of warm and cold air masses over Hangzhou were identified, respectively; the influence of air mass temperature, wind speed, and wind direction on PM2.5 concentrations and local accumulation or removal was quantified. The main results are as follows. (1) Pollution events occurred more frequently for cold than for warm air masses, but average pollutant concentration was lower for cold air masses; (2) 48% of the cold air mass cases corresponded to PM2.5 decreases and 52% to PM2.5 increases, with strong cold air masses (ΔT24h > 4°C; ∣V∣average > 4 m s−1) markedly reducing local pollution, but weak cold air masses (ΔT24h < 2°C; ∣V∣average < 2 m s−1) primarily inducing pollutant transport and accumulation; (3) for warm air masses, PM2.5 accumulation or removal occurred in 60% and 40% of the cases, respectively: warm air masses (ΔT24h > 4°C) reduced the PM2.5 concentration whereas weaker winds (∣V∣average < 2 m s−1) increased it; and (4) PM2.5 concentration decreased sharply within 4 h after the passage of strong cold air masses, but more gradually within 14 h after the passage of strong warm air masses. These results considerably improve the current understanding of the influence of cold and warm air masses on local pollution patterns. [ABSTRACT FROM AUTHOR]

Abstract Proposed in 1954, Alisov’s climate classification (CC) focuses on climatic changes observed in January–July in large-scale air mass zones and their fronts. Herein, data clustering by machine learning was applied to global reanalysis data to quantitatively and objectively determine air mass zones, which were then used to classify the global climate. The differences in air mass zones between two half-year seasons were used to determine climatic zones, which were then subdivided into continental or maritime climatic regions or according to east–west climatic differences. This study renews Alisov’s CC for the first time in almost 70 years and employs data-driven machine learning to establish a standard for causal CC based on air masses.

The ERA 5 reanalysis data and the daily average surface ozone concentrations (O3) measured at the TOR station from 1993 to 2020 are used to study the circulation pattern favoring the formation of extremely high ozone concentrations (95th percentile, henceforth О395). All months are characterized by an identical circulation mode accompanied by an increase in the surface air temperature in the area encompassing the ozone concentration measuring station. In addition to the increase in the air temperature, О395 events are characterized by strengthening of the southwesterly component of the wind velocity field. It is also found that these circulation features are associated with the development of meridional properties, probably due to the propagation of waves in the upper troposphere in midlatitudes. The identified circulation mode simultaneously favors the transboundary transport of ozone and its precursors from the southern regions, the enhancement of photochemical O3 formation, and the occurrence of wildfires. [ABSTRACT FROM AUTHOR]

The increasing installed volume of grid-connected PV systems in modern electricity networks induces variability and uncertainty factors which must be addressed from several different viewpoints, including systems' protection and management. This study aims to estimate the actual performance and degradation of photovoltaic (PV) parks in Central Greece after several years of operation. Monitoring data over several years are analyzed and filtered, the performance ratio and normalized efficiency are computed, and five different ANNs are employed: (i) a feed-forward network (one hidden layer); (ii) a deep feed-forward network (two hidden layers); (iii) a recurrent neural network; (iv) a cascade-forward network; and (v) a nonlinear autoregressive network. The following inputs are employed: in-plane irradiance; backsheet panel temperature; airmass; clearness index; and DC voltage of the inverter. Monitoring data from an 8-year operation of a grid-connected PV system are employed for training, testing, and validation of these networks. They act as a baseline, built from the first year, and the computed metrics act as indicators of faults or degradation. Best accuracy is reached with the DFFNN. The ANNs are trained with data from the first year of operation, and output prediction is carried out for the remaining years. Annual electricity generation exceeds 1600 kWh /kWp, and MAPE values show an increasing trend over the years. This fact indicates a possible change in PV performance. [ABSTRACT FROM AUTHOR]

Proposed in 1954, Alisov's climate classification (CC) focuses on climatic changes observed in January–July in large-scale air mass zones and their fronts. Herein, data clustering by machine learning was applied to global reanalysis data to quantitatively and objectively determine air mass zones, which were then used to classify the global climate. The differences in air mass zones between two half-year seasons were used to determine climatic zones, which were then subdivided into continental or maritime climatic regions or according to east–west climatic differences. This study renews Alisov's CC for the first time in almost 70 years and employs data-driven machine learning to establish a standard for causal CC based on air masses. [ABSTRACT FROM AUTHOR]

We discuss the results from the complex experiment aimed at studying the composition and time variations in urban aerosol in the surface air at the center of Moscow based on daily data on PM10 and PM2.5 concentrations. In addition to these continuous observations every season (for 35–40 days), the total aerosol mass concentration (by gravimetric method) and 65 chemical elements in aerosol composition were measured daily. Winters 2019/2020 and 2020/2021 are considered. The aerosol composition is juxtaposed to the meteorological parameters in the surface atmosphere in Moscow, the direction of long-range air mass transport toward the Moscow region, and the distribution of dust in air over the European Russia (using the MERRA-2 reanalysis data). The detailed analysis of the aerosol elemental composition in Moscow made it possible to identify the elements of global/local spread, as well as of natural/anthropogenic genesis. Concentrations of all aerosol constituents in Moscow during winter did not exceed the corresponding daily average MPC values for the air of residential territories. It is shown that the accumulation of PM10 and PM2.5 in urban air was favored by calm weather conditions. The maximal levels of aerosol pollution were observed in December 2020 during southeasterly winds, when long-range atmospheric transport of admixtures to Moscow occurred from sources located in the southern regions of European Russia, the Caspian Depression, and western Kazakhstan. [ABSTRACT FROM AUTHOR]

Featured Application: The accuracy in long-term prediction of the performance of a photovoltaic (PV) park following several years of operation is essential for a number of reasons, including the extraction of reliable data for the economic analysis, the valid support of claims regarding PV panels' performance degradation and other issues. The specific work was motivated by the need to economically assess future investment in photovoltaic installations during an economic cycle with increasing interest rates. The monitoring data from the actual operation of a 100 kW PV park are employed in the refinement and validation of the prediction methodology. The results are applicable to the profitability analysis of future PV investments in the region of Thessaly. Increased penetration of grid-connected PV systems in modern electricity networks induces uncertainty factors to be considered from several different viewpoints, including the system's protection and management. Accurate short-term prediction of a grid-connected PV park's output is essential for optimal grid control and grid resilience. Out of the numerous types of models employed to this end during the last decade, artificial neural networks, (ANNs) have proven capable of handling the uncertainty issues of solar radiation. Insolation and ambient, or panel temperature, are most commonly employed as the independent variables, and the system's output power is successfully predicted within 3 to 5% error. In this paper, we apply a common type of ANN for the long-term prediction of a 100 kWp grid-connected PV park's output, by exploiting experimental data from the last 8 years of operation. Solar radiation and backsheet temperature were utilized for the ANN training stage. The performance metrics of this model, along with a standard linear regression model, are compared against the actual performance data. The capabilities of the ANN model are exploited in the effort to decouple the fluctuating effect of PV panel soiling which interferes with the efficiency degradation process. The proposed methodology aimed to quantify degradation effects and is additionally employed as a fault diagnosis tool in long-term analysis. [ABSTRACT FROM AUTHOR]

Bodily pain plagues populations across the globe. Past studies have discovered some links between synoptic weather types and different kinds of pain. These relationships are essential as they can aide in treatment and potentially prevention of pain. In this study, the role of geographical characteristics on the relationships between synoptic weather type and pain were looked at. North Carolina was separated into three geographic sections: Appalachian Mountains, Piedmont Plateau, and Coastal Plain. Over a 7-year period, synoptic weather types and emergency department (ED) visits for various kinds of pain (migraine, fibromyalgia, rheumatoid arthritis, osteoarthritis, and general back pain) were collected. Bootstrapped confidence intervals of the mean number of population-adjusted ED visit rates (per 100,000 persons), for the different synoptic weather types, were compared across the different geographic regions. In the plateau region, Moist Tropical and Moist Moderate weather types were often linked to the highest rates of ED visits, while Polar weather types were frequently associated with the fewest visits. The mountainous portion of the state displayed similar patterns between synoptic weather types and the different forms of pain, with migraine and fibromyalgia being the exceptions. Few statistically significant relationships were noted for the coastal region. [ABSTRACT FROM AUTHOR]

This study aims to obtain the design and operation of methane (CH4) production equipment from burning of rice husk waste by burning it in a burner setup (testing) and to determine the effect of variations in air mass flow on the combustion temperature of rice husk waste, boiling time of water, and burning time maximum, combustion temperature. In this study using air mass flow of 0.020 m3 / s, 0.022 m3 / s, and 0.024 m3 / s, data collection included burning 5 kg of rice husk waste, boiling water volume, maximum flame time, combustion temperature. The results of the production of methane scale mass flow production tools have an effect on the effective flame and heat value. Or it can be concluded that the lower the mass of air mass used the longer the maximum flame produced, so that the heat obtained is also greater.

Directing solar panels in a way that collects the largest possible amount of solar energy is still attracting a lot of attention due to the continuous need to get clean, inexpensive renewable energy. Iraq is one of the countries characterized by the abundance of solar energy but the investment in this field has been far below ambition. In this study, an application developed with the visual basic programing language was used to compute precisely various solar angles and parameters, as a powerful tool for engineers and researchers. The outputs of the model were tested and discussed in detail. The air mass values were also computed for three cities: Mosul, Baghdad, and Basra. The results showed that the best time to acquire the solar radiation would be from 10 am to 2 pm (local time), the period that has the lowest values of air mass. Additional useful calculations that can be estimated by the application were the terrestrial irradiances from four empirical models for the clear sky: Roledo-Soler, Adnot, Kasten – Czeplak, and Berger-Duffie. The calculated values of terrestrial irradiance were compared with observed data measured by automatic weather station. The application simulated the actual values with some deviations due to the existence of clouds and aerosols. Kasten – Czeplak model was recommended to be used in Iraq since it was the best model to simulate the measured values. The comparison between the model’s output and the measured values on a daily basis on the 21st of June showed good agreement. The study suggested that the solar panels should face the south direction with a change of the tilt angle of the panels from 25o in June to a value of 60o each month towards the coldest months by an increment of 5 degrees. [ABSTRACT FROM AUTHOR]

Increased penetration of grid-connected PV systems in modern electricity networks induces uncertainty factors to be considered from several different viewpoints, including the system’s protection and management. Accurate short-term prediction of a grid-connected PV park’s output is essential for optimal grid control and grid resilience. Out of the numerous types of models employed to this end during the last decade, artificial neural networks, (ANNs) have proven capable of handling the uncertainty issues of solar radiation. Insolation and ambient, or panel temperature, are most commonly employed as the independent variables, and the system’s output power is successfully predicted within 3 to 5% error. In this paper, we apply a common type of ANN for the long-term prediction of a 100 kWp grid-connected PV park’s output, by exploiting experimental data from the last 8 years of operation. Solar radiation and backsheet temperature were utilized for the ANN training stage. The performance metrics of this model, along with a standard linear regression model, are compared against the actual performance data. The capabilities of the ANN model are exploited in the effort to decouple the fluctuating effect of PV panel soiling which interferes with the efficiency degradation process. The proposed methodology aimed to quantify degradation effects and is additionally employed as a fault diagnosis tool in long-term analysis.

Abstract Mid‐latitude cyclones are complex weather systems that are tightly related to surface weather impacts. Coherent air streams are known to be associated with such systems, in particular dry intrusions (DIs) in which dry air masses descend slantwise from the vicinity of the tropopause equatorward towards the surface. Often, DIs are associated with severe surface winds, heavy precipitation and frontogenesis. Currently, DIs can only be identified in hindsight by costly Lagrangian calculations using high resolution wind field data. Here, we use a novel method aiming to simplify the detection procedure of DI origins to allow their future identification in climate datasets, previously inaccessible for such diagnostic studies. A novel adaptation of a segmentation‐oriented neural network model is hereby presented as a successful tool to identify DI origins based solely on three ERA‐Interim reanalysis geopotential height fields, representing the state of the atmosphere. The model prediction skill is tested by calculating both the grid‐point and DI object based Matthews correlation coefficient. We find the model highly skilful in both reconstructing accurately the climatological distribution and predicting the vast majority of the individual DI origin objects. The skill decreases for relatively small objects and for objects occurring at locations where such cases are relatively less frequent. This indicates that geopotential height variability is related to the dynamic mechanisms involved in DI initiations. The results serve as a proof of concept for predicting DIs and other coherent air mass trajectories even when high resolution wind field data are not available, such as for model output for future climate projections.

Mid‐latitude cyclones are complex weather systems that are tightly related to surface weather impacts. Coherent air streams are known to be associated with such systems, in particular dry intrusions (DIs) in which dry air masses descend slantwise from the vicinity of the tropopause equatorward towards the surface. Often, DIs are associated with severe surface winds, heavy precipitation and frontogenesis. Currently, DIs can only be identified in hindsight by costly Lagrangian calculations using high resolution wind field data. Here, we use a novel method aiming to simplify the detection procedure of DI origins to allow their future identification in climate datasets, previously inaccessible for such diagnostic studies. A novel adaptation of a segmentation‐oriented neural network model is hereby presented as a successful tool to identify DI origins based solely on three ERA‐Interim reanalysis geopotential height fields, representing the state of the atmosphere. The model prediction skill is tested by calculating both the grid‐point and DI object based Matthews correlation coefficient. We find the model highly skilful in both reconstructing accurately the climatological distribution and predicting the vast majority of the individual DI origin objects. The skill decreases for relatively small objects and for objects occurring at locations where such cases are relatively less frequent. This indicates that geopotential height variability is related to the dynamic mechanisms involved in DI initiations. The results serve as a proof of concept for predicting DIs and other coherent air mass trajectories even when high resolution wind field data are not available, such as for model output for future climate projections.The study of coherent air mass trajectories associated with various weather systems requires costly calculations using high resolution data. An adaptation of a segmentation‐oriented neural network can identify the origins of such trajectories based solely on three instantaneous geopotential height fields, applied for identifying dry intrusion (DI) origins. The model successfully predicts the majority of individual DI origin objects and their climatological spatial distribution, serving as a proof of concept for predicting other coherent air mass trajectories when high resolution data are unavailable. [ABSTRACT FROM AUTHOR]

We investigated the impact of air mass origin on submicron particle size distributions and new particle formation (NPF) events using 10-year measurements at Gosan, Korea, in the Asian continental outflow. NPF events were identified on approximately 27.1% of total observation days, and 123 and 381 days of them were classified as strong and weak NPF days, respectively, based on the first-mode loading vectors and corresponding principal components in the cyclostationary empirical orthogonal function analysis. NPF events occurred less than 15% of the total observation days for the South China (SC), Pacific Ocean, and stagnation (ST) air mass sectors, whereas 33.1% (243 days out of total 734 observation days) were identified as NPF events for the air mass traveling from the North China (NC) sector. Consistently, the lowest mode diameter (50.5 nm), highest formation rate, and the lowest growth rate were found in the NC air mass sector. The highest mode diameter (89.8 nm) was observed at the SC air mass sector because of the coagulation of newly formed aerosols under relatively humid conditions during the transport in summer. The condensation sink for SC (10.70 ± 2.35 × 10−3 s−1) and ST (10.80 ± 4.24 × 10−3 s−1) was approximately 25% higher than that for the NC air mass sector. [ABSTRACT FROM AUTHOR]

Delineating the boundary between troposphere and stratosphere in a chemistry transport model requires a state variable for each air mass that maps out the ever shifting, overlapping three-dimensional (3-D) boundary at each time step. Using an artificial tracer, e90, with surface sources and 90 day decay time, the model e90 tropopause matches the 1-D temperature lapse rate definition of the tropopause as well as the seasonal variation of ozone at this boundary. This approach works from equator to pole, over all seasons, unlike methods based on potential vorticity or ozone. By focusing on the time scales that separate stratosphere from troposphere, we examine the cause of ozone seasonality at the midlatitude tropopause, the oldest air in the troposphere (winter descent in the subtropics), and a north-south bias in the age of air of the lowermost stratosphere as evaluated using a northern tracer. The tracer e90 is invaluable in 3-D modeling, readily separating stratosphere from troposphere and a giving quantitative measure of the effective distance from the tropopause.

Cyclone Ockhi hit Sri Lanka and southern parts of India in Nov–Dec 2017 with a devastating social impact. The present paper reports that the cyclone had a significant effect on the γ-ray flux measured by NaI (Tl) detector. An overall decrease is observed in the γ-ray flux during the passage of cyclone; however, a detailed investigation revealed that different energies show varying results. In the energy range between 250 – 450 keV, a decrease up to ~14% is observed, whereas an increase up to ~45% is observed in the energy range between 600 keV – 2.7 MeV. The energies above 2.7 MeV do not show any change. This is the first-ever observation of the varying effects of the cyclone with the energy bands of the γ-ray spectrum. We found that the increase observed in the energy range of 600 keV – 2.7 MeV is primarily due to the increase in the terrestrial radioactivity (peaks of 222Rn daughters), which is brought over by the rainfall accompanied with the cyclone. The study indicates that the decrease in the lower energy range of the γ-ray flux could be due to the attenuation caused by the increased tropospheric air-mass associated with the cyclone over the observation site. The high energy γ-rays are not affected due to the cyclone.

Multi-junction concentrator solar cells are a promising technology as they can fulfill the increasing energy demand with renewable sources. Focusing sunlight upon the aperture of multi-junction photovoltaic (PV) cells can generate much greater power densities than conventional PV cells. So, concentrated PV multi-junction solar cells offer a promising way towards achieving minimum cost per kilowatt-hour. However, these cells have many aspects that must be fixed to be feasible for large-scale energy generation. In this work, a model is developed to analyze the impact of various atmospheric factors on concentrator PV performance. A single-diode equivalent circuit model is developed to examine multi-junction cells performance in hot weather conditions, considering the impacts of both temperature and concentration ratio. The impacts of spectral variations of irradiance on annual performance of various high-concentrated photovoltaic (HCPV) panels are examined, adapting spectra simulations using the SMARTS model. Also, the diode shunt resistance neglected in the existing models is considered in the present model. The present results are efficiently validated against measurements from published data to within 2% accuracy. Present predictions show that the single-diode model considering the shunt resistance gives accurate and reliable results. Also, aerosol optical depth (AOD) and air mass are most important atmospheric parameters having a significant impact on HCPV cell performance. In addition, the electrical efficiency (η) is noticed to increase with concentration to a certain concentration degree after which it decreases. Finally, based on the model predictions, let us conclude that the present model could be adapted properly to examine HCPV cells' performance over a broad range of operating conditions.

Frequent heavy air pollution occurred during the winter heating season of northern China. In this study, PM2.5 (particles with an aerodynamic diameter less than 2.5 μm) was collected from a coastal city of China during the winter heating season from January 1 to March 31, 2018, and the soluble ions, organic carbon (OC), elemental carbon (EC), bacterial, endotoxin, and fungal concentration in PM2.5 were analyzed. During the winter heating season, PM2.5 and bioaerosols increased on polluted days, and the secondary inorganic ions, including NO3−, NH4+, and SO42−, increased significantly. Meteorological factors, such as wind direction and wind speed, had major impacts on the distributions of PM2.5 and bioaerosols. Pollutant concentration was high when there was a westerly wind with the speed of 3–6 m/s from inland area. Using the air mass backward trajectories and principal component analysis, we elucidate the potential origins of bioaerosol in PM2.5. The backward trajectory suggested that air mass for polluted samples (PM2.5 > 75 μg/m3) commonly originated from continent (9.62%), whereas air masses for clean samples (PM2.5 < 35 μg/m3) were mainly from marine (56.73%). The interregional transport of pollutants from continental area contributed most to PM2.5. Principal component analysis of the water-soluble ions and bioaerosol indicated that air pollution of the coastal city was greatly affected by coal combustion, biomass burning, and regional transmission of high-intensity pollutants from continent. Among that, interregional transport, biomass burning, and dust from soil and plants were main sources of bioaerosol. Our findings provide important insights into the origins and characteristics of bioaerosol in PM2.5 during the winter heating season of the coastal city in northern China. [ABSTRACT FROM AUTHOR]

We investigated the spatiotemporal features of the air mass and its transport during the lifetime of the four main blocking highs (the Greenland, Atlantic–Europe, Ural and North Pacific blocking highs) observed in the northern winter using the daily European Centre for Medium‐Range Weather Forecasts Re‐Analysis Interim data set for the time period 1979–2016. The results showed that the positive mass anomalies corresponding to a blocking high only appear in the mid‐troposphere, while negative mass anomalies persist in the lower layer during blocking events. Budget analysis based on the mass continuity equation under isentropic coordinates indicated that adiabatic mass transport is the main contributor to the build‐up of blocking highs and is always convergent in the mid‐troposphere before the peak day of blocking. By contrast, diabatic mass transport always moves the air mass from the mid‐ to lower troposphere and acts to destroy the blocking high. The meridional flow makes the strongest contribution to mass convergence in the Greenland and North Pacific blocking highs in the mid‐troposphere, whereas zonal flow is the main contributor to mass convergence in the Atlantic–Europe blocking high. Both zonal and meridional flows contribute to mass convergence in the Ural blocking high, although meridional flow makes a greater contribution. [ABSTRACT FROM AUTHOR]

In order to study the concentrations of major components, characteristics and comparison in hazy and non-hazy days of PM 10 in Beijing, aerosol samples were collected at urban site in Beijing from December 29, 2014 to January 22, 2015. Heavy metals like Zn, Pb, Mn, Cu, As, V, Cr and Cd were deeply studied considering their toxic effects on human being; nine water-soluble inorganic ions (SO 4 2−, NO 3 −, NH 4 +, Na+, K+, Cl−, Ca2+ and Mg2+) and carbon fractions (OC and EC) were also analyzed. The concentrations of heavy metals were 1.03–1.98 times higher in hazy days than those in non-hazy days, mainly due to biomass burning and coal burning. The trends in total heavy metals concentrations were basically consistent with the trends in PM concentrations except for two obvious periods (12.29–12.30; 1.14–1.15); but when air masses accumulated locally or around Beijing, trends in PM concentrations and heavy metals were opposite. The proportion for NO 3 −/SO 4 2− indicated that mobile sources such as automobiles were important reasons for haze in Beijing. Correlation between OC and EC during non-hazy days was strong (R 2 = 0.95) but it was low (R 2 = 0.67) during hazy days, and large variations for OC/EC values occurred in hazy days. The calculated mass concentration of SOC is 2.58 μg/m3, which only accounted for 10.1% of the OC concentration. When air masses from the far north-west, they decreased PM concentration in Beijing and they were relatively clean; however, those from the near east, south-east and south of the mainland increased PM concentration and they were dirty. Unlabelled Image [ABSTRACT FROM AUTHOR]

The north-east of Iran is a semi-arid region and faces a water shortage crisis. Therefore, monitoring water resources using accurate methods such as stable isotopes technique is vitally important. In this study, precipitation events were sampled in 10 stations in the Mashhad basin and the Bojnourd region in 2008, 2009, 2011, and 2015, additional surface and groundwater. These samples were analysed at the Ottawa University for both oxygen and hydrogen isotopes. In addition, the moisture sources were determined using the backward trajectories of the HYSPLIT model. The backward trajectories showed that both high- and low-latitude water bodies provide moisture for the north-east of Iran. However, the role of high-latitude water bodies including the Caspian, the Black, and the Mediterranean Seas is stronger. On the other hand, the stable isotopes showed large variations and the developed meteoric water lines deviated in both slope and intercept from the global meteoric water line. This showed that the precipitation events of the north-east of Iran were provided by various air masses and moisture sources. Finally, plotting the isotope values of the surface water resources on high- and low-latitude meteoric water lines demonstrated that these water resources were dominantly recharged by precipitation events originating from high-latitude water bodies. [ABSTRACT FROM AUTHOR]

Based on ERA-Interim and JRA-55 daily reanalysis datasets, connections among the variations in the Brewer–Dobson circulation (BDC) intensity, stratospheric air mass, surface pressure, and the tropospheric meridional circulation during the period from 1979 to 2015 are analyzed. The results show that the variations in the surface pressure, particularly at middle and high latitudes, have a close correlation with the variations in the stratospheric BDC intensity. When the upwelling at 450 K intensifies, the surface pressure increases in the high latitudes (poleward of 60°) and decreases in the adjacent mid-latitudes in both hemispheres. And these correlations are most significant during boreal winter in the Northern Hemisphere and during austral autumn in the Southern Hemisphere. It is found that the high latitude surface pressure changes follow the anomalous BDC by about 30 days. The increase in polar surface pressure associated with the stronger BDC is due to an increase in stratospheric air mass, while the decrease in mid-latitude surface pressure is related to a decrease in tropospheric air mass. These air mass changes are caused by the anomalous meridional transport of air mass by the residual mean circulation in the stratosphere and troposphere. In addition, we found a significant connection between the intensity of the BDC and the Ferrel cell, i.e., when the BDC strengthens (weakens), there is a weakened (strengthened) Ferrel cell with its position shifting equatorward (poleward). [ABSTRACT FROM AUTHOR]

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We report the first simultaneous eddy covariance flux measurements of CO2 and dimethylsulfide (DMS) over the open ocean for two North Atlantic cruises. After normalization for Schmidt number, the two gases give essentially identical gas transfer coefficients and wind speed dependences for the wind speed range 2–10 ms−1. The data indicate a linear relationship between the gas transfer coefficient and mean wind speed, with measured gas transfer coefficients slightly above the Wanninkhof (1992) parameterization, particularly at low wind speeds.

This study examines atmospheric reactive chlorine chemistry at the Cape Verde Atmospheric Observatory in the eastern tropical Atlantic. During May–June, 2007, Cl2 levels ranged from below detection (∼2 ppt) to 30 ppt. Elevated Cl2 was associated with high HNO3 (40 to 120 ppt) in polluted continental outflow transported in the marine boundary layer (MBL) to the site. Lower Cl2 was observed in recently subsided air masses with multiday free tropospheric oceanic trajectories and in air containing Saharan dust. Model simulations show that the observations of elevated Cl2 in polluted marine air are consistent with initiation of Cl chemistry by OH + HCl and subsequent heterogeneous, autocatalytic Cl cycling involving marine aerosols. Model estimates suggest that Cl atom reactions significantly impact the fates of methane and dimethylsulfide at Cape Verde and are moderately important for ozone cycling.

The southern Brazilian city of Canoas, situated in the metropolitan region of Porto Alegre, is subject to several annual meteorological phenomena, such as cold fronts and squall lines. Here, we assess the relationship between meteorological conditions and outpatient consultations for asthma or bronchitis in children from Canoas City. Data from outpatient consultations of children (below 9 years), between January/2005 and September/2008, were combined with daily meteorological data from 12UTC (morning) and 18UTC (afternoon). We identified 42 days with an excess of outpatient consultations (peaks). Consultations were negatively correlated with temperature and human thermal comfort index (HTCI) from the 3 previous days based on consultation data at 12 and 18UTC, and positively correlated with atmospheric pressure. A positive correlation with relative humidity was significant only at 12UTC. The highest correlations occurred on the day of consultation (12UTC) with temperature, relative humidity, and atmospheric pressure, as well as 2 days previous to the HTCI. The sensation of cold was associated with about 55% of the days of the period at 12UTC: considering only the peaks of consultations, this association exceeds 90% of days. The highest frequencies of respiratory complications (June, July, and August) were associated with negative temperature anomalies, wind speed and direction, and positive anomalies in relative humidity and atmospheric pressure. Nearly half (45%) of the air masses associated with respiratory complications arrived at Canoas from a SW direction, 19% from the south and 14% from the west. In summary, observed increases in respiratory complications were mainly associated with the presence of cold and humid air (and/or falling temperature with increasing humidity) in the morning. [ABSTRACT FROM AUTHOR]

The growth of renewable energy and especially photovoltaic energy in Greece is remarkable. There exist many grid-connected systems in Greek territory which have completed ten years operation. A challenging task for these systems is performance analysis, investigation of possible degradation in systems efficiency and formulation of a detailed solar potential record for each region. This paper focuses in the performance of a grid-connected PV system in central Greece which has completed six years' operation. The analysis methodology is based on three axes. The first is a calculation of the daily PR and yearly PR and their comparison for the 6 years of operation. The daily PR is further correlated with the averaged clearness index in order to assess the atmospheric effect on the PV performance. The second axis involves the application of a mathematic model, which describes PV power, to the available data. Computed values act as the reference values and deviation of the measured values thereof hint to probable changes in PV system performance. The third axis involves the computation of normalized efficiency to STC conditions. This includes (i) the computation of DC power from available AC data and inverters' efficiency, (ii) temperature normalization according to the temperature coefficients of manufacturer and (iii) comparison of efficiency at various weather conditions and computation of yearly average values, respectively, with Airmass. The analysis results hint to a small performance deterioration over the years, with degradation rates ranging from 1 to 4%. • The performance of a grid-connected Photovoltaic park after six years' operation is presented. • The processing of data is aided by the application of the most wide spread performance models. • An assessment methodology for PV parks efficiency calculation is formulated and applied. • The results hint to a performance deterioration, with degradation rates ranging from 1 to 4%. [ABSTRACT FROM AUTHOR]

The distribution characteristics and sources of gaseous elemental mercury (GEM) on haze and non-haze days are still not clear. During the winter heating period in 2017, the GEM concentrations in Qingdao were studied for their differences, sources, and pollution characteristics on haze and non-haze days. The GEM concentration on haze days (2.81 ± 2.23 ng/m3) was higher than that on non-haze days (1.90 ± 1.21 ng/m3) and the difference was significant (p < 0.01) during the period of artificial heating. The average concentration of GEM was 2.27 ng/m3 in the heating period, but lower than that before heating (3.30 ng/m3). However, the mercury to carbon monoxide ratio (GEM/CO) on haze days was lower than that on non-haze days. The ratio of GEM/CO in this study was lower than that in other studies reported from China. There was a positive correlation between the GEM/CO ratio and the air temperature (p < 0.01), suggesting that the mercury released from the Earth's surface was important. The environmental policies of China also contributed to decrease of the GEM/CO ratio. Similar diurnal patterns appeared on both haze and non-haze days, with one GEM peak at 14:00–15:00. This pattern was different from the bimodal pattern of other atmospheric pollutants in the morning and evening rush hours and was controlled by GEM from the Earth's surface (mostly re-emission of legacy Hg) whether on haze or non-haze days. Principal component analysis showed that the contribution of GEM directly from anthropogenic sources was relatively small. The main influencing factor on haze days was air temperature. GEM concentrations showed large spatial differences in air masses from different places. The GEM concentration in air masses from southern and the western Shandong Province was higher than from the north on haze days. Unlabelled Image • GEM concentration on haze days was higher than that on non-haze days. • GEM/CO ratio on haze days was lower than that on non-haze days. • GEM diurnal variation on haze days was controlled by solar radiation. • Air masses from the south had higher GEM and GEM/CO ratio than that from the north. [ABSTRACT FROM AUTHOR]

A study was made of the nature of the movement of air mass in the space between the device that warms the room and the confining outer wall of the room. The hydrodynamic motion of the air mass was simulated on the basis of the two-dimensional in space Navier-Stokes equations and the convective heat conduction equation to find out a detailed picture of the physical processes that occur. Also for some particular cases, analytical solutions were obtained for the conjugate problem, where the movement of air is caused by its thermal expansion and the action of gravity in areas with different densities (Archimedes' forces). The simulation of more complex types of air movement with the formation of vortex flows using numerical methods and the corresponding program codes written in C++. It was found that the movement of air mass in the space between the device and the fence strongly depends not only on the temperature of the device, the wall, and the outside air. It was revealed that hydrodynamics and heat transfer are significantly influenced by two geometrical parameters: the distance between the device and the wall, and the distance from the flooring to the bottom of the device. In particular, a thin layer of the downward flow of cold air along the fence and above the floor is possible. The condition for the occurrence of such a downward flow has been found, it is determined by the ratio of the temperature of the wall, the device, and the average temperature in the room. [ABSTRACT FROM AUTHOR]

Synoptic processes that occurred in the Tomsk region between 1993 and 2016 are analyzed. A significant decrease in the difference between the frequency of cyclones and anticyclones over the past decade is revealed. There are tendencies to a decrease in the frequency of Arctic air mass invasion, and to an increase, of subtropical and tropical air masses. [ABSTRACT FROM AUTHOR]

Abstract Solar spectrum plays an important role on electrical performance of PV modules via affecting their short circuit current. In this study, a new model combining the impacts of both air mass and diffuse solar radiation ratio is developed to evaluate the solar spectrum impacts on the short circuit current of photovoltaic (PV) modules. A new method, named air mass cumulative distribution function method (AMCDF), is introduced to represent the relationship between air mass and solar spectrum effect. The experimental data shows that when air mass is less than 4.5, the relationship between the normalized short-circuit current and the air mass cumulative distribution function can be well represented by a five-order polynomial. However, when air mass is larger than 4.5, the relationship becomes irregular. Further study on the irregular data indicates that the chaotic relationship is caused by the impact of diffuse solar radiation ratio (R d). Based on these findings, the new model which combines the air mass cumulative distribution function and the diffuse solar radiation ratio is developed to evaluate the spectrum effect. Compared to conventional models, the proposed model has higher prediction accuracy and it also can predict short circuit current even when the air mass is high. Highlights • The air mass cumulative distribution function method is introduced. • The relationship between short-circuit current and AMCDF is reported and analyzed. • The impact of diffuse solar radiation ratio on short circuit current is identified. • A model combining AMCDF and diffuse solar radiation ratio is developed. [ABSTRACT FROM AUTHOR]

Data of multiyear monitoring at the TOR station are used to calculate the average concentrations of gas and aerosol constituents in different air masses in the region of Tomsk. It is shown that CO2 and CH4 are characterized by a decrease in concentrations in going from an Arctic to a tropical air mass. Ozone shows the opposite pattern: the largest concentrations are recorded in the tropical air mass and the smallest concentrations in the Arctic air mass. Such gases as CO and SO2 show distributions more complex in character. [ABSTRACT FROM AUTHOR]

Abstract As a part of establishing a regional database on natural radioactivity, the atmospheric concentrations of 210Pb and 7Be were measured over a three and half year period (2014–2017) in Mangalore and Kaiga in the South West Coast of India. A total of 99 air samples, collected in the different months of the year, were analysed in this study. The mean activity concentrations of 7Be and 210Pb were found to be 5.5 ± 3.1 mBq m−3 and 1.1 ± 0.73 mBq m−3, respectively. Both the radionuclides exhibited strong seasonal variations, with maximum concentration of 7Be occurring in the summer and that of 210Pb in the winter season. The concentration of both the radionuclides was minimum in the rainy season. Higher 210Pb concentration during winter was attributed to the ingression of continental air masses due to the wind regime from the North East. The sunspot number index of the solar activity also plays an important role in the increase and decrease of 7Be concentration in the air. A clear trend of increased and lowered concentration of 7Be with lower and higher solar activity (low and high sunspot number), respectively, in accordance with the 11-year solar cycle, was observed in this study. The temporal variation of PM 10 concentration was also studied and it showed maximum value in the winter and minimum in the rainy season with an average of 56.9 μg m−3. Statistically significant positive correlation was observed between the PM 10 and 210Pb activity concentration, whereas a weak correlation was observed between PM 10 and 7Be. This is due to the fact that 7Be is largely associated with sub-micrometer size particles, whereas PM 10 is contributed by larger sizes. The dependence of the activity concentrations of 7Be and 210Pb with meteorological parameters such as rainfall, temperature, and humidity was studied through linear regression analysis. A significant correlation was observed between 7Be and 210Pb concentrations with rainfall intensity (with identical correlation coefficients), which suggested that the removal mechanisms of these two radionuclides were similar. 7Be showed a strong correlation with temperature, whereas 210Pb with humidity. A comparison of the data obtained in the present study for the South West Coast of India with the global literature values of 7Be and 210Pb in aerosols showed that the values did not reflect the well-known latitudinal dependence of the 7Be tropospheric fluxes. Overall, the study provides an improved understanding of the correlation and variability of 210Pb and 7Be concentrations in the atmosphere in the South West Coast of India. Highlights • Regional database on activity of atmospheric 7Be and 210Pb in Southwest Coast of India was established. • Rainfall is the major removal pathway for the 7Be and 210Pb from the atmosphere. • Dependence of solar activity with cosmogenic 7Be was studied. • A clear dependence of 7Be activity on solar activities was observed. • Causal factors for the temporal variability of 7Be and 210Pb concentrations were identified. [ABSTRACT FROM AUTHOR]