Editor’s Choice Articles

The modelling of thermal exposure in outdoor urban environments is a highly topical challenge in modern climate research. This paper presents the results derived from a new micrometeorological model that employs an integrated biometeorology module to model Universal Thermal Climate Index (UTCI). This is PALM-4U, which includes an integrated human body-shape parameterization, deployed herein for a pilot domain in Prague, Czech Republic. The results highlight the key role of radiation in the spatiotemporal variability of thermal exposure in moderate-climate urban areas during summer days in terms of the way in which this directly affects thermal comfort through radiant temperature and indirectly through the complexity of turbulence in street canyons. The model simulations suggest that the highest thermal exposure may be expected within street canyons near the irradiated north sides of east–west streets and near streets oriented north–south. Heat exposure in streets increases in proximity to buildings with reflective paints. The lowest heat exposure during the day may be anticipated in tree-shaded courtyards. The cooling effect of trees may range from 4 °C to 9 °C in UTCI, and the cooling effect of grass in comparison with artificial paved surfaces in open public places may be from 2 °C to 5 °C UTCI. In general terms, this study illustrates that the PALM modelling system provides a new perspective on the spatiotemporal differentiation of thermal exposure at the pedestrian level; it may therefore contribute to more climate-sensitive urban planning. Full article

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM. Full article

Olive and vine cultivations are two of the most important crops in Europe, yielding high quality and value food products. The climate change over the Balkans may elevate the agroecological pressure for the established crops and shift their cultivations areas. One of the widely-used agroclimatic indices is the growing degree days (GDD) which accumulates the necessary thermal units for the selected crops. Despite the advances on the agroclimatic research, there are few available methods for spatiotemporal estimation of this useful index. So, this research is focused on the construction of simple and reliable equations for the calculation and projection of olive and vine cultivations’ GDD over the Balkans. The models’ input parameters are the time, the altitude, the distance from the seashore, and the latitude. Its assembly is made by the extracted spatial data, combined with the Agri4Cast dataset for the period of 1980 to 2018 incorporating the regional climate change trend. The results indicate that the most influential parameter is the time, followed by the latitude, for both cultivations. According to the projections, as quantified by GDD, a vast sprawl of olive and vine cultivation areas will have been formed to the northern parts of the studied area. To be more precise, the viticulture could expand spatially by 28.8% (of the Balkans area) by 2040, and by 15.1% to 2060, when the olive cultivations’ area could sprawl 23.9% by 2040 and 20.3% by 2060. Full article

We compare the relationship between the Arctic Oscillation (AO) and ozone concentration in the lower stratosphere over the Arctic during 1980–1994 (P1) and 2007–2019 (P2) in January and February using reanalysis datasets. The out-of-phase relationship between the AO and ozone in the lower stratosphere is significant in January during P1 and February during P2, but it is insignificant in January during P2 and February during P1. The variable links between the AO and ozone in the lower stratosphere over the Arctic in January and February are not caused by changes in the spatial pattern of AO but are related to the anomalies in the planetary wave propagation between the troposphere and stratosphere. The upward propagation of the planetary wave in the stratosphere related to the positive phase of AO significantly weakens in January during P1 and in February during P2, which may be related to negative buoyancy frequency anomalies over the Arctic. When the AO is in the positive phase, the anomalies of planetary wave further contribute to the negative ozone anomalies via weakening the Brewer–Dobson circulation and decreasing the temperature in the lower stratosphere over the Arctic in January during P1 and in February during P2. Full article

In this paper, the effect of the lockdown measures on nitrogen dioxide (NO₂) in Europe is analysed by a statistical model approach based on a generalised additive model (GAM). The GAM is designed to find relationships between various meteorological parameters and temporal metrics (day of week, season, etc.) on the one hand and the level of pollutants on the other. The model is first trained on measurement data from almost 2000 monitoring stations during 2015–2019 and then applied to the same stations in 2020, providing predictions of expected concentrations in the absence of a lockdown. The difference between the modelled levels and the actual measurements from 2020 is used to calculate the impact of the lockdown measures adjusted for confounding effects, such as meteorology and temporal trends. The study is focused on April 2020, the month with the strongest reductions in NO₂, as well as on the gradual recovery until the end of July. Significant differences between the countries are identified, with the largest NO₂ reductions in Spain, France, Italy, Great Britain and Portugal and the smallest in eastern countries (Poland and Hungary). The model is found to perform best for urban and suburban sites. A comparison between the found relative changes in urban surface NO₂ data during the lockdown and the corresponding changes in tropospheric vertical NO₂ column density as observed by the TROPOMI instrument on Sentinel-5P revealed good agreement despite substantial differences in the observing method. Full article

We investigate the distribution of dimethyl sulfide (DMS) in the Southern Ocean’s (50° W to 170° W) surface water, including the Antarctic Peninsula and the marginal sea ice zone (MIZ) in the Ross and Amundsen Seas. This is the first high-frequency observation conducted in the austral autumn (in April) in the Southern Ocean. The mean DMS concentration was 2.7 ± 2.5 nM (1 σ) for the entire study area. Noticeably enhanced DMS (5 to 28 nM) concentrations were observed in the MIZ around the Ross and Amundsen Seas and the coastal regions in the Antarctic Peninsula; this could be attributed to biological production of local ice algae, which appears to be supplied with nutrients from glacial or sea ice melt water. These observed DMS inventories were significantly higher (an order of magnitude) than current climatological DMS inventories. The local DMS sources being transported outward from the polynyas, where strong bloom occurs during summer, could result in larger discrepancies between observed DMS and climatological DMS in the MIZ area (in the Amundsen Sea). Overall, this study is the first to highlight the significance of the underestimation of current DMS fluxes in the austral autumn, which consequently results in significant errors in the climate models. Full article

Circadian rhythms are 24-h oscillations driven by a hypothalamic master oscillator that entrains peripheral clocks in almost all cells, tissues and organs. Circadian misalignment, triggered by industrialization and modern lifestyles, has been linked to several pathological conditions, with possible impairment of the quality or even the very existence of life. Living organisms are continuously exposed to air pollutants, and among them, ozone or particulate matters (PMs) are considered to be among the most toxic to human health. In particular, exposure to environmental stressors may result not only in pulmonary and cardiovascular diseases, but, as it has been demonstrated in the last two decades, the skin can also be affected by pollution. In this context, we hypothesize that chronodistruption can exacerbate cell vulnerability to exogenous damaging agents, and we suggest a possible common mechanism of action in deregulation of the homeostasis of the pulmonary, cardiovascular and cutaneous tissues and in its involvement in the development of pathological conditions. Full article

This paper analyzes the PM₁₀ concentrations and influences of atmospheric condition (AC) and land coverage (LC) on a high-pollution megacity (Bogota, Colombia) from a public health viewpoint. Information of monitoring stations equipped with measuring devices for PM₁₀/temperature/solar-radiation/wind-speed were used. The research period lasted eight years (2007–2014). AC and LC were determined after comparing daily PM₁₀ concentrations (DPM₁₀) to reference limits published by the World Health Organization (WHO). ARIMA models for DPM₁₀ were also developed. The results indicated that urban sectors with lower atmospheric instability (AI) had a 2.85% increase in daily mortality (DM) in relation to sectors with greater AI. In these sectors of lower AI, impervious LC predominated, instead of vegetated LC. An ARIMA analysis revealed that a greater extent of impervious LC around a station led to a greater effect on previous days’ DPM₁₀ concentrations. Extreme PM₁₀ episodes persisted for up to two days. Extreme pollution episodes were probably also preceded by low mixing-layer heights (between 722–1085 m). The findings showed a 13.0% increase in WHO standard excesses (PE) for each 10 µg/m³ increase in DPM₁₀, and a 0.313% increase in DM for each 10% increase in PE. The observed average reduction of 14.8% in DPM₁₀ (−0.79% in DM) was probably due to 40% restriction of the traffic at peak hours. Full article

The early stages of a tropical cyclone can be a challenge to forecast, as a storm consolidates and begins to grow based on the local and environmental conditions. A high-resolution ensemble of the Hurricane Analysis and Forecast System (HAFS) is used to study the early intensification of Hurricane Dorian, a catastrophic 2019 storm in which the early period proved challenging for forecasters. There was a clear connection in the ensemble between early storm track and intensity: stronger members moved more northeast initially, although this result did not have much impact on the long-term track. The ensemble results show several key factors determining the early evolution of Dorian. Large-scale divergence northeast of the tropical cyclone (TC) appeared to favor intensification, and this structure was present at model initialization. There was also greater moisture northeast of the TC for stronger members at initialization, favoring more intensification and downshear development of the circulation as these members evolved. This study highlights the complex interplay between synoptic and storm scale processes in the development and intensification of early-stage tropical cyclones. Full article

The increase of global commerce and tourism makes the shipping sector an important contributor of atmospheric particles and gaseous pollutants. These have impacts on both health and climate, especially in populated coastal areas. Maritime activities could be an important driver for economic and social development, however, they are also an environmental pressure. Several policies were implemented in the last decades, at local/regional or international levels, mainly focused on reducing the content of sulphur in marine fuels. The last international IMO-2020 regulation was enforced on 1 January 2020. This work reviews some recent studies on this topic delineating current knowledge of the impacts of maritime emissions on air quality and health and the future projections relative to the benefits of the implementation of the new IMO-2020 regulation. In addition, future perspectives for further mitigation strategies are discussed. Full article

Global assessments of air quality and health require comprehensive estimates of the exposures to air pollution that are experienced by populations in every country. However, there are many countries in which measurements from ground-based monitoring are sparse or non-existent, with quality-control and representativeness providing additional challenges. While ground-based monitoring provides a far from complete picture of global air quality, there are other sources of information that provide comprehensive coverage across the globe. The World Health Organization developed the Data Integration Model for Air Quality (DIMAQ) to combine information from ground measurements with that from other sources, such as atmospheric chemical transport models and estimates from remote sensing satellites in order to produce the information that is required for health burden assessment and the calculation of air pollution-related Sustainable Development Goals indicators. Here, we show an example of the use of DIMAQ with the Copernicus Atmosphere Monitoring Service Re-Analysis (CAMSRA) of atmospheric composition, which represents the best practices in meteorology and climate monitoring that were developed under the World Meteorological Organization’s Global Atmosphere Watch programme. Estimates of PM_2.5 from CAMSRA are integrated within the DIMAQ framework in order to produce high-resolution estimates of air pollution exposure that can be aggregated in a coherent fashion to produce country-level assessments of exposures. Full article

Ambient exposure to particulate matter (PM) air pollution is known to have an adverse effect on public health worldwide. Rapid increase rates of economic and urbanization, industrial development, and environmental change in China have exacerbated the occurrence of air pollution. This study examines the temporal and spatial distribution of PM on national, regional and local scales in China during 2014–2016. The relationships between the PM_2.5 concentration rising rate (PMRR) and meteorological parameters (wind speed and wind direction) are discussed. The dataset of Air Quality Index (AQI), PM₁₀ (PM diameter < 10 $\mathsf{\mu }\mathrm{m}$ ) and PM_2.5 (PM diameter < 2.5 $\mathsf{\mu }\mathrm{m}$) were collected in 169, 369, and 367 cities in 2014, 2015, and 2016 over China, respectively. The results show that the air quality has been generally improved on the national scale, but deteriorated locally in areas such as the Feiwei Plain. The northwest China (NW) and Beijing-Tianjin-Hebei (BTH) regions are the worst areas of PM pollution, which are mainly manifested by the excessive PM₁₀ caused by blowing dust in spring in NW and the intensive emissions of PM_2.5 in winter in BTH. With the classified seven geographic regions, we demonstrate the significant spatial difference and seasonal variation of PM concentration and PM_2.5/PM₁₀ ratio, which indicate different emission sources. Furthermore, the dynamic analysis of the PM_2.5 pollution process in 11 large urban cities shows dramatic effects of wind speed and wind direction on the PM_2.5 loadings. Full article

Korea has occasionally suffered from various kinds of severe hazes such as long-range transported aerosol (LH), yellow sand (YS), and urban haze (UH). We classified haze days into LH, YS, and UH and analyzed the characteristics of its associated meteorological conditions for 2011–2016 using reanalysis data and surface observations. The results show that higher boundary layer height and stronger wind speed were found for the LH and YS hazes relative to those for UH. Intensive analysis on a golden episode of 10–18 January 2013 indicates that the cloud fraction increased along with extended light precipitation at a weaker rate by enhanced aerosol loading for an unprecedented LH event, which in turn brought about a decrease in boundary layer height (BLH) with less irradiance, that is, much stronger stability. Later, the intensified stability after the LH event accumulated and increased domestic aerosols, and eventually resulted in the longer-lasting severe haze. This study suggests that aerosol–meteorology interactions play an important role in both short-term weather and fine particle forecasts, especially on polluted days. Full article

Black carbon (BC) is one of the most harmful substances within traffic emissions, contributing considerably to urban pollution. Nevertheless, it is not explicitly regulated and the official laboratory derived emission factors are barely consistent with real world emissions. However, realistic emission factors (EFs) are crucial for emission, exposure, and climate modelling. A unique dataset of 10 years (2009–2018) of roadside and background measurements of equivalent black carbon (eBC) concentration made it possible to estimate real world traffic EFs and observe their change over time. The pollutant dispersion was modelled using the Operational Street Pollution Model (OSPM). The EFs for eBC are derived for this specific measurement site in a narrow but densely trafficked street canyon in Leipzig, Germany. The local conditions and fleet composition can be considered as typical for an inner-city traffic scenario in a Western European city. The fleet is composed of 22% diesel and 77% petrol cars in the passenger car segment, with an unknown proportion of direct injection engines. For the mixed fleet the eBC EF was found to be 48 mg km${}^{-1}$ in the long-term average. Accelerated by the introduction of a low emission zone, the EFs decreased over the available time period from around 70 mg km${}^{-1}$ to 30–40 mg km${}^{-1}$. Segregation into light (<3.5 t) and heavy (>3.5 t) vehicles resulted in slightly lower estimates for the light vehicles than for the mixed fleet, and one order of magnitude higher values for the heavy vehicles. The found values are considerably higher than comparable emission standards for particulate matter and even the calculations of the Handbook Emission Factors for Road Transport (HBEFA), which is often used as emission model input. Full article

Environmental microbial contamination in the operating room (OR) can favour contamination of the surgical wound, posing the risk of infection of the surgical site. Thus, environmental monitoring is a useful tool for assessing environmental health and the effectiveness and efficiency of the measures adopted to control the risk of infection in the OR. This work aimed to analyse the long term environmental quality of 18 ORs throughout Sardinia, Italy, through the quantitative and qualitative characterisation of the microbial flora present in the air and on surfaces, in order to evaluate the trend over time, including in relation to any control measures adopted. The results of the sampling carried out in the period from January 2010 to December 2019 have been extrapolated from the archive-database of the Laboratory of the Hygiene and Control of Hospital Infections Unit of the University Hospital in Sassari. During the period in question, 188 air evaluations were carried out, both in empty rooms and during surgery, and 872 surface samples were taken. When the air was monitored, it emerged that significant contamination was detectable in a reduced number of examinations and a limited number of rooms. Microbial load values higher than the reference values may have been mainly determined by sub-optimal operation/maintenance of the air conditioning system. Surface testing showed a good level of sanitisation, given the low percentage of non-compliant values detected. The possibility of having data available on environmental quality is a useful educational and training tool both for those responsible for sanitisation procedures and the surgical team, in order to increase awareness of the effects of a lack of compliance with behavioural standards. Full article

Daily solar radiation is a critical input for estimating plant growth and development, yet this variable is infrequently measured compared to other climate variables. This study evaluates the sensitivity of simulated maize and soybean production from the CERES-Maize and CROPGRO-Soybean modules of the Decision Support System for Agrotechnology Transfer (DSSAT) to daily solar radiation estimates obtained from traditional (stochastic, empirical, and mechanistic models) and non-traditional (satellite estimation, reanalysis datasets, and regional climate model simulations) approaches, using as an example radiation estimates for Hancock, Wisconsin, USA. When compared to observations, radiation estimates obtained from empirical and mechanistic models and a satellite-based dataset generally had smaller biases than other approaches. Daily solar radiation estimates from a reanalysis dataset and regional climate model simulations overestimate incoming daily solar radiation. When the radiation estimates were used as an input to CERES-Maize, no significant differences were found for maize yield obtained from the different radiation estimates compared to yield from observed radiation, even though differences were found in the daily values of leaf area index, crop evapotranspiration, and crop dry weight (biomass). In contrast, significant differences were found in simulated soybean yield from CROPGRO-Soybean for the majority of the radiation estimates. Full article

Computational modeling allows studying the air quality problems in depth and provides the best solution reducing the population risks. This research demonstrates the Graz Lagrangian model effectiveness for assessing emission sources contributions to the air pollution: particles tracking and accumulation estimate. The article describes model setting up parameters and datasets preparation for the analysis. The experiment simulated the dispersion from the main groups of emission sources for real weather conditions during 96 h of December 2018, when significant excess of NO₂, CO, SO₂, PM10, and benzo(a)pyrene concentrations were observed in the Krasnoyarsk surface atmospheric layer. The computational domain was a parallelepiped of 40 × 30 × 2.5 km, which was located deep inside the Eurasian continent on a heterogeneous landscape exaggerated by high-rise buildings, with various pollutions sources and the ice-free Yenisei River. The results demonstrated an excellent applicability of the Lagrange model for hourly tracking of particle trajectories, taking into account the urban landscape. For values <1 MPC (maximum permissible concentration) of peak pollutants concentrations, the coincidences were 93 cases, and for values < 0.1 shares of MPC, there were 36 cases out of the total number of 97. The same was found for the average daily concentration for values <1 MPC—31, and for values <0.1 MPC—5 matches out of 44. Wind speeds COR—65.3%, wind directions COR—68.6%. The Graz Lagrangian model showed the ability to simulate air quality problems in the Krasnoyarsk greater area conditions. Full article

Climate warming is causing permafrost thaw and there is an urgent need to understand the spatial distribution of permafrost and its potential changes with climate. This study developed a long-term (1901–2100), 1-km resolution daily meteorological dataset (Met1km) for modeling and mapping permafrost at high spatial resolutions in Canada. Met1km includes eight climate variables (daily minimum, maximum, and mean air temperatures, precipitation, vapor pressure, wind speed, solar radiation, and downward longwave radiation) and is suitable to drive process-based permafrost and other land-surface models. Met1km was developed based on four coarser gridded meteorological datasets for the historical period. Future values were developed using the output of a new Canadian regional climate model under medium-low and high emission scenarios. These datasets were downscaled to 1-km resolution using the re-baselining method based on the WorldClim2 dataset as spatial templates. We assessed Met1km by comparing it to climate station observations across Canada and a gridded monthly anomaly time-series dataset. The accuracy of Met1km is similar to or better than the four coarser gridded datasets. The errors in long-term averages and average seasonal patterns are small. The error occurs mainly in day-to-day fluctuations, thus the error decreases significantly when averaged over 5 to 10 days. Met1km, as a data generating system, is relatively small in data volume, flexible to use, and easy to update when new or improved source datasets are available. The method can also be used to generate similar datasets for other regions, even for the entire global landmass. Full article

We study the long-term consequences of air pollution on mental health, using a natural experiment in Indonesia. We find that exposure to severe air pollution has significant and persistent consequences on mental health. An extra standard deviation in the pollution index raises the probability of clinical depression measured 10 years past exposure by almost 1%. Women in particular seem to be more affected, but some effects persist for men as well. Pollution exposure increases the likelihood of clinical depression for women and also the severity of depressive symptoms for both sexes. It is not clear if men are more resistant to pollution or they simply recover faster from it. Education, perceived economic status, and marriage seem to be the best mitigators for these negative effects. Full article

Urban atmospheric environmental issues are commonly associated with the physical processes of urban surfaces. Much progress has been made on the building-resolving microscale atmospheric models, but a realistic representation of the physical processes of urban surfaces on those models is still lacking. This study presents a new microscale urban surface energy (MUSE) model for real urban meteorological and environmental applications that is capable of representing the urban radiative, convective, and conductive energy transfer processes along with their interactions, and that is directly compatible with the Cartesian grid microscale atmospheric models. The physical processes of shadow casting and radiative transfers were validated on an analytical accuracy level. The full capability of the model in simulating the three-dimensional surface heterogeneities in a real urban environment was tested for a hot summer day in August 2016 using the field measurements obtained from the Kongju National University campus, South Korea. The validation against the measurements showed that the model is capable of predicting surface temperatures and energy balance fluxes in a patch scale at the heterogeneous urban surfaces by virtue of the interactive representation of the urban physical processes. The excellent performance and flexible grid design emphasize the potential capabilities of the MUSE model for use in urban meteorological and environmental applications through the building-resolving microscale atmospheric models, such as computational fluid dynamics (CFD) and large-eddy simulations (LES). Full article

High Latitude Dust (HLD) deposition in the surface snow layer in two distant locations in Svalbard (Hornsund and Pyramiden) were collected during the June/July 2019 field campaign and examined in the laboratory. Despite the differences in their climate and topography, both locations are characterised by very similar spatial patterns of the deposition. On the one hand, strong linear negative relationship between the altitude of the sample taken and its concentration was found in low altitude (below 300 m a.s.l.), suggesting a strong influence of local HLD sources. On the other hand, almost constant concentrations were found at higher elevated sampling sites (above 300 m a.s.l.). This suggests a predominantly long-range transport in high altitude areas. The importance of local sources in the lower altitude corresponds well with the generally higher concentrations of HLD in the Pyramiden area. This region has a drier, continental climate and more deglaciated bare land surfaces, which favour more sediment to be uplifted in comparison with the more maritime climate of Hornsund area in the southern part of Svalbard. The spatial division between the local and long-range transport is supported by the proportion of certain lithophile elements in the altitude gradient. Full article

This study proposes a climate service named Smart Climate Hydropower Tool (SCHT) and designed as a hybrid forecast system for supporting decision-making in a context of hydropower production. SCHT is technically designed to make use of information from state-of-art seasonal forecasts provided by the Copernicus Climate Data Store (CDS) combined with a range of different machine learning algorithms to perform the seasonal forecast of the accumulated inflow discharges to the reservoir of hydropower plants. The machine learning algorithms considered include support vector regression, Gaussian processes, long short-term memory, non-linear autoregressive neural networks with exogenous inputs, and a deep-learning neural networks model. Each machine learning model is trained over past decades datasets of recorded data, and forecast performances are validated and evaluated using separate test sets with reference to the historical average of discharge values and simpler multiparametric regressions. Final results are presented to the users through a user-friendly web interface developed from a tied connection with end-users in an effective co-design process. Methods are tested for forecasting the accumulated seasonal river discharges up to six months in advance for two catchments in Colombia, South America. Results indicate that the machine learning algorithms that make use of a complex and/or recurrent architecture can better simulate the temporal dynamic behaviour of the accumulated river discharge inflow to both case study reservoirs, thus rendering SCHT a useful tool in providing information for water resource managers in better planning the allocation of water resources for different users and for hydropower plant managers when negotiating power purchase contracts in competitive energy markets. Full article

Since maize, peanut, and cotton are economically valuable crops in the southeast United States, their yield amount changes in a future climate are attention-grabbing statistics demanded by associated stakeholders and policymakers. The Crop System Modeling—Decision Support System for Agrotechnology Transfer (CSM-DSSAT) models of maize, peanut, and cotton are, respectively, driven by the North American Regional Climate Change Assessment Program (NARCCAP) Phase II regional climate models to estimate current (1971–2000) and future (2041–2070) crop yield amounts. In particular, the future weather/climate data are based on the Special Report on Emission Scenarios (SRES) A2 emissions scenario. The NARCCAP realizations show on average that there will be large temperature increases (~2.7 °C) and minor rainfall decreases (~−0.10 mm/day) with pattern shifts in the southeast United States. With these future climate projections, the overall future crop yield amounts appear to be reduced under rainfed conditions. A better estimate of future crop yield amounts might be achievable by utilizing the so-called weighted ensemble method. It is proposed that the reduced crop yield amounts in the future could be mitigated by altering the currently adopted local planting dates without any irrigation support. Full article

Ground-based lidars and ceilometers are widely used for dust and volcanic ash observation around the world. This is particularly interesting in Iceland where high-altitude dust events occur frequently during strong wind conditions and volcanic eruptions. To explore the possible application of such technologies in Iceland for monitoring dust events, we used a combination of Doppler wind lidars with depolarization channels, ceilometers, and other instruments, to monitor two dust events that occurred in Iceland during summer 2019. We applied a verified ceilometer data processing procedure with customized local corrections and developed a new procedure to process Doppler lidar data for aerosols measurements. Both lidar and ceilometer observations can be used to detect the dust layer and reveal the temporal and vertical distribution of dust aerosols in Iceland. The depolarization ratio measurements indicate that the weather conditions, e.g., relative humidity, could have a significant impact on lidar measurements. We conclude that using Doppler wind lidar and ceilometer measurements to monitor volcanic and sedimentary aerosols is possible and may be used to provide important information to the scientific community. Full article

Abstract: Exposure to outdoor air pollution has been shown to increase asthma symptoms. We assessed the potential role of particulate matter with aerodynamic diameter <2.5 μm (PM_2.5) on respiratory condition in schoolchildren in the south Mediterranean area. A total of 2400 children aged 11–14 years were recruited, and data on their symptoms were collected through an ISAAC (International Study of Asthma and Allergies in Childhood)-based questionnaire. Outdoor PM_2.5 was collected for 48 consecutive hours in the schoolyards of their schools and selected residential outdoor areas. The levels of PM_2.5 were measured, along with its elemental composition. The incidence of an acute respiratory illness within the first 2 years of life was higher amongst Sicilian children when compared to Maltese children (29.7% vs. 13.5% respectively, p < 0.0001). Malta had a significantly higher prevalence of doctor‐diagnosed asthma, when compared to Sicily (18.0% Malta vs. 7.5% Sicily, p <0.0001). Similarly, current asthma (7.8% vs. 2.9%, p < 0.0001) and use of asthma medication in the last 12 months (12.1% vs. 4.9%, p < 0.0001) were more frequent amongst Maltese children. Total median PM_2.5 was 12.9 μg/m³ in Sicily and 17.9 μg/m³ in Malta. PM_2.5 levels were highest in the Maltese urban town of Hamrun (23.6 μg/m³), while lowest in the rural Sicilian town of Niscemi (10.9 μg/m³, p < 0.0001). Hamrun also exhibited the highest levels of nickel, vanadium, lead, zinc, antimony, and manganese, whilst the Sicilian city of Gela had the highest levels of cadmium, and the highest level of PM_2.5 when compared to rural Sicily. Elevated levels of PM_2.5 were positively associated with the prevalence of doctor diagnosed asthma (odds ratio (OR) 1.05), current asthma (OR 1.06), and use of asthma medication (OR 1.06). All elements in PM_2.5 showed increased OR for doctor diagnosed asthma, while higher concentrations of Cd and Mn were associated with higher prevalence of rhinitis. Full article

The aim of this contribution is both to demonstrate and to explore the general assessment pertaining to the effects of atmospheric factors on human health and general wellbeing. While humans are aware of such effects, particularly individually, their concrete and synergetic effects with the human physiological system are, comparatively, not well comprehended. In human biometeorological studies and approaches, the aforementioned effects are analyzed in terms of their effect pathways, and the development of single or complex approaches. Recurrently in the existing literature, such approaches are mostly defined and, respectively, targeted as indexes. The evaluation and assessment of similar factors and parameters that present related effects were subsequently put together and quantified. This approach is described as ‘effective complexes’ or components. The most well-known examples are the thermal complex, air pollution complex (which can be divided into the biological (pollen) and anthropogenic (air pollutants) factors), actinic complex, and finally, the recent or rapid weather changes complex. Most of the approaches focus on the negative effects consequential to the established criteria ranging from empirical outputs, to epidemiological studies. As a result, the presented approach does not only include the negative effects or implications on humans. Instead, it also highlights the neutral and positive effects which were acknowledged by the research. The approach deals furthermore with the combined effects of different complexes or components and incorporates different weightings of the factors based on the disclosed effects. In addition, seasonal and exposure factors are deliberated upon to differentiate annual variability factors. Finally, the presented approach builds upon a way in which to cogitate how the complex interactions associated to weather and climate can be quantified in a more appropriate way in the context of human health. The approach aims to be applied for a specific weather forecast enabling the communication and balance between human health factors, and also more encompassing climatic analysis. Full article

This research was to conduct a pilot study for two consecutive days in order to assess fine particulate matter (PM_2.5) exposure of an entire population in a community. We aimed to construct a surveillance system by analyzing the observed spatio-temporal variation of exposure. Guro-gu in Seoul, South Korea, was divided into 2,204 scale grids of 100 m each. Hourly exposure concentrations of PM_2.5 were modeled by the inverse distance weighted method, using 24 sensor-based air monitoring instruments and the indoor-to-outdoor concentration ratio. Population distribution was assessed using mobile phone network data and indoor residential rates, according to sex and age over time. Exposure concentration, population distribution, and population exposure were visualized to present spatio-temporal variation. The PM_2.5 exposure of the entire population of Guro-gu was calculated by population-weighted average exposure concentration. The average concentration of outdoor PM_2.5 was 42.1 µg/m³, which was lower than the value of the beta attenuation monitor measured by fixed monitoring station. Indoor concentration was estimated using an indoor-to-outdoor PM_2.5 concentration ratio of 0.747. The population-weighted average exposure concentration of PM_2.5 was 32.4 µg/m³. Thirty-one percent of the population exceeded the Korean Atmospheric Environmental Standard for PM_2.5 over a 24 h average period. The results of this study can be used in a long-term aggregate and cumulative PM_2.5 exposure assessment, and as a basis for policy decisions on public health management among policymakers and stakeholders. Full article

The effects of meteorological changes on particulate matter with a diameter of 10 microns or less (PM₁₀, referred to as PM in this study) and aerosol optical depth (AOD) in Seoul were investigated using observational and modeling analysis. AOD satellite data were used, obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and PM concentration data were used from in-situ observations. The Modern-Era Retrospective Analysis for Research and Applications (MERRA) and MERRA Version 2 (MERRA-2) were used for meteorological field analysis in modeling and observation data. The results from this investigation show that meteorological effects on PM and AOD were strong in the month of June, revealing a clear decreasing trend in recent decades. The investigation focused on the underlying mechanisms influencing the reduction in PM resulting from meteorological changes during the months of June. The results of this study reveal that decreases in atmospheric stability and humidity induced the aerosol change observed in recent decades. The changes in atmospheric stability and humidity are highly correlated with changes in the intensity of the East Asian summer monsoon (EASM). This suggests that the unstable and drying atmosphere by weakening of the EASM in recent decades has improved PM air quality in Seoul during the summer. The effects of atmospheric stability and humidity were also observed to vary depending on the aerosol species. Humidity only affects hydrophilic aerosols such as sulfate, nitrate, and ammonium, whereas atmospheric stability affects all species of aerosols, including carbonaceous aerosols. Full article

This study investigates the effects of atmosphere-ocean coupling for medium-range forecasts by using coupled numerical weather prediction (NWP) experiments based on the unified model (UM) on a case study of the 2016 heatwave over the Korean Peninsula. Atmospheric nudging experiments were carried out to determine the key regions which may have large impacts on the forecasts of the heat wave. The results of the nudging experiments suggest that key forcing from the Mongolia region gives the largest impact to this case by causing a transport of warm air from the northwest part of Korea. Moreover, the Pacific region shows an important role in the global circulation in nudging experiments. Results from the atmosphere-ocean coupled model show no clear benefit for the extreme heat wave temperatures in this case. In addition, more model development seems to be needed to improve the representation of sea surface temperature (SST) in some key areas. Nevertheless, it is confirmed that the atmosphere-ocean coupled simulation produces a better representation of aspects of the large-scale flow such as the blocking high over the Kamchatka Peninsula, the high pressure system in the northwest Pacific and Hadley circulation. The results presented in this study show that atmosphere-ocean coupling can be an important way to improve the deterministic model forecasts as the lead time increases beyond a few days. Full article

A hot blob for near-surface water was identified eastward of New Zealand in the South Pacific in December 2019, which was the second strongest event on record in this region. Its sea surface temperature anomalies reached up to 5 °C, and the anomalous warming penetrated around 40 m deep vertically. From the atmospheric perspective, the anomalous high-pressure system from the surface up to 300 hPa lasted for about 50 days, accompanied by the blocking pattern at 500 hPa and a deep warming air column extending downward to the surface. A mixed-layer heat budget analysis revealed that the surface heat flux term was the primary factor contributing to the development of this hot blob, with more shortwave radiation due to the persistent high-pressure system and lack of clouds as well as higher temperature of the troposphere aloft denoted by sensible heat. The oceanic contribution including the horizontal advection and vertical entrainment was changeable and accounted for less than 50%. Moreover, we used the strongest hot blob event which peaked in December 2001 as another example to evaluate the robustness of results derived from the 2019 case. The results show similar circulation features and driving factors, which indicate the robustness of the above characteristics. Full article

International Ocean Discovery Program (IODP) Expedition 356 Site U1461 represents one of the few records from the North West Australian shelf that provides information about aridity fluctuations in Australia during the Quaternary. A combination of chronostratigraphic indicators revealed the (partial) preservation of two major glaciations (Marine Isotope Stage (MIS) 2 and MIS 12) in the sedimentary record. The faunal content (mainly benthic foraminifera, corals and bryozoans) was analyzed to estimate paleo-environments and paleo-depths in order to determine if these sediments have been remobilized by reworking processes. Despite the occurrence of a depositional hiatus (including MIS 5d to MIS 9-time interval), the excellent preservation of faunal content suggests that the preserved sediment is in situ. The geochemical composition of the sediments (Nd and major elements) indicates that during MIS 12 riverine input was likely reduced because of enhanced aridity, and the sediment provenance (mainly atmospheric dust) is likely in the central (Lake Eyre) or eastern (Murray Darling Basin) parts of the Australian continent. MIS 2 is confirmed to be one of the driest periods recorded in Australia but with mixed dust sources from the eastern and western parts of the continent. More humid conditions followed the glacial maximum, which might correspond to the peak of the Indian-Australian Summer Monsoon. Full article

Net radiation is an important component of the earth’s surface energy balance, which plays a vital role in the evolution of regional climate or climate change. The estimation of this component at regional or global scales is critical and challenging due to the sparse and limited ground-based observations. This paper made an attempt to analyze the feasibility of a remote sensing-based surface energy balance model using satellite (TERRA/MODIS) data to derive the net radiation (R_n). In the present study, MODIS data at 15 different days of the year (DOY) were utilized to visualize the spatial pattern of net radiation flux over three versatile and heterogeneous ecohydrological land surfaces (upstream, midstream, and downstream) of northwest China (Heihe river basin). The results revealed that the estimated net radiation from the satellite data agrees well with the ground-based measurements over three different surfaces, with a mean relative error of 9.33% over the upstream superstation (grasslands), 13.95% over the middle stream superstation (croplands), and 11.63% over the downstream superstation (mixed forests), where the overall relative error was 11.64% with an overall rmse of 29.36 W/m² in the study area. The regional distribution of net radiation over the versatile land surfaces was validated well at a large scale during the five-month period and over different land surfaces. It was also observed that the spatial pattern of net radiation varies spatially over three different landscape regions during four different days of the year, which might be associated with different climatic conditions and landscape features in these regions. The overall findings of this study concluded that satellite-derived net radiation can rationally be obtained using a single-source remote sensing model over different land surfaces. Full article

The article analyzes the chemical composition (ions, elements, and polycyclic aromatic hydrocarbons) of the atmospheric aerosol in the near-water layer of the atmosphere above Lake Baikal during wildfires in Siberia. Aerosol deposition affects the aquatic environment of the watershed basin and the lake itself. The current law on Lake Baikal limits the activity of the permanent stationary anthropogenic sources of the aerosol in the central ecological zone, and they do not have a significant negative impact. Wildfires can have a much greater impact on the environment. Smoke emissions entering the area of Lake Baikal due to wildfires change the chemical properties of the atmospheric aerosol and increase its mass and number concentration. The concentrations of NH₄⁺, K⁺, NO₃⁻, and SO₄²⁻, which enter with submicron aerosol fraction, increase in the ionic composition of the aerosol. The composition of polyaromatic compounds changes, and their concentrations increase. Elevated concentrations of B, Mn, Zn, As, Sr, Cd, and Pb in the composition of aerosol indicate the influx of air masses from the areas prone to wildfires. Despite the sporadic effects of these natural factors, they affect the pollution of various Baikal ecosystems, especially small tributaries of the lake, whose main supply is atmospheric. Full article

This study focuses on the long-term aerosol and precipitation chemistry measurements from colocated monitoring sites in Southern Florida between 2013 and 2018. A positive matrix factorization (PMF) model identified six potential emission sources impacting the study area. The PMF model solution yielded the following source concentration profiles: (i) combustion; (ii) fresh sea salt; (iii) aged sea salt; (iv) secondary sulfate; (v) shipping emissions; and (vi) dust. Based on these results, concentration-weighted trajectory maps were developed to identify sources contributing to the PMF factors. Monthly mean precipitation pH values ranged from 4.98 to 5.58, being positively related to crustal species and negatively related to SO₄²⁻. Sea salt dominated wet deposition volume-weighted concentrations year-round without much variability in its mass fraction in contrast to stronger seasonal changes in PM_2.5 composition where fresh sea salt was far less influential. The highest mean annual deposition fluxes were attributed to Cl⁻, NO₃⁻, SO₄²⁻, and Na⁺ between April and October. Nitrate is strongly correlated with dust constituents (unlike sea salt) in precipitation samples, indicative of efficient partitioning to dust. Interrelationships between precipitation chemistry and aerosol species based on long-term surface data provide insight into aerosol–cloud–precipitation interactions. Full article

Climate Data Science (CDS) Toolbox Species Distribution Model (SDM) aims identifying the suitable areas for species, community of species and landscape units. This model is based on the use of 23 variables available over the Internet, for which any assumptions are formulated about their relationships with the spatial distribution of species. The application of CDS Toolbox SDM on the assessment of the potential impact of two scenarios of climate change (Representative Concentration Pathways RCP4.5 and RCP6.0) on the suitability of grapevine crops in France shows a general decrease of the most suitable areas for grapevine crops between 41% and 83% towards 2070 according to the current location of the vineyard parcels. The results underline a potential shift of the suitable areas in northern part of the French territory. They also show a potential shift of the most suitable areas in altitude (60 m in average) for RCP6.0 scenario. Finally, the model shows that RCP4.5 scenario should be more drastic than RCP6.0 scenario by 2050 and 2070. In effect, the model underlines a significant potential decrease of cultivated crops in the areas of high probably of suitable areas, according to the baseline scenario. This decrease would be of 630,000 ha for 2070 RCP4.5 scenario and 330,000 ha for 2070 RCP6.0 scenario. Full article

In order to fight against the spread of COVID-19, the most hard-hit countries in the spring of 2020 implemented different lockdown strategies. To assess the impact of the COVID-19 pandemic lockdown on air quality worldwide, Air Quality Index (AQI) data was used to estimate the change in air quality in 20 major cities on six continents. Our results show significant declines of AQI in NO₂, SO₂, CO, PM_2.5 and PM₁₀ in most cities, mainly due to the reduction of transportation, industry and commercial activities during lockdown. This work shows the reduction of primary pollutants, especially NO₂, is mainly due to lockdown policies. However, preexisting local environmental policy regulations also contributed to declining NO₂, SO₂ and PM_2.5 emissions, especially in Asian countries. In addition, higher rainfall during the lockdown period could cause decline of PM_2.5, especially in Johannesburg. By contrast, the changes of AQI in ground-level O₃ were not significant in most of cities, as meteorological variability and ratio of VOC/NO_x are key factors in ground-level O₃ formation. Full article

The lockdown measures implemented worldwide to slow the spread of the COVID–19 pandemic have allowed for a unique real-world experiment, regarding the impacts of drastic emission cutbacks on urban air quality. In this study we assess the effects of a 7-week (23 March–10 May 2020) lockdown in the Greater Area of Athens, coupling in situ observations with estimations from a meteorology-atmospheric chemistry model. Measurements in central Athens during the lockdown were compared with levels during the pre- and post-lockdown 3-week periods and with respective levels in the four previous years. We examined regulatory pollutants as well as CO₂, black carbon (BC) and source-specific BC components. Models were run for pre-lockdown and lockdown periods, under baseline and reduced-emissions scenarios. The in-situ results indicate mean concentration reductions of 30–35% for traffic-related pollutants in Athens (NO₂, CO, BC from fossil fuel combustion), compared to the pre-lockdown period. A large reduction (53%) was observed also for the urban CO₂ enhancement while the reduction for PM_2.5 was subtler (18%). Significant reductions were also observed when comparing the 2020 lockdown period with past years. However, levels rebounded immediately following the lift of the general lockdown. The decrease in measured NO₂ concentrations was reproduced by the implementation of the city scale model, under a realistic reduced-emissions scenario for the lockdown period, anchored at a 46% decline of road transport activity. The model permitted the assessment of air quality improvements on a spatial scale, indicating that NO₂ mean concentration reductions in areas of the Athens basin reached up to 50%. The findings suggest a potential for local traffic management strategies to reduce ambient exposure and to minimize exceedances of air quality standards for primary pollutants. Full article

The results from studies of aerosol in the Arctic atmosphere are presented: the aerosol optical depth (AOD), the concentrations of aerosol and black carbon, as well as the chemical composition of the aerosol. The average aerosol characteristics, measured during nine expeditions (2007–2018) in the Eurasian sector of the Arctic Ocean, had been 0.068 for AOD (0.5 µm); 2.95 cm⁻³ for particle number concentrations; 32.1 ng/m³ for black carbon mass concentrations. Approximately two–fold decrease of the average characteristics in the eastern direction (from the Barents Sea to Chukchi Sea) is revealed in aerosol spatial distribution. The average aerosol characteristics over the Barents Sea decrease in the northern direction: black carbon concentrations by a factor of 1.5; particle concentrations by a factor of 3.7. These features of the spatial distribution are caused mainly by changes in the content of fine aerosol, namely: by outflows of smokes from forest fires and anthropogenic aerosol. We considered separately the measurements of aerosol characteristics during two expeditions in 2019: in the north of the Barents Sea (April) and along the Northern Sea Route (July–September). In the second expedition the average aerosol characteristics turned out to be larger than multiyear values: AOD reached 0.36, particle concentration up to 8.6 cm⁻³, and black carbon concentration up to 179 ng/m³. The increased aerosol content was affected by frequent outflows of smoke from forest fires. The main (99%) contribution to the elemental composition of aerosol in the study regions was due to Ca, K, Fe, Zn, Br, Ni, Cu, Mn, and Sr. The spatial distribution of the chemical composition of aerosols was analogous to that of microphysical characteristics. The lowest concentrations of organic and elemental carbon (OC, EC) and of most elements are observed in April in the north of the Barents Sea, and the maximal concentrations in Far East seas and in the south of the Barents Sea. The average contents of carbon in aerosol over seas of the Asian sector of the Arctic Ocean are OC = 629 ng/m³, EC = 47 ng/m³. Full article

Solar radiation received at the Earth’s surface provides the energy driving all micro-meteorological phenomena. Local solar radiation measurements are used to estimate energy mediated processes such as evapotranspiration (ET); this information is important in managing natural resources. However, the technical requirements to reliably measure solar radiation limits more extensive adoption of data-driven management. High-quality radiation sensors are expensive, delicate, and require skill to maintain. In contrast, low-cost sensors are widely available, but may lack long-term reliability and intra-sensor repeatability. As weather stations measure solar radiation and other parameters simultaneously, machine learning can be used to integrate various types of environmental data, identify periods of erroneous measurements, and estimate corrected values. We demonstrate two case studies in which we use neural networks (NN) to augment direct radiation measurements with data from co-located sensors, and generate radiation estimates with comparable accuracy to the data typically available from agro-meteorology networks. NN models that incorporated radiometer data reproduced measured radiation with an R² of 0.9–0.98, and RMSE less than 100 Wm⁻², while models using only weather parameters obtained R² less than 0.75 and RMSE greater than 140 Wm⁻². These cases show that a simple NN implementation can complement standard procedures for estimating solar radiation, create opportunities to measure radiation at low-cost, and foster adoption of data-driven management. Full article

A cloud image can provide significant information, such as precipitation and solar irradiation. Predicting short-time cloud motion from images is the primary means of making intra-hour irradiation forecasts for solar-energy production and is also important for precipitation forecasts. However, it is very challenging to predict cloud motion (especially nonlinear motion) accurately. Traditional methods of cloud-motion prediction are based on block matching and the linear extrapolation of cloud features; they largely ignore nonstationary processes, such as inversion and deformation, and the boundary conditions of the prediction region. In this paper, the prediction of cloud motion is regarded as a spatiotemporal sequence-forecasting problem, for which an end-to-end deep-learning model is established; both the input and output are spatiotemporal sequences. The model is based on gated recurrent unit (GRU)- recurrent convolutional network (RCN), a variant of the gated recurrent unit (GRU), which has convolutional structures to deal with spatiotemporal features. We further introduce surrounding context into the prediction task. We apply our proposed Multi-GRU-RCN model to FengYun-2G satellite infrared data and compare the results to those of the state-of-the-art method of cloud-motion prediction, the variational optical flow (VOF) method, and two well-known deep-learning models, namely, the convolutional long short-term memory (ConvLSTM) and GRU. The Multi-GRU-RCN model predicts intra-hour cloud motion better than the other methods, with the largest peak signal-to-noise ratio and structural similarity index. The results prove the applicability of the GRU-RCN method for solving the spatiotemporal data prediction problem and indicate the advantages of our model for further applications. Full article

The downward longwave radiation (L_d, 4–100 μm) is a major component of research for the surface radiation energy budget and balance. In this study, we applied five machine learning methods, namely artificial neural network (ANN), support vector regression (SVR), gradient boosting regression tree (GBRT), random forest (RF), and multivariate adaptive regression spline (MARS), to estimate L_d using ground measurements collected from 27 Baseline Surface Radiation Network (BSRN) stations. L_d measurements in situ were used to validate the accuracy of L_d estimation models on daily and monthly time scales. A comparison of the results demonstrated that the estimates on the basis of the GBRT method had the highest accuracy, with an overall root-mean-square error (RMSE) of 17.50 W m⁻² and an R value of 0.96 for the test dataset on a daily time scale. These values were 11.19 W m⁻² and 0.98, respectively, on a monthly time scale. The effects of land cover and elevation were further studied to comprehensively evaluate the performance of each machine learning method. All machine learning methods achieved better results over the grass land cover type but relatively worse results over the tundra. GBRT, RF, and MARS methods were found to show good performance at both the high- and low-altitude sites. Full article

Urban outdoor thermal conditions, and its impacts on the health and well-being for the city inhabitants have reached increased attention among biometeorological studies during the last two decades. Children are considered more sensitive and vulnerable to hot ambient conditions compared to adults, and are affected strongly by their thermal environment. One of the urban outdoor environments that children spend almost one third of their school time is the schoolyard. The aims of the present manuscript were to review studies conducted worldwide, in order to present the biophysical characteristics of the typical design of the urban schoolyard. This was done to assess, in terms of bioclimatology, the interactions between the thermal environment and the children’s body, to discuss the adverse effects of thermal environment on children, especially the case of heat stress, and to propose measures that could be applied to improve the thermal environment of schoolyards, focusing on vegetation. Human thermal comfort monitoring tools are mainly developed for adults, thus, further research is needed to adapt them to children. The schemes that are usually followed to design urban schoolyards create conditions that favour the exposure of children to excessive heat, inducing high health risks to them. The literature survey showed that typical urban schoolyard design (i.e., dense surface materials, absence of trees) triggered high surface temperatures (that may exceed 58 °C) and increased absorption of radiative heat load (that may exceed 64 °C in terms of Mean Radiant Temperature) during a clear day with intense solar radiation. Furthermore, vegetation cover has a positive impact on schoolyard’s microclimate, by improving thermal comfort and reducing heat stress perception of children. Design options for urban schoolyards and strategies that can mitigate the adverse effects of heat stress are proposed with focus on vegetation cover that affect positively their thermal environment and improve their aesthetic and functionality. Full article

Strong tornadoes are common for the European part of Russia but happen rather rare east of the Urals. June 2017 became an exceptional month when two tornado outbreaks occurred in the Ural region of Russia, yielded $3 million damage, and resulted in 1 fatality and 14 injuries. In this study, we performed detailed analysis of these outbreaks with different data. Tornadoes and tornado-related environments were diagnosed with news and eyewitness reports, ground-based meteorological observations, sounding data, global numerical weather prediction (NWP) models data, synoptic charts, satellite images, and data of specially conducted aerial imaging. We also estimated the accuracy of short-term forecasting of outbreaks with the WRF-ARW mesoscale atmospheric model, which was run in convection-permitting mode. We determined the formation of 28 tornadoes during the first outbreak (3 June 2017) and 9 tornadoes during the second outbreak (18 June 2017). We estimated their intensity using three different approaches and confirmed that, based on the International Fujita scale (IF), one of the tornadoes had the IF4 intensity, being the first IF4 tornado in Russia in the 21st century and the first-ever IF4 tornado reported beyond the Ural Mountains. The synoptic-scale analysis revealed the similarity of two outbreaks, which both formed near the polar front in the warm part of deepening southern cyclones. Such synoptic conditions yield mostly weak tornadoes in European Russia; however, our analysis indicates that these conditions are likely favorable for strong tornadoes over the Ural region. Meso-scale analysis indicates that the environments were favorable for tornado formation in both cases, and most severe-weather indicators exceeded their critical values. Our analysis demonstrates that for the Ural region, like for other regions of the world, combined use of the global NWP model outputs indicating high values of severe-weather indices and the WRF model forecast outputs explicitly simulating tornadic storm formation could be used to predict the high probability of strong tornado formation. For both analyzed events, the availability of such tornado warning forecast could help local authorities to take early actions on population protection. Full article

Despite the societal and economic impacts of the COVID-19 pandemic, the lockdown measures put in place by the Italian government provided an unprecedented opportunity to increase our knowledge of the effect transportation and industry-related emissions have on the air quality in our cities. This study assessed the effect of reduced emissions during the lockdown period, due to COVID-19, on air quality in three Italian cities, Florence, Pisa, and Lucca. For this study, we compared the concentration of particulate matter PM₁₀, PM_2.5, NO₂, and O₃ measured during the lockdown period, with values obtained in the same period of 2019. Our results show no evidence of a direct relationship between the lockdown measures implemented and PM reduction in urban centers, except in areas with heavy traffic. Consistent with recently published studies, we did, however, observe a significant decrease in NO₂ concentrations among all the air-monitoring stations for each city in this study. Finally, O₃ levels remained unchanged during the lockdown period. Of note, there were slight variations in the meteorological conditions for the same periods of different years. Our results suggest a need for further studies on the impact of vehicular traffic and industrial activities on PM air pollution, including adopting holistic source-control measures for improved air quality in urban environments. Full article

The multifractal properties of six acknowledged agro-meteorological parameters, such as reference evapotranspiration (ET0), wind speed (U), incoming solar radiation (SR), air temperature (T), air pressure (P), and relative air humidity (RH) of five stations in California, USA were examined. The investigation of multifractality of datasets from stations with differing terrain conditions using the Multifractal Detrended Fluctuation Analysis (MFDFA) showed the existence of a long-term persistence and multifractality irrespective of the location. The scaling exponents of SR and T time series are found to be higher for stations with higher altitudes. Subsequently, this study proposed using the novel multifractal cross correlation (MFCCA) method to examine the multiscale-multifractal correlations properties between ET0 and other investigated variables. The MFCCA could successfully capture the scale dependent association of different variables and the dynamics in the nature of their associations from weekly to inter-annual time scales. The multifractal exponents of P and U are consistently lower than the exponents of ET0, irrespective of station location. This study found that joint scaling exponent was nearly the average of scaling exponents of individual series in different pairs of variables. Additionally, the α-values of joint multifractal spectrum were lower than the α values of both of the individual spectra, validating two universal properties in the MFCCA studies for agro-meteorological time series. The temporal evolution of cross-correlation determined by the MFCCA successfully captured the dynamics in the nature of associations in the P-ET0 link. Full article

The sea surface temperature (SST) front in the Gulf Stream (GS) extension region is important to synoptic variations in atmosphere. In winter, large amounts of heat and moisture are released from the SST front, modulating the baroclinicity and humidity of the atmosphere, which is important for extratropical cyclones and atmospheric rivers (ARs). In this study, the variation of SST in the North Atlantic in winters since 1981 is investigated using satellite and reanalysis datasets, and a 23-year (1997 to 2019) warming trend of SST in the GS extension region is detected. The increase of SST is mainly distributed along the SST front, with more than 2 °C warming and a northward shift of the SST gradient from 1997 to 2019. Connected with the SST warming, significant increases in turbulent heat flux and moisture release into the atmosphere were found along the ocean front. As a result, baroclinic instability, upward water vapor flux and AR occurrence frequency increased in recent decades. Meanwhile, there was an increase in extreme rainfall along with the increase in AR landfalling on continental Western Europe (especially in the Iberian Peninsula and on the northern coast of the Mediterranean Sea). Full article

Ambient air pollution is one of eight global risk factors for deaths and accounts for 38.44 all causes death rates attributable to ambient PM pollution, while in Bosnia and Herzegovina, it is 58.37. We have estimated health endpoints and possible gains if two policy scenarios were implemented and air pollution reduction achieved. Real-world health and recorded PM pollution data for 2018 were used for assessing the health impacts and possible gains. Calculations were performed with WHO AirQ+ software against two scenarios with cut-off levels at country-legal values and WHO air quality recommendations. Ambient PM_2.5 pollution is responsible for 16.20% and 22.77% of all-cause mortality among adults in Tuzla and Lukavac, respectively. Our data show that life expectancy could increase by 2.1 and 2.4 years for those cities. In the pollution hotspots, in reality, there is a wide gap in what is observed and the implementation of the legally binding air quality limit values and, thus, adverse health effects. Considerable health gains and life expectancy are possible if legal or health scenarios in polluted cities were achieved. This estimate might be useful in providing additional health burden evidence as a key component for a clean air policy and action plans. Full article

Increasing evidence links air pollution (AP) exposure to effects on the central nervous system structure and function. Particulate matter AP, especially the ultrafine (nanoparticle) components, can carry numerous metal and trace element contaminants that can reach the brain in utero and after birth. Excess brain exposure to either essential or non-essential elements can result in brain dyshomeostasis, which has been implicated in both neurodevelopmental disorders (NDDs; autism spectrum disorder, schizophrenia, and attention deficit hyperactivity disorder) and neurodegenerative diseases (NDGDs; Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and amyotrophic lateral sclerosis). This review summarizes the current understanding of the extent to which the inhalational or intranasal instillation of metals reproduces in vivo the shared features of NDDs and NDGDs, including enlarged lateral ventricles, alterations in myelination, glutamatergic dysfunction, neuronal cell death, inflammation, microglial activation, oxidative stress, mitochondrial dysfunction, altered social behaviors, cognitive dysfunction, and impulsivity. Although evidence is limited to date, neuronal cell death, oxidative stress, and mitochondrial dysfunction are reproduced by numerous metals. Understanding the specific contribution of metals/trace elements to this neurotoxicity can guide the development of more realistic animal exposure models of human AP exposure and consequently lead to a more meaningful approach to mechanistic studies, potential intervention strategies, and regulatory requirements. Full article

It is quite difficult to investigate thermal comfort in hot–humid regions, and there have not been many real case studies or research related to this issue. In this article, four running events held in nearby popular travel spots in Kaohsiung, the largest city in southern Taiwan, were selected to analyze the influence of thermal environment and air quality on thermal comfort. Mostly real time environmental monitoring data were applied for estimating thermal indicators, along with Sky View Factor (SVF) data taken at the sites of the running scheduled routes, to analyze the thermal performance of participants at running events. Compared with runners, walkers (local residents, fans, and staff of the events) would be exposed to a greater risk of thermal discomfort with increasing time spent on the routes. With the integrated analysis, mPET (modified physiologically equivalent temperature) can be viewed as a relatively comprehensive indicator in considering both environmental thermal conditions and the biometrical differences of activities and clothing types. From the results, a good correlation between mPET and solar radiation/SVF was obtained, which indicated that mPET could be sufficiently sensible in revealing the thermal condition variation from one site to another during the route with time. Based on the discomfort risk assessment, for runners, the event held in autumn with lower SVF at the route sites would be less risky of thermal discomfort, while the event held in spring with lower solar radiation would be more comfortable for walkers. As for air quality condition, the inappropriateness of holding winter outdoor activities in Kaohsiung was obviously shown in both real time monitoring data and long term analysis. Full article

Cloud and precipitation radar mounted on a polar orbiting satellite opens up a new opportunity for global wind observation to improve numerical weather forecasting and prevent weather disasters. However, no related works have been done to retrieve the wind field for spaceborne cloud and precipitation radar. This is mainly because the high-speed motion of satellites makes wind field retrieval complex. This paper developed the first spaceborne version of the velocity–azimuth display (VAD) technique for wind field retrieval, which was originally created for ground-based radar. After derivation of VAD for spaceborne radar, we found that the product of the azimuth of the radar beam and its first harmonic was introduced into the Fourier series of radar radial velocity due to the motion of the satellites. The wind retrieval equations were developed by considering the effects of satellite motion and conical scanning strategy of radar. Numerical simulations of the spaceborne radar showed that the proposed VAD method provided a mean vertical profile of the horizontal wind with high vertical resolution over a large observation swath. Validations on airborne radar data with the same conical scan strategy as the spaceborne radar were carried out to capture the average wind structure in one hurricane event. The real data results demonstrated that the wind-retrieved results by the proposed method were consistent with the ground truth data, indicating the potential use of our proposal for spaceborne radar. Full article