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Published: 31 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080990

Abstract:
Air pollution is becoming increasingly serious along with social and economic development in the southwest of China. The distribution characteristics of particle matter (PM) were studied in Chengdu from 2016 to 2017, and the changes of PM bearing water-soluble ions and heavy metals and the distribution of secondary ions were analyzed during the haze episode. The results showed that at different pollution levels, heavy metals were more likely to be enriched in fine particles and may be used as a tracer of primary pollution sources. The water-soluble ions in PM2.5 were mainly Sulfate-Nitrate-Ammonium (SNA) accounting for 43.02%, 24.23%, 23.50%, respectively. SO42−, NO3, NH4+ in PM10 accounted for 34.56%, 27.43%, 19.18%, respectively. It was mainly SO42− in PM at Clean levels (PM2.5 = 0~75 μg/m3, PM10 = 0~150 μg/m3), and mainly NH4+ and NO3 at Light-Medium levels (PM2.5 = 75~150 μg/m3, PM10 = 150~350 μg/m3). At Heavy levels (PM2.5 = 150~250 μg/m3, PM10 = 350~420 μg/m3), it is mainly SO42− in PM2.5, and mainly NH4+ and NO3 in PM10. The contribution of mobile sources to the formation of haze in the study area was significant. SNA had significant contributions to the PM during the haze episode, and more attention should be paid to them in order to improve air quality.
Published: 31 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080992

Abstract:
Particle size distribution is one of the important microphysical parameters to characterize the aerosol properties. The aerosol optical depth is used as the function of wavelength to study the particle size distribution of whole atmospheric column. However, the inversion equation of the particle size distribution from the aerosol optical depth belongs to the Fredholm integral equation of the first kind, which is usually ill-conditioned. To overcome this drawback, the integral equation is first discretized directly by using the complex trapezoid formula. Then, the corresponding parameters are selected by the L curve method. Finally the truncated singular value decomposition regularization method is employed to regularize the discrete equation and retrieve the particle size distribution. To verify the feasibility of the algorithm, the aerosol optical depths taken by a sun photometer CE318 over Yinchuan area in four seasons, as well as hazy, sunny, floating dusty and blowing dusty days, were used to retrieve the particle size distribution. In order to verify the effect of truncated singular value decomposition algorithm, the Tikhonov regularization algorithm was also adopted to retrieve the aerosol PSD. By comparing the errors of the two regularizations, the truncated singular value decomposition regularization algorithm has a better retrieval effect. Moreover, to understand intuitively the sources of aerosol particles, the backward trajectory was used to track the source. The experiment results show that the truncated singular value decomposition regularization method is an effective method to retrieve the particle size distribution from aerosol optical depth.
Published: 31 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080993

Abstract:
Downslope winds and lee gravity waves are common features of mountainous environments. A similar weather type at Mt. Parnassos in Arachova, Greece is known as “Katevatos” and has devastating results for the population and visitors at the local touristic resorts. In this study, we analyze three incidents of this atmospheric pattern at local scale resolution (1 × 1 km) with WRF model. This is the first study of this local weather hazard, and the following key factors are identified. (I) The main synoptic forcing is the propagation of an upper-level trough from central Europe towards the Balkans. (II) The associated generation of a surface low-pressure system over the Aegean Sea results in a northeast flow in the lower troposphere that is perpendicular to the main topographic ridge of Mt. Parnassos. (III) Generation of gravity waves and downward reflection of wave energy at the critical level between the upper level flow and the undercutting northeast current result in the formation of “Katevatos” downslope wind at the lee side of the mountain. This hurricane-scale wind is accompanied with horizontal transport of frozen rain and snow from the mountain tops towards the village of Arachova. This wind pattern appeared also during the battle of Arachova in November 1826 between the Greek and Ottoman forces resulting in enormous casualties due to the adverse weather conditions.
Published: 31 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080994

Abstract:
Green infrastructure has a role to play in climate change adaptation strategies in cities. Alternative urban spaces should be designed considering new requirements in terms of urban microclimate and thermal comfort. Pervious pavements such as green parking lots can contribute to this goal through solar evaporative cooling. However, the cooling benefits of such systems remain under debate during dry and warm periods. The aim of this study was to compare experimentally the thermal behavior of different parking lot types (PLTs) with vegetated urban soil. Four parking lots were instrumented, with temperature probes buried at different depths. Underground temperatures were measured during summer 2019, and the hottest days of the period were analyzed. Results show that the less mineral used in the surface coating, the less it warms up. The temperature difference at the upper layer can reach 10 °C between mineral and non-mineral PLTs. PLTs can be grouped into three types: (i) high surface temperature during daytime and nighttime, important heat transfer toward the sublayers, and low time shift (asphalt system); (ii) high (resp. low) surface temperature during daytime (resp. nighttime), weak heat transfer toward the sublayers, and important time shift (paved stone system); and (iii) low surface temperature during daytime and nighttime, weak heat transfer toward the sublayers, and important time shift (vegetation and substrate system, wood chips system, vegetated urban soil). The results of this study underline that pervious pavements demonstrate thermal benefits under warm and dry summer conditions compared to conventional parking lot solutions. The results also indicate that the hygrothermal properties of urban materials are crucial for urban heat island mitigation.
Published: 31 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080987

Abstract:
The Himalayas, especially the Everest region, are highly sensitive to climate change. Although there are research works on this region related to cryospheric work, the ecological understandings of the alpine zone and climate impacts are limited. This study aimed to assess the changes in surface water including glacier lake and streamflow and the spatial and temporal changes in alpine vegetation and examine their relationships with climatic factors (temperature and precipitation) during 1995–2019 in the Everest region and the Dudh Koshi river basin. In this study, Landsat time-series data, European Commission’s Joint Research Center (JRC) surface water data, ECMWF Reanalysis 5th Generation (ERA5) reanalysis temperature data, and meteorological station data were used. It was found that the glacial lake area and volume are expanding at the rates of 0.0676 and 0.0198 km3/year, respectively; the average annual streamflow is decreasing at the rate of 2.73 m3/s/year. Similarly, the alpine vegetation greening as indicated by normalized difference vegetation index (NDVI) is increasing at the rate of 0.00352 units/year. On the other hand, the annual mean temperature shows an increasing trend of 0.0329 °C/year, and the annual precipitation also shows a significant negative monotonic trend. It was also found that annual NDVI is significantly correlated with annual temperature. Likewise, the glacial lake area expansion is strongly correlated with annual minimum temperature and annual precipitation. Overall, we found a significant alteration in the alpine ecosystem of the Everest region that could impact on the water–energy–food nexus of the Dudh Koshi river basin.
Published: 31 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080988

Abstract:
The occurrence of extreme drought poses a severe threat to forest ecosystems and reduces their capability to sequester carbon dioxide. This study analysed the impacts of a central European summer drought in 2015 on gross primary productivity (GPP) at two Norway spruce forest sites representing two contrasting climatic conditions—cold and humid climate at Bílý Kr̆íz̆ (CZ-BK1) vs. moderately warm and dry climate at Rájec (CZ-RAJ). The comparative analyses of GPP was based on a three-year eddy covariance dataset, where 2014 and 2016 represented years with normal conditions, while 2015 was characterized by dry conditions. A significant decline in the forest GPP was found during the dry year of 2015, reaching 14% and 6% at CZ-BK1 and CZ-RAJ, respectively. The reduction in GPP coincided with high ecosystem respiration (Reco) during the dry year period, especially during July and August, when several heat waves hit the region. Additional analyses of GPP decline during the dry year period suggested that a vapour pressure deficit played a more important role than the soil volumetric water content at both investigated sites, highlighting the often neglected importance of considering the species hydraulic strategy (isohydric vs. anisohydric) in drought impact assessments. The study indicates the high vulnerability of the Norway spruce forest to drought stress, especially at sites with precipitation equal or smaller than the atmospheric evaporative demand. Since central Europe is currently experiencing large-scale dieback of Norway spruce forests in lowlands and uplands (such as for CZ-RAJ conditions), the findings of this study may help to quantitatively assess the fate of these widespread cultures under future climate projections, and may help to delimitate the areas of their sustainable production.
Published: 31 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080989

Abstract:
Despite the growing popularity of heated tobacco products, there are few comprehensive studies on their environmental aerosols. Therefore, the impact of the Tobacco Heating System 2.2 (THS 2.2) on indoor air quality was evaluated on the basis of a comprehensive list of 31 airborne constituents along with targeted screening of the gas–vapor and particulate phases of the environmental aerosol. The assessments were conducted at three ventilation rates. Indoor use of THS 2.2 increased the levels of nicotine, acetaldehyde, glycerin, and (if mentholated products were used) menthol relative to background levels, with a corresponding increase in total volatile organic compounds (TVOC) values. Moreover, a temporary increase in ultrafine particles was observed when two or more tobacco sticks were used simultaneously or with a short time lapse between usages, but the concentrations returned to close to background levels almost immediately. This is because THS 2.2 generates an aerosol of liquid droplets, which evaporate quickly. Nicotine, acetaldehyde, glycerin, and TVOC levels were measured in the low μg/m3 range and were below the existing guideline limits. A comparison of airborne constituent levels during indoor THS 2.2 use with emissions from combustion products and common everyday activities revealed a substantially lower impact of THS 2.2 on the indoor environment.
Published: 31 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080995

Abstract:
Precipitation extremes such as heavy rainfall and floods are of great interest for climate scientists, particularly for small islands vulnerable to weather phenomena such as hurricanes. In this study, we investigated the spatio-temporal evolution of extreme rainfall over Cuba from 1980 to 2019, separating the dry and rainy periods. In addition, a ranking of extreme precipitation events was performed, which provides the number of events, the area affected, and a ranking of their magnitude by considering the magnitude of anomalies. The analysis was conducted using daily data from the multi-source weighted-ensemble precipitation (MSWEPv2). In determining the extreme precipitation ranking, the daily extreme precipitation anomaly was calculated with respect to the 95th percentile climatological distribution, giving a measure of the rarity of the event for each day and each grid point. For a more detailed analysis regarding the ranking, a separation was made by regions applying the K-mean methodology. The months belonging to the rainy period of the year presented the highest amount of precipitation above the 95th percentile compared to results obtained for the dry period. Of the six months belonging to the cyclonic season, in five of them Cuba was affected, directly or indirectly, by a tropical cyclone. The years 1982–83 and 1998 presented the highest-ranking value for the dry and rainy periods, respectively. Moreover, a trend analysis revealed an increase in the trend of occurrence of extreme events and a decrease in the percentage of the area affected. The analysis by regions showed a similar behavior to that carried out for all of Cuba. It was found that the warm phase of the ENSO events influenced approximately ~22% of the occurrence of extreme events for both periods.
Published: 31 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080991

Abstract:
Sea-surface roughness length is a key parameter for characterizing marine atmospheric boundary layer. Although aerodynamic roughness lengths for homogeneous land and open water surfaces have been examined extensively, the extension of relevant knowledge to the highly inhomogeneous coastal area is problematic due to the complex mechanisms controlling coastal meteorology. This study presented a lidar-based observational analysis of sea-surface roughness length at a coastal site in Hong Kong, in which the wind data recorded from March 2012 to November 2015 were considered and analyzed. The results indicated the turning of wind near the land-sea boundary, leading to a dominative wind direction parallel to the coastline and an acceleration in wind. Moreover, the roughness lengths corresponding to two representative azimuthal sectors were compared, in which the roughness lengths for the onshore wind sector (i.e., 120°–240°) appear to be larger than the constant value (z0 = 0.2 mm) recommended in much existing literature, whereas the values for the alongshore wind sector (i.e., 60°–90°) are significantly smaller, i.e., about two orders of magnitude less than that of a typical sea surface. However, it is to be noted that the effect of atmospheric stability, which is of crucial importance in governing the marine atmospheric boundary layer, is not taken into account in this study.
Published: 31 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080996

Abstract:
The purpose of the present study is to investigate the impact of rain, snow and hail on potential gradient (PG), as observed in a period of ten years in Xanthi, northern Greece. An anticorrelation between PG and rainfall was observed for rain events that lasted several hours. When the precipitation rate was up to 2 mm/h, the decrease in PG was between 200 and 1300 V/m, in most cases being around 500 V/m. An event with rainfall rates up to 11 mm/h produced the largest drop in PG, of 2 kV/m. Shortly after rain, PG appeared to bounce back to somewhat higher values than the ones of fair-weather conditions. A decrease in mean hourly PG was observed, which was around 2–4 kV/m during the hail events which occurred concurrently with rain and from 0 to 3.5 kV/m for hail events with no rain. In the case of no drop, no concurrent drop in temperature was observed, while, for the other cases, it appeared that, for each degree drop in temperature, the drop in hourly mean PG was 1000 V/m; hence, we assume that the intensity of the hail event regulates the drop in PG. The frequency distribution of 1-minute PG exhibits a complex structure during hail events and extend from −18 to 11 kV/m, with most of the values in the negative range. During snow events, 1-minute PG exhibited rapid fluctuations between high positive and high negative values, its frequency distribution extending from −10 to 18 kV/m, with peaks at −10 and 3 kV/m.
Published: 30 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080986

Abstract:
The outbreak of COVID-19 necessitates developing reliable tools to derive safety measures, including safe social distance and minimum exposure time under different circumstances. Transient Eulerian–Lagrangian computational fluid dynamics (CFD) models have emerged as a viably fast and economical option. Nonetheless, these CFD models resolve the instantaneous distribution of droplets inside a computational domain, making them incapable of directly being used to assess the risk of infection as it depends on the total accumulated dosage of infecting viruses received by a new host within an exposure time. This study proposes a novel risk assessment model (RAM) to predict the temporal and spatial accumulative concentration of infectious exhaled droplets based on the bio-source’s exhalation profile and droplet distribution using the CFD results of respiratory events in various environmental conditions. Unlike the traditional approach in the bulk movement assessment of droplets’ outreach in a domain, every single droplet is traced inside the domain at each time step, and the total number of droplets passing through any arbitrary position of the domain is determined using a computational code. The performance of RAM is investigated for a series of case studies against various respiratory events where the horizontal and the lateral spread of risky zones are shown to temporarily vary rather than being fixed in space. The sensitivity of risky zones to ambient temperature and relative humidity was also addressed for sample cough and sneeze cases. This implies that the RAM provides crucial information required for defining safety measures such as safety distances or minimum exposure times in different environments.
Published: 30 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080983

Abstract:
High resolution air quality models combining emissions, chemical processes, dispersion and dynamical treatments are necessary to develop effective policies for clean air in urban environments, but can have high computational demand. We demonstrate the application of task farming to reduce runtime for ADMS-Urban, a quasi-Gaussian plume air dispersion model. The model represents the full range of source types (point, road and grid sources) occurring in an urban area at high resolution. Here, we implement and evaluate the option to automatically split up a large model domain into smaller sub-regions, each of which can then be executed concurrently on multiple cores of a HPC or across a PC network, a technique known as task farming. The approach has been tested for a large model domain covering the West Midlands, UK (902 km2), as part of modelling work in the WM-Air (West Midlands Air Quality Improvement Programme) project. Compared to the measurement data, overall, the model performs well. Air quality maps for annual/subset averages and percentiles are generated. For this air quality modelling application of task farming, the optimisation process has reduced weeks of model execution time to approximately 35 h for a single model configuration of annual calculations.
Published: 30 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080984

Abstract:
Climate change impacts the characteristics of the vegetation carbon-uptake process in the northern Eurasian terrestrial ecosystem. However, the currently available direct CO2 flux measurement datasets, particularly for central Siberia, are insufficient for understanding the current condition in the northern Eurasian carbon cycle. Here, we report daily and seasonal interannual variations in CO2 fluxes and associated abiotic factors measured using eddy covariance in a coniferous forest and a bog near Zotino, Krasnoyarsk Krai, Russia, for April to early June, 2013–2017. Despite the snow not being completely melted, both ecosystems became weak net CO2 sinks if the air temperature was warm enough for photosynthesis. The forest became a net CO2 sink 7–16 days earlier than the bog. After the surface soil temperature exceeded ~1 °C, the ecosystems became persistent net CO2 sinks. To change into the full spring photosynthesis recovery, the forest is likely to need a minimum accumulated air temperature of ~80 to 137 °C, and the bog requires 141 to 211 °C. During these periods, soil temperature in the forest still remained nearly 0 °C, suggesting that it is likely that forests appear more sensitive to the rise of air temperature than bogs. Net ecosystem productivity was highest in 2015 for both ecosystems because of the anomalously high air temperature in May compared with other years. Our findings demonstrate that long-term monitoring of flux measurements at the site level, particularly during winter and its transition to spring, is essential for understanding the responses of the northern Eurasian ecosystem to spring warming.
Published: 30 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080985

Abstract:
In-situ knowledge on characteristics of mineral aerosols is important for weather and climate prediction models, particularly for modeling such processes as the entrainment, transport and deposition of aerosols. However, field measurements of the dust emission flux, dust size distribution and its chemical composition under realistic wind conditions remain rare. In this study, we present experimental data over annual expeditions in the arid and semi-arid zones of the Caspian Lowland Desert (Kalmykia, south of Russia); we evaluate characteristics of mineral aerosol concentration and fluxes, estimate its chemical composition and calculate its long-distance transport characteristics. The mass concentration in different years ranges from several tens to several hundred of μg m–3. The significant influence of wind velocity on the value of mass and counting concentration and on the proposed entrainment mechanisms is confirmed. An increased content of anthropogenic elements (S, Sn, Pb, Bi, Mo, Ag, Cd, Hg, etc.), which is characteristic for all observation points in the south of the European Russia, is found. The trajectory analysis show that long-range air particles transport from the Caspian Lowland Desert to the central regions of European Russia tends to increase in the recent decades.
Published: 29 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080978

Abstract:
Regional climate projections are widely used in impact studies such as adaptations in agronomy. The big challenge of the climate modeling community is to serve valuable instructions regarding the reliability of these simulations to encourage agronomists to use this kind of information properly. The study validates 15 high-resolution ensembles from the Coordinated Regional Climate Downscaling Experiment-European Domain (EURO-CORDEX) for maximum temperature, minimum temperature, and precipitation to fulfill this task. Three evaluation metrics are calculated (mean absolute error, root mean square error, and correlation) for the means and the 5th and 95th percentiles. The analyses are elaborated for annual and monthly means and the vegetation periods of maize and winter wheat. Only arable lands are considered to exclude the effects of the topography. Furthermore, an ensemble selection is applied based on the evaluation metrics to reduce the data use. The five models with the best performance in the case of winter wheat are CNRM-CM5-CLMcom-CCLM4-8-17_v1, MOHC-HadGEM2-ES-IPSL-WRF381P_v1, MOHC-HadGEM2-ES-KNMI-RACMO22E_v2, MOHC-HadGEM2-ES-CLMcom-CCLM4-8-17_v1, and MPI-M-MPI-ESM-LR-KNMI-RACMO22E_v1. In the case of the vegetation period of maize, the models with the best skills are MPI-M-MPI-ESM-LR-KNMI-RACMO22E_v1, CNRM-CM5-IPSL-WRF381P_v2, MPI-M-MPI-ESM-LR-SMHI-RCA4_v1a, MOHC-HadGEM2-ES-IPSL-WRF381P_v1, and MOHC-HadGEM2-ES-KNMI-RACMO22E_v2. Quantifying the errors in climate simulations against observations and elaborating a selection procedure, we developed a consistent ensemble of high time and space resolution climate projections for agricultural use in Romania.
Published: 29 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080979

Abstract:
This study compared drop size distribution (DSD) measurements on the surfaces, the corresponding properties, and the precipitation modes among three deep convective regions within the Americas. The measurement compilation corresponded to two sites in the midlatitudes: the U.S. Southern Great Plains and Córdoba Province in subtropical South America, as well as to one site in the tropics: Manacapuru in central Amazonia; these are all areas where intense rain-producing systems contribute to the majority of rainfall in the Americas’ largest river basins. This compilation included two types of disdrometers (Parsivel and 2D-Video Disdrometer) that were used at the midlatitude sites and one type of disdrometer (Parsivel) that was deployed at the tropical site. The distributions of physical parameters (such as rain rate R, mass-weighted mean diameter Dm, and normalized droplet concentration Nw) for the raindrop spectra without rainfall mode classification seemed similar, except for the much broader Nw distributions in Córdoba. The raindrop spectra were then classified into a light precipitation mode and a precipitation mode by using a cutoff at 0.5 mm h1 based on previous studies that characterized the full drop size spectra. These segregated rain modes are potentially unique relative to previously studied terrain-influenced sites. In the light precipitation and precipitation modes, the dominant higher frequency observed in a broad distribution of Nw in both types of disdrometers and the identification of shallow light precipitation in vertically pointing cloud radar data represent unique characteristics of the Córdoba site relative to the others. As a result, the co-variability between the physical parameters of the DSD indicates that the precipitation observed in Córdoba may confound existing methods of determining the rain type by using the drop size distribution.
Published: 29 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080981

Abstract:
Climate change, with warming temperatures and shifting precipitation patterns, may increase natural-caused forest fire activity. Increasing natural-caused fires throughout western United States national forests could place people, property, and infrastructure at risk in the future. We used the fine K nearest neighbor (KNN) method coupled with the downscaled Multivariate Adaptive Constructed Analogs (MACA) climate dataset to estimate changes in the rate of natural-caused fires in western United States national forests. We projected changes in the rate of minor and major forest fires from historical (1986–2015) to future (2070–2099) conditions to characterize fire-prone national forests under a range of climate change scenarios. The results indicate that climate change can add to the occurrence of forest fires in western United States national forests, particularly in Rocky Mountain, Pacific Southwest, and Southwestern United States Forest Service regions. Although summer months are projected to have the highest rate of natural-caused forest fire activity in the future, the rate of natural-caused forest fires is likely to increase from August to December in the future compared to the historical conditions. Improved understanding of altered forest fire regimes can help forest managers to better understand the potential effects of climate change on future fire activity and implement actions to attenuate possible negative consequences.
Published: 29 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080980

Abstract:
Future drought-hazard assessments using standardized indices depend on the period used to calibrate the probability distributions. This appears to be particularly important in a changing climate with significant trends in drought-related variables. This study explores the effect of using different approaches to project droughts, with a focus on changes in drought characteristics (frequency, duration, time spent in drought, and spatial extent), estimated with a calibration period covering recent past and future conditions (self-calibrated indices), and another one that only applies recent-past records (relative indices). The analysis focused on the Iberian Peninsula (IP), a hot-spot region where climate projections indicate significant changes by the end of this century. To do this, a EURO-CORDEX multi-model ensemble under RCP8.5 was used to calculate the Standardized Precipitation-Evapotranspiration Index (SPEI) at both 3- and 12-month timescales. The results suggest that projections of drought characteristics strongly depend on the period used to calibrate the SPEI, particularly at a 12-month timescale. Overall, differences were larger for the near future when relative indices indicated more severe droughts. For the distant future, changes were more similar, although self-calibrated indices revealed more frequent and longer-lasting droughts and the relative ones a drought worsening associated with extremely prolonged drought events.
Published: 29 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080982

Abstract:
The ozone concentration in the atmosphere has been recovering with the reduction in atmospheric ozone-depleting substances (ODS). However, ODS remain in the atmosphere for long periods, slowing recovery. Furthermore, greenhouse gas-induced climate change complicates ozone recovery. East Asia is a significant contributor to global climate change due to the increase in industrialization and the presence of complex climate conditions. We investigated ozone variations in East Asia using total column ozone data based on satellite and ground observations and compared the results and trends derived from a multi-linear regression (MLR) model. We found that the MLR model has relatively poor explanatory power for recent extraterrestrial and dynamical proxies, but the uncertainty can be reduced using monthly data and atmospheric proxies. The ozone trend in East Asia had the greatest increase in the vicinity of the Korean Peninsula and Manchuria from 1997 to 2017 (~1% per decade). Similarly, the trend derived from Brewer spectrophotometer data was 1.02 ± 1.45% per decade in Pohang and 1.27 ± 0.85% per decade in Seoul. When the analysis period was extended to 2020, the impact of atmospheric variability was greater, suggesting that recent climate change can increasingly contribute to total ozone variability.
Published: 29 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080977

Abstract:
The number of studies evaluating flux or concentration footprints has grown considerably in recent years. These footprints are vital to understand surface–atmosphere flux measurements, for example by eddy covariance. The newly developed backwards trajectory model LaStTraM (Lagrangian Stochastic Trajectory Model) is a post-processing tool, which uses simulation results of the holistic 3D microclimate model ENVI-met as input. The probability distribution of the particles is calculated using the Lagrangian Stochastic method. Combining LaStTraM with ENVI-met should allow us to simulate flux and concentration footprints in complex urban environments. Applications and evaluations were conducted through a comparison with the commonly used 2D models Kormann Meixner and Flux Footprint Predictions in two different meteorological cases (stable, unstable) and in three different detector heights. LaStTraM is capable of reproducing the results of the commonly used 2D models with high accuracy. In addition to the comparison with common footprint models, studies with a simple heterogeneous and a realistic, more complex model domain are presented. All examples show plausible results, thus demonstrating LaStTraM’s potential for the reliable calculation of footprints in homogeneous and heterogenous areas.
Published: 29 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080975

Abstract:
Mosses are one of the best bioindicators in the assessment of atmospheric aerosol pollution by heavy metals. Studies using mosses allow both short- and long-term air quality monitoring. The increasing contamination of the environment (including air) is causing a search for new, cheap and effective methods of monitoring its condition. Once such method is the use of mosses in active biomonitoring. The aim of the study was to assess the atmospheric aerosol pollution with selected heavy metals (Ni, Cu, Zn, Cd, Hg and Pb) from the smoke of fireworks used during New Year’s Eve in the years 2019/2020 and 2020/2021. In studies a biomonitoring moss-bag method with moss Pleurozium schreberi (Willd. ex Brid.) Mitt. genus Pleurozium was used. The research was conducted in the town Prószków (5 km in south direction from Opole, opolskie voivodship, Poland). The moss was exposed 14 days before 31 December (from 17 to 30 of December), on New Year’s Eve (31 December and 1 January) and 2 weeks after the New Year (from 2–15 January). Higher concentrations of analysed elements were determined in samples exposed during New Year’s Eve. Increases in concentrations were demonstrated by analysis of the Relative Accumulation Factor (RAF). The results indicate that the use of fireworks during New Year’s Eve causes an increase in air pollution with heavy metals. In addition, it was shown that the COVID-19 induced restrictions during New Year’s Eve 2020 resulted in a reduction of heavy metal content in moss samples and thus in lower atmospheric aerosol pollution with these analytes. The study confirmed moss usefulness in monitoring of atmospheric aerosol pollution from point sources.
Published: 29 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080976

Abstract:
Nitrogen (N) addition is an important nutrient strategy for alpine grassland in northwestern China to improve productivity for livestock needs. A field experiment was conducted in a semi-arid alpine grassland in northwestern China to investigate the effect of N addition rates on soil N2O emissions over the growing seasons of 2017 and 2018. Treatments included six N addition rates (0, 10, 30, 60, 120, 240 kg N ha−1 y−1), which were applied before each growing season. The N2O fluxes increased with N addition rates and showed different episodic changes between the two growing seasons. In 2017, the maximum N2O flux rate occurred within 2 weeks following N addition. In 2018, however, the maximum N2O flux rate occurred later in the growing season due to a heavy rainfall event. Growing season cumulative N2O emissions ranged between 0.32 and 1.11 kg N ha−1, and increased linearly with N addition rates. Increasing N addition rates over 60 kg N ha−1 yr−1 did not further increase plant above-ground biomass. The inter-annual variability of N2O flux suggests the importance of soil moisture in affecting N2O emissions. It is particularly important to avoid over-applying N nutrients beyond plant needs to reduce its negative effect on the environment while maintaining livestock productivity. The N2O flux rate increased with soil dissolved organic carbon (DOC) and soil pH. These results suggest the optimal N addition rate to the livestock grassland in this region should be 60 kg N ha−1 yr−1.
Published: 28 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080970

Abstract:
Chronic obstructive pulmonary disease (COPD) is a major and increasingly prevalent respiratory health problem worldwide and the fine particulate matter (PM2.5) is now becoming a rising health threat to it. This study aims to conduct a comparison analysis of health effect on acute exacerbation of COPD (AECOPD) associated with PM2.5 exposure in two typical cities (Beijing and Shenzhen) with different levels of PM2.5 pollution. Both correlational relationship and causal connection between PM2.5 exposure and AECOPD are investigated by adopting a time series analysis based on the generalized additive model (GAM) and convergent cross mapping (CCM). The results from GAM indicate that a 10 μg/m3 increase in PM2.5 concentration is associated with 2.43% (95% CI, 0.50–4.39%) increase in AECOPD on Lag0-2 in Beijing, compared with 6.65% (95% CI, 2.60–10.87%) on Lag0-14 in Shenzhen. The causality detection with CCM reveals similar significant causative impact of PM2.5 exposure on AECOPD in both two study areas. Findings from two methods agree that PM2.5 has non-negligible health effect on AECOPD in both two study areas, implying that air pollution can cause adverse consequences at much lower levels than common cognition. Our study highlights the adverse health effect of PM2.5 on people with COPD after exposure to different levels of PM2.5 and emphasizes that adverse effect in area with relative low pollution level cannot be overlooked. Governments in both high-pollution and low-pollution cities should attach importance to the adverse effects of PM2.5 on humans and take corresponding measures to control and reduce the related losses.
Published: 28 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080968

Abstract:
To quantify the ecosystem services of trees in urban environments, it is necessary to assess received direct solar radiation of each tree. While the Sky View Factor (SVF) is suitable for assessing the total incoming short- and longwave radiation fluxes, its information is limited to specific points in space. For a spatial analysis, it is necessary to sample the area for SVF. A new geometrical method, Area View Factor (AVF), for the calculation of sunlit areas is proposed. AVF is the ratio of the unhidden, projected surface of an object to the whole projected surface of an object in a complex environment. Hereby, a virtual, orthographic camera is oriented in accordance to the sun’s position in the 3D model domain. The method is implemented in the microscale model SkyHelios, utilizing efficient rendering techniques to assess AVF of all urban trees in parallel. The method was applied to Rieselfeld in Freiburg, Germany. The assessed sunlit area is compared to the SVF at the top of each tree and solar altitude angle, revealing a strong relationship between sunlit areas to solar altitude angles. This study shows that AVF is an efficient methodology to assess received direct radiation of urban trees. Based on AVF, it is possible to identify urban areas with shaded and sunlit trees, but it can also be applied to other objects in complex environments. Therefore, AVF is applicable for urban architecture or energetic research questions.
Published: 28 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080969

Abstract:
Biological systems are shaped by environmental pressures. These processes are implemented through the organisms exploiting their adaptation abilities and, thus, improving their spreading. Photosynthesis, transpiration, and water use efficiency are major physiological parameters that vary among organisms and respond to abiotic conditions. Invasive species exhibited special physiological performance in the invaded habitat. Photosynthesis and transpiration intensity of Fallopia japonica, Heracleum sosnowskyi, and Rumex confertus of northern and trans-Asian origin were performed in temperate extensive seminatural grassland or natural forest ecotones. The observed photosynthetically active radiation (PAR) ranged from 36.0 to 1083.7 μmol m−2 s−1 throughout the growing season depending on the meteorological conditions and habitat type. F. japonica and H. sosnowskyi settled in naturally formed shadowy shrub habitats characterized by the lowest mean PAR rates of 58.3 and 124.7 μmol m−2 s−1, respectively. R. confertus located in open seminatural grassland habitats where the mean PAR was 529.35 μmol m−2 s−1. Correlating with the available sunlight radiation (r = 0.9), the highest average photo assimilation rate was observed for R. confertus (p = 0.000). The lowest average intensity of photosynthesis rates was exhibited of F. japonica and H. sosnowskyi in shadowy shrub habitats. Transpiration and water use effectivity at the leaf level depended on many environmental factors. Positive quantitative responses of photosynthesis and transpiration to soil and meteorological conditions confirmed positive tolerance strategies of the invasive species succeeded by environmental adaptation to new habitats during their growing period sustained across a range of environments.
Published: 28 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080972

Abstract:
The purpose of this study was to analyze the effect of titanium dioxide (TiO2) on reducing nitrogen oxide (NOx) concentrations using the statistical method of the Anderson-Darling test. To compare and analyze this effect, a spray-type form of TiO2 was applied to the asphalt pavement surface on urban roads. Data acquisition for NOx concentration was collected from a test section with TiO2 applied and a reference section without TiO2 applied. The probabilities of occurrence of the NOx concentration in the test and reference section were estimated and compared using the Anderson-Darling test. In sum, most of the NOx concentrations were probabilistically lower in the test section. The average probability of the NOx concentration in the test section in the ‘low’ range was 46.2% higher than in the reference section. In the ‘high’ and ‘moderate’ ranges, the average probability of the NOx concentration compared to that of the reference section was lower by 28.1% and 18.8%, respectively. These results revealed that the photochemical reaction from the TiO2 material applied on asphalt pavement was effective in reducing NOx.
Published: 28 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080973

Abstract:
Having an extreme topography and heterogeneous climate, the Upper Indus Basin (UIB) is more likely to be affected by climate change and it is a crucial area for climatological studies. Based on the monthly minimum temperature (Tmin), maximum temperature (Tmax) and precipitation from nine meteorological stations, the spatiotemporal variability of temperature and precipitation were analyzed on monthly, seasonal, and annual scales. Results show a widespread significant increasing trend of 0.14 °C/decade for Tmax, but a significant decreasing trend of −0.08 °C/decade for Tmin annually, during 1955–2016 for the UIB. Seasonally, warming in Tmax is stronger in winter and spring, while the cooling in Tmin is greater in summer and autumn. Results of seasonal Tmax indicate increasing trends in winter, spring and autumn at rates of 0.38, 0.35 and 0.05 °C/decade, respectively, while decreasing in summer with −0.14 °C/decade. Moreover, seasonal Tmin results indicate increasing trends in winter and spring at rates of 0.09 and 0.08 °C/decade, respectively, while decreasing significantly in summer and autumn at rates of −0.21 and −0.22 °C/decade respectively for the whole the UIB. Precipitation exhibits an increasing trend of 2.74 mm/decade annually, while, increasing in winter, summer and autumn at rates of 1.18, 2.06 and 0.62 mm/decade respectively. The warming in Tmax and an increase in precipitation have been more distinct since the mid-1990s, while the cooling in Tmin is observed in the UIB since the mid-1980s. Warming in the middle and higher altitude (1500–2800 m and >2800 m) are much stronger, and the increase is more obvious in regions with elevation >2800 m. The wavelet analysis illustrated sporadic inter-annual covariance of seasonal Tmax, Tmin and precipitation with ENSO, NAO, IOD and PDO in the UIB. The periodicities were usually constant over short timescales and discontinuous over longer timescales. This study offers a better understanding of the local climate characteristics and provides a scientific basis for government policymakers.
Published: 28 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080974

Abstract:
Grass pollen allergy is widespread all around the globe. With an increasing number of people living in cities, the examination of grass pollen levels within cities and their surroundings has increased in importance. The aim of this study was to examine different temporal and spatial scales of grass pollen concentration and deposition across urban and semi-rural environments in the years 2019 and 2020. We installed different types of pollen traps in the city of Ingolstadt (Bavaria, Germany) and its surroundings: volumetric pollen traps at roof level to assess background pollen concentration and gravimetric pollen traps and portable volumetric traps at street level. We considered grass pollen concentration and deposition in the context of land use and management. Our data showed that the grass pollen season in 2020 was longer and more intense than in 2019. Background grass pollen concentration was generally higher at the semi-rural site in both years: peak values were eight times (2019) and more than four times (2020) higher, and Seasonal Pollen Index was more than four times and almost three times higher in 2019 and 2020, respectively. Analyses of spatial variations measured at street level revealed higher numbers for pollen deposition and concentrations at semi-rural than at urban sites. Recorded values were linked to local vegetation and the management of grass areas surrounding the traps. Analyses of diurnal variations at street level in June 2019 showed that pollen concentration for all sites, independent of their degree of urbanization, were highest at noon (22.2 pollen grains/m³ vs. 8.5 pollen grains/m³ in the morning and 10.4 pollen grains/m³ in the evening). Diurnal variations at roof level showed similarities for the same days but differed when considering the whole season. Our data suggest the importance of the management of grass areas as areas cut earlier have a decreased amount of emitted pollen.
Published: 28 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080971

Abstract:
Recently, some commercially available active-type radon–thoron monitors were developed; however, their performance has not been characterized. This article presents the characteristics of three commercially available active-type radon–thoron monitors (RAD7, Radon Mapper, and AlphaGUARD) at different sampling flow rates. The thoron concentration measured by the monitors was compared with the reference value measured by a grab sampling method. As a result, the ratio of the measured concentration to the reference increased with flow rate for the RAD7 and the Radon Mapper although that of the AlphaGUARD decreased. The difference may be attributed to the coefficients used in the calculation and the measurement time scheme. The results indicate the importance of the sampling flow rate in thoron measurement. Monitoring of flow rate at the measurement and periodic calibration at multiple sampling flow rates should be conducted for quality assurance and quality control of the measurand.
Published: 28 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080967

Abstract:
Ensuring high air quality in the atmosphere of Zhijindong Cave is essential, for it is one of the most scenic in Asia and has received millions of tourists each year. Radon, as the most important radioactive carcinogen, is a priority and has been measured since just after its opening. However, an artificial exit was opened in 2002, and it is still unclear what the influence of that has been on the radon concentration in the cave atmosphere. In this study, we use RAD7 to monitor the spatiotemporal variations of radon concentration in the atmosphere of Zhijindong Cave for a whole year. The results show that radon concentration is generally higher in the hot season and lower in the cold season, and both with a distinct spatial differences. The highest measured radon concentration is 1691 Bq/m3, which is lower compared with the previous study. The reduced radon concentration could be caused by the strengthened cave ventilation due to the artificial exit. The temporal variation of radon concentration is related to the outside temperature change, while the spatial variation is mostly related to the different cave layers. The effective dose is negligible for tourists, but can be as high as 9.7 mSv for tour guides and 22.6 mSv for photographers.
Published: 27 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080963

Abstract:
Accurate estimation of the timing of intensive spring leaf growth initiation at mid and high latitudes is crucial for improving the predictive capacity of biogeochemical and Earth system models. In this study, we focus on the modeling of climatological onset of spring leaf growth in Central Europe and use three spring phenology models driven by three meteorological datasets. The MODIS-adjusted NDVI3g dataset was used as a reference for the period between 1982 and 2010, enabling us to study the long-term mean leaf onset timing and its interannual variability (IAV). The performance of all phenology model–meteorology database combinations was evaluated with one another, and against the reference dataset. We found that none of the constructed model–database combinations could reproduce the observed start of season (SOS) climatology within the study region. The models typically overestimated IAV of the leaf onset, where spatial median SOS dates were best simulated by the models based on heat accumulation. When aggregated for the whole study area, the complex, bioclimatic index-based model driven by the CarpatClim database could capture the observed overall SOS trend. Our results indicate that the simulated timing of leaf onset primarily depends on the choice of model structure, with a secondary contribution from the choice of the driving meteorological dataset.
Published: 27 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080962

Abstract:
Tea is one of the most significant cash crops and plays an important role in economic development and poverty reduction. On the other hand, tea is an optimal choice in the extreme weather conditions of Tanuyen Laichau, Vietnam. In our study, the NDVI variation of tea in the growing season from 2009 to 2018 was showed by calculating NDVI trend and the Mann-Kendall analysis to assess trends in the time series. Support Vector Machine (SVM) and Random Forest (RF) model were used for predicting tea yield. The NDVI of tea showed an increasing trend with a slope from −0.001–0.001 (88.9% of the total area), a slope from 0.001–0.002 (11.1% of the total area) and a growing rate of 0.00075/year. The response of tea NDVI to almost climatic factor in a one-month time lag is higher than the current month. The tea yield was estimated with higher accuracy in the RF model. Among the input variables, we detected that the role of Tmean and NDVI is stronger than other variables when squared with each of the independent variables into input data.
Published: 27 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080965

Abstract:
Climate change causes more frequent and destructive wildfires even transforming them into megafire. Moreover, all biomass fires produce emissions of carbon compounds in the form of soot to the atmosphere with a significant impact on the environment and human health. Indeed, the soot is causing the formation of PAHs from (a) the high temperature thermal alteration of natural product precursors in the source organic matter and (b) the recombination of molecular fragments in the smoke. However, these molecules are known to have carcinogenic effects on human health. It is therefore interesting to quantify the 16 PAHs concentration extracted from soot emitted in open diffusion flame of biomass combustion. To achieve this objective, an analytical method developed for the study of kerosene combustion has been adapted for soot from biomass. This new method allowed to quantify the 16 PAHs defined as priority pollutants by the US EPA for their carcinogenic mutagenic effect and on human health.
Published: 27 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080960

Abstract:
Understanding rainfall anomalies and their relationship with floods in the Yangtze River Basin (YRB) is essential for evaluating flood disasters, which have a great impact on the development of agriculture and the economy. On the basis of daily rainfall data from 1961 to 2010 from 178 meteorological stations, the temporal and spatial characteristics of rainfall anomalies in the YRB were studied on an annual scale, seasonal scale, and monthly scale. The annual rainfall of the YRB showed a generally increasing trend from 1961 to 2010 (14.22 mm/10 a). By means of the Bernaola–Galvan abrupt change test and Redfit spectrum analysis, it was found that the annual average rainfall increased abruptly after 1979 and had a cycle of 2–3 years. On the seasonal scale, the rainfall in spring and autumn showed a gradually decreasing trend, especially in September, while it showed a significant increasing trend in summer and winter in the YRB. As for the monthly scale, the rainfall in the rainy season from June to July presented a clear increasing trend during the study period, which greatly enhanced the probability of floods in the YRB. Additionally, through the analysis of the spatial distribution characteristics of rainfall in the entire YRB from 1961 to 2010, it was observed that the annual rainfall amount in the YRB presented an “increase–decrease–increase” tendency from east to west, accompanied by a rain belt that continuously moved from west to east. Moreover, the rainfall characteristics in flood years were summarized, and the results revealed that the years with rainfall anomalies were more likely to have flood disasters. However, anomalies alone would not result in big floods; the spatially and temporally inhomogeneous rainfall distribution might be the primary reason for flood disasters in the entire YRB.
Published: 27 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080966

Abstract:
The implementation of statistical postprocessing of ensemble forecasts is increasingly developed among national weather services. The so-called Ensemble Model Output Statistics (EMOS) method, which consists of generating a given distribution whose parameters depend on the raw ensemble, leads to significant improvements in forecast performance for a low computational cost, and so is particularly appealing for reduced performance computing architectures. However, the choice of a parametric distribution has to be sufficiently consistent so as not to lose information on predictability such as multimodalities or asymmetries. Different distributions are applied to the postprocessing of the European Centre for Medium-range Weather Forecast (ECMWF) ensemble forecast of surface temperature. More precisely, a mixture of Gaussian and skewed normal distributions are tried from 3- up to 360-h lead time forecasts, with different estimation methods. For this work, analytical formulas of the continuous ranked probability score have been derived and appropriate link functions are used to prevent overfitting. The mixture models outperform single parametric distributions, especially for the longest lead times. This statement is valid judging both overall performance and tolerance to misspecification.
Published: 27 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080964

Abstract:
The use of weather satellite recordings has been growing rapidly over the last three decades. Determining the patterns between meteorological and topographical features is an important scientific job. Cloud cover analysis and properties can be of the utmost significance for potential cloud seeding. Here, the analysis of the cloud properties was conducted by means of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite recordings. The resolution of used data was 1 km2 within the period of 30 years (1989–2019). This research showed moderate changing of cloudiness in the territory of Serbia with a high cloudiness in February, followed by cloudiness in January and November. For the past three decades, May has been the month with the highest cloudiness. The regions in the east and south-west, and particularly in the west, have a high absolute cloudiness, which is connected with the high elevation of the country. By means of long term monitoring, the whole territory of Serbia was analyzed for the first time, in terms of cloudiness. Apart from the statistical and numerical results obtained, this research showed a connection between relief and clouds, especially in the winter season. Linear regression MK (Mann-Kendall test) has proven this theory right, connecting high elevation sides with high absolute cloudiness through the year.
Published: 27 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080961

Abstract:
The increased availability of commercially-available low-cost air quality sensors combined with increased interest in their use by citizen scientists, community groups, and professionals is resulting in rapid adoption, despite data quality concerns. We have characterized three out-the-box PM sensor systems under different environmental conditions, using field colocation against reference equipment. The sensor systems integrate Plantower 5003, Sensirion SPS30 and Alphasense OCP-N3 PM sensors. The first two use photometry as a measuring technique, while the third one is an optical particle counter. For the performance evaluation, we co-located 3 units of each manufacturer and compared the results against optical (FIDAS) and gravimetric (KFG) methods for a period of 7 weeks (28 August to 19 October 2020). During the period from 2nd and 5th October, unusually high PM concentrations were observed due to a long-range transport episode. The results show that the highest correlations between the sensor systems and the optical reference are observed for PM1, with coefficients of determination above 0.9, followed by PM2.5. All the sensor units struggle to correctly measure PM10, and the coefficients of determination vary between 0.45 and 0.64. This behavior is also corroborated when using the gravimetric method, where correlations are significantly higher for PM2.5 than for PM10, especially for the sensor systems based on photometry. During the long range transport event the performance of the photometric sensors was heavily affected, and PM10 was largely underestimated. The sensor systems evaluated in this study had good agreement with the reference instrumentation for PM1 and PM2.5; however, they struggled to correctly measure PM10. The sensors also showed a decrease in accuracy when the ambient size distribution was different from the one for which the manufacturer had calibrated the sensor, and during weather conditions with high relative humidity. When interpreting and communicating air quality data measured using low-cost sensor systems, it is important to consider such limitations in order not to risk misinterpretation of the resulting data.
Published: 26 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080959

Abstract:
Adverse health outcomes caused by ambient particulate matter (PM) pollution occur in a progressive process, with neutrophils eliciting inflammation or pathogenesis. We investigated the toxico-transcriptomic mechanisms of PM in real-life settings by comparing healthy residents living in Beijing and Chengde, the opposing ends of a well-recognised air pollution (AP) corridor in China. Beijing recruits (BRs) uniquely expressed ~12,000 alternative splicing (AS)-derived transcripts, largely elevating the proportion of transcripts significantly correlated with PM concentration. BRs expressed PM-associated isoforms (PMAIs) of PFKFB3 and LDHA, encoding enzymes responsible for stimulating and maintaining glycolysis. PMAIs of PFKFB3 featured different COOH-terminals, targeting PFKFB3 to different sub-cellular functional compartments and stimulating glycolysis. PMAIs of LDHA have longer 3′UTRs relative to those expressed in Chengde recruits (CRs), allowing glycolysis maintenance by enhancing LDHA mRNA stability and translational efficiency. PMAIs were directly regulated by different HIF-1A and HIF-1B isoforms. BRs expressed more non-functional Fas isoforms, and a resultant reduction of intact Fas proportion is expected to inhibit the transmission of apoptotic signals and prolong neutrophil lifespan. BRs expressed both membrane-bound and soluble IL-6R isoforms instead of only one in CRs. The presence of both IL-6R isoforms suggested a higher migration capacity of neutrophils in BRs. PMAIs of HIF-1A and PFKFB3 were downregulated in Chronic Obstructive Pulmonary Disease patients compared with BRs, implying HIF-1 mediated defective glycolysis may mediate neutrophil dysfunction. PMAIs could explain large variances of different phenotypes, highlighting their potential application as biomarkers and therapeutic targets in PM-induced diseases, which remain poorly elucidated.
Published: 26 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080958

Abstract:
Heavy and localized summer events are very hard to predict and, at the same time, potentially dangerous for people and properties. This paper focuses on an event occurred on 15 July 2020 in Palermo, the largest city of Sicily, causing about 120 mm of rainfall in 3 h. The aim is to investigate the event predictability and a potential way to improve the precipitation forecast. To reach this aim, lightning (LDA) and radar reflectivity data assimilation (RDA) was applied. LDA was able to trigger deep convection over Palermo, with high precision, whereas the RDA had a key role in the prediction of the amount of rainfall. The simultaneous assimilation of both data sources gave the best results. An alert for a moderate–intense forecast could have been issued one hour and a half before the storm developed over the city, even if predicting only half of the total rainfall. A satisfactory prediction of the amount of rainfall could have been issued at 14:30 UTC, when precipitation was already affecting the city. Although the study is centered on a single event, it highlights the need for rapidly updated forecast cycles with data assimilation at the local scale, for a better prediction of similar events.
Published: 25 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080957

Abstract:
A dendrochronological series of Araucaria angustifolia was analyzed for a better understanding of the climatic factors that operate in Campos do Jordão city, São Paulo state, Brazil. The dendroclimatic analysis was carried out using 45 samples from 16 Araucaria angustifolia trees to reconstruct the precipitation and the temperature over the 1803–2012 yearly interval. To this end, Pearson’s correlation was calculated between mean chronology and the climatic time series using a monthly temporal resolution to calibrate our models. We obtained correlations as high as r=0.22(α=0.1) for precipitation (February), and r=0.21(α=0.1) for temperature (March), both corresponding to the end of the summer season. Our results show evidence of temporal instabilities because the correlations for the halves of 1963–2012 were very different, as well as for the full period. To overcome this problem, the dendrochronological series and the climatic data were investigated using the wavelet techniques searching for time-dependent cause–effect relationships. From these analyses, we find a strong influence of the region’s precipitation and temperature on the growth of tree ring widths.
Published: 24 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080953

Abstract:
In the event of an accidental or intentional hazardous material release in the atmosphere, researchers often run physics-based atmospheric transport and dispersion models to predict the extent and variation of the contaminant spread. These predictions are imperfect due to propagated uncertainty from atmospheric model physics (or parameterizations) and weather data initial conditions. Ensembles of simulations can be used to estimate uncertainty, but running large ensembles is often very time consuming and resource intensive, even using large supercomputers. In this paper, we present a machine-learning-based method which can be used to quickly emulate spatial deposition patterns from a multi-physics ensemble of dispersion simulations. We use a hybrid linear and logistic regression method that can predict deposition in more than 100,000 grid cells with as few as fifty training examples. Logistic regression provides probabilistic predictions of the presence or absence of hazardous materials, while linear regression predicts the quantity of hazardous materials. The coefficients of the linear regressions also open avenues of exploration regarding interpretability—the presented model can be used to find which physics schemes are most important over different spatial areas. A single regression prediction is on the order of 10,000 times faster than running a weather and dispersion simulation. However, considering the number of weather and dispersion simulations needed to train the regressions, the speed-up achieved when considering the whole ensemble is about 24 times. Ultimately, this work will allow atmospheric researchers to produce potential contamination scenarios with uncertainty estimates faster than previously possible, aiding public servants and first responders.
Published: 24 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080956

Abstract:
Atmospheric turbulent circulations in the vicinity of wildland fire fronts play an important role in the transfer of momentum into and out of combustion zones, which in turn can potentially affect the behavior and spread of wildland fires. The vertical turbulent transfer of momentum is accomplished via individual sweep, ejection, outward interaction, and inward interaction events, collectively known as sweep-ejection dynamics. This study examined the sweep-ejection dynamics that occurred before, during, and after the passage of a surface fire front during a prescribed fire experiment conducted in an open-canopied forest in the New Jersey Pine Barrens. High-frequency (10 Hz), tower-based, sonic anemometer measurements of horizontal and vertical wind velocity components in the vicinity of the fire front were used to assess the relative frequencies of occurrence of the different types of momentum-flux events, their contributions to the overall momentum fluxes, and their periodicity patterns. The observational results suggest that the presence of surface fire fronts in open-canopied forests can substantially change the sweep-ejection dynamics that typically occur when fires are not present. In particular, sweep events resulting in the downward transport of high horizontal momentum air from above were found to be more prominent during fire-front-passage periods.
Published: 24 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080952

Abstract:
As the main source of dust in Asia, China often suffers from dust events. The temporal and spatial characteristics of dust events change with the variations of geography, climate and human activities. Based on the criteria of selecting dust events proposed recently by the China Environmental Monitoring Station, the hourly concentration of PM10 and PM2.5 of 336 cities in China from 2015 to 2020 were used to study the temporal and spatial characteristics of dust events more accurately and objectively. The results showed that all of the dust events in China clearly decreased, but the strong dust events did not decrease. There were 334 cities that had dust events except Shenzhen and Dongguan, 299 cities were seriously polluted due to dust events, 134 cities encountered dust level III and 56 cities encountered dust level IV. The high frequencies of dust events were mainly distributed in Northern China, especially in Northwest China. The dust contribution of PM10 to the cities in Northwest China was more than 10% and about 5–10% for PM2.5. The most likely month for dust was May. The starting time of dust was bimodally distributed, and the most common starting time was 10:00–11:00 BJT, followed by 22:00–23:00 BJT. According to the PSCF (Potential Source Contribution Function) results, the dust potential source contribution of different cities mainly came from the northwest, and was mainly affected by Mongolia in addition to the local dust in China. In addition, Beijing was obviously affected by dust recirculation. This study is of great significance to the improvement of the forecast of dust weather and the warning of heavy pollution caused by dust events.
Published: 24 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080954

Abstract:
The Indian Summer Monsoon (ISM) plays a vital role in the livelihoods and economy of those living on the Indian subcontinent, including the small, mountainous country of Bhutan. The ISM fluctuates over varying temporal scales and its variability is related to many internal and external factors including the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). In 2015, a Super El Niño occurred in the tropical Pacific alongside a positive IOD in the Indian Ocean and was followed in 2016 by a simultaneous La Niña and negative IOD. These events had worldwide repercussions. However, it is unclear how the ISM was affected during this time, both at a regional scale over the whole ISM area and at a local scale over Bhutan. First, an evaluation of data products comparing ERA5 reanalysis, TRMM and GPM satellite, and GPCC precipitation products against weather station measurements from Bhutan, indicated that ERA5 reanalysis was suitable to investigate ISM change in these two years. The reanalysis datasets showed that there was disruption to the ISM during this period, with a late onset of the monsoon in 2015, a shifted monsoon flow in July 2015 and in August 2016, and a late withdrawal in 2016. However, this resulted in neither a monsoon surplus nor a deficit across both years but instead large spatial-temporal variability. It is possible to attribute some of the regional scale changes to the ENSO and IOD events, but the expected impact of a simultaneous ENSO and IOD events are not recognizable. It is likely that 2015/16 monsoon disruption was driven by a combination of factors alongside ENSO and the IOD, including varying boundary conditions, the Pacific Decadal Oscillation, the Atlantic Multi-decadal Oscillation, and more. At a local scale, the intricate topography and orographic processes ongoing within Bhutan further amplified or dampened the already altered ISM.
Published: 24 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080955

Abstract:
The atmosphere over the Atlantic Ocean is highly impacted by human activities on the surrounding four major continents. Globally, human activity creates significant burdens for the sustainability of key Earth systems, pressuring the planetary boundaries of environmental sustainability. Here, we propose a science-based integrated approach addressing linked science and policy challenges in the North Atlantic. There is a unique combination of ongoing anthropogenic changes occurring in the coupled atmosphere–ocean environment of the region related to climate, air and water quality, the biosphere and cryosphere. This is matched by a unique potential for the societies that surround the North Atlantic to systematically address these challenges in a dynamic and responsive manner. Three key linked science-policy challenges to be addressed as part of this proposed integrated regional approach are: (1) understanding physical and dynamic changes, (2) sustaining human and ecosystem health and (3) reducing existing knowledge gaps on the carbon budget and the Earth’s energy balance. We propose a North Atlantic multidisciplinary scientific assessment system and observation network to address these thematic challenges. We propose to build on and link with the existing research activities and observational networks and infrastructures to specifically address the key North Atlantic challenges that encompass a range of policy areas. This will strengthen the institutional response to weather, climate, environmental and ecological threats and reduce societal risk.
Published: 23 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080949

Abstract:
We discuss the measurements of black carbon concentrations in the composition of atmospheric aerosol over the seas of the North Atlantic and European sector of the Arctic Ocean (21 expeditions in 2007–2020). The black carbon concentrations were measured by an aethalometer and filter method. The comparison of the two variants of the measurements of the black carbon concentrations showed that the data acceptably agreed and can be used jointly. It is noted that the spatial distribution of black carbon over the ocean is formed under the influence of outflows of air masses from the direction of continents, where the main sources of emission of absorbing aerosol are concentrated. We analyzed the statistical characteristics of black carbon concentrations in five marine regions, differing by the outflows of continental aerosol. The largest black carbon content is a salient feature of the atmosphere of the North and Baltic Seas, surrounded by land: average values of concentrations are 210 ng/m3, and modal values are 75 ng/m3. In other regions (except in the south of the Barents Sea), the average black carbon concentrations are 37–44 ng/m3 (modal concentrations are 18–26 ng/m3). We discuss the specific features of the spatial (latitude-longitude) distributions of black carbon concentrations, relying on ship-based measurements and model calculations (MERRA-2 reanalysis data). A common regularity of the experimental and model spatial distributions of black carbon is that the concentrations decrease in the northern direction and with the growing distance from the continent: from several hundred ng/m3 in the southern part of the North Sea to values below 50 ng/m3 in polar regions of the ocean.
Published: 23 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080944

Abstract:
In this study, a Land Data Assimilation System (LDAS) is applied over the Carpathian Basin at the Hungarian Meteorological Service to monitor the above-ground biomass, surface fluxes (carbon and water), and the associated root-zone soil moisture at the regional scale (spatial resolution of 8 km × 8 km) in quasi-real-time. In this system the SURFEX model is used, which applies the vegetation growth version of the Interactions between Soil, Biosphere and Atmosphere (ISBA-A-gs) photosynthesis scheme to describe the evolution of vegetation. SURFEX is forced using the outputs of the ALADIN numerical weather prediction model run operationally at the Hungarian Meteorological Service. First, SURFEX is run in an open-loop (i.e., no assimilation) mode for the period 2008–2015. Secondly, the Extended Kalman Filter (EKF) method is used to assimilate Leaf Area Index (LAI) Spot/Vegetation (until May 2014) and PROBA-V (from June 2014) and Soil Water Index (SWI) ASCAT/Metop satellite measurements. The benefit of LDAS is proved over the whole country and to a selected site in West Hungary (Hegyhátsál). It is demonstrated that the EKF can provide useful information both in wet and dry seasons as well. It is shown that the data assimilation is efficient to describe the inter-annual variability of biomass and soil moisture values. The vegetation development and the water and carbon fluxes vary from season to season and LDAS is a capable tool to monitor the variability of these parameters.
Published: 23 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080950

Abstract:
Sea breezes have been observed to move inland over 100 km. These airmasses can be markedly different from regional airmasses, creating a shallow layer with differences in humidity, wind, temperature and aerosol characteristics. To understand their influence on boundary layer and cloud development on subsequent days, we identify their frequency and characteristics. We visually identified sea breeze fronts on radar passing over the Savannah River Site (SRS) between March and October during 2015–2019. The SRS is ~150 km from the nearest coastal location; therefore, our detection suggests further inland penetration. We also identified periods when sea breeze fronts may have passed but were not visually observed on radar due to the shallow sea breeze airmass remaining below the radar beam elevation that ranges between approximately 1–8 km depending on the beam angle and radar source (Columbia, SC or Charleston, SC). Near-surface atmospheric measurements indicate that the dew point temperature increases, the air temperature decreases, the variation in wind direction decreases and the aerosol size increases after sea breeze frontal passage. A synoptic classification procedure also identified that inland moving sea breezes are more commonly observed when the synoptic conditions include weak to moderate offshore winds with an average of 35 inland sea breezes occurring each year, focused primarily in the months of April, May and June.
Published: 23 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080948

Abstract:
The main goal of this study is to present a recently developed classification method for weather types based on the vorticity and the location of the synoptic centers relative to the Adriatic region. The basis of the present objective classification, applied to the Adriatic region, is the subjective classification developed by Poje. Our algorithm considered daily mean sea-level pressure and 500 hPa geopotential height to define one out of 17 possible weather types. We applied the algorithm to identify which weather type was relevant in the generation of the two typical near-surface winds over the Adriatic region, namely Bora and Sirocco. Two high-resolution (0.11°) EURO-CORDEX regional climate models were used, SMHI-RCA4 and DHMZ-RegCM4, forced by several CMIP5 global climate models and analyzed for two 30-year periods: near-present day and mid-21st century climate conditions under the high-end Representative Concentration Pathway (RCP8.5) scenario. Bora and Sirocco days were extracted for each weather type and a distribution over the 30-year period was presented. Our results suggest that in the winter season, climate model projections indicate a reduction in the main cyclonic types relevant in the formation of Bora over the entire Adriatic region and an increase in the number of anticyclonic types relevant in Sirocco events. In contrast, for the summer season, an increase in the main anticyclonic Bora-related weather types is found in the ensemble over the northern Adriatic region.
Published: 23 July 2021
by MDPI
Atmosphere, Volume 12; doi:10.3390/atmos12080951

Abstract:
The COVID-19 pandemic resulted in stay-at-home policies and other social distancing behaviors in the United States in spring of 2020. This paper examines the impact that these actions had on emissions and expected health effects through reduced personal vehicle travel and electricity consumption. Using daily cell phone mobility data for each U.S. county, we find that vehicle travel dropped about 40% by mid-April across the nation. States that imposed stay-at-home policies before March 28 decreased travel slightly more than other states, but travel in all states decreased significantly. Using data on hourly electricity consumption by electricity region (e.g., balancing authority), we find that electricity consumption fell about 6% on average by mid-April with substantial heterogeneity. Given these decreases in travel and electricity use, we estimate the county-level expected improvements in air quality, and, therefore, expected declines in mortality. Overall, we estimate that, for a month of social distancing, the expected premature deaths due to air pollution from personal vehicle travel and electricity consumption declined by approximately 360 deaths, or about 25% of the baseline 1500 deaths. In addition, we estimate that CO2 emissions from these sources fell by 46 million metric tons (a reduction of approximately 19%) over the same time frame.
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